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The Intersection of Health Informatics and Disparities: Understanding How Data Promotes Health Equity.

Record Type:	Electronic resources : Monograph/item
Title/Author:	The Intersection of Health Informatics and Disparities: Understanding How Data Promotes Health Equity./
Author:	Wilson, Kala S.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2022,
Description:	190 p.
Notes:	Source: Dissertations Abstracts International, Volume: 84-05, Section: A.
Contained By:	Dissertations Abstracts International84-05A.
Subject:	Information technology. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29398341
ISBN:	9798357577290

The Intersection of Health Informatics and Disparities: Understanding How Data Promotes Health Equity.
Wilson, Kala S.

The Intersection of Health Informatics and Disparities: Understanding How Data Promotes Health Equity. - Ann Arbor : ProQuest Dissertations & Theses, 2022 - 190 p.

Source: Dissertations Abstracts International, Volume: 84-05, Section: A.

Thesis (Ph.D.)--The University of North Carolina at Charlotte, 2022.

This item must not be sold to any third party vendors.

In this collection of manuscripts, I developed a deeper understanding and insight into how the Coronavirus Disease 2019 (COVID-19) pandemic and subsequent transition to telehealth impacted 1) clinical electronic health record (EHR) data quality and data entry patterns, 2) provider perceptions of the EHR's influence on care delivery, and 3) patient perceptions on barriers related to pandemic-induced telemedicine.The COVID-19 public health crisis has disproportionately affected individuals and populations historically marginalized in healthcare and public health, including racial and ethnic minorities and individuals with low-income status. The COVID-19 pandemic has drawn new attention to and compounded the existing health and digital disparities in healthcare, with Black Americans being almost 4 times as likely to die from the virus than White Americans. Racial and ethnic health disparities have been historically unwavering and persistent within the United States. Furthermore, this crisis has ignited rapid implementation of digital healthcare solutions such as virtual healthcare (telehealth and telemedicine capabilities) and health information technology (HIT) accessed via mobile applications or online platforms. When assessing HIT's effectiveness, efficiency, quality, safety, and equity, it is essential to consider the reciprocal relationship between HIT and the COVID-19 pandemic. This is of marked significance, considering that virtual care technologies have been shown to exacerbate the digital divide and worsen disparities in a patient's ability to access high-quality care.The research in this dissertation is informed by the socio-technical and complex systems perspectives of improved human health via high-quality, safe, HIT-driven care, which maintains two central concepts: 1) multiple levels of influence affect a patient's health outcomes, such as care quality, costs, and patient safety; and 2) complex adaptive systems occur when many agents work together within an organization and patterns materialize as the agents adopt, "simple rules" that optimize outcomes, such as the patient experience and the clinical team's performance. Understanding how these HIT-related behaviors and perceptions multidimensionally affect care delivery is imperative to maximizing the potential benefits of technology and data in healthcare and promoting the need for a concerted effort to ensure safe, high-quality, and equitable care delivery.Chapter 1 reviewed literature on the relationships between HIT and care quality, patient safety, health equity, biases, and discrimination. In Chapter 2, we assessed external, societal factors' influence on data quality and data entry patterns disparities. We found that an external change to healthcare operations - which modifies clinical practice - was correlated with clinical data entry patterns. Also, we found significant