Project Baby Bear: Rapid precision care incorporating rWGS in 5 California children's hospitals demonstrates improved clinical outcomes and reduced costs of care.

Genetic disorders are a leading contributor to mortality in neonatal and pediatric intensive care units (ICUs). Rapid whole-genome sequencing (rWGS)-based rapid precision medicine (RPM) is an intervention that has demonstrated improved clinical outcomes and reduced costs of care. However, the feasibility of broad clinical deployment has not been established. The objective of this study was to implement RPM based on rWGS and evaluate the clinical and economic impact of this implementation as a first line diagnostic test in the California Medicaid (Medi-Cal) program. Project Baby Bear was a payor funded, prospective, real-world quality improvement project in the regional ICUs of five tertiary care children's hospitals. Participation was limited to acutely ill Medi-Cal beneficiaries who were admitted November 2018 to May 2020, were <1 year old and within one week of hospitalization, or had just developed an abnormal response to therapy. The whole cohort received RPM. There were two prespecified primary outcomes-changes in medical care reported by physicians and changes in the cost of care. The majority of infants were from underserved populations. Of 184 infants enrolled, 74 (40%) received a diagnosis by rWGS that explained their admission in a median time of 3 days. In 58 (32%) affected individuals, rWGS led to changes in medical care. Testing and precision medicine cost $1.7 million and led to $2.2-2.9 million cost savings. rWGS-based RPM had clinical utility and reduced net health care expenditures for infants in regional ICUs. rWGS should be considered early in ICU admission when the underlying etiology is unclear.

Updating the Chronic Illness and Disability Payment System.

BACKGROUND: Of the 38 Medicaid programs that risk adjust payments to Medicaid managed care organizations (MCOs), 33 of them use the Chronic Illness and Disability Payment System (CDPS). There has been recent interest in adding social determinants of health (SDH) into risk-adjustment models. OBJECTIVE: To update the CDPS models using recent MCO data based on the International Classification of Diseases version 10 coding system and to explore whether indicators of SDH are predictive of expenditures. RESEARCH DESIGN: Data from 3 national Medicaid MCOs and 8 states are used to update the CDPS model. We test whether spending on Medicaid beneficiaries living in economically and socially deprived communities is greater than spending on similar beneficiaries in less deprived communities. SUBJECTS: Medicaid beneficiaries with full benefits and without dual eligibility under Medicare enrolled in Medicaid MCOs in 8 states during 2017-2019, including 1.4M disabled beneficiaries, 9.2M children, and 6.4M adults. MEASURES: Health care eligibility and claims records. Indicators based on the Social Deprivation Index were used to measure SDH. RESULTS: The revised CDPS model has 52 CDPS categories within 19 major categories. Six major categories of CDPS were revised: Psychiatric, Pulmonary, Renal, Cancer, Infectious Disease, and Hematological. We found no relationship between health care spending and the Social Deprivation Index. CONCLUSIONS: The revised CDPS models and regression weights reflect the updated International Classification of Diseases-10 coding system and recent managed care delivery. States should choose alternative payment strategies to address disparities in health and health outcomes.

Physician Turnover in the United States.

BACKGROUND: Medical groups, health systems, and professional associations are concerned about potential increases in physician turnover, which may affect patient access and quality of care. OBJECTIVE: To examine whether turnover has changed over time and whether it is higher for certain types of physicians or practice settings. DESIGN: The authors developed a novel method using 100% of traditional Medicare billing to create national estimates of turnover. Standardized turnover rates were compared by physician, practice, and patient characteristics. SETTING: Traditional Medicare, 2010 to 2020. PARTICIPANTS: Physicians billing traditional Medicare. MEASUREMENTS: Indicators of physician turnover-physicians who stopped practicing and those who moved from one practice to another-and their sum. RESULTS: The annual rate of turnover increased from 5.3% to 7.2% between 2010 and 2014, was stable through 2017, and increased modestly in 2018 to 7.6%. Most of the increase from 2010 to 2014 came from physicians who stopped practicing increasing from 1.6% to 3.1%; physicians moving increased modestly from 3.7% to 4.2%. Modest but statistically significant (P < 0.001) differences existed across rurality, physician sex, specialty, and patient characteristics. In the second and third quarters of 2020, quarterly turnover was slightly lower than in the corresponding quarters of 2019. LIMITATION: Measurement was based on traditional Medicare claims. CONCLUSION: Over the past decade, physician turnover rates have had periods of increase and stability. These early data, covering the first 3 quarters of 2020, give no indication yet of the COVID-19 pandemic increasing turnover, although continued tracking of turnover is warranted. This novel method will enable future monitoring and further investigations into turnover. PRIMARY FUNDING SOURCE: The Physicians Foundation Center for the Study of Physician Practice and Leadership.

