Doctoral Study Project (DSP)

DSP700 Doctoral Study Project I (SPR2024-34)

 

Abstract

This dissertation investigates the correlation between telehealth adoption and severe maternal mortality in relation to rural areas. Despite advancements in healthcare, severe maternal mortality remains a pressing issue in many regions, particularly in rural areas where access to quality healthcare is limited. This study seeks to understand the factors contributing to Severe Maternal Mortality (SMM) and explore its multifaceted correlations in rural communities. By analyzing existing literature, conducting empirical research, and utilizing statistical methods. This research intends to provide valuable insights into the complex relationship between Severe Maternal Mortality (SMM) and its impacts on pregnant women in rural areas. The findings of this study will contribute to the development of targeted interventions and policy recommendations aimed at reducing severe maternal mortality rates and improving maternal healthcare in rural regions.

Keywords: Telehealth, healthcare access, health disparities, low-income population, maternal health outcomes, pregnancy outcomes, rural settings, severe maternal mortality, severe maternal morbidity.

Preface

 

My aim of authoring the dissertation is to investigate the correlation between telehealth adoption and severe maternal mortality (SMM) in relation to rural areas. My inspiration comes from the fact that severe maternal mortality remains a pressing issue in many regions, particularly in rural areas where access to quality healthcare is limited. My desire is to conduct research that provides valuable insights into the complex relationship between SMM and its impacts on pregnant women in rural areas. I expect the study findings to contribute to the development of targeted interventions and policy recommendations aimed at reducing severe maternal mortality rates and improving maternal healthcare in rural regions. I have learned and gained positive experience about the research process in terms of sample selection, data collection, analysis, report writing and presentation. 

 

 

 

Acknowledgements

 My acknowledgments go to my family for the mutual support they have offered to me to achieve the successful completion of my dissertation project. I thank them for providing the needed resources in terms of finances and other material items. I sincerely thank my lecturers for taking me through the research process as they offered the necessary insights needed to accomplish the project. I also appreciate the efforts of other stakeholders including the participants who functioned as the study sample for their open and unbiased information and whose contribution has helped make the study a reality. Lastly, I thank my fellow students, librarian, and Its personnel for any form of support offered towards the preparation of the dissertation report.

 

Contents

Abstract 2

List of Tables. 6

Background. 10

Problem Statement 12

Purpose Statement 13

Theoretical and Conceptual Frameworks. 14

Research Questions. 16

Overall research question. 16

Specific research questions. 16

Definition of Key Terms. 16

Summary. 17

Chapter 3: Methodology. 61

Research Methodology and Design. 64

Role of the Researcher. 65

Population and Sample Selection. 66

Pilot Study / Field Testing. 73

Variables and operational definitions. 73

Data Analysis. 73

Assumptions. 87

Limitations. 87

Delimitations. 89

Reliability and Validity. 91

Ensuring the reliability and validity of this study is crucial to maintaining the integrity and credibility of the findings. The following strategies will be implemented to establish reliability and validity for both quantitative and qualitative aspects of the research: 91

Ethical Assurances. 97

Summary. 127

 

 

 

 

 

List of Tables

Table 1: Instruments Matrix

Table 2: Summary of Variables

Table 3: Statistical analysis table

 

List of Figures

Figure 1: Research model

 

 CHAPTER 1: INTRODUCTION

Severe Maternal Morbidity (SMM) poses a critical and escalating public health concern in the United States and globally. The rising incidence of maternal deaths and SMM cases sparks concern for the safety and well-being of expectant individuals. SMM encompasses life-threatening complications and medical interventions, including stroke, heart failure, thromboembolism, emergency hysterectomy, and childbirth-related blood transfusions. Disturbingly, the occurrences of SMM have nearly tripled between 1998 and 2014, paralleled by a dramatic rise in maternal mortality cases from 1990 to 2013 (Kozhimannil et al., 2019). This trend highlights the urgent need for comprehensive research and effective interventions to address and mitigate the risks associated with SMM and improve maternal health outcomes.

Moreover, Severe Maternal Morbidity (SMM) exhibits contrasting patterns in urban and rural settings and among high and low-income populations. There are higher maternal death and morbidity rates among vulnerable populations, particularly in rural and low-income areas. Stroke, heart disease, accidental injury, chronic lower respiratory illness, and cancer are the top causes of death in rural and low-income areas (Murray et al., 1996). These alarming tendencies put pregnant women in these regions at higher risk of maternal and infant death and morbidity. Reducing the prevalence of SMM and increasing access to maternal healthcare for underserved populations requires addressing these inequalities.

There are several social determinants of health, including lack of access to technology housing, poverty, violence, racism, food insecurity, trauma, which contribute to the gap in telehealth access between low- and high-income populations (Kozhimannil et al., 2019). In rural areas, lower-income people face greater barriers to accessing high-quality medical care, including prenatal care and delivery services. The lack of medical facilities and obstetric care available in numerous outlying areas compounds the dangers of Severe Maternal Morbidity (SMM). Implementing telehealth policies and interventions specifically created to address the root causes of current inequalities and increase disadvantaged groups’ access to high-quality medical care may result in better maternal health outcomes and lower rates of SMM.

Financial constraints and limited telehealth access in rural areas exacerbate the repercussions and risks associated with SMM. Low-income individuals in rural regions experience significant shortages in healthcare personnel, necessitating long journeys to access maternity care. Moreover, the absence of insurance and Medicaid coverage amplifies the vulnerability to SMM (GAO, 2021). Consequently, infant mortality rates are higher in these areas, partially attributable to increased rates of preterm births. Furthermore, numerous rural births occur outside hospitals or facilities lacking obstetric units, compromising the safety of expectant individuals and their newborns. Addressing these pressing issues and enhancing maternal healthcare in rural areas, interventions must target financial barriers, increase healthcare resources, and ensure access to comprehensive obstetric services.

Despite the evident urgency to address healthcare access and Severe Maternal Morbidity (SMM) trends among low-income residents in rural areas, research in this domain remains limited. The scarcity of evidence impedes a comprehensive understanding of the relationship between healthcare access and SMM, hindering the implementation of effective interventions. As a result, urgent research is imperative to inform targeted policies and clinical efforts to reverse the escalating rate of SMM in the United States. By filling this critical knowledge gap, policymakers and healthcare practitioners can develop geographically tailored strategies to improve maternal health outcomes and mitigate vulnerable populations’ risks in rural areas. Prioritizing research in this area is essential to ensuring equitable access to quality maternal healthcare and promoting positive maternal and infant health outcomes.

Given the urgency of these concerns, this study aims to investigate telehealth utilization and accessibility trends among low-income residents in rural areas and their influence on Severe Maternal Morbidity (SMM). Examining this subject within a comprehensive theoretical framework aims to enhance existing knowledge and support evidence-based policymaking and clinical interventions. Through these efforts, we seek to effectively address and reduce the escalating incidence of SMM in the United States. By shedding light on the factors affecting healthcare access and SMM in vulnerable populations, this research will contribute valuable insights to inform targeted and effective strategies for improving maternal health outcomes. Ultimately, this study endeavors to promote equitable healthcare access and foster positive changes in maternal healthcare practices, benefiting pregnant individuals in rural areas and their communities.

Background

Maternal morbidity encompasses a range of health conditions that affects women during pregnancy and childbirth. It is intricately linked with maternal mortality, which involves deaths resulting from complications during pregnancy and childbirth and in the weeks following delivery. The burden of Severe Maternal Morbidity (SMM) on a global scale is not fully understood, but the World Bank estimates indicate an increasing trend. Like maternal mortality, SMM rates are higher in low-to-middle-income nations than in high-income countries (Geller et al., 2018). Although maternal mortality rates may be low in each country, the World Health Organization (WHO) advises that SMM rates be assessed and monitored to pinpoint systemic weaknesses and prioritize improvements. According to surveillance data, the most common causes of SMM are hypertensive diseases and significant obstetric hemorrhage. Factors such as delays in diagnosis, inability to identify high-risk people, and delays in the therapy provided by healthcare providers all play a role in the development of SMM cases. Maternal morbidity endangers not only the health of the mother but also the unborn child or fetus. There are around 198 instances of SMM for every 1000 births in Sub-Saharan Africa (Geller et al., 2018). Worldwide, hypertensive, and hemorrhagic illnesses continue to be the leading triggers of SMM.

Lack of extensive case evaluations and inconsistent implementation of evidence-based measures to prevent SMM contribute to subpar maternal healthcare practices. This study investigates the causes of SMM, analyzes current medical procedures, and locates knowledge gaps to develop more effective therapies. By filling this information vacuum, researchers can create efficient and effective plans to lower SMM rates and improve maternal health outcomes. This research aimed to examine the theoretical underpinnings of maternal morbidity, focusing on SMM. This field of study has significant theoretical, empirical, and practical value. Understanding the factors contributing to SMM and its influence on maternal health has practical implications for improving healthcare policy and practice. Empirically, the study will contribute to the growing body of evidence on SMM, especially in regions with limited research. Theoretically, this research will enhance our understanding of the multifaceted factors contributing to SMM and how evidence-based practices can be incorporated into healthcare systems to prevent its occurrence. Given the high prevalence of SMM in sub-Saharan Africa and other low-to-middle-income countries, this research is particularly relevant to global health. By shedding light on the challenges and opportunities in managing SMM, this study aims to advance maternal healthcare, ultimately leading to improved health outcomes for women and their infants.

Problem Statement

The problem to be addressed by this study is the lack of comprehensive research on Severe Maternal Morbidity (SMM) among pregnant women in low-income populations in rural settings of the United States and the limited telehealth adoption in understanding of the impact of healthcare access and utilization on SMM rates. Existing literature has primarily focused on SMM in general or among specific minority groups, neglecting the challenges faced by low-income pregnant individuals living in rural areas. This gap is identified based on literature review, which revealed that few studies have examined the relationship between healthcare access and SMM rates, specifically among low-income residents in rural areas. As a result, governments and healthcare providers do not have the information they need to create effective interventions and policies to reduce the increased prevalence of SMM among this vulnerable demographic.

The urgent need to enhance maternal health outcomes and decrease SMM rates among low-income persons in rural areas highlights the importance of tackling this gap. Healthcare systems may not effectively devote resources to address the core causes of SMM without knowing the variables leading to SMM and the obstacles to healthcare access in this group. As a result, risks to mother and infant health and subsequent rises in medical expenses are possible. Insights into the SMM experiences of pregnant persons with low incomes in rural locations are a primary goal of this study. Evidence-based initiatives to enhance maternal health outcomes will be proposed because of this investigation of the unique difficulties faced by this demographic. The findings of this study will be valuable for healthcare policymakers and practitioners, enabling them to develop targeted interventions that address the unique needs of low-income pregnant individuals in rural settings and ultimately reduce the burden of SMM.

Failure to conduct this study may perpetuate the existing knowledge gap and hinder efforts to address SMM effectively among low-income residents in rural areas. The lack of evidence-based interventions may result in missed opportunities to improve healthcare access, leading to continued high rates of SMM and associated negative health consequences for mothers and infants. Furthermore, the absence of research on this vulnerable population may perpetuate health disparities and widen the gap between healthcare outcomes in rural low-income areas compared to urban and higher-income regions. Therefore, conducting this study is crucial to inform targeted policies and interventions that promote equitable access to quality maternal healthcare and ultimately enhance maternal and neonatal health outcomes in the United States.

Purpose Statement

This study aims to fill the information gap regarding Severe Maternal Morbidity (SMM) among pregnant women residents, particularly focusing on causal factors and effective interventions to address the increasing trends and encourage healthier outcomes among low-income populations in rural settings within the United States. This study aims to enhance the understanding of SMM, specifically emphasizing telehealth adoption by low-income residents in rural areas with limited healthcare access.

The study will review socioeconomic factors that influence healthcare accessibility among U.S. residents, including healthcare coverage, low income, and the lack of resources that hinder pregnant women from accessing affordable medical services. The study will benefit specific of population of people, including medical professionals, policymakers, and those who offer healthcare services, since it will shed light on the causes and effects of SMM.

This study will look at ways to help low-income people with limited access to healthcare management and prevent SMM based on what we already know works. Policymakers may use the research results to improve the insurance and medical coverage, accessibility, and cost of healthcare for low-income citizens by enacting laws, directives, guidelines, and regulations governing healthcare service providers. To accomplish its aims, the project will gather quantitative and qualitative data via questionnaires, medical record reviews, and in-depth interviews with healthcare professionals and pregnant participants. The study aims to decrease SMM rates and enhance maternal health outcomes among pregnant women from low-income households living in rural locations by identifying their unique barriers and proposing tailored treatments especially through telehealth. This study aims to add to the existing literature on SMM and healthcare access for low-income rural residents. The findings of this study will influence evidence-based policies and programs that prioritize maternal health and try to lower SMM rates in underserved communities. The research aims to fill in information gaps and bolster efforts to expand access to high-quality maternal healthcare in the United States, hoping to improve maternal and newborn health outcomes.

Theoretical and Conceptual Frameworks

Theoretical framework

 

Increased prevalence of chronic diseases and obesity, cesarean delivery rates, and delayed childbearing have been considered significant contributors to SMM. Conversely, health-based social determinants increase risks of more proximal causal factors and have become substantial drivers of SMM. Based on the World Health Organization (WHO) framework, developed using studies by epidemiologists Richard Wilkinson and Michael Marmot, health-based social determinants involve the social environment and material conditions defining where people live, age, born, and work that has a direct impact on an individual’s health. Political and social processes and institutions create a social class division and stratification within the community (Wang et al., 2020). The primary indicators of these divisions and stratifies include aspects leading to socioeconomic positions such as occupation, education, income, gender, ethnicity, and race. People within various positions have different vulnerabilities and exposure to intermediary health-based social determinants like behavioral or biological factors, material circumstances, healthcare quality and access, and psychological circumstances. Thus, people end up experiencing different rates of pregnancy-related challenges, disability, and death.

 

 

The study’s conceptual framework is based on hypotheses attempting to explain SMM among women and its toll on their health, children, and families. It posits that woman experiencing severe morbidity face long-term social, mental, and physical consequences or death (Koblinsky et al., 2012). SMM affects pregnancy outcomes, increasing the risks of neonatal or infant deaths and stillbirths (Koblinsky et al., 2012). Children of affected women may also experience adverse effects, showing the intergenerational impact of maternal health on child well-being (Koblinsky et al., 2012). Families with SMM cases risk facing violence, dissolution, and impoverishment, revealing broader societal implications (Koblinsky et al., 2012). The study aims to explore SMM’s multifaceted impacts and identify contributing factors, consequences for pregnancy outcomes, and familial repercussions. Utilizing this framework, it seeks to understand SMM and its implications comprehensively. The mixed-methods approach aligns with this framework, facilitating a holistic exploration of SMM. The research aims to address the gap in the literature concerning SMM among low-income rural residents and inform evidence-based policies and interventions to improve maternal and neonatal health.

Research Questions

• RQ1. What are the barriers and facilitators to telehealth adoption among low-income pregnant individuals in rural areas?
• RQ2. How does telehealth adoption impact healthcare utilization patterns and access to maternal healthcare services among low-income rural populations?
• RQ3. What are the long-term health outcomes and experiences of low-income women in rural areas who have experienced severe maternal morbidity (SMM)?

Definition of Key Terms

• Health disparities:Differences in health outcomes and access to healthcare services among different population groups, often related to social determinants of health (gov, 2021).
• Healthcare access:The ability of individuals to obtain timely and appropriate healthcare services (Center for Health Ethics, n.d.).
• Low-Income population: Individuals or households with limited financial resources and income below a certain threshold, often determined by poverty guidelines or median income levels (gc.ca, 2022).
• Maternal health outcomes:The overall health status and well-being of pregnant individuals and mothers, particularly during and after childbirth (WHO, 2019.
• Pregnancy outcomes: The results of pregnancies, including live births, stillbirths, neonatal deaths, and maternal health status (Tadese et al., 2022).
• Rural settings: Geographic areas with sparse populations, limited infrastructure, and distance from urban centers (Kozhimannil et al., 2019).
• Severe maternal morbidity: unexpected labor and delivery outcomes causing significant short-term and long-term effects on women’s health (Geller et al., 2018).
• Severe maternal mortality:The death of women due to life-threatening complications during or after childbirth (Geller et al., 2018).
• Telehealth: The delivery of health care, health education, and health information services via remote technologies (NEJM Catalyst, 2018).