differences between departments within the healthcare organization, suggesting data entry differences based on distinct care goals housed within different units. These findings underscore some of the conclusions found in Chapter 3 where we determined the multidimensional relationship between HIT processes and patient safety and quality by exploring how healthcare provider demographic and health system-related characteristics were associated with their perception of the EHR's impact on care delivery.Perception disparities were present by providers based on sex, age, race, ethnicity, board certification, telemedicine utilization, and years of EHR experience. The results from this research are striking - we uncovered that providers using the EHR and telemedicine were roughly 20 times more likely to perceive the EHR as beneficial for patient safety (OR=20.25; p<0.001), compared to approximately only 4 times more likely for care quality (OR=4.48; p<0.05). Despite providers reporting that they found the EHR more beneficial for patient safety than care quality - we found conflicting practical evidence when assessing patient perceptions of telemedicine barriers and their reported outcomes.Chapter 4 assessed the effect of demographic and healthcare-related factors on patient perceptions of telemedicine barriers. We found that 76% of patients reported facing at least one telemedicine barrier, and 66% reported experiencing a medical error via telemedicine during the pandemic. Similarly, we uncovered patients were more likely to report experiencing a telemedicine barrier if they utilized the patient-facing EHR (OR=27.72), had been diagnosed with 1 to 2 chronic conditions (OR=10.06), and experienced a medical error (OR=1.22). Interestingly, patients were less likely to report experiencing a telemedicine barrier if they identified as Black (OR=0.10; p<0.001), Female (OR=0.06; p<0.05), and reported 3 to 4 diagnosed chronic conditions (OR=0.10; p<0.01). These findings align with prior literature indicating the historically pervasive inequities and disparities amongst these subpopulations. This has led to less patient engagement and activation, specifically in Black women and those considered as "super-utilizers" of the healthcare system, often due to complex physical, behavioral, and social needs.Collectively, these studies advance our understanding of how external factors such as COVID-19, modified workflows, demographic, health system, and healthcare-related characteristics impact health information technology and data perceptions and behaviors. Our findings suggest that these perceptions influence diagnostic EHR data entry, technological utilization, digital care barriers, and corresponding patient outcomes. This dissertation contributes to the public health and healthcare literature by providing practical implications for health systems, clinicians, care teams, and patients interacting with technology and data in healthcare settings. This contribution is significant to better understanding how their interactions with data and technology affect the efficiency, safety, quality, and equity of care delivery, as well as generated clinical and population health data. Our findings underscore the need for further analysis to understand the interactions between the environment, processes, workflows, technological designs, patients, and the core operative nature of the system itself. Health administrators, policymakers, and researchers must acknowledge that technology and data can act as a roadblock to achieving health equity throughout this nation's healthcare systems if human and information technology systems continue to co-exist but not co-evolve concurrently.In policy and practice, we must pull back the curtain and recognize and address the many forms of coded inequity that is present throughout our healthcare systems by becoming more aware of the social dimensions of technology that generate dominant and discriminatory structures encoded in apps, algorithms, and payment data used in health and healthcare.

