Leveraging health informatics to foster a smart systems response to health disparities and health equity challenges

Advancing health equity through nursing research

BACKGROUND

Health inequities are major predictors of poor health and remain a complex and persistent challenge globally and in the United States. Research has documented the underlying causes and mechanisms that give rise to health disparities. However, it lacks adequate attention to the strategies needed to build upon promulgated research to address equity-based challenges to improve health.

PURPOSE

This paper describes how building and supporting diverse research teams can play a central role in increasing the research capacity and participation of diverse populations to improve the health of individuals, families, and communities.

METHODS

Exemplars from work and discussion of strategies to grow nursing's health equity workforce are presented.

DISCUSSION

Actions to build and leverage partnerships to expand capacity, maximize the impact of health equity outcomes, and cultivate a supportive environment to grow the health equity scientific workforce are discussed.

CONCLUSION

Nurse scientists can address health equity through the research process.

Examining ACCURE's Nurse Navigation Through an Antiracist Lens: Transparency and Accountability in Cancer Care

There are persistent disparities in the delivery of cancer treatment, with Black patients receiving fewer of the recommended cancer treatment cycles than their White counterparts on average. To enhance racial equity in cancer care, innovative methods that apply antiracist principles to health promotion interventions are needed. The parent study for the current analysis, the Accountability for Cancer Care through Undoing Racism and Equity (ACCURE) intervention, was a system-change intervention that successfully eliminated the Black-White disparity in cancer treatment completion among patients with early-stage breast and lung cancer. The intervention included specially trained nurse navigators who leveraged real-time data to follow-up with patients during their treatment journeys. Community and academic research partners conducted thematic analysis on all clinical notes (n = 3,251) written by ACCURE navigators after each contact with patients in the specialized navigation arm (n = 162). Analysis was informed by transparency and accountability, principles adapted from the antiracist resource Undoing Racism and determined as barriers to treatment completion through prior research that informed ACCURE. We identified six themes in the navigator notes that demonstrated enhanced accountability of the care system to patient needs. Underlying these themes was a process of enhanced data transparency that allowed navigators to provide tailored patient support. Themes include (1) patient-centered advocacy, (2) addressing system barriers to care, (3) connection to resources, (4) re-engaging patients after lapsed treatment, (5) addressing symptoms and side effects, and (6) emotional support. Future interventions should incorporate transparency and accountability mechanisms and examine the impact on racial equity in cancer care.

An informatics-driven intelligent system to improve healthcare accessibility for vulnerable populations

Broad disparities persist in access to healthcare and health outcomes in the United States, especially among vulnerable populations. An important step towards improving their healthcare access is to ensure "having access", or "accessibility". Drawing together the Behavioral Model of Health Services Use, social determinants of health (SDOH), and spatial healthcare accessibility literature, the research attempts to create an integrative accessibility measure to support the improvement of "having access" for vulnerable populations. A Vulnerable Population Healthcare Accessibility Framework (VPHAF) is proposed to systematically integrate vulnerable population characteristics, health behavior, customer satisfaction, and other SDOH factors to measure healthcare accessibility using advanced analytics. The qualitative and quantitative evaluation of VPHAF demonstrates that it enhances the existing spatial accessibility methods. An intelligent spatial decision support system (SDSS) instantiates the framework to support the decision making in improving healthcare accessibility for vulnerable populations in a regional healthcare plan. The system was evaluated by decision makers from a real-world organization as a useful tool with high usability. The intelligent SDSS enables the collection of SDOH data from multiple sources and uses analytics to measure healthcare accessibility focusing on characteristics of vulnerable populations. Policymakers and health plan providers can use the system to increase awareness of social risks and advocate for better policy decisions in creating equitable healthcare access and reducing health disparity.

Challenges in the development of digital public health interventions and mapped solutions: Findings from a scoping review

Background

“Digital public health” has emerged from an interest in integrating digital technologies into public health. However, significant challenges which limit the scale and extent of this digital integration in various public health domains have been described. We summarized the literature about these challenges and identified strategies to overcome them.