Summary

This dissertation explores the relationship between healthcare utilization and severe maternal morbidity (SMM) rates among pregnant women in low-income rural populations. The term “severe maternal morbidity” describes major difficulties during delivery that substantially harm the mother’s health. Inadequate infrastructure, excessive costs, and a lack of insurance coverage are some obstacles that low-income rural communities must overcome to get quality healthcare. The research strategy will combine quantitative analysis with qualitative probing into the topic. Quantitative and qualitative studies will investigate the variables that influence healthcare utilization and the experiences of SMM. Understanding the relationship between healthcare utilization and SMM rates in low-resource rural regions would help policymakers and healthcare practitioners design more effective interventions and add to the current body of research. Maternal health outcomes may be improved, and health inequities lessened if the results inspire action to improve healthcare access and quality. Evidence-based insights are provided for public health interventions and policies to reduce SMM rates and improve maternal health in low-income rural communities, which is the dissertation’s focus. Severe maternal morbidity (SMM), healthcare access, and healthcare utilization among low-income populations in rural settings will be discussed in depth in the next chapter. The review will lay the groundwork for the research, pinpoint the causes of the high SMM rates in rural regions with low income, and delve into the impact of healthcare access and use on maternal health outcomes. The literature study will also identify evidence-based techniques for dealing with SMM and increasing vulnerable groups’ access to healthcare, which will inform the development of a strong mixed-methods approach.

CHAPTER 2: LITERATURE REVIEW

Introduction

In the context of low-income rural areas in the United States, maternal health is one of the most pressing concerns. This issue touches on the complexity of human experience and goes deeper than what numbers alone can convey. The complex relationship between increased use of telehealth services and lower incidence of SMM is central to this investigation (Alonzo et al., 2022). This literature review sets out careful and in-depth research, aiming to discover factual links and understand the complex human accounts behind these statistics. This in-depth investigation sheds light on how telehealth and maternal health intersect within the tough fabric of life for low-income rural Americans.

Research Questions and Objectives

The following research questions will serve as the basis for this investigation:

• How does the level of telehealth adoption in low-income rural areas correlate with the incidence and severity of Severe Maternal Morbidity (SMM) among pregnant women, considering factors such as accessibility, technological infrastructure, and cultural acceptance?
• What role do socioeconomic factors play in influencing the correlation between telehealth adoption and Severe Maternal Morbidity (SMM) rates among pregnant women in low-income rural areas, and how can interventions address disparities to improve maternal health outcomes through telehealth initiatives?

To achieve this goal, the study will delve into qualitative aspects to capture the core of human tales hidden inside quantitative patterns and carefully deconstruct quantitative linkages. The guiding research objectives include:

• To evaluate the extent of telehealth adoption in low-income rural areas, considering factors such as the availability of telehealth services, technological infrastructure, and cultural acceptance among pregnant women.
• To analyze the correlation between the utilization of telehealth services for prenatal care in low-income rural populations and the incidence and severity of Severe Maternal Morbidity (SMM) among pregnant women.
• To assess the effectiveness of telehealth services in facilitating the early detection of maternal health issues during pregnancy, exploring how timely identification through telehealth interventions contributes to the reduction of SMM rates.

Significance of Study

This research has implications beyond academia; it speaks directly to the realities faced by the millions of expecting moms who must negotiate the complexities of maternal health in low-income, rural areas. The prevalence of severe maternal morbidity, characterized by potentially fatal problems during delivery, casts a shadow over these women’s lives. The rising popularity of telehealth is a beacon of hope in an otherwise grim healthcare landscape. However, the extent to which telehealth can be used in the complicated area of maternal health remains an empirical and human issue. The values of curiosity and compassion at the core of this research bode well for positive social transformation. Its goal is to provide practical solutions for mothers navigating the complex delivery process by investigating the correlation between telehealth and maternal morbidity. This research has implications beyond the realm of academia; it has the potential to serve as a source of inspiration and confidence, a catalyst for positive social and economic transformation.

Rural health

Rural settings are intertwined with issues that significantly influence healthcare accessibility across the vast terrain of the United States. According to Huot et al. (2019), these barriers include geographical and budgetary limits, significantly impacting healthcare decision-making. Expectant women travel a unique route within this complex milieu, characterized by eager expectations and the weight of healthcare inequities that underline their maternal journey. This study takes place in low-income rural areas to acknowledge the people whose lives are entwined with the results. These people’s backgrounds, challenges, goals, and unfailing tenacity are the foundation for the research’s rigor and analytical depth. This collaboration between academic study and human experience recognizes the practical effect that scientific discoveries may have on lives navigating the complicated tapestry of problems in rural maternal health. A significant problem is at the forefront of this study: the need for further research into the delicate interaction between the adoption of telehealth services and the rates of Severe Maternal Morbidity (SMM) in low-income rural communities throughout the United States. Despite the growing importance of telehealth as a possible solution to healthcare access difficulties, its specific influence on SMM rates has received little research, especially among pregnant women living in resource-limited rural areas (Huot et al., 2019).

The present corpus of study has focused chiefly on SMM in various groups. Still, it has primarily ignored the complications encountered by pregnant women with low financial means in rural settings and the possible consequences of telehealth usage. A systematic review of the present literature reveals a glaring gap: the need for more extensive investigations into the possible link between telehealth uptake and SMM rates in low-income rural areas. This research gap is critical because understanding the complicated relationships between telehealth services and maternal health outcomes is the key to developing targeted treatments and evidence-based policy. These initiatives aim to reduce the problematic occurrence of SMM in this vulnerable demographic. By addressing this research gap, this project hopes to provide light on routes to better maternal health, emphasizing neglected low-income rural regions where the need for new healthcare solutions is greatest.

Literature Review Synthesis

Telehealth is a wider term which covers the use of digital communications and information technologies to obtain and manage health services from a distance. Telehealth widely leverages technologies including mobile devices like smartphones, tablets, and computers. Telemedicine covers an extensive spectrum of applications, including telemedicine monitoring, telehealth nursing, and e-consultations (Al-Shorbaji & Al-Shorbaji, 2021). Various clinical services can be customized to empower individual patients, promote independence, and ensure that they are more involved in the decisions related to their maternal care. Telehealth’s patient-centered care centers on listening to individual patients and finding the matters in which they need support. Snoswell et al. (2020) asserts that telehealth-enabled services are a cost-effective option for pregnant women and may be more cost-effective than subsidized patient travel as well as outreach clinics. Examples of scenarios where telehealth has proven cost effective include prevention of emergency transfers, remote monitoring of high-risk pregnancies, reduced need for in-hospital monitoring, and reduced travel costs. Among the key objectives of telemedicine is that it creates an opportunity for people who live in the remotest areas to get healthcare services accessible (Gokula, 2020). Telehealth enables remote access of the healthcare services which allows the patients to interact and communicate with doctors and each other through a secure internet network. A profound impact in terms of healthcare access is what is experienced in areas where there are no healthcare facilities or those where healthcare facilities are not sufficient. To make a correct medical history, all medical professionals as well as patients must obtain the necessary software, hardware, and data security devices they need.

Telehealth was understudied and underutilized until the COVID-19 pandemic, during which government agencies and healthcare organizations reduced regulations and increased payment parity, facilitating a surge in telemedicine adoption. Stay-at-home orders and other mitigation strategies associated with quarantine measures led healthcare facilities to increase and expand telehealth services, particularly for pregnant women (Chiesa et al., 2021). Examples of telehealth services for pregnant women whose utilization proliferated during the COVID 19 pandemic include virtual prenatal consultations telemonitoring of vital signs, remote ultrasound consultations, telehealth counseling, genetic counseling, and tele physical therapy for pregnancy-related aches (Kern-Goldberger & Srinivas, 2022). Even after the restrictions associated with the pandemic were lifted, most maternal healthcare institutions retained a good amount of these telehealth services. The lift in COVID-19 restrictions provides a chance to take care of telehealth services in relation to maternal healthcare utilization in both urban and rural areas. However, the obstacles of implementation and use should be known, understood, and overcame to reap all the telehealth advantages.

Barriers to the implementation and utilization of telehealth

The primary obstacle to the implementation of telehealth services among pregnant women in rural populations and low-income areas is limited access to technology. The technology illiteracy circles around the curtailed dispensation of devices, poor internet connection, the low level of digital literacy, cultural obstructions in technology use and the lack of technical assistance (Nakayama et al., 2023). These factors reduce the effectiveness of telehealth approach about linking neglected communities to care. In a recent study by Maloney et al. (2020), the technological factors hampering telehealth services were characterized. The study was conducted using the data from the Nebraska Annual Social Indicators Survey which focused on the nexus between non-utilization of technology and use of healthcare services. 7.2% of the sample size rated as the barrier refers to getting internet, which is reliable, 9% is evaluated as a barrier with regards to telehealth adoption and the reason for being so is the cost of internet services, and 7.1% agreed that access to electronic devices is a barrier to telehealth. Maintaining the same level of equal access to technology Maloney et al. (2020) concluded that the use of telehealth was also comparatively less among the rural population. As a result of having limited access to technology and subsequently telehealth services, those living in poverty in rural areas have a higher rate of missed appointments that progress to more disparities and more disruptions in their continuity of care (Jeganathan et al., 2020). For instance, technology deprives clinicians and pregnant women not to do exchange of health-related information. Without the rapid-messaging, remote-monitoring, and data-sharing which they are essential in the identification of warning signs and handling complications, the ability to manage high-risk pregnancy and provide timely interventions is significantly weakened.

Besides the limited access to technology, privacy and security issues can be obstacles to the embracement and utilization of telehealth. Pregnant women just like any other patients might be apprehensive about their privacy and the integrity of their telehealth data during telehealth interactions. According to the study conducted by Houser et al. (2023), the amount of people in the US with better access to care was higher than 80% due to telehealth. Nonetheless, it was found that telehealth services deployment during the COVID-19 pandemic had both positive and negative impact. Along with the expansion of virtual and telehealth services, risks of technology and cyber security-related issues such as data breaches and privacy vulnerabilities are also emerging. On the topic of privacy and cyber security complexities, it is found by Houser et al. (2023) that most patients lack trust and knowledge on telehealth technology use, and it adds to their concerns for security and privacy. Despite the considerable temporary alterations of telehealth regulations to improve the data security, more slow permanent amendments were observed. When it comes to Pregnancy, there is also a greater amount of sharing of private and sensitive information. Consequently, the mothers to be may express a stronger sense of fear and desire to protect the details about their reproductive health and their overall well-being as well. This fear of accessing this extremely sensitive information by unauthorized people may escalate the privacy concerns about the data (Camarines & Camarines, 2022). The confidence of pregnant women in the safety of the data collected through monitoring platforms may have an impact on their participation in telehealth-centered programs. It can result in overlooked opportunities for early detection of complications and decisive interventions, which could be the bringing about of higher rates of severe maternal morbidity.

In comparison, language and cultural barriers also present a major factor that limits the uptake of telehealth services among pregnant women in low-income, rural areas. While a systemic review and thematic synthesis conducted by Whitehead et al. (2023) found that linguistic barriers and cultural factors had a major effect on the utilization of digital health technologies. Indeed, there may be a variety of digital health technologies available as well as massive investment in technology, but their applicability is low among the certain population categories. They cover language groups and cultural minorities, which includes First Nations People, immigrants and refugees, and lower-socio-economic community. Whitehead et al. (2023) demonstrated that the utilization and uptake of telehealth services is lower in linguistically and culturally diverse populations than non-linguistically and culturally diverse ones. As an example, Black women were three times less likely to use digital health technologies compared with White women. This disparity in telehealth service usage could be due in part to a failure to properly address cultural, linguistic, or health literacy needs of these diverse population groups (Saeed & Masters, 2021). Language and cultural barriers have always been positively correlated with miscommunication between pregnant women and health care providers. Misunderstandings regarding medical instructions, severity of symptoms, or treatment plans may lead to an increased risk of SMM (Wong & Kitsantas, 2020). In addition, some cultural backgrounds may attach stigma to certain healthcare practices or medical conditions. Alexander et al. (2021) revealed that strong ties to tradition and a deep-seated sense of pride in Appalachian culture may lead to resistance when adopting recent technologies. According to the long-standing beliefs of the Appalachian culture, telehealth represents a departure from traditional in-person healthcare, which may be met with reluctance or skepticism. Traditional beliefs, coupled with the lack of trust in the healthcare system, can deter pregnant women from seeking necessary telehealth services, potentially leading to complications associated with SMM.

Definition and scope

Telehealth has made tremendous achievements in the maternal health sector as a comprehensive strategy that leverages telecommunications and information technology to provide healthcare services to remote areas (Brown & DeNicola, 2020). In this setting, telehealth surpasses traditional boundaries to embrace numerous services critical to pregnant mothers, including prenatal care, birthing education, postpartum support, and more (Cantor et al., 2022). This all-encompassing strategy represents a watershed moment in maternal care, allowing pregnant moms to obtain crucial healthcare treatments regardless of their geographic location (Mishori & Antono, 2020). This dramatic move lowers geographical barriers, ensuring maternity care reaches women in distant or disadvantaged locations. It expands the scope of maternity care, making it available to a larger population. Mishori and Antono (2020) explain how telehealth’s inclusive approach redefines the scope of maternal care, establishing it as a dynamic, accessible, and adaptive paradigm that resonates with the changing needs of pregnant women.

Telehealth adoption and implementation Trends

The increased use of telehealth for maternity care indicates a changing healthcare environment characterized by interrelated issues. The COVID-19 pandemic was the setting for significant research by Madden et al. (2020), documenting the exponential increase of telemedicine in prenatal care in New York City’s teeming megalopolis. The study found that the pandemic accelerated the need for remote healthcare solutions due to the COVID-19 imperatives of reducing face-to-face contact and maintaining healthcare services. It exposed the pressing need to integrate telehealth to satisfy the rising demand for maternity care services securely and conveniently. In addition, Stifani et al. (2021) investigated the field of family planning, providing further context for telemedicine’s rapid adoption. Their results shed light on the game-changing potential of telehealth, showing that it can impact all aspects of maternal care, not just prenatal and postpartum. These illuminating studies highlight the rising tide of telehealth adoption in maternal health. The potential it offers for improving maternal care delivery at all points along the continuum drives this expansion in addition to the immediate needs of the time, such as a global pandemic.

Maternal health care is extremely critical for the long-term health of both the mother and the child. Yet, maternal care inequality has been a longstanding struggle especially for the poor and people living in neglected and rural communities. According to the Center for Disease Control and Prevention, the current maternal mortality rate is 17.4 per 100,000 live births. On top of these statistics, Black mothers are two and a half times more likely to die from childbirth or pregnancy causes than white women. Overall, nearly 65% of pregnancy-related deaths are preventable, telehealth is one of the ways to reduce severe maternal mortality rates. As of today, the U.S. offers the most advanced digital health technologies for maternal healthcare across the globe.

One of the main telehealth trends in 2024 is wearables and the Internet of Medical Things (IoMT). Growing application of wearable sensors and IoMT devices, with a CAGR of 18.3% from 327 million in 2021 to 1487 million in 2030 serve as the main drivers behind the emerging demand for telehealth and real-time health monitoring among pregnant women (Shmerling et al., 2022). IoMT, in essence, encapsulates applications and devices with Internet connectivity. The overall category of IoMT devices and applications designed with healthcare in mind are typically consumer oriented. They include glucose monitors, ingestible sensors, MRI machines, infusion pumps and smart thermometers, remote patient monitoring devices, and MRI machines (Mishra & Singh, 2023). On the other side, wearable technology encompasses health monitoring devices designed to be worn on the body for tracking the wearer’s health data. Generally, wearables and the Internet of Medical Things (IoMT) consist of three essential components: a sensing device, a data transfer device, and a power supply device (Kalasin & Surareungchai, 2023). The sensing device captures real-time bio-signals, converting them into electrical impulses that are wirelessly transmitted to the cloud or a mobile phone for subsequent analysis. Both the sensing and data transmission processes necessitate a dependable power source. In contrast to traditional electronics, wearables and IoMT have distinct power source criteria, requiring attributes such as flexibility, stretchability, biocompatibility, wearability, and comfort.