ISBN: 9798357577290Subjects--Topical Terms:

532993
Information technology.
Subjects--Index Terms:

Electronic health records

The Intersection of Health Informatics and Disparities: Understanding How Data Promotes Health Equity.
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520 $a In this collection of manuscripts, I developed a deeper understanding and insight into how the Coronavirus Disease 2019 (COVID-19) pandemic and subsequent transition to telehealth impacted 1) clinical electronic health record (EHR) data quality and data entry patterns, 2) provider perceptions of the EHR's influence on care delivery, and 3) patient perceptions on barriers related to pandemic-induced telemedicine.The COVID-19 public health crisis has disproportionately affected individuals and populations historically marginalized in healthcare and public health, including racial and ethnic minorities and individuals with low-income status. The COVID-19 pandemic has drawn new attention to and compounded the existing health and digital disparities in healthcare, with Black Americans being almost 4 times as likely to die from the virus than White Americans. Racial and ethnic health disparities have been historically unwavering and persistent within the United States. Furthermore, this crisis has ignited rapid implementation of digital healthcare solutions such as virtual healthcare (telehealth and telemedicine capabilities) and health information technology (HIT) accessed via mobile applications or online platforms. When assessing HIT's effectiveness, efficiency, quality, safety, and equity, it is essential to consider the reciprocal relationship between HIT and the COVID-19 pandemic. This is of marked significance, considering that virtual care technologies have been shown to exacerbate the digital divide and worsen disparities in a patient's ability to access high-quality care.The research in this dissertation is informed by the socio-technical and complex systems perspectives of improved human health via high-quality, safe, HIT-driven care, which maintains two central concepts: 1) multiple levels of influence affect a patient's health outcomes, such as care quality, costs, and patient safety; and 2) complex adaptive systems occur when many agents work together within an organization and patterns materialize as the agents adopt, "simple rules" that optimize outcomes, such as the patient experience and the clinical team's performance. Understanding how these HIT-related behaviors and perceptions multidimensionally affect care delivery is imperative to maximizing the potential benefits of technology and data in healthcare and promoting the need for a concerted effort to ensure safe, high-quality, and equitable care delivery.Chapter 1 reviewed literature on the relationships between HIT and care quality, patient safety, health equity, biases, and discrimination. In Chapter 2, we assessed external, societal factors' influence on data quality and data entry patterns disparities. We found that an external change to healthcare operations - which modifies clinical practice - was correlated with clinical data entry patterns. Also, we found significant differences between departments within the healthcare organization, suggesting data entry differences based on distinct care goals housed within different units. These findings underscore some of the conclusions found in Chapter 3 where we determined the multidimensional relationship between HIT processes and patient safety and quality by exploring how healthcare provider demographic and health system-related characteristics were associated with their perception of the EHR's impact on care delivery.Perception disparities were present by providers based on sex, age, race, ethnicity, board certification, telemedicine utilization, and years of EHR experience. The results from this research are striking - we uncovered that providers using the EHR and telemedicine were roughly 20 times more likely to perceive the EHR as beneficial for patient safety (OR=20.25; p<0.001), compared to approximately only 4 times more likely for care quality (OR=4.48; p<0.05). Despite providers reporting that they found the EHR more beneficial for patient safety than care quality - we found conflicting practical evidence when assessing patient perceptions of telemedicine barriers and their reported outcomes.Chapter 4 assessed the effect of demographic and healthcare-related factors on patient perceptions of telemedicine barriers. We found that 76% of patients reported facing at least one telemedicine barrier, and 66% reported experiencing a medical error via telemedicine during the pandemic. Similarly, we uncovered patients were more likely to report experiencing a telemedicine barrier if they utilized the patient-facing EHR (OR=27.72), had been diagnosed with 1 to 2 chronic conditions (OR=10.06), and experienced a medical error (OR=1.22). Interestingly, patients were less likely to report experiencing a telemedicine barrier if they identified as Black (OR=0.10; p<0.001), Female (OR=0.06; p<0.05), and reported 3 to 4 diagnosed chronic conditions (OR=0.10; p<0.01). These findings align with prior literature indicating the historically pervasive inequities and disparities amongst these subpopulations. This has led to less patient engagement and activation, specifically in Black women and those considered as "super-utilizers" of the healthcare system, often due to complex physical, behavioral, and social needs.Collectively, these studies advance our understanding of how external factors such as COVID-19, modified workflows, demographic, health system, and healthcare-related characteristics impact health information technology and data perceptions and behaviors. Our findings suggest that these perceptions influence diagnostic EHR data entry, technological utilization, digital care barriers, and corresponding patient outcomes. This dissertation contributes to the public health and healthcare literature by providing practical implications for health systems, clinicians, care teams, and patients interacting with technology and data in healthcare settings. This contribution is significant to better understanding how their interactions with data and technology affect the efficiency, safety, quality, and equity of care delivery, as well as generated clinical and population health data. Our findings underscore the need for further analysis to understand the interactions between the environment, processes, workflows, technological designs, patients, and the core operative nature of the system itself. Health administrators, policymakers, and researchers must acknowledge that technology and data can act as a roadblock to achieving health equity throughout this nation's healthcare systems if human and information technology systems continue to co-exist but not co-evolve concurrently.In policy and practice, we must pull back the curtain and recognize and address the many forms of coded inequity that is present throughout our healthcare systems by becoming more aware of the social dimensions of technology that generate dominant and discriminatory structures encoded in apps, algorithms, and payment data used in health and healthcare.
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