COMMENTARY
Reframing the Disparities Agenda: A Time to Rethink, a Time to Focus Ivor B. Horn, MD, MPH; Fernando S. Mendoza, MD, MPH From the Department of Pediatrics, Children’s National Health System, George Washington University School of Medicine, Washington, DC (Dr Horn); and Department of Pediatrics, Stanford University School of Medicine, Lucile Packard Children’s Hospital, Palo Alto, Calif (Dr Mendoza) The authors declare that they have no conflict of interest. Address correspondence to Ivor B. Horn, MD, MPH, Department of Pediatrics, Children’s National Health System, 111 Michigan Ave NW, Washington, DC 20010 (e-mail: [email protected]). Received for publication December 16, 2013; accepted December 21, 2013.
ACADEMIC PEDIATRICS 2014;14:115–116
THE RELEASE OF the Institute of Medicine’s reports Un-
the ACA and focus our efforts on eliminating inequities in quality of care? Universally, health care systems have recognized the importance of quality of care issues and their link to economic well-being and competitiveness. Concurrently, accountable care organization executives are shifting their discussions from individual health to population health and prevention. These changes in the health care system provide tremendous opportunity to change how we address disparities, from one of needing resources to one of effective resource utilization. But perhaps most importantly, the disparity discussion may now resonate from our clinics to the boardrooms, moving the elimination of health disparities to the cost-containment side of the health care ledger. In the final analysis, health disparities reduction should be a part of overall efforts to improve health outcomes and reduce health costs. When health systems can see the economic return on investment for efforts to reduce health disparities in the same way that they have begun to see health care quality, it will be the most important step in our efforts to eliminate health disparities. Two other key changes in health care make now an optimal time to make this shift in our thinking. First, the Health Information Technology for Economic and Clinical Health (HITECH) Act and Meaningful Use, which have resulted in a significant adoption of electronic health records (EHRs) in recent years. As of April 2013, approximately 80% of eligible hospitals in the United States and over 50% of physicians and other eligible health professionals had adopted EHRs.5 This will greatly expand the information on patients and populations, and it provides an opportunity for more productive use of EHRs for work on disparities. These new data resources will allow us to gain more in-depth and actionable information. However, the critical question is whether these systems will capture social determinants of health needed to evaluate disparities. Hatch et al utilized data from the electronic health database of a community health center network to track health insurance status of their patient population. Through these data analytics, they were able to develop a system of
equal Treatment: Confronting Racial and Ethnic Disparities in Health and Crossing the Quality Chasm: A New Health System for the 21st Century over a decade ago led to numerous efforts in programs, practice, and research to improve health equity and health care quality.1,2 The pediatric community has been in the forefront of this effort providing “high touch” community participatory efforts to reduce health disparities among children. However, the article in this month’s Academic Pediatrics by Dougherty and colleagues describing broad trends using the 2011 National Healthcare Quality Report (NHQR) and National Healthcare Disparities Report (NHDR) database highlight that at the macro level, little measurable change has occurred.3 In his foreword to the 2013 Centers for Disease Control (CDC) Health Disparities and Inequalities Report, Thomas Frieden, director of the CDC, noted that reports such as these give an overview of national level data sets and serve to “shine a bright light on the problem to be solved.”4 Yet given that we have shined the light for several decades, is it now time for analyses to provide insights on potential solutions? The shortcomings of actionable data from the article by Dougherty and colleagues and that of the CDC report are a reflection of the limitations of national data sets, not the reporting of the results. Reflection on the current study creates an opportunity to reframe the health disparities conversation. Dougherty and colleagues in their article report the results of the NHQR and NHDR database. The fact that neither database alone can answer the fundamental question of whether health disparities are improving, nor can they give us actionable metrics, is problematic if we are going to make progress in eliminating them. In the setting of the Affordable Care Act (ACA), with improved access to care for those traditionally underserved, the time is right to rethink how we conceptualize health disparities for children so we have metrics that will induce action. If inequity has resulted in disparities, and if inequity is transmitted through less access and lower quality, should we leverage ACADEMIC PEDIATRICS Copyright ª 2014 by Academic Pediatric Association
115
Volume 14, Number 2 March–April 2014
116
HORN AND MENDOZA