Another key trend in telehealth is assistance with remote patient monitoring. In resource-scarce environments, the overwhelming number of women encounters the difficulties to obtain vital maternal and newborn health care services. This includes a dearth of prenatal care, qualified birth attendants, and emergency obstetric care (Tikkanen et al., 2020). Among the impediments to overcome are transportation shortages, geographical barriers, and financial hindrances. However, the topography of maternal and neonatal care is being redefined through Remote Patient Monitoring, thanks to the use of technology in improving healthcare outcomes. It is quite comprehensive and deals with the issues of online appointments, video conferencing for patient-provider interactions, and virtual care provisions. Digital patient’s entry with Remote Patient Monitoring is exceptional since any individual no matter where they are will have access to the fundamental health care services (Mhajna et al., 2020). Remote Patient Monitoring plays a pivotal role in real-time maternal health monitoring, which leads to the emergence of fundamental implications. It allows healthcare providers to discover complications like hypertension and gestational diabetes early thereby giving a window for an economic intervention (Peahl et al., 2020). Through the timely detection of these conditions, Remote Patient Monitoring has a direct impact on the decline of maternal morbidity and mortality rates. Pregnant clients can be addressed by medical personnel at once, thus avoiding serious health complications and ensuring a more seamless pregnancy trail.

Another groundbreaking innovation in telehealth for maternal care in addition to the expansion of the technology concept across transmissions, Internet of Medical Things is the remote patient monitoring. Robotic Process Automation (RPA) or software facilitates the employment of automated bots working as a bridge that connects disparate systems and applications, which carry out the high-volume and critical processes with accuracy and doing so without incurring the massive duties of an already overworked workforce (Mohamed et al., 2022). These RPA bots can mimic human interactions as concerns healthcare systems, so good doing the front-end and the back-end administration processes. RPA is in operation 24/7 without any need for a break and the level of errors is almost zero. Therefore, RPA serves as a life-saver technology in healthcare. Staff roles optimization becomes the crucial factor with human-cooperative and autonomous robots. AI algorithms using the advanced scanning method offer better accuracy than usual search engines through the precision of search. This elevated level of accuracy in AI enables us to connect patients to the ideal medical practitioners, which in turn improves the general patient experience (Lee & Yoon, 2021). RPA has found wide adoption in maternity care with the most significant adoption in general staff functions such as appointment scheduling, hospital administration and the enabling of standardized data management protocols. The rapid adoption and deployment of RPA in the health care industry highlights the fact that RPA transforms not only operational efficiency but also patient care as well.

Telehealth Benefits and challenges

Integrating telehealth into maternal care presents several advantages but poses challenges. It is essential to navigate these aspects comprehensively to understand the landscape of telehealth in maternal health.

Benefits.

• Enhanced access to care.Telehealth appears as a critical solution to the long-standing issue of healthcare accessibility, providing a lifeline to pregnant moms living in distant or disadvantaged areas (Brown & DeNicola, 2020). This transformational strategy crosses geographical boundaries, ensuring that vital maternity care services are available regardless of the distance between women and conventional healthcare facilities. As illustrated by telehealth, the convergence of technology and healthcare delivery signals a hopeful age for pregnant moms, increasing their access to crucial treatment and support (Mishori & Antono, 2020).
• Augmented convenience and flexibility.Telehealth provides expecting mothers with unparalleled convenience and flexibility, allowing them to obtain care from places of their choice, significantly increasing accessibility, and aligning with individual timetables (Madden et al., 2020). This paradigm shift in maternal care encourages women to participate in healthcare on their terms, enabling a more patient-centered approach that resonates with pregnant moms’ shifting needs and lifestyles (Stifani et al., 2021).
• Improved patient-provider communication.Due to telehealth’s digital platform, pregnant women and their healthcare providers may benefit from a more interactive and cooperative care setting (Brown & DeNicola, 2020). Mishori and Antono (2020) argue that increased communication may lead to better, more personalized decision-making about maternity care. The potential health benefits of expecting women from this dynamic contact go beyond simply sharing information. A more patient-centered approach that prioritizes discussion shared decision-making, and ultimately improved maternal health is being implemented, marking a radical departure from conventional healthcare delivery, which may limit timely and complete communication.
• Cost-Efficiency. The emergence of telehealth as a catalyst for reducing the need for travel and increasing the efficacy of care delivery highlights the potential for significant cost savings in maternal health (Brown & DeNicola, 2020). This revolutionary aspect of telehealth means less inconvenience for pregnant moms who would otherwise have to travel laboriously to receive care. In addition, it provides a path for healthcare providers to simplify their operations, resulting in a more cost-effective method of delivering maternity care. The ensuing cost savings may have a domino effect across the healthcare system, helping patients and healthcare providers alike (Stifani et al., 2021).
• Enhanced identification of high-risk pregnancies. With telehealth services, women can be continuously monitored remotely so that any potential complications or high-risk situations can be detected early. According to a recent report by Rayford et al. (2023), telehealth has been widely utilized in obstetrics clinics in several locations after the COVID-19 pandemic. An interesting observation was that, after the initial telehealth appointment, at least half of the patients contemplated using telehealth appointments when needed. Physicians also expressed interest in virtual follow-ups after the initial visit. Telehealth interventions in 119 high-risk patients resulted in better breastfeeding outcomes and safety of fetus and mother with decrease in in-person visits. The early monitoring of telehealth services led to early detection of high-risk conditions, such as fetal heart rate, blood pressure, and glucose levels, facilitating timely management and intervention for high-risk pregnancies.

Challenges.

• Reimbursement challenges. A significant obstacle to expecting mothers’ access to telehealth is the possibility of inadequate payment from insurance providers. This financial challenge threatens to limit access to crucial maternity care services, especially for women who depend on insurance coverage to manage their healthcare bills. A holistic strategy is necessary to address the problems of affordability and insurance-related issues to guarantee telehealth stays an accessible and cost-effective alternative within maternity care. This issue must be addressed if expecting women to have equal access to telehealth services and if financial obstacles are to be removed that prevent their use (Madden et al., 2020).
• Technological barriers. A key barrier for some expecting women is limited access to technology, which may prevent them from using virtual healthcare services. Closing technical gaps like the one the digital divide highlights is crucial. To ensure that telehealth is accessible to all women, it highlights the need to implement initiatives to close these disparities so that women from all social classes may reap the advantages of telehealth without facing any barriers. This diversity is critical to reducing healthcare inequalities and providing equal opportunities for all mothers-to-be, regardless of their economic or technical standing. Mishori and Antono 2020).
• Provider and patient acceptance. The adoption of telemedicine faces a considerable barrier due to resistance from healthcare professionals and patient groups (Brown & DeNicola, 2020). According to Sullivan et al. (2023), providers of healthcare who are used to more conventional methods of patient care may need help learning to use telehealth technologies. They may be wary because they doubt the quality of care that can be provided remotely or because they need more experience with modern technological systems. Patient resistance may manifest as doubt about the effectiveness of remote treatment or an aversion to technology. This reluctance emphasizes the significance of thorough training and education programs for healthcare professionals and patients. Healthcare systems may reduce the barriers to adoption and encourage telehealth’s incorporation as a valuable part of maternity care by addressing these issues and providing the appropriate assistance. Using telehealth services benefits patients’ busy schedules and helps the healthcare system become more robust and flexible (Sullivan et al., 2023).
• Ethical and legal concerns. Telehealth services have been increasingly practiced in recent years. During the COVID-19 pandemic, telemedicine emerged as an essential service to prevent the transmission of the virus between healthcare professionals and patients, encompassing a diverse range of medical disciplines (Koonin et al., 2020). However, despite its growing prominence, several ethical and legal challenges associated with telehealth practices persist, necessitating effective regulation. A comprehensive study conducted by Solimini et al. (2021) uncovered that unresolved legal and ethical concerns, particularly regarding patient autonomy (87%), patient privacy (78%), data protection and security (74%), and confidentiality (57%), contribute to patient reluctance in adopting telehealth. In cases involving pregnant women, it becomes imperative to ensure that they fully understand the implications of safeguarding their privacy and the complexities of virtual care. Addressing these ethical and legal considerations requires careful attention to foster the acceptance and utilization of telehealth services among pregnant women.
• Limited physical examination. Limited physical examinations are one of the biggest limitations of telehealth. It is worth noting that maternal care involves firsthand assessments, such as pelvic exams or palpation of the abdomen, which may be limited in virtual settings (Kumar & Sweet, 2020). In addition to physical assessments, therapeutic relationships are critical to effective maternal training. As indicated in the Breton et al. (2021) Investigation, the adoption of telehealth in the provision of maternal care results in the weakening of therapeutic relationships and decreased continuity of care, as well as depersonalization of practice and lack of psychosocial support. The inability to conduct thorough physical examinations could impact the accuracy of diagnoses and treatment plans, especially for conditions requiring in-person assessments.

Severe Maternal Morbidity Rates in Low-Income Rural Areas

Severe maternal morbidity implications

Beyond being a simple healthcare statistic, severe maternal morbidity (SMM) captures the essence of a mother’s health throughout the complex processes of pregnancy, delivery, and postpartum recovery (Kozhimannil et al., 2019). Its existence reverberates across numerous dimensions, defined by a constellation of major medical issues. First, it is a sentinel sign of maternal health that reveals more subtle issues with maternal health than just the obvious ones. Secondly, SMM is a litmus test for the durability and adaptation of healthcare systems, requiring a complete response to achieve optimum results for moms. Lastly, its importance is felt across society since maternal health is directly related to the success of households, neighborhoods, and future generations. Kozhimannil et al.’s (2019) investigation of SMM rates in the United States from 2007 to 2015 demonstrated that maternal health outcomes differ significantly between rural and urban areas. Their work highlights SMM as a top priority, especially in low-income rural communities. The effects of SMM are seen most strongly in places where inadequate healthcare resources compound the effects of socioeconomic variables. It is crucial to address these inequalities and understand the underlying causes that contribute to them so that interventions may be developed to reduce the burden of SMM among at-risk communities significantly.

Disparities in maternal health outcomes

Pregnant women in low-income rural communities face additional challenges due to the prevalence of maternal health inequalities in these regions (Kozhimannil et al., 2019). These populations, particularly Indigenous women, have more difficulties, increasing their vulnerability to SMM (Kozhimannil et al., 2020). The confluence of race and locality exacerbates inequalities in maternal health outcomes within this complex web of vulnerability. Women of color in rural areas frequently face additional challenges due to living in areas with few resources, increasing their vulnerability to SMM (Luke et al., 2021). This research findings suggest that the frightening differences in maternal health outcomes need immediate attention and specific measures. A specialized strategy that recognizes the various causes at play is necessary because of the exceptional healthcare requirements of low-income rural communities. It is a societal need and an issue of healthcare equality that these inequities be eliminated. The health and stability of families and communities are directly tied to the well-being of mothers in these areas. Telehealth adoption has the potential to reduce inequities and enhance equitable maternal health outcomes in low-income rural areas; investigating this potential is an urgent priority in this setting.

Factors contributing to SMM.

The prevalence of severe maternal morbidity (SMM) in low-income rural settings harms maternal health (Kozhimannil et al., 2019; Luke et al., 2021). Inadequate healthcare infrastructure is a widespread problem in these areas and a significant barrier to providing prompt and thorough maternity care. The hazards of SMM are exacerbated because of the pervasive socioeconomic inequalities in such places. Kozhimannil et al. (2019) and Luke et al. (2021) shed light on the systemic healthcare issues that overlap with these inequalities, revealing a complex web of healthcare vulnerabilities. The lack of medical facilities and practitioners in low-income rural areas worsens disparities in healthcare access and quality (Ahn et al., 2020). Consequently, pregnant women in these areas have fewer healthcare alternatives, increasing their risk of suffering from SMM.

Maternal mortality rates are highest in nations where women are least likely to receive skilled attendance during childbirth, lacking access to midwives, doctors, or trained health professionals. Similarly, within countries, the most vulnerable to maternal death and disability are often the poorest and least educated women. High maternal mortality rates not only reflect poorly functioning health systems but also underscore entrenched gender inequalities, limiting women’s control over decision-making and impeding their access to social support, economic opportunities, and healthcare (Crear-Perry et l., 2021). In many developing countries, legal systems barely support women and girls as they try to protect their reproductive rights. In certain cases, laws as such are designed to undermine these rights, e.g., prohibiting adolescent girls from accessing contraception or requiring women to get the consent of their husbands or fathers. These disparities become apparent early in life, with girls born into poverty facing an increased susceptibility to child marriage and exploitation, including sex trafficking, or forced labor. Adolescent girls have little autonomy to decide for themselves whether to use contraception or not or allow sexual intercourse. Cultural stereotypes from communities, such as husbands demanding physically heavy tasks to be performed by expectant mothers, are a major cause of maternal mortality and placenta abruption in the rural areas. Such cultural practices put them at significant risk of early pregnancy and related complications. Moreover, even if nondiscriminatory laws are in place, their consistent implementation becomes an issue.

Reducing SMM and maternal mortality in these areas is crucial. According to Ahn et al. (2020) and Howell (2018), initiatives must be comprehensive, considering the many factors contributing to these inequalities to achieve this. These findings suggest that clinical treatments are necessary, but broader structural reforms are also needed to improve healthcare access, quality, and fairness (Ahn et al., 2020; Howell, 2018). Telehealth adoption appears as a possible tool in this attempt, promising more significant access to maternity care services, improved communication, and cost-effective solutions customized to the requirements of low-income rural communities.

Telehealth Adoption

Although severe maternal morbidity (SMM) rates are extremely high in low-income rural areas, telemedicine has proven to be an effective solution, outpacing traditional healthcare models (Geller et al., 2018). Geller et al. (2018) argue that telehealth has the prospective to improve maternity care access by eliminating geographical limitations and fostering more operative communication between patients and healthcare providers. Besides, it offers low-priced alternatives, which is principally valuable in low-income rural areas with limited resources (Geller et al., 2018). While telehealth can transform maternal care, more information is required to understand its prevalent use and how it affects SMM rates in low-income rural areas (Geller et al., 2018).

The Correlations between Telehealth Adoption and Severe Maternal Morbidity Rates

Link between telehealth and morbidity rates: Telehealth is on the rise as a viable option for improving maternal health in low-resource rural areas, with its diverse solutions and potential to significantly affect SMM rates. Several essential characteristics define the conceptual connection between telemedicine and SMM rates. First, telehealth removes physical barriers by providing remote access to vital maternal care services, which is especially important for pregnant women in underserved rural regions (Geller et al., 2018). This improved reach has the potential to lessen the severity of maternal health concerns by allowing for earlier diagnosis of difficulties and the introduction of appropriate therapies. Second, Geller et al. (2018) point out telemedicine facilitates better dialogue between pregnant women and medical staff. The lowering of SMM rates is primarily because of this enhanced communication, which allows for better monitoring of maternal health, earlier detection of warning indicators, and more educated decision-making. As a result of reducing the need for far-flung travel and simplifying treatment delivery, telehealth also provides a cost-efficient component (Geller et al., 2018). Low-income populations may profit from this strategy because it frees up more money for other purposes. However, healthcare systems that are already overburdened can also use the savings to invest in preventative care and better serve their patients. In essence, telehealth’s varied potential in maternal care can change the landscape of SMM rates among low-income rural areas by solving essential access and communication difficulties and generating economic advantages.