Methods

We adopted Arksey and O’Malley's framework (2005) integrating adaptations by Levac et al. (2010). OVID Medline, Embase, Google Scholar, and 14 government and intergovernmental agency websites were searched using terms related to “digital” and “public health.” We included conceptual and explicit descriptions of digital technologies in public health published in English between 2000 and June 2020. We excluded primary research articles about digital health interventions. Data were extracted using a codebook created using the European Public Health Association's conceptual framework for digital public health.

Results and analysis

Overall, 163 publications were included from 6953 retrieved articles with the majority (64%, n = 105) published between 2015 and June 2020. Nontechnical challenges to digital integration in public health concerned ethics, policy and governance, health equity, resource gaps, and quality of evidence. Technical challenges included fragmented and unsustainable systems, lack of clear standards, unreliability of available data, infrastructure gaps, and workforce capacity gaps. Identified strategies included securing political commitment, intersectoral collaboration, economic investments, standardized ethical, legal, and regulatory frameworks, adaptive research and evaluation, health workforce capacity building, and transparent communication and public engagement.

Conclusion

Developing and implementing digital public health interventions requires efforts that leverage identified strategies to overcome diverse challenges encountered in integrating digital technologies in public health.

Assessing Health Data Security Risks in Global Health Partnerships: Development of a Conceptual Framework

Background

Health care databases contain a wealth of information that can be used to develop programs and mature health care systems. There is concern that the sensitive nature of health data (eg, ethnicity, reproductive health, sexually transmitted infections, and lifestyle information) can have significant impact on individuals if misused, particularly among vulnerable and marginalized populations. As academic institutions, nongovernmental organizations, and international agencies begin to collaborate with low- and middle-income countries to develop and deploy health information technology (HIT), it is important to understand the technical and practical security implications of these initiatives.

Objective

Our aim is to develop a conceptual framework for risk stratification of global health data partnerships and HIT projects. In addition to identifying key conceptual domains, we map each domain to a variety of publicly available indices that could be used to inform a quantitative model.

Methods

We conducted an overview of the literature to identify relevant publications, position statements, white papers, and reports. The research team reviewed all sources and used the framework method and conceptual framework analysis to name and categorize key concepts, integrate them into domains, and synthesize them into an overarching conceptual framework. Once key domains were identified, public international data sources were searched for relevant structured indices to generate quantitative counterparts.

Results

We identified 5 key domains to inform our conceptual framework: State of HIT, Economics of Health Care, Demographics and Equity, Societal Freedom and Safety, and Partnership and Trust. Each of these domains was mapped to a number of structured indices.

Conclusions

There is a complex relationship among the legal, economic, and social domains of health care, which affects the state of HIT in low- and middle-income countries and associated data security risks. The strength of partnership and trust among collaborating organizations is an important moderating factor. Additional work is needed to formalize the assessment of partnership and trust and to develop a quantitative model of the conceptual framework that can help support organizational decision-making.

Influential Usage of Big Data and Artificial Intelligence in Healthcare

Artificial intelligence (AI) is making computer systems capable of executing human brain tasks in many fields in all aspects of daily life. The enhancement in information and communications technology (ICT) has indisputably improved the quality of people's lives around the globe. Especially, ICT has led to a very needy and tremendous improvement in the health sector which is commonly known as electronic health (eHealth) and medical health (mHealth). Deep machine learning and AI approaches are commonly presented in many applications using big data, which consists of all relevant data about the medical health and diseases which a model can access at the time of execution or diagnosis of diseases. For example, cardiovascular imaging has now accurate imaging combined with big data from the eHealth record and pathology to better characterize the disease and personalized therapy. In clinical work and imaging, cancer care is getting improved by knowing the tumor biology and helping in the implementation of precision medicine. The Markov model is used to extract new approaches for leveraging cancer. In this paper, we have reviewed existing research relevant to eHealth and mHealth where various models are discussed which uses big data for the diagnosis and healthcare system. This paper summarizes the recent promising applications of AI and big data in medical health and electronic health, which have potentially added value to diagnosis and patient care.

TechQuity is an imperative for health and technology business: Let's work together to achieve it

Open discussions of social justice and health inequities may be an uncommon focus within information technology science, business, and health care delivery partnerships. However, the COVID-19 pandemic—which disproportionately affected Black, indigenous, and people of color—has reinforced the need to examine and define roles that technology partners should play to lead anti-racism efforts through our work. In our perspective piece, we describe the imperative to prioritize TechQuity—equity and social justice as a technology business strategy—through collaborating in partnerships that focus on eliminating racial and social inequities.