insurance surveillance to inform interventions to help their patients obtain and retain coverage.6 Also relevant is the work of Tomasallo et al, who used EHR data to determine the prevalence of asthma in Wisconsin.7 This use of EHR data to improve chronic disease surveillance on a local level can effectively identify areas of disparity, and more importantly can guide education and health care inventions. Finally, the technology revolution is not just occurring in the health care system but also among our patients, rich and poor—a fact that health care systems are investigating for their advantage in their efforts to connect to patients. Mobile health (mHealth), defined as the use of mobile and wireless devices to improve health outcomes, is offering significant opportunities overall.8 Steinhubl et al recently noted the potential of mHealth to transform health care by improving self-tracking, management of acute and chronic conditions, and clinical management by providers.9 This creates a unique opportunity for addressing health disparities that is not frequently discussed but clearly needs to become a focus. Given the fact that African Americans and English-speaking Latinos are actually more likely to own a mobile phone and to use mobile technology than whites,10 and that Latinos and African Americans are more likely than whites to look for health information on their phones,11 a unique opportunity exists to engage early in mHealth development those interested in eliminating health disparities. Both forms of technology (EHR and mHealth) demonstrate the new opportunities for data sources to provide actionable data at individual, local, regional, and national levels. Thus, we believe that now is the time to rethink how we measure and address health disparities, and now is the time to refocus our efforts to eliminate them. Although we believe we need to maintain and further develop “high touch” community participatory interventions, seeking the common ground among those interested in health disparities, health care quality, health economics, and technology will shift the discussion of disparities from the periphery of health care to its center. Quality based on health care dollar value will inevitably require discussions about how to improve quality and decrease cost—not only for those who traditionally have had insurance but also for those who have not. A discussion on health care quality and disparities then becomes a discussion that will necessitate new data sources targeted at understanding the social determinants of disease as well as the disease itself. Yet having more robust data sources does not guarantee a change in the currently stagnant progress toward reducing health disparities.
ACADEMIC PEDIATRICS
To that end, we propose the following recommendations. First, there needs to be a general agreement on areas to target. Rather than diluting effects by providing resources to disparate small but unrelated health outcomes, we suggest identification of key quality areas to be addressed in depth that will provide a framework for future efforts to be more productive. We encourage local and regional discussions among key constituents, patients, and communities that have experienced disparities. We recommend convening an Institute of Medicine committee focused on this area as a follow-up to the Unequal Treatment and Crossing the Chasm reports but that also builds on the more recent efforts related to the use of technology in health. Last, the results of this committee report should inform policy to target efforts and allocate resources to address health disparities through these venues. At the end of the day, creating incentives to encourage public and private sector participation will be the only way to finally eliminate health disparities for children in our country.
REFERENCES 1. Smedley BD, Stith AY, Nelson AR, eds. Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care. Washington, DC: National Academies Press; 1999. 2. Institute of Medicine. Crossing the Quality Chasm: A New Health System for the 21st Century. Washington, DC: National Academies Press; 2001. 3. Dougherty D, Chen X, Gray DT, Simon AE. Child and adolescent health care quality and disparities—are we making progress? Acad Pediatr. 2014;14:137–148. 4. Centers for Disease Control and Prevention. CDC health disparities and inequalities report—United States, 2013. MMWR Morb Mortal Wkly Rep. 2013;62(suppl 3):1. 5. Doctors and hospitals’ use of health IT more than doubles since 2012. Available at: http://www.hhs.gov/news/press/2013pres/05/20130522a. html. Accessed December 13, 2013. 6. Hatch B, Angier H, Marino M, et al. Using electronic health records to conduct children’s health insurance surveillance. Pediatrics. 2013; 132:e1584–e1591. 7. Tomasallo CD, Hanrahan LP, Tandias A, et al. Estimating Wisconsin asthma prevalence using clinical electronic health records and public health data. Am J Public Health. 2014;104:e65–e73. 8. NIH Consensus Group. Video report: what is mHealth? Available at: http://www.hrsa.gov/healthit/mhealth.html. Accessed December 13, 2013. 9. Steinhubl SR, Muse ED, Topol EJ. Can mobile health technologies transform health care? JAMA. 2013;310:2395–2396. 10. Brenner J. Pew Internet: mobile. http://pewinternet.org/Commentary/ 2012/February/Pew-Internet-Mobile.aspx. Accessed July 11, 2013. 11. Fox S, Duggan M. Mobile health, 2012. Pew Internet and American Life Project. Available at: http://www.pewinternet.org/Reports/ 2012/Mobile-Health/Main-Findings/Mobile-Health.aspx. Accessed November 8, 2012.
