Equity in health and health care in America continues to be a goal unmet. Certain demographic groups in the United States—including racial and ethnic minorities and individuals with lower socioeconomic status—are less likely to get the preventive care they need to stay healthy, more likely to suffer from chronic illnesses such as diabetes and heart disease, more often to live in neighborhoods where they are exposed to harmful environmental pollutants, less likely to have access to optimal health care, and, in general, have poorer health outcomes across a wide array of diseases and have higher all-cause mortality.1–3 These disparities have deep roots in the social determinants of health: the circumstances in which people are born, grow, live, work, and age.4 Yet despite our growing understanding of how social-, structural-, and individual-level factors maintain and create inequities, solutions to reduce or eliminate them have been elusive.
Given this intransigence, it is no surprise that reducing systematic, avoidable differences in health between socially advantaged and disadvantaged groups has become a priority for providers, researchers, and policy makers alike.4–7 The decade-old Institute of Medicine report, Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care, documented pervasive disparities across the health care system and called for research-driven solutions and the dissemination and implementation of those solutions.6 The National Healthcare Disparities Report 2012 from the Agency for Healthcare Research and Quality (the most recent of these reports) suggests that progress has been minimal or absent.2 Despite decades of effort and commitment, the existing evidence base for policy- and research-driven solutions remains insufficient.8–11
Certainly there are examples where local, context-specific interventions to achieve health and health care equity have proven successful,12 and efforts to embed cultural and linguistic competency and cultural humility into medical education and clinical care have been embraced.13–15 However, a powerful lever has yet to be pulled: the implementation of upstream policies that change the underlying systems that promote health inequities. Although policy interventions at the clinical and payer levels cannot single-handedly eliminate disparities given the significant role the social determinants of health play in morbidity and mortality,16,17 such policies can allow our health care system to better identify and leverage community assets; provide high-quality, more equitable care; and narrow the gaps.
The Patient Protection and Affordable Care Act (ACA) contains numerous provisions with the power to reduce inequities in both health and health care.18–20 These include improved demographic data collection, broader clinical and community-based prevention efforts, funding for community health grants, expanded health care access for underserved populations, and stronger commitments to workforce training for public health and clinical health care providers. The legislation has also set into motion changes in Medicare and Medicaid reimbursement and performance incentive plans for hospitals and physicians that could further help reduce health care inequities. The new payment models move away from fee-for-service rates to models that favor reimbursement for episodes of care (“bundled payments”) or to those that emphasize quality-driven, coordinated, population-based care through medical homes and accountable care organizations. Under the Centers for Medicare and Medicaid Services’ (CMS’s) Hospital Value Based Purchasing program, for instance, hospitals will be given incentives to meet quality targets related to improved health outcomes and patient satisfaction, and penalized for “excessive readmissions” (starting in 2013) and iatrogenic infections (starting in 2015). CMS is also implementing a value-based modifier that directly targets physicians and physician groups, paying them differentially based on performance on quality and on cost measures. The upshot for health and health care inequities? Many of the proposed value-driven payment models in the ACA focus on preventable conditions that disproportionately affect racial/ethnic minorities and the poor.21,22
The focus of the new payment models—on conditions that more often affect those groups who suffer from health and health care disparities—presents an unprecedented moment in time to make real and measurable progress in closing these gaps. Linking explicit ACA disparities provisions with incentives around value-based health care would encourage providers, researchers, and health care administrators to hasten the development of evidence-based solutions to inequities. Successfully linking these elements will hinge, however, on creating incentives that specifically reflect the complexities of caring for historically underserved groups most adversely affected by social determinants of health. History has shown that well-intentioned policies and programs that do not directly address the challenges of improving outcomes for such populations will not necessarily benefit all equally, and health inequities will persist and, in fact, may increase.23–25
There is no time to lose: Efforts to align the shifts in our health care landscape toward equity are more likely to be successful if they are made before policies and programs are fully implemented and the opportunity to exert influence has passed.
Aligning ACA Disparities Provisions and Value-Based Health Care
Below, we offer a few examples of how disparities provisions and value-based health care could be aligned, weaving together the principles of payment reform, health information technology (HIT), community health needs assessments (CHNAs), and expanding health equity research.
The ACA-proposed policies for payment reform are compelling targets for incorporating metrics to counter socioeconomic and racial/ethnic inequities in health. Integrating incentives to minimize or eradicate health care inequities alongside the currently proposed health outcome and patient satisfaction targets can increase focus on developing solutions for those avoidable gaps in care. To be effective, any metrics used to reduce disparities must be contextually relevant and sensitive enough to detect and monitor population health differences, and must integrate the perspectives of hospital executives and frontline practitioners who provide care for those groups most affected.26,27
As a case in point, Massachusetts was one of the first states to incorporate health disparities metrics into pay-for-performance schemes. The chosen metrics were predicated on the assumptions that racial and ethnic disparities in hospital-delivered health care did exist and that every hospital’s patient population was diverse enough to measure these inequities. Neither assumption was supported.28 In addition, the Massachusetts hospital community found that incorporating the disparities measures was burdensome, given other reporting requirements, and that the emphasis on compliance with top-down metrics left little time for meaningful structural changes that could potentially narrow health care gaps revealed in their site-level analyses.28
Thus, in designing future inequity-related incentive programs, pay-for-performance efforts should target quality improvements that are relevant to the patient population served by targeted hospitals. These efforts must also engage the hospitals and care providers in metrics creation and not be too costly or burdensome to implement. Finally, incentives must be thoughtfully constructed to avoid penalizing safety-net hospitals or other institutions that are most likely to care for populations affected by disparities and affected by social determinants of health.
