Health Costs And Financing: Challenges And Strategies For A New Administration.

It is likely that 2021 will be a dynamic year for US health care policy. There is pressing need and opportunity for health reform that helps achieve better access, affordability, and equity. In this commentary, which is part of the National Academy of Medicine's Vital Directions for Health and Health Care: Priorities for 2021 initiative, we draw on our collective backgrounds in health financing, delivery, and innovation to offer consensus-based policy recommendations focused on health costs and financing. We organize our recommendations around five policy priorities: expanding insurance coverage, accelerating the transition to value-based care, advancing home-based care, improving the affordability of drugs and other therapeutics, and developing a high-value workforce. Within each priority we provide recommendations for key elected officials and political appointees that could be used as starting points for evidence-based policy making that supports a more effective, efficient, and equitable health system in the US.

Implementing a targeted approach to social determinants of health interventions.

The scale of the coronavirus disease 2019 pandemic and its disproportionate impact on vulnerable populations has spurred unprecedented focus on and investment in social determinants of health (SDOH). Although the greater focus on social determinants is laudable and necessary, there is a tendency for health care organizations to implement SDOH programs at scale without rigorous evidence of effect, rather than targeting interventions to specific patients and assessing their impact. This broad, and sometimes blind, application of SDOH interventions can be costly and wasteful. We argue for rejecting the "more is better" mindset and specifically targeting patients who truly need and would substantially benefit from SDOH interventions. Matching interventions to the most appropriate patients involves screening for social needs, developing rigorous evidence of effect, and accompanying policy reform.

The Beneficial Effects Of Medicare Advantage Special Needs Plans For Patients With End-Stage Renal Disease.

Patients with end-stage renal disease (ESRD) are a vulnerable population with high rates of morbidity, mortality, and acute care use. Medicare Advantage Special Needs Plans (SNPs) are an alternative financing and delivery model designed to improve care and reduce costs for patients with ESRD, but little is known about their impact. We used detailed clinical, demographic, and claims data to identify fee-for-service Medicare beneficiaries who switched to ESRD SNPs offered by a single health plan (SNP enrollees) and similar beneficiaries who remained enrolled in fee-for-service Medicare plans (fee-for-service controls). We then compared three-year mortality and twelve-month utilization rates. Compared with fee-for-service controls, SNP enrollees had lower mortality and lower rates of utilization across the care continuum. These findings suggest that SNPs may be an effective alternative care financing and delivery model for patients with ESRD.

Addressing Patient Bias and Discrimination Against Clinicians of Diverse Backgrounds.

The duty to care for all patients is central to the health professions, but what happens when clinicians encounter patients who exhibit biased or discriminatory behaviors? While significant attention has focused on addressing clinician bias toward patients, incidents of patient bias toward clinicians also occur and are difficult to navigate.Clinicians anecdotally describe their experiences with patient bias, prejudice, and discrimination as profoundly painful and degrading. Though this phenomenon has not been rigorously studied, it is not unreasonable to postulate that the moral distress caused by patient bias may ultimately contribute to clinician burnout. Because women and minority clinicians are more likely to be targets of patient bias, this may worsen existing disparities for these groups and increase their risk for burnout. Biased behavior may also affect patient outcomes.Although some degree of ignoring derogatory comments is necessary to maintain professionalism and workflow, clinicians also have the right to a workplace free of mistreatment and abuse. How should clinicians reconcile the expectation to always "put patients first" with their basic right to be treated with dignity and respect? And how can health care organizations develop policies and training to mitigate the effects of these experiences?The authors discuss the ethical dilemmas associated with responding to prejudiced patients and then present a framework for clinicians to use when directly facing or witnessing biased behavior from patients. Finally, they describe strategies to address patient bias at the institutional level.

Mobile health clinic model in the COVID-19 pandemic: lessons learned and opportunities for policy changes and innovation.