Reframing the Disparities Agenda: A Time to Rethink, a Time to Focus Ivor B. Horn, MD, MPH; Fernando S. Mendoza, MD, MPH From the Department of Pediatrics, Children’s National Health System, George Washington University School of Medicine, Washington, DC (Dr Horn); and Department of Pediatrics, Stanford University School of Medicine, Lucile Packard Children’s Hospital, Palo Alto, Calif (Dr Mendoza) The authors declare that they have no conflict of interest. Address correspondence to Ivor B. Horn, MD, MPH, Department of Pediatrics, Children’s National Health System, 111 Michigan Ave NW, Washington, DC 20010 (e-mail: [email protected]). Received for publication December 16, 2013; accepted December 21, 2013.
ACADEMIC PEDIATRICS 2014;14:115–116
THE RELEASE OF the Institute of Medicine’s reports Un-
the ACA and focus our efforts on eliminating inequities in quality of care? Universally, health care systems have recognized the importance of quality of care issues and their link to economic well-being and competitiveness. Concurrently, accountable care organization executives are shifting their discussions from individual health to population health and prevention. These changes in the health care system provide tremendous opportunity to change how we address disparities, from one of needing resources to one of effective resource utilization. But perhaps most importantly, the disparity discussion may now resonate from our clinics to the boardrooms, moving the elimination of health disparities to the cost-containment side of the health care ledger. In the final analysis, health disparities reduction should be a part of overall efforts to improve health outcomes and reduce health costs. When health systems can see the economic return on investment for efforts to reduce health disparities in the same way that they have begun to see health care quality, it will be the most important step in our efforts to eliminate health disparities. Two other key changes in health care make now an optimal time to make this shift in our thinking. First, the Health Information Technology for Economic and Clinical Health (HITECH) Act and Meaningful Use, which have resulted in a significant adoption of electronic health records (EHRs) in recent years. As of April 2013, approximately 80% of eligible hospitals in the United States and over 50% of physicians and other eligible health professionals had adopted EHRs.5 This will greatly expand the information on patients and populations, and it provides an opportunity for more productive use of EHRs for work on disparities. These new data resources will allow us to gain more in-depth and actionable information. However, the critical question is whether these systems will capture social determinants of health needed to evaluate disparities. Hatch et al utilized data from the electronic health database of a community health center network to track health insurance status of their patient population. Through these data analytics, they were able to develop a system of
equal Treatment: Confronting Racial and Ethnic Disparities in Health and Crossing the Quality Chasm: A New Health System for the 21st Century over a decade ago led to numerous efforts in programs, practice, and research to improve health equity and health care quality.1,2 The pediatric community has been in the forefront of this effort providing “high touch” community participatory efforts to reduce health disparities among children. However, the article in this month’s Academic Pediatrics by Dougherty and colleagues describing broad trends using the 2011 National Healthcare Quality Report (NHQR) and National Healthcare Disparities Report (NHDR) database highlight that at the macro level, little measurable change has occurred.3 In his foreword to the 2013 Centers for Disease Control (CDC) Health Disparities and Inequalities Report, Thomas Frieden, director of the CDC, noted that reports such as these give an overview of national level data sets and serve to “shine a bright light on the problem to be solved.”4 Yet given that we have shined the light for several decades, is it now time for analyses to provide insights on potential solutions? The shortcomings of actionable data from the article by Dougherty and colleagues and that of the CDC report are a reflection of the limitations of national data sets, not the reporting of the results. Reflection on the current study creates an opportunity to reframe the health disparities conversation. Dougherty and colleagues in their article report the results of the NHQR and NHDR database. The fact that neither database alone can answer the fundamental question of whether health disparities are improving, nor can they give us actionable metrics, is problematic if we are going to make progress in eliminating them. In the setting of the Affordable Care Act (ACA), with improved access to care for those traditionally underserved, the time is right to rethink how we conceptualize health disparities for children so we have metrics that will induce action. If inequity has resulted in disparities, and if inequity is transmitted through less access and lower quality, should we leverage ACADEMIC PEDIATRICS Copyright ª 2014 by Academic Pediatric Association
115
Volume 14, Number 2 March–April 2014
116
HORN AND MENDOZA