Fortunately, programs and policies that support HIT, CHNAs, and patient- and community-centered research are either already in place or poised to be implemented that could, if strengthened and focused, leverage ACA-driven payment reform in a way that is cost-effective, respectful of local contexts and needs, and nonpunitive to hospitals and providers who care for the sickest among us.
Health information technology
HIT and electronic health records (EHRs) are recognized as invaluable tools in the search for solutions to health care disparities.29–31 To jump-start this process, the American Recovery and Reinvestment Act of 2009 established a federal program for adopting EHRs and for defining federal standards, including data for patient demographic characteristics. However, the current slate of milestones (also known as meaningful use) for the EHR Incentive Program does not tap the full potential of EHRs’ disparities-reducing power. To comply with the sole objective explicitly related to health disparities, eligible providers or practices need only “generate at least one report listing patients … with a specific condition.”32 Stratification and subgroup analyses are neither specified nor required.33,34
The ACA has set additional standards for the collection of data on race, ethnicity, sex, primary language, and disability status that could be used to stratify patient lists and quality/outcome data to identify health care inequities. Do hospital data reveal gender differences in blood pressure control, for example? Or differences by zip code in readmissions for congestive heart failure? Such subgroup analyses could be internally reported to focus quality improvement efforts on pertinent inequities,35 or publicly reported to motivate physicians, administrators, and other stakeholders to reduce or eliminate health care inequities and to reward the maintenance of equity.
For publicly reported disparity data, providers and hospital groups could serve as their own benchmarks in terms of local health care gaps and could be rewarded in future years for providing data showing that such gaps have closed. This self-benchmarking would help ensure that the targeted disparities are contextually relevant and that progress toward equity is tied to their sites and not to a national, one-size-fits-all criterion. That said, some general measurement standardization will be crucial. The National Quality Forum (NQF) and the Disparities Solutions Center have written extensively about how disparities-sensitive and -specific measures could be developed, implemented, and analyzed.36,37 Because meaningful use standards already require the collection of demographic data and the generation of patient lists, any additional financial burden for data collection would be minimal or nonexistent.
Community health needs assessments
Currently, CMS’s fee-for-service physician and hospital reimbursement schedule includes a geographic adjustment that accounts for the varying cost of rent and staff compensation. This geographic adjustment does not, however, consider the difficulties associated with providing and receiving care in environments that give rise to inherent barriers to good health. How do a team of health professionals and a patient craft a plan to control diabetes in a town with no access to fresh fruits and vegetables? How easily can people with asthma avoid emergency department visits in a neighborhood plagued by air pollution? Any payment or reward scheme that includes health equity metrics must take such questions into account so that expectations of change are context-specific. Yet, despite growing evidence that social factors affect readmission and mortality rates for conditions like pneumonia and heart failure,38 there is no current effort to adjust for such factors in incentive structures.
Under the ACA, 501(c)(3), nonprofit hospitals are newly required to undertake a CHNA every three years in order to maintain tax-exempt status. By design, the CHNA process is collaborative and involves input from public health experts and community members served by the hospital—specifically, “members of medically underserved, low-income, and minority populations.”39 Subsequent to the assessment, each organization must submit a plan and implementation strategy that delineates the needs it will address and those it will not.
Although the Internal Revenue Service has only recently proposed draft regulations, the ACA’s CHNA requirement went into effect for taxable years beginning after March 23, 2012. It is possible to envision how the local data collected regarding the social determinants that affect a hospital’s patient population could contribute to evidence-based adjustments for hospital incentives and reimbursements.
First, for physician reimbursement, a new composite variable could be created that incorporates aspects of the local environment—food availability, transportation, quality of schools, unemployment levels, and so forth—into a community-level adjustment. This risk adjustment, when incorporated into a broader patient risk adjustment or stratification methodology, could serve to further level the field in terms of the “cost” of providing health care to a community; some areas require more of an investment.
Second, hospital-based pay-for-performance incentives could be adjusted for the relative difficulty in achieving inequity-reduction goals. The same gain in different communities would yield different rewards based on a social-determinants-of-health metric. Similarly, a smaller gain in a particularly disadvantaged community may be “worth” as much as a larger gain in a more affluent one. Both of these adjustments would make it less likely that safety-net providers would be penalized for the geographic characteristics of their patient populations. Community-level data derived from scientifically rigorous CHNAs and other local health outcomes data could provide researchers the requisite information to craft such adjustments.