Existing studies about the correlation: The indirect relationship between telehealth adoption and severe maternal morbidity (SMM) rates has been the subject of much research, and these findings give essential insights. A recent study by Sundstrom et al. (2019) looking at its use in increasing contraceptive access among rural women demonstrated the potential for telehealth to improve maternal health outcomes in underserved regions. Although this research did not directly address SMM, it did imply that telemedicine may help pregnant women in places with few medical facilities. Even though it does not explicitly address SMM rates, Kusyanti et al.’s (2022) comprehensive literature analysis on technology-based maternal care also helps us better grasp the current state of telehealth in maternal health. While not explicitly focused on telehealth, the Mother Health Multilevel Intervention for Racial Equality (Maternal Health MIRACLE) Project by Johnson et al. (2022) highlights the importance of equitable access to mother care, consistent with telehealth’s capacity to foster such equality.

Correspondingly, Chuo et al. (2021) assessed neonatal telemedicine services, providing lessons for evaluating maternal care programs. Even though their research focuses primarily on neonatal care, there are important takeaways for evaluating telehealth programs that may be applied to maternal health. Kramer et al. (2019) highlighted the significance of providing equal care to all mothers using a health equality approach. Although this paradigm does not explicitly examine telehealth, it highlights its potential contribution to more equal maternal health outcomes. Even though it is not a review of maternal health specifically, Moise et al.’s (2023) global scoping review on digital technology-enabled health interventions provides a broad perspective on digital health technologies such as telehealth and their potential impact on healthcare outcomes, providing context for telehealth’s potential role in enhancing maternal care and decreasing SMM rates.

Methodologies examining the correlation: The above research’s varied techniques for measuring the association between telehealth implementation and severe maternal morbidity (SMM) rates reflect the difficulty of this task. Sundstrom et al. (2019) used quantitative methods to assess the availability of contraceptives to rural women. To determine how much telehealth affects the accessibility and use of contraceptives, they conducted surveys and data analysis. On the other hand, Moise et al. (2023) opted for a qualitative global scoping review. This review offers a comprehensive overview of a subject by collecting and evaluating a large body of relevant literature. Moise et al. (2023) reviewed various research, reviews, and publications on digital health treatments, including telehealth, to determine patterns and effects on healthcare outcomes. The multilevel intervention strategy proposed by Johnson et al. (2022) includes quantitative and qualitative approaches. Data gathering and statistical analysis are examples of quantitative methods that might be used to assess the success of the Maternal Health Multilevel Intervention for Racial Equity (Maternal Health MIRACLE) Project in its goal of increasing racial equity in maternal health care. Qualitative methods might include conducting in-depth interviews or holding focus groups with project participants to get their perspectives. Considering quantitative data and qualitative insights from multiple perspectives, the possible association between telehealth acceptance and SMM rates is better understood thanks to these differing techniques.

Factors Influencing Telehealth Adoption in Low-Income Rural Populations

Telehealth use and access barriers: Numerous studies highlight significant obstacles preventing low-income rural communities from accessing and using telehealth services. Barbosa-Leiker et al. (2021) provide insightful information on prenatal women’s exposure to stress, coping mechanisms, and necessary resources during the COVID-19 pandemic. They do not zero in on telehealth specifically, but their examination of difficulties brought on by pandemics highlights the crucial setting in which telehealth adoption becomes essential. Kronforst et al. (2023) expand on this by investigating the availability and uptake of telehealth services for children in Chicago during the first phases of the COVID-19 epidemic. Their findings highlight the importance of telehealth in emergency settings by highlighting its role in sustaining healthcare access for disadvantaged people during emergencies. Maloney et al. (2022) also investigated early pandemic healthcare visits, telemedicine use, and the presence of technical hurdles. They highlight the necessity of bridging the digital divide by identifying constraints inherent in technological access that might limit the efficient use of telehealth services. Under these results, He et al. (2023) provide new perspectives on Medicare beneficiaries’ access to and use of telehealth services, particularly for those with diabetes. Their findings stress the need to eliminate barriers to telehealth to promote fair access for underserved groups, particularly those with lower socioeconomic status. Patient-reported delays in breast cancer screening, diagnosis, and treatment were also investigated by Du et al. (2022) during the COVID-19 pandemic. They discuss the rise of telemedicine during this period, noting its potential to reduce waiting times for medical treatment, especially in remote areas. Qin et al. (2023) build on this idea by discussing how the widespread use of telemedicine might reduce the gap between the attendance rates of patients from different socioeconomic backgrounds at outpatient clinics. Their results highlight how telehealth might help improve healthcare access for underprivileged groups by reducing access to in-person treatment inequalities. These studies show the complex challenges low-income rural communities have in gaining entry to and using telehealth services, even amid an emergency such as the recent COVID-19 outbreak. They stress the need for focused interventions to promote equitable telehealth uptake and usage by addressing technology inequities, structural impediments, and socioeconomic considerations.

Socioeconomic factors against telehealth: Ko et al. (2023) challenge the commonly held belief that desire is the key predictor of telehealth inequalities by providing essential insights into the role of socioeconomic variables on access and usage of telehealth within low-income rural locations. By contrasting the results of Ko et al. with those of other researchers, we may get a fuller picture. Rahim et al. (2023), who examined the difficulties parents of pediatric patients in Alabama faced in accessing telehealth services during the 2009 COVID-19 pandemic, presented findings that contrast with those of Ko et al. While Rahim et al. acknowledge the existence of access hurdles, they place more weight on users’ expectations and motivations. However, Ko et al. claim that socioeconomic factors are at the root of telehealth inequalities, delving further into this area’s societal and institutional constraints. In addition, Qin et al. (2023), who focus on decreasing socioeconomic inequalities in outpatient clinic no-show rates via telemedicine, share the same insights as Ko et al. Both highlight the need to tackle these socioeconomic variables to ensure everyone has equal access to healthcare, whether in-person or via telehealth. Ko et al.’s study adds a vital layer to the conversation on telehealth adoption in low-income rural areas. Their focus on socioeconomic characteristics as major drivers is consistent with research like Qin et al., demonstrating the need to address these inequalities to guarantee that everyone can access telehealth services. This contrast demonstrates the complexity of barriers to telemedicine adoption and the need for holistic approaches to eliminating socioeconomic inequalities in telehealth usage.

Telehealth infrastructure role in rural areas: Understanding the importance of telehealth infrastructure in rural healthcare systems during the 2009 COVID-19 pandemic is made more explicit by Meyer et al. (2020). Their findings highlight the need for a sustained effort to create a reliable telehealth infrastructure for underserved communities over time. According to Meyer et al.’s research, not only does this kind of infrastructure make it easier to provide conventional treatment, but it also makes rural populations more resistant to disasters. This emphasizes the significance of infrastructure in making telehealth a viable and effective healthcare delivery alternative for geographically dispersed communities. Instead of concentrating on its use in remote places, Takahashi et al. (2022) consider telemedicine’s potential to reduce cardiovascular disease. Their research statement, however, recognizes the value of telehealth infrastructure in filling the gaps in service in remote and underserved areas. While not directly addressing rural regions, their results highlight the value of telehealth infrastructure for reaching underserved communities with specialized medical treatment. Chandrasekaran (2023) examines the state of telemedicine after a pandemic, looking at its use patterns and the impact of several circumstances. Learn more about how telehealth infrastructure, socioeconomic factors, health status, and social determinants interact in this informative resource. The findings from Chandrasekaran’s study provide an in-depth knowledge of the many aspects that influence urban and rural telehealth settings. Integrating these sources confirms what Meyer et al. and, to a lesser extent, Takahashi et al. have already pointed out: that infrastructure plays a crucial role in facilitating telehealth uptake and resiliency in rural regions. Chandrasekaran’s study provides a complete picture of the elements that affect telehealth use in both urban and rural settings, which broadens this viewpoint by analyzing the complicated dynamics of telemedicine in different settings.

Comparative analysis and implications: When compared side by side, these sources highlight the consistent need to tackle socioeconomic gaps and infrastructural problems to boost telehealth adoption in low-income rural regions. The setting of the global COVID-19 epidemic is critical for analyzing the challenges and potentials of telemedicine. Studies like those by Barbosa-Leiker et al. (2021) and Kronforst et al. (2023) demonstrate the relevance of telehealth in maintaining access to care throughout the pandemic. However, Maloney et al. (2022) and He et al. (2023) discover impediments inherent in technical inequities, underscoring the vital need for fair technology infrastructure to ensure telehealth’s success. Ko et al. (2023) provide a paradigm shift by questioning the common belief that patients’ lack of desire is solely to blame for telehealth’s uneven uptake. The research of Du et al. (2022) and Qin et al. (2023) further supports this opinion by demonstrating that the widespread use of telemedicine may successfully reduce disparities in access to in-person treatment, contributing to the larger goal of ensuring universal healthcare coverage. Although not limited to them, Meyer et al. (2020) and Takahashi et al. (2022) present an all-encompassing perspective on the significance of well-developed telehealth infrastructure. Their insights emphasize the fundamental significance of infrastructure in enabling healthcare delivery, especially for marginalized communities. Chandrasekaran (2023) offers a new understanding of the changing post-pandemic telemedicine scenario. This highlights the significance of flexibility and creativity in providing for the healthcare requirements of a more complex and multifaceted population. Generally, these research findings highlight the complex interaction of constraints, socioeconomic considerations, and infrastructure in telehealth adoption among rural low-income communities. These complex issues must be resolved if telehealth services, which have the potential to revolutionize healthcare delivery in disadvantaged regions, are to be made available to everyone who needs them.

Addressing Disparities: Telehealth as a Tool for Maternal Health Improvement

Telehealth impact on SMM rates: Telehealth’s potential effect on severe maternal morbidity rates in underserved areas is becoming an increasingly important study area in maternal healthcare. Several new research studies have investigated this topic, providing insights into the potential of telehealth to mitigate the high rates of maternal morbidity in marginalized communities. According to the findings, some recurring ideas and patterns are as follows:

Reducing racial disparities: To reduce racial gaps in maternal healthcare, Jean-Francois et al. (2021) highlight the game-changing potential of health information technology tools, especially telehealth. Their findings emphasize the potential of telehealth to play a critical role in reducing these inequalities by increasing minority access to healthcare. Telehealth removes geographical boundaries by facilitating remote consultations, increasing the likelihood that people in disadvantaged places would have access to quality prenatal care. In addition, it can be remotely monitored to help spot problems early on, cutting down on maternal mortality even further. To further establish maternal healthcare equality, telehealth platforms may be adapted to deliver culturally sensitive care, recognizing, and addressing the requirements of minority patients.

Obesity and morbidity risk. Baranco et al. (2022) examine the complex link between maternal morbid obesity and increased morbidity risks. Their findings stress the need for tailor-made programs to help overweight pregnant women. In this setting, Telehealth has an excellent promise to deliver individualized care. Medical professionals may better meet the requirements of obese pregnant women by creating individualized treatment regimens using telemedicine tools. As part of this effort, we provide nutritional advice and ongoing remote monitoring to help reduce the dangers of maternal obesity. As a result, healthcare providers may play a crucial role in lowering rates of severe maternal morbidity among this at-risk group by leveraging the benefits of telehealth.

 Rural residency as a risk factor. With great insight, Hansen, Slavova, and O’Brien (2022) investigate rural residence as a significant risk factor for severe maternal morbidity. Their findings shed light on a fundamental problem: women in rural regions often have difficulty accessing full-spectrum maternity care services. The diagnosis and treatment of maternal health problems are slowed due to these obstacles. However, the potential of telehealth to overcome these geographical obstacles is clear. Through telehealth, expectant mothers in remote areas may contact obstetric professionals and receive access to a wealth of previously unavailable maternal care services. Telemedicine might provide fresh hope and better healthcare results for pregnant moms in remote locations, thus lowering severe maternal morbidity rates in these historically neglected regions.

Early risk identification. Sweeney et al. (2019) provide a unique, nurse-driven strategy to identify pregnant women at risk for severe maternal morbidity. Their findings stress the critical role of identifying and treating potential risks to mothers as soon as possible. With its potential to aid in the early detection of risk factors, telehealth stands out as a valuable tool for accomplishing this objective. Pregnant women may start talking to doctors early because of telehealth and remote consultations. This method guarantees the continuity of care necessary for early detection and treatment of high-risk pregnancies. Healthcare practitioners may more effectively monitor and assist pregnant women via telemedicine, leading to a lower incidence of severe maternal morbidity.

Postdelivery preeclampsia care. The study by Kern-Goldberger and Hirshberg (2021) focuses on the use of telehealth techniques to reduce inequalities in treating preeclampsia in the postpartum period. Preeclampsia is a potentially fatal condition that disproportionately affects underserved communities, contributing to disparities in healthcare access. By providing postpartum women with universal access to lifesaving medical care, telehealth interventions represent a promising solution. Scholars have found that telehealth platforms allow for the remote monitoring of blood pressure, the regular assessment of symptoms, and the prompt provision of medical care. These characteristics are significant for pregnant women at risk of or experiencing preeclampsia because they allow for earlier diagnosis and treatment. Healthcare providers can guarantee that no woman will go without postpartum care if they actively use telehealth to involve women in their care. Broader efforts to reduce severe maternal morbidity rates consistently reduce preeclampsia care disparities through telehealth. Health disparities that have plagued maternal health outcomes, especially among marginalized communities, have been a problem for a long time, and this study highlights the potential of telehealth to address these issues (Kern-Goldberger & Hirshberg, 2021).

Comparative analysis and implications: The potential of telehealth to reduce differences in severe maternal morbidity rates emerges as a unifying theme when comparing different sources. The spread of the COVID-19 pandemic has hastened the use of telehealth, illuminating both the challenges and the prospects for better maternal health in underprivileged areas. Both Jean-Francois et al. (2021) and Hansen et al. (2022) stress the importance of telehealth in ensuring that disadvantaged regions continue to have access to care throughout the epidemic. To fill the gaps in maternity care, telehealth allows for distant access and offers culturally appropriate treatments. Both Baranco et al. (2022) and Kern-Goldberger and Hirshberg (2021) stress the need for individualized treatment regimens to help pregnant women manage the risks associated with conditions like maternal obesity and preeclampsia. The risk of severe maternal morbidity may be reduced because of telehealth’s ability to provide individualized therapies, track patients’ progress, and provide immediate care. Both Sweeney et al. (2019) and Hansen et al. (2022) emphasize the importance of early risk identification. In regions of the country where medical facilities are few, telehealth equipment may offer round-the-clock monitoring, enabling doctors to see early warning signals and respond swiftly. Collectively, these studies show how telehealth might help minimize inequalities in the prevalence of severe maternal morbidity. Treatment in remote regions, early risk detection, improved postpartum preeclampsia treatment, and reduced hazards linked with maternal obesity are all possible thanks to telehealth. The potential of telehealth to improve maternal health outcomes and decrease the prevalence of severe maternal morbidity in underserved areas is becoming more apparent as the field develops.

 

Telehealth Interventions Targeting Low-Income Rural Populations

Research suggests that there is a lot of hope that telehealth treatments will improve maternal health in rural communities with low incomes. The effectiveness of telehealth programs targeting the healthcare requirements of pregnant women and new mothers in underprivileged regions has been the subject of many studies. Jezewski et al. (2022) stressed the significance of focused telehealth education to increase interest and acceptability among low-income older individuals. This strategy might benefit women in remote regions who are expecting or have just given birth. Similar approaches might successfully close the gap in access to prenatal and postpartum treatments by educating and creating awareness about the advantages of telemedicine for mother-child care. Childhood obesity is a problem that Barefield and Rollins (2021) examined, and that has an indirect impact on maternal health. The demographics of low-income rural regions are like those of minority, low-income, and underserved communities. The research results indicate that telehealth programs may include families, expanding possibilities for promoting children’s and mothers’ health. Sultana and Pagán (2023) focused on how telemedicine might help those in low-income communities with mental health issues, including sadness and anxiety. While the mother’s mental health was not the primary emphasis, it is a significant component of total maternal well-being. By modifying current telehealth strategies for mental health care, it may be possible to address pregnant women’s particular mental health concerns in remote areas. Considering maternal and family health, Nguyen et al. (2023) assessed rural families’ reactions to a telehealth-delivered intervention for childhood obesity. Indirectly, this underscores the need for treatments focused on mothers’ support networks. Since mother and family well-being are intertwined, telehealth programs that increase family satisfaction may benefit maternal health outcomes. In contrast, Jezewski et al. (2022) and Sultana and Pagán (2023) emphasize awareness and, more specifically, treating mental health complications, both critical to maternal health. Barefield and Rollins (2021) highlight the potential for family interaction to promote maternal health, although their focus is on treatments for childhood obesity. Nguyen et al. (2023) underline the role of family dynamics in enhancing maternal health, implying that telehealth treatments may benefit the health of both mothers and their children. Despite their varied foci, telehealth treatments for low-income rural communities are a consistent theme in the reviewed sources. Thus, these methods may be used to improve maternal health outcomes to create all-encompassing telehealth programs for prenatal and postnatal care, mental health support, and family-centered approaches.