A case study of the 1115 waiver using population health informatics to address disparities

As participants in the California Medicaid 1115 waiver, the University of California San Diego Health (UCSDH) used population health informatics tools to address health disparities. This case study describes a modern application of health informatics to improve data capture, describe health disparities through demographic stratification, and drive reliable care through electronic medical record-based registries. We provide a details in our successful approach using (1) standardized collection of race, ethnicity, language, sexual orientation, and gender identity data, (2) stratification of 8 quality measures by demographic profile, and (3) improved quality performance through registries for wellness, social determinants of health, and chronic disease. A strong population health platform paired with executive support, physician leadership, education and training, and workflow redesign can improve the representation of diversity and drive reliable processes for care delivery that improve health equity.

Back to the Future: Achieving Health Equity Through Health Informatics and Digital Health

The rapid proliferation of health informatics and digital health innovations has revolutionized clinical and research practices. There is no doubt that these fields will continue to have accelerated growth and a substantial impact on population health. However, there are legitimate concerns about how these promising technological advances can lead to unintended consequences such as perpetuating health and health care disparities for underresourced populations. To mitigate this potential pitfall, it is imperative for the health informatics and digital health scientific communities to understand the challenges faced by disadvantaged groups, including racial and ethnic minorities, which hinder their achievement of ideal health. This paper presents illustrative exemplars as case studies of contextually tailored, sociotechnical mobile health interventions designed with community members to address health inequities using community-engaged research approaches. We strongly encourage researchers and innovators to integrate community engagement into the development of data-driven, modernized solutions for every sector of society to truly achieve health equity for all.

Big Data in Context: Addressing the Twin Perils of Data Absenteeism and Chauvinism in the Context of Health Disparities Research

Recent advances in the collection and processing of health data from multiple sources at scale-known as big data-have become appealing across public health domains. However, present discussions often do not thoroughly consider the implications of big data or health informatics in the context of continuing health disparities. The 2 key objectives of this paper were as follows: first, it introduced 2 main problems of health big data in the context of health disparities-data absenteeism (lack of representation from underprivileged groups) and data chauvinism (faith in the size of data without considerations for quality and contexts). Second, this paper suggested that health organizations should strive to go beyond the current fad and seek to understand and coordinate efforts across the surrounding societal-, organizational-, individual-, and data-level contexts in a realistic manner to leverage big data to address health disparities.

Using Electronic Health Records Data to Evaluate the Impact of Information Technology on Improving Health Equity: Evidence from China

This study evaluates the impact of health information technology in accessing medical resources and identifies its role in improving health equity. We used 262, 771 records from the electronic medical records and outpatient appointment systems of three clinics for logistic regression to analyze the impact of information technology on patients' access to medical care. We interviewed a few health professionals to gauge their reactions and to validate and understand our quantitative results. The proportion of inpatients affected by information technology is low, accounting for only 16.7% (N = 43, 870). The difference between rural and urban groups is statistically significant, and rural households are more susceptible to information technology. In addition, distance has a significant positive effect. We demonstrate an inverted U-shaped relationship between severity of disease and the impact of information technology. Moreover, our interview results are consistent with our quantitative results. Quantitative and interview results suggest that health information technology plays a positive role in accessing medical care for patients with rural household and those in remote areas. Meanwhile, this effect is complex for patients with different severities of illnesses. Governments and managers should vigorously promote health information technology for healthcare delivery in the future and focus their attention on patients with serious diseases.