Furthermore, whereas monetary penalties accompany failure to complete a CHNA, the federal government has not announced incentives for successfully addressing the identified social determinants and local needs within the three-year period between assessments. Incentives tied to CHNA-based improvements would foster meaningful collaborations, ease the financial burden on nonprofit hospitals for carrying out these assessments, and yield partnerships and research opportunities to identify downstream solutions to improve the conditions in which people are born, live, work, and age.
Finally, whereas all hospitals are subject to the payment reforms moving us toward value-based health care and could therefore potentially benefit from adjustments derived from CHNA and other data sources, for-profit hospitals are currently not required to conduct a CHNA. If we are truly committed to achieving health equity, all institutions, regardless of tax-exempt status, should develop plans to address salient social determinants of health based on a current understanding of their communities’ needs and assets.
Expanding health equity research
The proposals presented here are ambitious and must be supported by a concomitant focus on solutions-oriented health equity research that aims to develop appropriate outcome metrics and craft process evaluation protocols that elucidate the mechanisms through which interventions succeed or fail. While researchers should continue to conduct descriptive studies documenting inequities—indeed, measuring disparities is how we judge progress toward equity—the breadth and depth of health inequities demand that we move beyond describing and documenting to rapidly building an evidence base of what works to close the gaps.40
The ACA presents a major step forward in the national commitment to building this evidence base by allocating Medicare and Medicaid trust fund dollars to the creation of the Patient Centered Outcomes Research Institute (PCORI). PCORI’s mission is to build a patient- and population-centered evidence base of what works best, for whom, and why, and health disparities is one of their priority funding areas. Tying physician and hospital payments to novel, local data-adjusted health equity metrics and to a documented narrowing of local health and health care inequities would require input from various research sectors that could draw on this critical new funding stream.
Health systems researchers and clinical care teams would necessarily play an integral role in establishing and monitoring the EHR-based measurement of local health inequities and in setting reasonable, context-sensitive improvement goals.41 Practitioners of community-based participatory research (CBPR), along with community partners and program evaluators, would be instrumental in creating meaningful CHNAs that could be used to inform any new adjustment on the basis of social determinants of health. Health economists and epidemiologists would need to work together to translate these results into new metrics for fee and incentive schedules. Finally, implementation scientists and quality improvement officers would be essential if we are to translate effective inequity-narrowing policies and programs from the community or system where they originate into other contexts.
The ACA provides other research building blocks as well. The legislation elevated the former National Center on Minority Health and Health Disparities (NCMHD) to a full-fledged institute (the National Institute on Minority Health and Health Disparities [NIMHD]) within the National Institutes of Health. The NIMHD supports three funding streams that hold great promise for forging successful research collaborations: its Center of Excellence program, its Transdisciplinary Collaborative Centers for Health Disparities Research, and its CBPR awards. Additionally, the ACA created the Community Transformation Grants, funded by the Centers for Disease Prevention and Control, that seek to improve health and reduce disparities by building the capacity of communities and states to analyze data, forge relevant partnerships, and develop plans with related health impact measures. All of these funding streams could be leveraged to weave together health equity research, payment reform, and community-based initiatives. PCORI’s requirement that investigators plan in advance how best to disseminate findings to all stakeholders stands out in its acknowledgment that community- and patient engagement are essential to broaden the impact of this research. Finally, given the different state-level approaches to Medicaid expansion and health insurance exchanges, research funding should be applied to studying the impact of these decisions on population health and health equity.
Challenges and Opportunities
Establishing practices to affect structural, system-based inequities will not be easy. We have outlined why incentives associated with payment reform, meaningful use of EHRs, and CHNAs require appropriate metrics to measure disparities. Thankfully, guidance on the measurement of disparities exists,36,42 and we applaud the NQF for recently endorsing 12 disparities-related quality metrics that focus on processes and intermediate outcomes like language services and cultural competency.43 Now is the time to build on those metrics and focus on health outcomes. We are encouraged by the NQF’s current efforts to review their full portfolio of endorsed performance measures to identify those that are most disparity-sensitive based on disease prevalence, documented inequity, and demonstrated impact on the health of a community. Once such measures are endorsed, it will be paramount to support institutions as they work to employ them and implement evidence-based solutions.
Also, developing the list of health disparities that could qualify for reimbursement incentives will require a systematic determination that takes into account the complexities of providing care to vulnerable populations and then makes the list relevant for various contexts of care. One step forward would be for researchers and advocates to present further evidence to persuade CMS to reverse its recent decision against adjusting for socioeconomic status and dual eligibility in its readmissions incentives.
The road to health equity has to engage every sector of society to fully address social determinants of health and minimize their impact on disparities. Our suggestions focus almost exclusively on the integral role the health care system can play in reducing or eliminating health and health care inequities. They are not a collective magic solution, but they are a start. The ACA and other recent legislation have sown the seeds to reverse the momentum: Data collection standards, meaningful use, payment reform, novel funding opportunities, and community-focused assessments are all in place. Now is the time to accelerate the pace at which these components grow together so that policy makers, care providers, and researchers can use this historic moment to demonstrate that equity is a value in health.
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