Success Stories and Lessons Learned from Telehealth Implementation

The COVID-19 pandemic, which presented unprecedented challenges to healthcare systems worldwide and made it necessary to maintain healthcare delivery while reducing the number of in-person encounters, necessitated the rapid adoption of telehealth. These sources give insight into how telehealth has become a transformational force in healthcare, highlighting the relevance of adaptability, patient-centered care, program assessment, and the impact of technology. Abdel-Wahab et al.’s (2020) research shows that telehealth was widely used throughout the epidemic. It highlights the urgent necessity for telemedicine solutions during a public health emergency. The authors argue that telemedicine was critical to maintaining access to healthcare and reducing interruptions during the pandemic. This source highlights the capacity of healthcare systems to change in the face of emergencies. The research paper by Giacalone et al. (2022) details the lessons learned from the telehealth boom that the epidemic caused. Their findings suggested that the pandemic had shed light on the need for healthcare universality, flexibility, and the possibility of remote treatment. They contend that the lessons learned go beyond the epidemic and indicate the continued importance of telemedicine in the healthcare industry. Miyamoto et al. (2021) present an implementation case study of a telehealth center for forensic examinations of sexual assault. This research stresses the necessity of reviewing telehealth programs to guarantee their usefulness and efficiency. In 2020, Talal et al. presented the idea of telemedicine with a focus on the individual patient. Their model stresses the significance of customizing telehealth services for individual patients, especially those at risk. This article highlights the importance of patient-centered care in telehealth. The advantages and disadvantages of telehealth are widely acknowledged as factors in the evolution of healthcare delivery. Despite its many advantages, it is not always easy to make technology accessible and user-friendly for patients, particularly those from marginalized groups. The compilation of these resources highlights the achievements and lessons learned from the use of telehealth during and after the COVID-19 epidemic. It highlights the continuous relevance of telehealth in healthcare delivery and the necessity of quick adaptation, patient-centered care, and program assessment. This research also emphasizes resolving technical obstacles to guarantee everyone can access telehealth services. A game-changer in the healthcare industry, telehealth may provide light on how to improve healthcare delivery in the future.

Theoretical Framework: Applying Health Equity and Access Theories

Health equity theories and telehealth adoption: The Social Determinants of Health (SDOH) paradigm, which recognizes the importance of numerous variables in influencing health disparities, is consistent with the findings of the research by Edmiston and AlZuBi (2022) on telehealth and healthcare inequalities. Their focus on telehealth’s ability to increase access to care rings true with the SDOH framework’s mission to address systemic causes of inequitable health outcomes. Also, a recent systematic study by Anderson-Lewis et al. (2018) emphasizes the value of telehealth and other technological treatments for reaching disadvantaged communities. By allowing marginalized communities to get medical attention from afar, telehealth helps mitigate the effects of socioeconomic factors such as distance from facilities.  It is crucial to consider local healthcare infrastructure, as Talal et al. (2020) advocated in their patient-centered telemedicine framework to guarantee ready access to maternal healthcare services in underserved regions. There may be fewer healthcare inequalities if telemedicine is integrated with current infrastructure. Thus, the findings of Edmiston and AlZuBi’s report are consistent with health equity theories. Their insights are consistent with those of studies such as Anderson-Lewis et al. (2018) and Talal et al. (2020), which highlight the potential of telehealth to address social determinants, mitigate barriers, and enhance healthcare infrastructure, ultimately leading to more equitable maternal care in underserved areas.

Access theories and maternal care in rural areas: Anderson-Lewis et al. (2018) investigate access theories, providing new insight into the use of mHealth technologies in underprivileged communities. These concepts address a wide range of aspects of access, including accessibility, affordability, and acceptability. When these ideas are applied to maternity care in rural regions, it becomes clear that telehealth can increase service availability by putting patients in touch with healthcare professionals in other locations. It may alleviate financial stress by providing low-priced online doctor’s appointments. Eliminating geographical barriers and incorporating cultural considerations into care delivery are two additional benefits of telehealth that lead to its widespread adoption.

Identifying Gaps in the Literature about telehealth and maternal morbidity correlation

Limited research on maternal morbidity. Several research works, such as those by Jean-Francois et al. (2021) and Baranco et al. (2022), have highlighted the potential of telehealth in maternal healthcare. However, these studies have primarily focused on one or a few specific elements of a mother’s health, such as improving access to prenatal care. The lack of extensive, in-depth research on the prevalence of severe maternal morbidity is a glaring omission. This research does not explore the specific ways telehealth treatments may affect or lessen severe maternal morbidity, such as complications from hypertensive disorders, bleeding, or infections. While these studies contribute much to our knowledge of maternal healthcare in general, they do not address whether telehealth has a role in lowering rates of severe maternal morbidity.

Telehealth adoption metrics. According to Jezewski et al. (2022), researchers need better metrics or indicators to determine whether telehealth affects the prevalence of severe maternal morbidity. Inadequate metrics currently limit our ability to determine whether telehealth treatments contribute to lower rates of maternal morbidity. Life-threatening complications after labor may be reduced with telemedicine, such as obstetric hemorrhage, hypertension, and sepsis. Still, it is difficult to tell how effective this is without indicators concentrating on severe maternal morbidity. Therefore, this void highlights the necessity for research that specifically investigates the many factors contributing to severe maternal morbidity and how telehealth initiatives may help reduce it.

Unexplored aspects of telehealth impact on severe maternal morbidity rates.

Underlying causes of morbidity. A part of telehealth and severe maternal morbidity that has not been figured out yet is how well telehealth treatments can target and treat the root causes of health problems in mothers, such as hypertension, bleeding, and infections. Kern-Goldberger and Hirshberg (2021) represent the kind of existing research that has focused mainly on the benefits of telehealth in expanding access to care and postpartum monitoring. Studies on the causes of severe maternal morbidity are increasing, but they seldom examine how telehealth techniques might directly address the core clinical issues. To further create focused treatments for maternal health, we need a deeper understanding of the potential of telehealth in managing these core problems. Research on the efficacy of telemedicine in preventing and treating the diseases that cause severe maternal morbidity is entering unknown territory.

 Rural and underserved populations. The absence of an explicit evaluation of telehealth’s effect on maternal morbidity rates in rural and underserved groups is a significant gap in the existing corpus of research. While some studies, like that by Hansen et al. (2022), acknowledge the potential for telehealth to reduce healthcare disparities, they rarely do so in the context of maternal health outcomes. Higher rates of maternal morbidity are significant to study since they tend to occur in rural and neglected areas. Closing this knowledge gap is essential for fully grasping how telehealth might improve maternal health outcomes in areas disproportionately afflicted by severe maternal morbidity. To further design focused methods for improving maternal health, future research should emphasize exploring the direct association between telehealth treatments and maternal morbidity rates in these vulnerable locations.

Limitations of Existing Studies

Methodological Limitations. Abdel-Wahab et al. (2020) and Talal et al. (2020) point out that a significant flaw in the current corpus of research is its dependence on retrospective data analysis or observational methodologies. These methods may not be adequate for determining whether telehealth treatments affect the prevalence of maternal morbidity. There is an urgent need for prospective, controlled research to address this restriction and give more convincing data. Structured treatments with defined control groups would be used in such trials, allowing for a more accurate assessment of telehealth’s effect on the incidence of severe maternal morbidity. Adopting such rigorous study methods will help us better understand how telehealth affects maternal health outcomes, which will increase our capacity to create specific treatments and policies aimed at bettering mother health.

Short-term focus. Several studies, like Sweeney et al.’s (2019), show that current research focuses primarily on immediate results after telemedicine interventions, such as increased prenatal care availability. The long-term effects of telehealth on maternal morbidity rates have yet to be well evaluated. Future research should consider extending follow-up periods to close this gap and acquire a more comprehensive knowledge of telehealth’s effects. Researchers may learn more about the long-term impact of telemedicine on lowering severe maternal morbidity by monitoring maternal health outcomes over an extended period. The potential of telehealth to improve maternal health and alleviate long-standing inequities may be better understood with this longer time limit in mind.

Healthcare infrastructure. Talal et al. (2020) stress the importance of local healthcare infrastructure and its smooth integration with telehealth services in determining maternal morbidity rates, and this point cannot be overstated. Despite its centrality, this needs to be considered in the current literature on the effects of telehealth on maternal health. Future research should include an analysis of the local healthcare system to understand further how telemedicine might successfully lower rates of severe maternal morbidity. Researchers may learn more about the contextual aspects that may help or hurt the performance of telehealth treatments in improving maternal health outcomes by analyzing the current healthcare infrastructure, its strengths, shortcomings, and integration with telehealth technology. This all-encompassing method will illuminate the complex relationship between telehealth, healthcare infrastructure, and maternal mortality rates.

 

Synthesis and Implications

Key findings from reviewed literature: The examined literature’s synthesis sheds light on the connection between telehealth adoption and high rates of maternal morbidity in areas with low per capita income. According to the study’s primary results, telehealth can reduce health inequalities by increasing women’s access to prenatal care. Geographical isolation, lack of available healthcare services, and economic disparity can occasionally worsen maternal mortality rates in disadvantaged areas. The literature underlines the potential of telehealth and the need for further research, better study designs, and longer-term outcome evaluations.

Implications for policy, practice, and future research. These results have far-reaching consequences for practice, policy, and future study. To reduce inequalities in maternal morbidity, policymakers should prioritize incorporating telehealth into initiatives for providing maternity care, particularly in rural regions. Telehealth may help healthcare providers detect risks sooner, intervene sooner, and expand patient access to services. Controlled, prospective studies that explicitly examine the effect of telemedicine on severe maternal morbidity rates, resolve methodological difficulties, and assess long-term results are needed for future research.

Potential pathways for addressing maternal morbidity disparities through telehealth. Telehealth might be used to reduce maternal morbidity inequalities in a wide variety of ways. By connecting patients in remote areas with experts, telehealth may help improve access to treatment and reduce health disparities. It may be used for remote monitoring, early risk assessment, and intervention to reduce maternal morbidity. Moreover, telemedicine may educate patients, encourage self-care, and shorten the time between diagnosis and treatment. Addressing inequalities in maternal morbidity requires incorporating telemedicine into existing healthcare infrastructure and guaranteeing affordability.

 

Literature Search Strategy

A rigorous and comprehensive literature search method is required to explore the relationship between telehealth adoption and severe maternal morbidity rates in low-income rural areas. This attempt is based on searching for contemporary, relevant, and peer-reviewed materials pertinent to the study’s emphasis and aims. The literature search technique casts a broad net while adhering to a strict selection procedure. Both internet databases and university libraries will be investigated for access to various intellectual resources. Leading databases such as PubMed, MEDLINE, CINAHL, and Web of Science will be helpful to archives of pertinent research publications, providing a comprehensive understanding of the topic. The selected search phrases will guide lights as this research navigates the vast number of literature sources. To achieve specific outcomes, terms such as “telehealth adoption,” “maternal morbidity rates,” “low-income rural populations,” “United States,” and variants will be painstakingly used. A sophisticated mix of Boolean operators, such as “AND” and “OR” will allow for a more precise investigation of the relationships between these critical ideas.

Given the fast-changing world of healthcare and technology, the emphasis will be mostly on work published within the previous five years. This timetable assures the incorporation of recent advances in telehealth methods and current awareness of maternal health problems. The conscious decision to highlight contemporary literature consistently captures the most recent advancements and ideas published for the past 5 years.  As Leedy and Ormrod (2019) suggest regarding effective literature search, the literature search will emphasize peer-reviewed materials in line with academic standards. This procedure guarantees that the research has undergone a thorough review by subject-matter experts, giving the data acquired credibility and reliability. Striving to include 50% or more current and peer-reviewed references strengthens the study’s commitment to academic quality. This literature search technique is dynamic, evolving coordinated with the study’s growth and depth. Continuous communication with the academic chair and advisers shapes the strategy’s trajectory, aligning it with the study’s evolving emphasis and methodological framework (Leedy & Ormrod, 2019). The literature search strategy seeks to be an ever-changing compass that directs the research toward an in-depth comprehension of the correlation between telehealth adoption and severe maternal morbidity rates in low-income rural populations in the United States by remaining adaptable and tailored to the subject’s distinct contours.

 

 

Chapter 3: Methodology

Introduction

This study aims to investigate the relationship between telehealth adoption and severe maternal morbidity (SMM) rates among low-income rural populations in the United States. Despite the potential benefits of telehealth in improving healthcare access and maternal health outcomes, there is a lack of comprehensive research examining the impact of telehealth adoption on SMM rates, particularly in underserved rural communities. The methodology outlined in this chapter is carefully designed to address this gap and provide insights into the complex interplay between telehealth utilization and SMM rates among this vulnerable population.

Ensuring the alignment between the study’s objectives, research questions, and the proposed methodology is crucial to obtaining meaningful and actionable findings. This chapter describes a mixed-methods approach that combines quantitative and qualitative techniques to comprehensively investigate the relationship between telehealth adoption and SMM rates. The quantitative component will examine the statistical trends and patterns, while the qualitative component will explore the barriers, facilitators, and lived experiences related to telehealth utilization and maternal health outcomes. By integrating these complementary approaches, the study aims to provide a holistic understanding of the research problem and contribute to the development of evidence-based strategies for improving maternal healthcare in low-income rural areas.

Problem Statement

across the United States underscores the significance of this investigation. The prevailing research landscape predominantly revolves around SMM within broad contexts or specific minority groups, leaving a noticeable void in comprehending the nuanced challenges of low-income pregnant individuals residing in rural settings. This stark research gap comes to the fore through an exhaustive literature review, distinctly revealing the necessity for in-depth studies that scrutinize the intricate dynamics linking telehealth adoption, healthcare access, and SMM rates, explicitly focusing on low-income residents within rural regions.

Purpose Statement

This research aims to bridge the identified gap by elucidating the correlation between Telehealth Adoption and Severe Maternal Morbidity (SMM) rates among women inhabiting low-income rural settings within the United States. This endeavor signifies an unwavering commitment and an earnest intent to discern the causal determinants and efficacious interventions capable of curbing the ascending trajectory of SMM rates. By doing so, the research aspires to pave the path for elevated well-being within this vulnerable demographic by fostering healthier maternal outcomes. At its core, this study aims to contribute to a broader comprehension of the intricate fabric of SMM by meticulously scrutinizing its manifestations within the unique tapestry of low-income rural communities. This comprehensive inquiry is the bedrock for formulating evidence-driven policies and interventions, functioning as a transformative force advancing maternal health. This research bestows a profound agency upon stakeholders by illuminating the nuanced intricacies of SMM within underserved rural landscapes. With better knowledge, stakeholders may devise tailored strategies to address this population’s difficulties. This deliberate alignment of strategy and demographic context results in a comprehensive approach positioned to untangle the knots of inequitable healthcare access, ushering in higher outcomes for both the mother’s health and the baby’s well-being.