insurance surveillance to inform interventions to help their patients obtain and retain coverage.6 Also relevant is the work of Tomasallo et al, who used EHR data to determine the prevalence of asthma in Wisconsin.7 This use of EHR data to improve chronic disease surveillance on a local level can effectively identify areas of disparity, and more importantly can guide education and health care inventions. Finally, the technology revolution is not just occurring in the health care system but also among our patients, rich and poor—a fact that health care systems are investigating for their advantage in their efforts to connect to patients. Mobile health (mHealth), defined as the use of mobile and wireless devices to improve health outcomes, is offering significant opportunities overall.8 Steinhubl et al recently noted the potential of mHealth to transform health care by improving self-tracking, management of acute and chronic conditions, and clinical management by providers.9 This creates a unique opportunity for addressing health disparities that is not frequently discussed but clearly needs to become a focus. Given the fact that African Americans and English-speaking Latinos are actually more likely to own a mobile phone and to use mobile technology than whites,10 and that Latinos and African Americans are more likely than whites to look for health information on their phones,11 a unique opportunity exists to engage early in mHealth development those interested in eliminating health disparities. Both forms of technology (EHR and mHealth) demonstrate the new opportunities for data sources to provide actionable data at individual, local, regional, and national levels. Thus, we believe that now is the time to rethink how we measure and address health disparities, and now is the time to refocus our efforts to eliminate them. Although we believe we need to maintain and further develop “high touch” community participatory interventions, seeking the common ground among those interested in health disparities, health care quality, health economics, and technology will shift the discussion of disparities from the periphery of health care to its center. Quality based on health care dollar value will inevitably require discussions about how to improve quality and decrease cost—not only for those who traditionally have had insurance but also for those who have not. A discussion on health care quality and disparities then becomes a discussion that will necessitate new data sources targeted at understanding the social determinants of disease as well as the disease itself. Yet having more robust data sources does not guarantee a change in the currently stagnant progress toward reducing health disparities.
ACADEMIC PEDIATRICS
To that end, we propose the following recommendations. First, there needs to be a general agreement on areas to target. Rather than diluting effects by providing resources to disparate small but unrelated health outcomes, we suggest identification of key quality areas to be addressed in depth that will provide a framework for future efforts to be more productive. We encourage local and regional discussions among key constituents, patients, and communities that have experienced disparities. We recommend convening an Institute of Medicine committee focused on this area as a follow-up to the Unequal Treatment and Crossing the Chasm reports but that also builds on the more recent efforts related to the use of technology in health. Last, the results of this committee report should inform policy to target efforts and allocate resources to address health disparities through these venues. At the end of the day, creating incentives to encourage public and private sector participation will be the only way to finally eliminate health disparities for children in our country.
REFERENCES 1. Smedley BD, Stith AY, Nelson AR, eds. Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care. Washington, DC: National Academies Press; 1999. 2. Institute of Medicine. Crossing the Quality Chasm: A New Health System for the 21st Century. Washington, DC: National Academies Press; 2001. 3. Dougherty D, Chen X, Gray DT, Simon AE. Child and adolescent health care quality and disparities—are we making progress? Acad Pediatr. 2014;14:137–148. 4. Centers for Disease Control and Prevention. CDC health disparities and inequalities report—United States, 2013. MMWR Morb Mortal Wkly Rep. 2013;62(suppl 3):1. 5. Doctors and hospitals’ use of health IT more than doubles since 2012. Available at: http://www.hhs.gov/news/press/2013pres/05/20130522a. html. Accessed December 13, 2013. 6. Hatch B, Angier H, Marino M, et al. Using electronic health records to conduct children’s health insurance surveillance. Pediatrics. 2013; 132:e1584–e1591. 7. Tomasallo CD, Hanrahan LP, Tandias A, et al. Estimating Wisconsin asthma prevalence using clinical electronic health records and public health data. Am J Public Health. 2014;104:e65–e73. 8. NIH Consensus Group. Video report: what is mHealth? Available at: http://www.hrsa.gov/healthit/mhealth.html. Accessed December 13, 2013. 9. Steinhubl SR, Muse ED, Topol EJ. Can mobile health technologies transform health care? JAMA. 2013;310:2395–2396. 10. Brenner J. Pew Internet: mobile. http://pewinternet.org/Commentary/ 2012/February/Pew-Internet-Mobile.aspx. Accessed July 11, 2013. 11. Fox S, Duggan M. Mobile health, 2012. Pew Internet and American Life Project. Available at: http://www.pewinternet.org/Reports/ 2012/Mobile-Health/Main-Findings/Mobile-Health.aspx. Accessed November 8, 2012.