BACKGROUND: Mobile Clinics represent an untapped resource for our healthcare system. The COVID-19 pandemic has exacerbated its limitations. Mobile health clinic programs in the US already play important, albeit under-appreciated roles in the healthcare system. They provide access to healthcare especially for displaced or isolated individuals; they offer versatility in the setting of a damaged or inadequate healthcare infrastructure; and, as a longstanding community-based service delivery model, they fill gaps in the healthcare safety-net, reaching social-economically underserved populations in both urban and rural areas. Despite an increasing body of evidence of the unique value of this highly adaptable model of care, mobile clinics are not widely supported. This has resulted in a missed opportunity to deploy mobile clinics during national emergencies such as the COVID-19 pandemic, as well as using these already existing, and trusted programs to overcome barriers to access that are experienced by under-resourced communities. MAIN TEXT: In March, the Mobile Healthcare Association and Mobile Health Map, a program of Harvard Medical School's Family Van, hosted a webinar of over 300 mobile health providers, sharing their experiences, challenges and best practices of responding to COVID 19. They demonstrated the untapped potential of this sector of the healthcare system in responding to healthcare crises. A Call to Action: The flexibility and adaptability of mobile clinics make them ideal partners in responding to pandemics, such as COVID-19. In this commentary we propose three approaches to support further expansion and integration of mobile health clinics into the healthcare system: First, demonstrate the economic contribution of mobile clinics to the healthcare system. Second, expand the number of mobile clinic programs and integrate them into the healthcare infrastructure and emergency preparedness. Third, expand their use of technology to facilitate this integration. CONCLUSIONS: Understanding the economic and social impact that mobile clinics are having in our communities should provide the evidence to justify policies that will enable expansion and optimal integration of mobile clinics into our healthcare delivery system, and help us address current and future health crises.

Impact of complex care management on spending and utilization for high-need, high-cost Medicaid patients.

OBJECTIVES: Complex care management programs have emerged as a promising model to better care for high-need, high-cost patients. Despite their widespread use, relatively little is known about the impact of these programs in Medicaid populations. This study evaluated the impact of a complex care management program on spending and utilization for high-need, high-cost Medicaid patients. STUDY DESIGN: Randomized quality improvement trial conducted at CareMore Health in Memphis, Tennessee. A total of 253 high-need, high-cost Medicaid patients were randomized in a 1:2 ratio to complex care management or usual care. METHODS: Intention-to-treat analysis compared regression-adjusted rates of spending and utilization between patients randomized to the complex care program (n = 71) and those randomized to usual care (n = 127) over the 12 months following randomization. Primary outcomes included total medical expenditures (TME) and inpatient (IP) days. Secondary outcomes included IP admission, emergency department (ED) visits, care center visits, and specialist visits. RESULTS: Compared with patients randomized to usual care, patients randomized to complex care management had lower TME (adjusted difference, -$7732 per member per year [PMPY]; 95% CI, -$14,914 to -$550; P = .036), fewer IP bed days (adjusted difference, -3.46 PMPY; 95% CI, -4.03 to -2.89; P <.001), fewer IP admissions (adjusted difference, -0.32 PMPY; 95% CI, -0.54 to -0.11; P = .014), and fewer specialist visits (adjusted difference, -1.35 PMPY; 95% CI, -1.98 to -0.73; P <.001). There was no significant impact on care center or ED visits. CONCLUSIONS: Carefully designed and targeted complex care management programs may be an effective approach to caring for high-need, high-cost Medicaid patients.

Eliminating barriers to virtual care: implementing portable medical licensure.

Telemedicine offers a promising solution to the growing physician shortage, but state-based medical licensing poses a significant barrier to the widespread adoption of telemedicine services. We thus recommend a mutual recognition scheme whereby states honor each other's medical licenses. Successfully implementing mutual recognition requires policy, technological, and administrative changes, including a federal mandate for states to participate in mutual recognition, consistent standards for using and regulating telemedicine, a mechanism to enable interstate data sharing, financial support for states, and a "state of principal license" requirement for physicians. Reforming the United States' outdated system of state-based medical licensure can help meet patient demand for virtual care services and improve access to care in rural and medically underserved areas.

The sociobehavioral phenotype: applying a precision medicine framework to social determinants of health.

Sociobehavioral phenotypes are actionable risk profiles based on empirically derived social, economic, and behavioral factors that, if applied appropriately, can help healthcare organizations address social determinants of health.