Research Model Narrative

The study uses a rigorous quantitative method that is precisely planned to evaluate the relationship between Telehealth Adoption and Severe Maternal Morbidity (SMM) rates in low-income rural areas. This methodological decision is consistent with the study goal, emphasizing numerical analysis to decipher the complex link between telehealth adoption and maternal health outcomes. The study approach systematically gathers and analyzes quantitative data drawn from well-crafted questionnaires and rigorously inspected medical records. The procedure guarantees that information relevant to the study topic is extracted ethically and precisely. This research uses quantitative data to look deeply into the statistical trends and patterns that impact SMM rates. These quantitative findings provide the groundwork for evidence-based judgments and appropriate treatments. The study technique prioritizes numerical accuracy, offering insight into the unique processes that drive the relationship between telehealth uptake and SMM rates. This quantitative approach lays the way for a thorough understanding of the issue at hand, allowing for the development of focused interventions that successfully address the unique problems the low-income rural population encounters. This technique enables the study to add substantially to the dialogue around maternal health outcomes and telehealth adoption strategies by meticulously analyzing data patterns.

Chapter Overview

This chapter rigorously delineates the methodological blueprint established to untangle the complicated association between telehealth adoption and Severe Maternal Morbidity (SMM) rates in low-income rural areas while strictly following the study parameters specified. The technique aligns well with the study’s goal, stressing a robust quantitative approach to deconstruct the association between telehealth adoption and maternal health outcomes. The study’s methodology is based on the systematic gathering and rigorous examination of quantitative data. The ethical delivery of well-structured questionnaires and a comprehensive medical data analysis support this technique. The quantitative data from these sources provides a solid platform for thoroughly investigating statistical trends and patterns underlying the association between telehealth uptake and SMM rates. This study intends to outline specific numerical practices that will influence evidence-based judgments via thorough quantitative analysis. Based on a large quantitative dataset, these findings establish the framework for prospective interventions to reduce SMM rates in low-income rural areas. This research uses quantitative methods to substantially add to the ongoing conversation on maternal health outcomes and the value of telehealth adoption. The results of this study provide essential information that politicians and healthcare providers may use to create programs tailored to the needs of people living in rural areas with low incomes.

Research Methodology and Design

A precisely designed sequential explanatory strategy was used to study the complicated association between telehealth usage and Severe Maternal Morbidity (SMM) rates in low-income rural regions. This strategy adheres to the standards perfectly, relying entirely on quantitative approaches. Wilson (2016) confirms the complete character of this methodological synthesis, emphasizing the importance of this complex fusion in gaining a holistic understanding. This method uncovers relevant patterns and connections by combining structured questionnaires with medical record checks. Furthermore, qualitative interviews with healthcare specialists and pregnant women unearth personal narratives that deepen understanding (Wilson, 2016). This methodological alignment is consistent with Creswell’s (2014) viewpoint, which advocates for mixed-methods research as an effective tool for navigating the intricacies of phenomena. The selected strategy avoids the limits inherent in exclusively quantitative or qualitative approaches, resulting in data triangulation that provides a complete view of SMM trends and healthcare usage patterns (Jamshed, 2014). Following Creswell and Plano Clark’s (2018) advice, the methodological attempt employs a sequential explanatory technique. This method is consistent with the study design, which emphasizes quantitative data while encouraging the discovery of patterns and connections through standardized questionnaires and rigorous analysis of medical records. Following that, qualitative interviews dive into firsthand experiences, providing subtle insights that supplement the results. While other designs, such as solely quantitative cross-sectional research or qualitative grounded theory, were investigated, the sequential explanatory design emerged as the best match. This choice is consistent with Daguay-James and Bulusan’s (2020) viewpoint, attesting to the usefulness of this strategy in balancing the benefits of both methods. As a result, the sequential explanatory technique is set to explore the complex relationship between telehealth usage and SMM rates in low-income rural regions (Daguay-James & Bulusan, 2020).

Role of the Researcher

As the principal investigator, I am committed to maintaining ethical standards and objectivity while negotiating the complex link between telehealth usage and Severe Maternal Morbidity (SMM) rates in low-income rural settings. My interactions with participants are characterized by respect and empathy, highlighting the confidentiality and trust necessary for successful study conclusions. My tasks at hand will include the rigorous collection of quantitative and qualitative data. I am prepared to deliver systematically organized surveys for the quantitative aspect, assuring accuracy in data acquisition. Meanwhile, I will conduct in-depth interviews to allow participants to tell their real stories. Throughout the study process, I analyze objective data, balancing quantitative approaches with qualitative subtleties. This integrated method provides a comprehensive understanding, considering data patterns and participant viewpoints. My ultimate objective is to find underlying trends and insights contributing to a thorough understanding of the connection between telehealth access and SMM rates. This comprehensive knowledge is the foundation for developing evidence-based treatments with the overriding objective of improving maternal health outcomes in low-income rural areas.

Population and Sample Selection

This research aims to decipher the complex relationship between telehealth usage and Severe Maternal Morbidity (SMM) rates among low-income rural communities in Appalachia, the Mississippi Delta, and distant agricultural towns. This demographic alignment guarantees that the study subject is thoroughly explored. The study attempts to unravel how healthcare access affects the incidence of SMM by concentrating on this convergence of low-income and rural features. The sample has been painstakingly designed to reflect the different fabrics of low-income pregnant women aged eighteen and above from various rural locations. This tactical strategy ensures geographic, socioeconomic, and cultural diversity. Individuals are further subdivided based on area, race, and access to prenatal care to enhance the sample. This tiered method adds depth to the analysis and allows for a more sophisticated view of SMM patterns. A reliable power analysis informs the selection of ideal quantitative sample sizes by balancing statistical significance with practical practicality. A sample of 50-200 people is chosen for the quantitative phase, while 30-40 people are included in the qualitative phase, allowing for a detailed study of firsthand experiences. This mixed-methods study is set to shed light on the complex link between telehealth usage and SMM rates. The research stresses participants’ rights and well-being following high ethical standards. Informed permission, confidentiality, and participant privacy are fundamental foundations for trust and safety throughout the study.

Instrumentation

This section outlines the diverse array of instruments this research employs to glean comprehensive insights. Both primary and secondary data collection methods were harnessed to ensure a robust understanding of the correlation between telehealth adoption and severe maternal morbidity rates in low-income rural populations.

Secondary data. Data from publicly available archives, such as national healthcare databases and vital statistics records, will be used in this study. These statistics will be used to track how the public deals with their healthcare now provide a significant contextual framework that includes patterns and trends in maternal health. While these factors are not designed to answer the study’s research questions, they will provide a context for understanding the telehealth adoption and severe maternal morbidity rates in low-income rural populations.

Published instruments. The Healthcare Access and Utilization Questionnaire (HAUQ) will be modified to evaluate healthcare usage patterns. The validity and reliability of this tool, initially developed by Andersen and Aday (1978), have been shown via its widespread use in various populations. This study’s adaptation of the instrument included painstaking changes to reflect better the unique difficulties faced by those living in rural areas with low incomes (Allanore et al., 2020). According to Cu et al. (2021), these adjustments ensure the questions were more in tune with the complex realities experienced by the intended sample, making the instrument a powerful resource for elucidating the telehealth adoption and severe maternal morbidity rates in low-income rural populations (Cu et al., 2021).

Interview protocols. This research will obtain quantitative data via semi-structured interviews. The interview approach was carefully designed, utilizing phenomenological concepts to provide open-ended questions, allowing for in-depth narrative analysis. This method aims to understand the participants’ histories and points of view thoroughly. The iterative creation of these questions was supervised by expert advice, assuring agreement with research aims and participant sensitivities. By incorporating these ideas, the research will capture an entire tapestry of insights into the delicate correlation between telehealth adoption and severe maternal morbidity rates in low-income rural populations.

Materials and apparatus. Survey tools and interview methodologies will be subjected to extensive field and pilot testing. Feedback from various possible participants enhanced clarity, readability, and relevance. This stage was critical in eliminating ambiguities and improving question phrasing for improved comprehension and engagement. Sony ICD-UX560 digital audio recorders were used for interviews to capture spontaneity while maintaining anonymity. These factors sustain stringent data-gathering requirements by balancing mobility, audio quality, and user-friendliness. These careful approaches increase the study’s validity, providing solid insights into the complex relationship between telehealth adoption and severe maternal morbidity rates in low-income rural populations.

 

Appendix A shows permission to use the instrument(s) above.

Table 1: Instruments Matrix

Instruments	Construct / RQ Examined	Sample Size and Rationale	Traits of Group/ Subgroup	Permissions
Questionnaire	Healthcare Utilization – RQ1	600 – Determined through power analysis	Low-income pregnant individuals	Author permission TBD: site permission granted TBD (Appendix A)
Interview	Qualitative Insights – RQ2	30 – Achieve thematic saturation	Pregnant individuals aged 18 and above	Researcher-developed; IRB approval TBD (Appendix B)
Focus Group	Barriers to Access – RQ3	4 groups, 6 members each – Purposive	Healthcare professionals and policymakers	Researcher-developed; IRB approval TBD (Appendix C)

 

 

 

Instrument Development Process

Quantitative instrument (Healthcare Access and Utilization Questionnaire – HAUQ). The Healthcare Access and Utilization Questionnaire (HAUQ) is a quantitative tool whose careful creation followed strict criteria to assure its integrity, validity, and reliability. Due to the complexity and delicate nature of the study project, it was decided that researchers would not use any self-developed equipment. Instead, the HAUQ, which has been used successfully in the past, was modified. The instrument’s proven dependability and generalizability across distinct groups led to its selection; its creators, Andersen and Aday (1978), were responsible for both. Its selection is an intentional action taken to guarantee a reliable data collection process, and it highlights the dedication to producing credible and meaningful insights into the intricate connection between telehealth adoption and severe maternal morbidity rates in low-income rural populations (Cu et al., 2021).

Development process.

1. Literature review.A literature assessment validated the HAUQ’s compatibility with the study’s aims and environment. The tool’s applicability was ensured by adjusting to meet the problems of low-income rural pregnant women. The research aims to improve knowledge of the relationship between telehealth adoption and severe maternal morbidity rates in low-income rural populations.
2. Expert consultation.Collaboration with maternal health and healthcare access professionals verified the HAUQ as a suitable tool. These interactions guaranteed that the study’s objectives and contextual relevance for low-income rural communities were met. Expert advice drove changes to improve the instrument’s applicability for capturing the intricacies of healthcare usage among pregnant women with low incomes in rural locations. This iterative approach reinforced the study’s dedication to rigorous methodology, resulting in a precisely designed HAUQ that successfully investigates the nuanced association between telehealth adoption and severe maternal morbidity rates in low-income rural populations.

1. Item selection and adaptation. Adapting the first HAUQ components focused on personalizing the instrument for the intended audience. Strategic changes were made to the survey’s questions to effectively represent the healthcare issues of low-income pregnant women in rural locations. The question recalibration ensured that the survey appropriately reflected the healthcare access challenges experienced in low-resource rural areas. The primary goal of the research was to improve healthcare consumption and reduce Severe Maternal Morbidity (SMM) rates by improving an existing instrument to correspond with the complicated reality of this unique demographic. This purposeful modification emphasizes the dedication to accuracy and relevance in investigating healthcare dynamics among low-income rural persons.

 Quantitative instrument (semi-structured interview protocol). A semi-structured interview approach will be designed following quantitative inquiry standards to capitalize on qualitative benefits. According to Hendren et al. (2023), this method allows for subtle insights and complete knowledge. When linked with established concepts, participants’ narratives give substantial insight into Severe Maternal Morbidity (SMM) in low-income rural areas. This narrative technique allows for an in-depth investigation of causes and consequences. The creation of the interview approach demonstrates the researchers’ dedication to a rigorous methodology and productive inquiry (Hendren et al., 2023). The research hopes to acquire significant insights into the subtle dynamics of SMM in disadvantaged rural areas by adopting this strategy.

Development process.

1. Phenomenological approach. The interview guide will be designed to include free-form questions in the spirit of the phenomenological method. The setting was purposefully made to encourage an in-depth narrative examination of individual experiences by the participants. The phenomenological approach sheds light on the complex relationship between access to healthcare and rates of Severe Maternal Morbidity (SMM) in low-income rural areas. The study’s emphasis on free-form questions reflects a dedication to getting to the heart of this group’s experiences and drawing meaningful conclusions. This methodological decision emphasizes the study’s commitment to include various viewpoints and enables a thorough investigation of the multifaceted subject matter.
2. Professional input. The interview questions will be significantly improved through iterative talks with professionals in quantitative data collection. These deliberations aimed to ensure the questions asked were appropriate given the study’s goals and, more crucially, the participants’ backgrounds and experiences. The interview questions were crafted with input from these experts to enable a deep dive into the relationship between healthcare access and SMM rates in low-income rural communities. The iteration process shows how committed the researchers were to methodological rigor and how much they valued the unique experiences of each participant.
3. Iterative refinement. Multiple rounds of iteration and expert input will be used to fine-tune the interview methodology. This iterative method was used to build in-depth questions that effectively fulfill the research’s aims. Healthcare use and Severe Maternal Morbidity (SMM) rates in low-income rural populations were studied, and the protocol was constructed with the help of insights and skills from qualitative research professionals. The focus on accuracy and applicability led to each revision, resulting in a collection of questions that will generate thoughtful answers from the study’s participants. This process of methodological improvement exemplifies the study’s commitment to generating deep and nuanced insights, highlights the depth of participants’ accounts, and strengthens the reliability of the findings.

Pilot Study / Field Testing

A planned pilot trial will be deployed to evaluate the survey’s clarity and readability. Participants in this pilot study are those who are already familiar to the researcher but are kept separate from the whole sample. This pilot study aims to rigorously assess the survey questions’ practicality, checking whether they are understandable and effectively collecting the desired information. This preliminary review aims to help the researcher see any underlying ambiguities, difficulties, or possible points of misunderstanding in the survey before it is administered. The pilot study’s findings will guide the survey’s subsequent iterations. This iterative approach aims to refine the survey’s wording and improve quality. This preemptive action exemplifies the researcher’s unwavering dedication to methodological accuracy by preventing problems before they arise. The goal of this research was to provide solid and insightful conclusions, and this pilot study was conducted with the foresight to increase the dependability and validity of the data gathered during the primary research effort.

Variables and operational definitions.

Independent Variable: Telehealth Adoption

Definition: Telehealth adoption refers to the extent to which telehealth technologies and services are utilized by healthcare providers and patients in delivering and receiving medical care remotely.

Operationalization: Telehealth adoption will be measured using a composite score derived from multiple items assessing factors such as:

• Availability and utilization of telehealth services (e.g., video consultations, remote monitoring)
• Healthcare providers’ familiarity and comfort with telehealth technologies
• Patients’ access to and acceptance of telehealth modalities
• Integration of telehealth into existing healthcare systems and workflows

Dependent Variable: Severe Maternal Morbidity (SMM) Rates

Definition: Severe maternal morbidity (SMM) encompasses life-threatening complications and medical interventions during pregnancy, childbirth, and the postpartum period that pose substantial risks to maternal health.

Operationalization: SMM rates will be measured using a composite score based on the presence and severity of specific pregnancy-related complications and medical conditions, such as:

• Hemorrhage or blood transfusion
• Hypertensive disorders (e.g., preeclampsia, eclampsia)
• Acute renal failure
• Sepsis or systemic infections
• Respiratory distress
• Cardiac complications

Demographics and control variables.

Justification: Age is a critical demographic factor influencing healthcare utilization patterns and SMM rates among pregnant individuals.

Measurement: Age will be measured as a continuous variable, capturing participants’ age in years.

Source: Survey responses provided by participants.

Level of measurement: Interval.

2. Income Level.

Justification: Income level is essential in understanding the socioeconomic context and potential barriers to healthcare access.

Measurement: Income level will be measured through self-reported annual household income.

Source: Survey responses provided by participants.

Level of measurement: Ordinal.

3. Education level.

Justification: Education level can impact health literacy and the ability to navigate healthcare systems effectively.

Measurement: Education level will be measured as a categorical variable capturing participants’ highest level of education.

Source: Survey responses provided by participants.

Level of Measurement: Nominal.