Technological improvement in modern health care applications using Internet of Things (IoT) and proposal of novel health care approach

Purpose

With the development of emerging engineering technology and industrialization, there are greater changes in the life style of people in smart urban cities; therefore, there is also more chance of various health problems in urban areas. The life style of persons in metro urban areas with the expansive volume of population is similarly influenced by different application and administration frameworks. These are affecting the human health system up to an extended extent and there are more health-related issues and health hazard concerns that can be identified in urban areas. The purpose of this paper is to present an analytical study on various aspects of the smart health care system in a smart perspective by analyzing them with respect to emerging engineering technologies such as mobile network, cloud computing, Internet of Things (IoT), big data analytics and ubiquitous computing. This paper also carries out a detailed survey of health issues and improved solutions in automated systems using these technologies. Second, the paper also presents a novel health care system using smart and safe ambulances and their appropriate control at traffic points with safety and security features in a smart city, so that the valuable life of patients can be saved in time by immediate treatment in nearest hospital or health care units.

Design/methodology/approach

In this paper, an analytical survey was conducted for improvement in the health care sector using computer technology and IoT-based various modern health care applications. An idea of Smart Health Care Hospital using sensors, mobile agent smart vehicle configuration and safety traffic control for ambulance was proposed.

Findings

A simulation was carried out to see the performance of a safety mechanism in the proposed approach. Comparative analysis was carried out with other approaches to know the execution time, response time and probable delay due to the implementation of this approach.

Originality/value

It is an original research work with motivation inspired from current emergent technology to apply in the health care system.

Measuring Health Equity for Ambulatory Care Sensitive Conditions in a Large Integrated Health Care System: The Development of an Index

Disparities in outcomes for preventive and primary health care services often result when vulnerable patients rely on episodic encounters for emergency services that do not meet their long-term health needs. Understanding health outcomes in socially or economically disadvantaged subgroups is crucial to improving community health, and it requires innovative analytics and dynamic application of clinical and population data. While it is common practice to use proxy indicators, such as quality of life and mortality, when discussing health equity, these have shown limited utility and are rarely applied at a population-level within a health system. Therefore, we designed and implemented an index, calculated as the ratio of observed-to-expected encounters, to identify and quantify health inequalities in health care systems. Providing equitable care, as measured by health outcomes, is analogous to precision medicine applied to social determinants. For health systems, the use of this index will facilitate the development of specially-tailored interventions to address inequity and provides a tool to measure the impact of such programs.

A content analysis of the views of genetics professionals on race, ancestry, and genetics

Over the past decade, the proliferation of genetic studies on human health and disease has reinvigorated debates about the appropriate role of race and ancestry in research and clinical care. Here we report on the responses of genetics professionals to a survey about their views on race, genetics, and ancestry across the domains of science, medicine, and society. Through a qualitative content analysis of free-text comments from 515 survey respondents, we identified key themes pertaining to multiple meanings of race, the use of race as a proxy for genetic ancestry, and the relevance of race and ancestry to health. Our findings suggest that for many genetics professionals the questions of what race is and what race means remain both professionally and personally contentious. Looking ahead as genomics is translated into the practice of precision medicine and as learning health care systems offer continued improvements in care through integrated research, we argue for nuanced considerations of both race and genetic ancestry across research and care settings.

Local Health Departments' Engagement in Addressing Health Disparities: The Effect of Health Informatics

CONTEXT

Health disparities and health inequities can lead to poor health outcomes. However, health disparities continue to persist in communities across the United States, presenting a crucial public health challenge. Persisting budget cuts and workforce challenges tend to hinder local health departments' (LHDs') ability to assess and address health disparities.

OBJECTIVES

To examine the extent to which LHDs' use of informatics effects their engagement in strategies and activities addressing health disparities.

METHODS

Data from the 2016 Profile of LHDs were used in examining the association of informatics with 9 activities addressing health disparities/inequities.

RESULTS

Fifty-nine percent of LHDs used data and described health disparities in their jurisdiction, and 12% conducted original research to link health disparities to differences in social or environmental conditions. Less than 40% of LHDs prioritized resources for the reduction of health disparities. LHDs that implemented information systems had increased odds of describing the disparities in their jurisdiction (P < .01) and having prioritized resources for the reduction of disparities (P < .01). Per capita expenditures, participation in a national accreditation program process, and a larger LHD population were also positively associated with 7 of 9 activities for addressing health disparities/inequities.

CONCLUSIONS

As LHDs advance efforts to reduce health disparities and inequities, leadership will find informatics a useful strategy. National initiatives aimed to boost LHDs' engagement in the reduction of disparities might benefit from our findings, positing a positive influence of informatics.