 

Table

 

Variable	Definition	Operationalization	Data Source	Level of Measurement
Telehealth Adoption (IV)	Extent of utilization of telehealth technologies and services in healthcare delivery	Composite score based on availability, utilization, provider familiarity, patient acceptance, integration	Survey	Continuous
Severe Maternal Morbidity (SMM) Rates (DV)	Life-threatening complications and interventions during pregnancy, childbirth, and postpartum	Composite score based on presence and severity of complications (e.g., hemorrhage, hypertensive disorders, sepsis)	Secondary data sources	Continuous
Age (CV)	Participant’s age	Years	Survey	Ratio
Income Level (CV)	Household income	Self-reported annual income	Survey	Ordinal
Education Level (CV)	Highest level of education attained	Categorical options (e.g., high school, college, graduate)	Survey	Ordinal
Geographic Location (CV)	Specific rural region	Categorical options (e.g., Appalachia, Mississippi Delta, remote farming communities)	Survey	Nominal
Access to Prenatal Care (CV)	Availability and utilization of prenatal care services	Composite score based on frequency of visits, barriers to access	Survey	Continuous
Comorbidities (CV)	Presence of coexisting medical conditions	Binary (yes/no) for conditions (e.g., diabetes, obesity)	Survey, Secondary data	Nominal

Note: IV = Independent Variable, DV = Dependent Variable, CV = Control Variable

 

 

 

Data Collection

To effectively investigate the relationship between telehealth adoption and severe maternal morbidity (SMM) rates in low-income rural populations, a mixed-methods research design will be employed. This approach combines quantitative and qualitative techniques, allowing for a comprehensive understanding of the research problem.

 

The quantitative component will involve a cross-sectional survey design to examine the statistical associations between telehealth adoption and SMM rates. This approach is suitable for capturing a snapshot of the current state of telehealth utilization and its potential impact on maternal health outcomes.

Data collection instruments:

1. A validated survey instrument will be developed to measure telehealth adoption, incorporating items related to availability, utilization, provider familiarity, patient acceptance, and integration into healthcare systems.
2. Secondary data sources, such as national healthcare databases and vital statistics records, will be utilized to obtain information on SMM rates and related maternal health indicators.

A stratified random sampling strategy will be employed to ensure adequate representation of low-income rural populations from various geographic regions. The sample size will be determined through power analysis to ensure sufficient statistical power for detecting meaningful effects.

 

1. Qualitative Approach

The qualitative component will involve semi-structured interviews and focus groups to explore barriers and facilitators to telehealth adoption, as well as the lived experiences of women who have experienced severe maternal morbidity.

Development and validation of qualitative data collection instruments:

2. Pilot testing and cognitive interviewing will be conducted to ensure the clarity and relevance of the questions and to identify potential areas for improvement.
3. Mixed-Methods Integration

An explanatory sequential mixed-methods design will be employed, where the quantitative data collection and analysis will be followed by the qualitative component. The qualitative findings will be used to provide context and deeper insights into the quantitative results. This design is suitable for the study as it allows for an initial examination of the statistical relationships between telehealth adoption and SMM rates, followed by an exploration of the underlying mechanisms, barriers, and experiences that shape these relationships.

Data Collection Procedures

The data collection for this mixed methods study will take both quantitative and qualitative approaches and with such actions we hope to have comprehensive assessment on the impact of telehealth adoption on SMM rates among the low-income rural populations. These study protocols will be rigorously authored and executed to ensure we obtain a sufficiently large dataset that will enable us to arrive at dependable data.
Quantitative Data Collection
Survey Development: Through the development of a validated survey instrument, measures will be applied to various themes related to telehealth adoption, such as availability, usage, providers familiarity, patients’ acceptance, and systematic integration. In addition, the survey will help to gather demographic complaints and healthcare-seeking behavior.
Sampling Strategy: A stratified approach, including subgroups of households from various regions by size and shape, will be employed to represent the rural low-income population from different geographic regions (Yazdi et al., 2021). The strategy involves the assumption of participants into homogeneous sub-groups according to relevant characteristics, such as geographical location, after which a random selection process is applied to the sub-groups (Mweshi & Sakyi, 2020).
Survey Administration: Survey will be done both electronically or in person depending on whether the participants would prefer that way or not. The method of survey should accommodate the participants depending on their availability. The response rates will be increased as much as possible with regular reminders, incentives, and personalized correspondence.
Secondary Data Collection: Primary databases and vital stats records will be queries for secondary data to monitor trends in SMM and maternal health indicators. Such databases will duplicate other questions posed during the survey and are meant to add more context (Brown et al., 2021).
Qualitative Data Collection:
Interview and Focus Group Development: Semi-structured schedule and focus group protocols will be designed with weighed principles of qualitative research and with the opinion from subject matter experts. In these protocols, we will study how telehealth is being adopted and oppose factors that limit its use as well as we will look deeper into the weekly.
Sampling Strategy: Being aimed to receive sample of participants for interviews and focus group will be used. The aim of this will be to get unbiased opinions and experiences (Nyumba et al., 2018). We will endeavor to recruit people who are not only service providers but also different categories of mothers who have varying level of telemedicine utilization and maternal health outcomes.
Data Collection Sessions: It can be carried out via one-on-one interviews or group discussions, using in-person or virtual modes as per the consent of the participants and considering the logistics. We will ask for permission before recording and transcribe the information verbatim, it will be analyzed afterwards.
Pilot Testing: Before full-data collection, interview and focus group protocols will be piloted, and cognitive interviews will be performed to ensure precision, pertinence and cultural adequacy of the questions.
The collection process of these data will determine the overall picture of telehealth adoption. It will also determine the types of socio-medical inequities that are associated with its use vis-a-vis the low-income rural populations (Ohioma, 2023). This will help with gaining more insight into the intricate realities of the socio-medical inequalities.

Participant Recruitment and Selection Criteria

Participant recruitment for this study will adhere to specific criteria designed to ensure the representation of low-income rural populations facing maternal health challenges. The selection process will target individuals meeting the following eligibility criteria:
Residence in Low-Income Rural Areas: Applicants are required to live in selected rural areas known to have low-income citizens during the program period. Such areas may include, but are not limited to, the Appalachia region, Mississippi Delta region, and farms located in remote areas (Ohioma, 2023). Hence, due to this criterion, participants are selected from disadvantaged populations where disparities in health access and maternal health outcomes persist because of geographical and socioeconomic factors.
Pregnancy Status or Recent Maternal Experience: Women aged 18 or above either expecting or who recently experienced SMM form part of the eligible candidates if they do not have any of the eligibility exclusions mentioned below. Mothers-to-be and those with recent experiences of childbirth will be of invaluable importance as participants, offering opinions on the way telehealth services are being used for the duration of pregnancy and birth, and their influence on maternal health outcomes.
Income Level: Participants must be either categorized as low-income households, or above the federal poverty guidelines threshold, or any other rural income levels. This criterion is thus essential to grasp the situation as seen by people who lack affordability entailing healthcare services infrastructures.
Willingness to Participate: For participation in the study, although bound by their free will to accept or decline, prospective participants are obliged to provide written informed consent. They will be detailed about the study purpose, procedures, risks and benefits they have ahead before giving their consent to take part of the research.
The recruitment campaign will be broader and will utilize multiple channels, such as medical institutions and rural healthcare centers, non-governmental organizations, social media websites and local contacts. Strategies like tailored outreach, community partnerships, and incentivized participation will be used to ensure that the target population sign up, as well as participate in the optimum magnitude (Taghikhah et al., 2024). Given the selection criteria adherence and using multiple recruitment approaches, researchers are only able to select a sample that mimics the expressed experiences and views of low-income population residing in rural areas living with severe maternal morbidity.

Data Management and Storage

The quality of data collection in research depends on how thorough the data management and storage procedures are, especially on issues of data quality and availability (Fan & Geerts, 2022). The following outlines the data management and storage protocols for both quantitative and qualitative data collected in this mixed-methods study: The following outlines the data management and storage protocols for both quantitative and qualitative data collected in this mixed-methods study:
Quantitative Data Management
Data Entry: These responses including the quantitative part will be entered into a secure electronic database using the standardized data entry protocol to make mistake-free and consistent information.
Data Cleaning: Data cleaning will precede analysis. Errors or outliers will be exposed by the process and identified precisely (Van der Loo & De Jonge, 2018). This will be accomplished by building in the data validation controls and checking against the survey sources.
Data Coding: The relevant survey questions will be designed with the purpose of being coded in line with predetermined schemes to facilitate data inquiry and analysis (Elliott, 2018). These codes will represent each category or responses depending on the set of operations that will ease data management by just interpreting and manipulating information.
Data Security: Extensive measures will be done to maintain the privacy and security of the quantitative data we collect. A password will be issued to the online website, and thus will be restricted to users only (Rafiq et al., 2022). The data encryption and password protection will be employed to deter unauthorized access.
Backup Procedures: The included quantitative dataset will be backed up on a routine basis as a contingency for technical failures or other unexpected reasons. Duped copies will be protected in the multiple storage locations -Cloud based servers and offline device storage.
Qualitative Data Management
Transcription: Interviews and focus groups will be audio recorded by research professionals who will later transcribe them verbatim. Such records will enable us to track the changes and understand the dynamics of these patterns better (Tracy, 2019). Transcripts will be checked for assembling rhythms and completeness and then, people will move forward to the analysis.
Data Coding: Qualitative data analysis tools (NVivo) will be applied to aid the responses in formatting and organizing (Maher et al., 2018). Codes will be used as part of the process of text segmentation that takes place based on what is emerging as the significant themes and patterns that have been discovered by means of analysis.
Data Security: Like quantitative data, the process of data security of qualitative data that involves confidentiality will be undertaken keenly. Audio recordings and transcripts will be restricted and available only to authorized individuals, and protected encryption methods will be used for storing/transmitting sensitive information.
Backup Procedures: Backups of qualitative data (audio clips and transcripts) will be produced frequently and safely after being saved. Many copies of the data will be kept because they help avoid its destruction or corruption (McMullin, 2023). Safety for this data process will the priority during submission and storing process.
Strong data management and storage strategy will be developed. They will guarantee data quality and security for the result presented at the end of the study (). The implementation of data management processes will be in line with research data management best practice standards, and it will set the ground to protect participant confidentiality and research integrity by following ethical and regulatory guidelines.

 

Data Analysis

 

 

 

 

1. Qualitative Analysis

Thematic analysis will be employed to identify recurring patterns and themes in the qualitative data from interviews and focus groups. Coding and analysis will be conducted using qualitative data analysis software (e.g., NVivo) to facilitate the organization and management of the data. The analysis will focus on identifying barriers and facilitators to telehealth adoption, as well as exploring the experiences and perspectives of women who have experienced severe maternal morbidity.

1. Integration of Quantitative and Qualitative Findings

The quantitative and qualitative findings will be integrated using a joint display approach, where the statistical results and thematic findings are presented side-by-side for comparison and interpretation. This integration will allow for a comprehensive understanding of the relationship between telehealth adoption and SMM rates, as well as the contextual factors and lived experiences that shape this relationship. The integrated findings will be used to develop evidence-based recommendations and strategies for improving telehealth adoption and maternal health outcomes in low-income rural populations.

 

Software. Quantitative data will be analyzed using SPSS, while qualitative data will be analyzed using MAXQDA. These programs have been selected for their capacity to rigorously examine the research topics by evaluating the obtained data. While MAXQDA will help with coding and thematic analysis of qualitative insights, SPSS will assist with statistical testing, regression analysis, and evaluation of control variable interaction. Combining the finest characteristics of both programs, this method sheds light on the complicated relationship between healthcare access and Severe Maternal Morbidity (SMM) rates in low-income, rural communities.

 

 

Analysis	Purpose	Data Source	Software
Descriptive Statistics	Summarize sample characteristics, telehealth adoption levels, SMM rates	Secondary data sources	SPSS
Multiple	Examine the relationship between telehealth adoption and SMM rates, controlling for confounding variables	Survey data, Secondary data sources	SPSS
Moderation Analysis	Assess whether demographic/contextual factors moderate the relationship between telehealth adoption and SMM rates	Survey data, Secondary data sources	SPSS (PROCESS macro)
Thematic Analysis	Identify patterns and themes related to barriers/facilitators of telehealth adoption and experiences of SMM	Interview/focus group transcripts	NVivo
Joint Display	Integrate quantitative and qualitative findings for comprehensive understanding	Survey data, secondary data, interview/focus group transcripts	N/A

 

Assumptions

The study is built upon several key assumptions that underlie the study population and design, ensuring the validity and reliability of the findings. These assumptions are integral to the successful execution of the research objectives.

1. It is assumed that the survey instruments and interview protocols accurately capture the constructs of telehealth adoption, healthcare utilization patterns, and maternal health outcomes.
2. It is assumed that participants will provide honest and accurate responses to the survey and interview questions, without significant social desirability bias.
3. It is assumed that the secondary data sources used to obtain information on SMM rates and related maternal health indicators are reliable and representative of the target population.
4. It is assumed that the sampling strategy will result in a representative sample of low-income rural populations, allowing for the generalizability of the findings.

 

Limitations

• Sampling bias. The study’s reliance on a convenience sampling strategy could introduce sampling bias, potentially limiting the generalizability of the results. To mitigate this, the research will employ a diverse recruitment approach, engaging with multiple rural regions across the United States and ensuring a broad representation of low-income pregnant individuals.
• Self-report bias. The reliance on self-reported data for quantitative and qualitative aspects could introduce recall and social desirability biases. To address this, participants will be encouraged to provide honest and accurate responses, and the survey instruments and interview protocols will be designed to minimize leading questions.
• Missing data and nonresponse rates. The possibility of missing data and nonresponse rates in both survey and interview data could impact the completeness of the dataset. To manage this, rigorous data collection procedures will be implemented, and missing data will be addressed through appropriate statistical techniques during data analysis.
• Cross-sectional design: The cross-sectional nature of the study design restricts the ability to establish causality between healthcare utilization and Severe Maternal Morbidity (SMM) rates. To enhance causal inference, future longitudinal research could be considered.
• Instrument limitations. While the HAUQ and interview protocol have been adapted for relevance, they may only capture some nuances of low-income rural contexts. Open-ended questions in the interview protocol will be designed to extract rich qualitative insights and mitigate potential limitations.
• External Factors: External factors such as policy changes or socioeconomic shifts could impact the study’s findings over time. The research will address this by documenting any significant external influences during the data collection.
• Participant honesty and social desirability bias. Given the topic’s sensitivity, participants might be inclined to provide socially desirable responses or withhold certain information. Efforts will be made to foster a comfortable and non-judgmental environment during interviews and surveys, promoting honest responses.
• Participant Fatigue: Participants might experience survey or interview fatigue due to the length and depth of the data collection process. To mitigate this, surveys will be designed to be concise, and interview sessions will be spaced to prevent exhaustion.
• Limited secondary data scope. While secondary data sources provide contextual information, they may need more granularity specific to the study’s objectives. To overcome this limitation, the research will carefully interpret and triangulate secondary data with primary data.

Delimitations

This study operates within specific boundaries and delimitations to ensure a focused investigation aligned with the research objectives. These delimitations provide clarity, relevance, and applicability to the existing literature, theoretical framework, problem statement, and research questions.

• Geographic scope. The research focuses on low-income rural populations in selected regions of the United States, including the Appalachian region, the Mississippi Delta, and remote farming communities. These regions were chosen due to their distinct socioeconomic, geographical, and cultural characteristics, reflecting the study’s emphasis on understanding Severe Maternal Morbidity (SMM) dynamics in diverse rural settings.
• Age and gender. The study targets low-income pregnant individuals aged 18 and above. While acknowledging the importance of maternal health in various demographic groups, this delimitation allows for a deep dive into the unique challenges pregnant individuals face in rural areas with low incomes.
• Healthcare access and SMM relationship. The primary focus of the study is to explore the intricate interplay between healthcare utilization and SMM rates among low-income rural populations. While recognizing the broader factors influencing maternal health outcomes, the research delimits its scope to the specific relationship between healthcare access and SMM rates within the defined demographic.
• Quantitative and qualitative mix. The study adopts a mixed-methods approach to understand the research phenomenon comprehensively. This delimitation ensures that quantitative trends and qualitative narratives are captured, holistically exploring the research questions.
• Sample size and composition. The study targets approximately 500-700 participants for quantitative data collection and 30-40 participants for qualitative interviews. These sample sizes were determined through rigorous power analysis and feasibility considerations, ensuring a balanced approach between statistical robustness and rich narrative exploration.
• Secondary data scope. While secondary data sources are utilized for contextual insights, the study does not solely rely on them for hypothesis testing. This delimitation ensures that primary data collected directly from low-income pregnant individuals form the core of the analysis.
• Temporal scope. The study captures data within a specific timeframe, acknowledging that external influences or trends beyond this period might impact the findings differently. This delimitation is essential for maintaining the study’s focus and relevance.

Reliability and Validity

Ensuring the reliability and validity of this study is crucial to maintaining the integrity and credibility of the findings. The following strategies will be implemented to establish reliability and validity for both quantitative and qualitative aspects of the research:

Quantitative research.

• Instrument reliability. The Healthcare Access and Utilization Questionnaire (HAUQ) will undergo internal consistency reliability analysis using Cronbach’s alpha. A high alpha value (>0.70) will indicate satisfactory internal reliability.
• Instrument validity. Content validity will be ensured through consultation with experts in maternal health and healthcare access. Additionally, construct validity will be assessed by conducting factor analysis to confirm that the items within the HAUQ measure the intended constructs.
• Sampling. A well-defined sampling plan will be followed to enhance the study’s external validity. Including diverse rural regions will increase the transferability of findings across similar settings.

 

Bias Mitigation

The acknowledgement that potential biases exist deliberately and sufficient measures for their mitigation are to be implemented to sustain research integrity and veracity (Smith & Noble, 2014). This part describes anticipatable biases in this study, such as hidden assumptions which unconsciously contribute to the researcher’s standpoint, participants ‘reluctance to reveal some private details on their health status; nonrandom sampling within the isolated rural locations group of interests could be represented slighted wittingly or unwittingly; and selective reporting of findings. It further outlines deliberate strategies built within the study design that explicitly aim to address and neutralize these biases. Such measures may involve not only different forms of reflexivity processes on the part of a researcher, but also various non-probabilistic sampling techniques intended to ensure maximum heterogeneity within groups of people. Any release should possess both favorable and unfavorable data, which will help prevent reporting bias. The variegated means of bias elimination montage strictness in approach and balance reporting to bring into play, trust in born end notes.

Researcher Bias

Since the author is an experienced and resolute researcher in this field, it is necessary to discuss the hidden assumptions and beliefs generated by such a vast background about what advantages, disadvantages and effectiveness of telehealth services have for pacifying maternal health risks. A bias risk which is the research orientation and positionality that tend to justify telemedicine adoption is a likely obstacle predictable; therefore, requires conscious avoidance and minimization strategies. Since the investigator is a long-time involved rural healthcare advocate with deeply rooted regional connections, they might have unconscious assumptions and blind spots regarding community reception, utilization patterns, and attitudes referring to telehealth in remote places out of scope from their experience (Meidert et al., 2023). Thus, the geographic insularity that limits a better comprehension of sociocultural processes could be peculiar to other isolated places, where integration and adoption of telemedicine services are viewed (Du et al., 2022).

To actively challenge implicit prejudices that pertain to the telehealth advocates stance and regional isolation, some of the protocols will be included as a part of the methodological design. For his purpose, this reflexivity journaling will also enable an introspective review of how deep previous telemedicine involvement can influence the interpretation process for interview data and shape the orientation seen by participants. Building a degree of subject matter knowledge is to identify and challenge assumptions with a peer debriefer who lacks it, Seelandt et al. (2021) noted that such consultations improve perceptual acuity. Additionally, rich purposive snowball investigator-led recruitment sampling across several remote counties will provide far transcendence of the influencer’s geographical limitations (Robinson, 2014).

Participant Bias

Confidential statements can ensure the establishment of a friendly environment that should promote open disclosure, and thus, let participants freely talk about their experience involving telehealth platforms and author essays on this topic. However, there is a potential risk of partial bias emerging during interviews when discussing telehealth experiences or perspectives. Other potential misrepresentations like social desirability or acquiescence biases may unknowingly influence how some participants describe the acceptance and use of such factors identified within their respective. One of the cultural aspects that could be seen as more common among different rural areas is self-reliance, which can lead to under-report perceived barriers that may be influenced by low technological literacy or limitations in infrastructure. On the contrary, initial telehealth enthuses following adoption may lead to attributing favorable evaluations, which could pose an inability to fully capture years of integration issues focusing particularly on regular protocols (Kruse et al., 2018). Present-day traumatic childbirth incidences occurring in the rural healthcare set-up might distort perspectives stemming from resentment arising out of ignorance regarding substitute delivery concepts.

The design elements would include different patterns that will help in manufacturing possibilities of incorporation into the mechanism and detection and minimization of participant bias. The use of a standard set of prompts of bias either positive or negative will help as much in reducing the leading questions that could otherwise be introduced into responses by such an interviewer (Maaravi et al., 2023). An influence of social desirability would be captured at the level of qualitative analysis in which patterns will be analyzed across narrative data by using emerging qualitative software tools (Morgan & Nica, 2020). Heightened representation will be enhanced using purposive sampling that varies from one age group, and gender to various risks related to childbirth particularly those in developing nations (Campbell et al., 2020). Culturally, this is crucially important to have a “no right or wrong” view being mentioned as well and unbiased impressions are vital for the charged evaluation of telehealth adoption issues faced in isolated areas.

 

Selection Bias

Selection bias is primarily caused by any nonrandom, unrepresentative sampling that systematically leaves out segments of the target population within the confines of the research, hence distorting the results (Clayton et al., 2023). In a dispersed research project including multiple rural counties, recruiting participants from a single geographic area or healthcare organization presents significant selection bias risks for the validity of telehealth uptake and effectiveness results. Even in seemingly comparable isolated places, factors including personnel capacity, digital aptitudes, integration support approaches, and prevailing community views might differ considerably. Results could be significantly skewed by inadvertently leaving out some isolated counties or oversampling from a subset where the researcher’s prior associations encourage higher response (Vomberg & Klarmann, 2021). Generalizations inconsistent with regular rural locations may result from a disproportionate selection of residents who have had positive telehealth experiences because of superior implementation or outside advocacy groups. On the other hand, focusing recruitment efforts on a population that is marginalized and characterized by extreme poverty, low technology literacy, and poor telecommunications could distort and exaggerate barriers that are above average.

Recruitment communications will heavily saturate all remote county health departments, obstetric clinics, and community anchors specific to the area, such as places of worship, tribal health centers, and cultural hubs, to prevent such selection effects from distorting conclusions on maternal telehealth access, usage, and related outcomes (Coombs et al., 2022). Rather than representing any specific medical environment’s usage patterns or socioeconomic mix, robust responses through multi-pronged outreach should provide adequate representation like underlying population distributions (Haldane et al., 2019). Through county-specific telehealth adoption metrics to guide purposive sampling, external validity will be strengthened by preventing mismatches between sample characteristics and base population parameters (Mishra, 2020).

 

Reporting Bias

Like with any research, reporting bias is a concern if the study findings favorably highlight information that supports the investigator’s expectations or telehealth innovation. As a result, findings may inadvertently downplay or leave out contradicting data that challenges ideas of increased maternal access or better delivery models through remote care (Gayesa et al., 2023). For instance, assumptions about expanded care channels may be refuted by non-significant quantitative facts regarding service consumption rates before and after implementation. De-emphasizing qualitative themes that indicate unexpected impediments to older community members’ technology adoption may also be warranted.

Several techniques will mitigate the dangers of reporting bias resulting from unintentional selective analysis. If all evidence has been adequately considered within interpretative frameworks and result syntheses, it will be determined by an audit trail involving external evaluators analyzing raw qualitative transcripts and quantitative statistics (Nazar et al., 2022). Applying deductive and inductive methods consistently can help prevent rejecting data that contradicts top-down theoretical frameworks or emergent patterns that align with positive telehealth viewpoints (Woiceshyn & Daellenbach, 2018). Analytical memoranda will encourage a reflective evaluation of the reasons behind the integration difficulties of specific evidence. To avoid reporting bias distortions, attention is placed on balancing all viewpoints and experiences linked to adoption, access, and health implications to frame the findings purposefully impartially.

Within qualitative and quantitative research traditions, it is fundamentally ethical to proactively address the potential for insidious biases in design, implementation, analysis, and dissemination to maintain the integrity and reliability of procedures and conclusions (Johnson et al., 2020). As stated, robust protocols are integrated into this proposed study to mitigate the possibility of multiple biases, which investigates potential relationships between distant maternal care access models and birth outcomes. Preparedness measures are designed to support receptivity to emergent themes from the data and equitable evaluation of discordant perspectives (Anderson et al., 2021). These can take many forms, from researcher reflexivity encouraging introspection on ingrained positionalities to diversified purposeful sampling varying participant representation. Reducing biases that could lead to distortion is necessary to ensure an accurate contextualized representation of the complex dynamics surrounding the adoption and usage of telehealth.

Ethical Assurances

This study complies with human subject protection requirements. All volunteers will be asked to provide informed permission after being entirely told about the study’s aims, methods, possible risks, and benefits. Using pseudonyms in qualitative transcripts and safe data storage according to Institutional Review Board (IRB) criteria will ensure confidentiality (Strandberg, 2019). The researcher recognizes their role and possible biases but will diligently prevent them from distorting the analysis and deductions. They will execute this mandate using reflexivity, peer debriefing, and data source triangulation strategies. Trident University International will get formal IRB permission before data collection to guarantee compliance with ethical guidelines. The research certifies that it will acquire IRB clearance to maintain the highest levels of ethics and safeguard participants’ rights and well-being.

Summary

This chapter thoroughly explains the study’s procedures and design, which have been rigorously customized to coincide with the research topic. The suggested technique is based on a quantitative paradigm, which supports the study’s focus on the “Correlation between Telehealth Adoption and Severe Maternal Morbidity Rates in Low-Income Rural Populations.” This quantitative technique is expertly constructed to condense empirical data that meticulously elucidates the subtle relationship between telehealth use and SMM rates in low-income rural regions. The methodological plan for the research has been rigorously created to capture numerical patterns, allowing for a detailed analysis of the desired connections. Through this data-driven approach, the study hopes to uncover trends leading to a more nuanced understanding of the complex link between healthcare access and SMM rates. The study sample, painstakingly chosen from low-income rural areas, adds complexity and relevance to the research. The instruments used, which included an adapted Healthcare Access and Utilization Questionnaire (HAUQ), were rigorously developed. This assures agreement with the study’s objectives and participant experiences, further strengthening methodological rigor. Ethical concerns have been carefully considered using informed permission, participant anonymity, and researcher reflexivity. Notably, the study’s commitment to ethical norms is highlighted by the study’s formal pursuit of Institutional Review Board clearance. The subsequent chapters will delve into the data collection and analysis phases, where the findings will shed light on the intricate relationships between healthcare access and SMM rates, ultimately contributing to improving maternal health outcomes for vulnerable populations.

 

 

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Appendices

Appendix A: Participant Consent Form – Instrumentation Permission

 

Study Title: Correlation between Healthcare Utilization and Severe Maternal Morbidity Rates in Low-Income Rural Populations

 

Instrumentation Permissions

I, [Your Name], the principal investigator of the research study titled “Correlation between Healthcare Utilization and Severe Maternal Morbidity Rates in Low-Income Rural Populations,” confirm that I have obtained the necessary permissions to utilize the following instruments for this research:

1. Healthcare Access and Utilization Questionnaire (HAUQ): I have received explicit permission from the original author of the instrument, Dr. [Author’s Name], to adapt and use a modified version of the Healthcare Access and Utilization Questionnaire. This permission was granted on [Date of Permission], and the corresponding documentation is available in the research files.
2. Semi-Structured Interview Protocol: I have developed the interview protocol based on established qualitative research principles, with iterative input from qualitative research experts. The protocol was approved by the Institutional Review Board (IRB) of [Your Institution Name] on [Date of IRB Approval]. A sample of the interview questions is provided in the research documentation.

I assure you that your participation in this study is voluntary, and you can withdraw at any time without facing any consequences. Your responses will be kept confidential and anonymized in any research outputs. By participating, you grant permission to use the abovementioned instruments for data collection.

 

Please feel free to ask any questions before providing your informed consent. Your decision to participate or decline participation will not affect your relationship with [Your Institution Name] or any associated individuals.

By signing this consent form, you acknowledge that you have read and understood the information provided and voluntarily agree to participate in the study, granting permission to utilize the specified instruments.

 

Participant’s Name Name: __________________________ Date: ______________ (Signature, if applicable)

Principal Investigator: _______________________ Date: ______________ (Signature)

 

Appendix B: Participant Consent – Questionnaire

I hereby confirm that I, [Participant’s Name], have read and understood the information regarding the research study titled “Healthcare Utilization and Severe Maternal Morbidity in Low-Income Rural Populations.” I have been informed about the purpose, procedures, potential risks, benefits, and my rights as a participant in this study.

I understand that my participation is voluntary and that I can withdraw without penalty. I know that my responses will be treated confidentially, and my anonymity will be maintained in any publications resulting from this research.

I consent to participate in the questionnaire and provide honest and accurate responses to the best of my knowledge.

Signature: _____________________ Date: ______________

 

 

Appendix C: Participant Consent – Interview

I, [Participant’s Name], have been provided with information about the research study titled “Qualitative Insights into Maternal Health Experiences.” I understand the purpose, procedures, potential risks, benefits, and my rights as a participant in this study.

I voluntarily agree to participate in the interview and understand that my responses will be audio-recorded for transcription and analysis. I acknowledge that my participation is entirely voluntary, and I can choose not to answer any questions or withdraw from the interview at any time without repercussions.

I know my confidentiality will be upheld, and my real NameName will not be disclosed in research outputs.

Signature: _____________________ Date: ______________

 

 

Appendix D: Participant Consent – Focus Group

I, [Participant’s Name], have been informed about the research study titled “Barriers to Healthcare Access in Rural Communities.” I understand the nature of the focus group discussion and my role as a participant.

I willingly agree to participate in the focus group session and understand that the discussion will be recorded for analysis. I have been assured that my responses will be anonymized and that my privacy will be respected.

Participation is voluntary, and I can contribute as much or as little as possible. My withdrawal from the focus group will not impact my relationship with the research team or the study.

Signature: _____________________ Date: ______________

Appendix E

 

Figure 1

Research Model

 

Table of Hypotheses

 

Summary

In summary, it is crucial to understand how widespread telehealth is in rural communities with low incomes and how this relates to the prevalence of severe maternal morbidity. According to the analyzed research, telemedicine can revolutionize maternity care by reducing access, infrastructure, and socioeconomic inequalities. To improve maternal health outcomes in disadvantaged areas, comprehensive methods are required to incorporate telehealth into maternity care plans. Collaboration between policymakers, clinicians, and academics is essential to realizing telehealth’s full potential. As a result, telehealth stands out as a powerful tool that might dramatically alter prenatal care for those living in remote areas with low incomes. It demonstrates the potential of novel healthcare solutions for resolving long-standing healthcare inequities and promises to lower rates of severe maternal morbidity. Integrative approaches that use telehealth’s potential are the future of maternal care because they will ensure that all mothers, regardless of where they live or their financial situation, are treated with dignity and compassion. This chapter has offered a thorough review of the current literature, laying a solid groundwork for the next section. Chapter 3 will go into the research methodology, data collection techniques, and analytical methodologies adopted in this study to evaluate the present situation of telehealth adoption in underserved locations. The following chapters of the dissertation will focus on exploring the present state of telehealth and how that knowledge might influence strategies for the optimal integration of telehealth into maternity care programs.

Double space your entire paper. This is part of APA format.

List all authors up to 20.

 

Always capitalize the first word of a subtitle.