Measuring Medicaid Physician Participation Rates and Implications for Policy.

Policy makers continue to debate Medicaid expansion under the Affordable Care Act, and concerns remain about low provider participation in the program. However, there has been little research on how various measures of physician participation may reflect different elements of capacity for care within the Medicaid program and how these distinct measures correlate with one another across states. Our objectives were to describe several alternative measures of provider participation in Medicaid using recently publicly available data, to compare state rankings across these different metrics, and to discuss potential advantages and disadvantages of each measure for research and policy purposes. Overall, we find that Medicaid participation as measured by raw percentages of physicians taking new Medicaid patients is only weakly correlated with population-based measures that account for both participation rates and the numbers of physicians per capita or physicians per Medicaid beneficiary. Participation rates for all physicians versus primary care physicians also offer different information about state-level provider capacity. Policy makers should consider multiple dimensions of provider access in assessing policy options in Medicaid, and further research is needed to evaluate the linkages between these provider-based measures and beneficiaries' perceptions of access to care in the program.

Bringing Patient-Centered Outcomes Research to Life.

A substantial gap exists between medical evidence that is known and medical evidence that is put into practice. Although the Agency for Healthcare Research and Quality (AHRQ) has a long history of developing the content of evidence, the agency now pivots to close that gap by focusing on evidence dissemination and implementation. Achieving better health outcomes requires both the generation of new patient-centered outcomes research (PCOR) knowledge and the appropriate and timely implementation of that knowledge into practice. The Affordable Care Act provided funds to support both types of PCOR efforts, with AHRQ building on years of experience to advance research dissemination and implementation. This article describes the work the AHRQ has done, is doing, and will do in the future. To communicate PCOR evidence findings, AHRQ is currently synthesizing research findings into convincing collections of evidence that can be best taken up by clinicians, patients and caregivers, and policymakers. The future direction for AHRQ is to improve the context for evidence and practice improvement, thereby creating an environment receptive to PCOR. Toward this goal, AHRQ is actively engaging partners, such as professional societies and insurers, to make evidence central to decision making. In addition, AHRQ recently launched two programs that seek to both understand and encourage the use of evidence in clinical practice. Throughout these efforts, AHRQ will continually assess needs and adapt initiatives to ensure that PCOR translates into improved patient-centered health outcomes.

Impact of individual-, environmental-, and policy-level factors on health care utilization among US farmworkers.

OBJECTIVES: We examined individual-, environmental-, and policy-level correlates of US farmworker health care utilization, guided by the behavioral model for vulnerable populations and the ecological model. METHODS: The 2006 and 2007 administrations of the National Agricultural Workers Survey (n = 2884) provided the primary data. Geographic information systems, the 2005 Uniform Data System, and rurality and border proximity indices provided environmental variables. To identify factors associated with health care use, we performed logistic regression using weighted hierarchical linear modeling. RESULTS: Approximately half (55.3%) of farmworkers utilized US health care in the previous 2 years. Several factors were independently associated with use at the individual level (gender, immigration and migrant status, English proficiency, transportation access, health status, and non-US health care utilization), the environmental level (proximity to US-Mexico border), and the policy level (insurance status and workplace payment structure). County Federally Qualified Health Center resources were not independently associated. CONCLUSIONS: We identified farmworkers at greatest risk for poor access. We made recommendations for change to farmworker health care access at all 3 levels of influence, emphasizing Federally Qualified Health Center service delivery.

The effects of coding intensity in Medicare Advantage on plan benefits and finances.

OBJECTIVE: To assess how beneficiary premiums, expected out-of-pocket costs, and plan finances in the Medicare Advantage (MA) market are related to coding intensity. DATA SOURCES/STUDY SETTING: MA plan characteristics and administrative records from the Centers for Medicare and Medicaid Services (CMS) for the sample of beneficiaries enrolled in both MA and Part D between 2008 and 2015. Medicare claims and drug utilization data for Traditional Medicare (TM) beneficiaries were used to calibrate an independent measure of health risk. STUDY DESIGN: Coding intensity was measured by comparing the CMS risk score for each MA contract with a contract level risk score developed using prescription drug data. We conducted regressions of plan outcomes, estimating the relationship between outcomes and coding intensity. To develop prescription drug scores, we assigned therapeutic classes to beneficiaries based on their prescription drug utilization. We then regressed nondrug spending for TM beneficiaries in 2015 on demographic and therapeutic class identifiers for 2014 and used the coefficients to predict relative risk. PRINCIPAL FINDINGS: We found that, for each $1 increase in potential revenue resulting from coding intensity, MA plan bid submissions declined by $0.10 to $0.19, and another $0.21 to $0.45 went toward reducing plans' medical loss ratios, an indication of higher profitability. We found only a small impact on beneficiary's projected out-of-pocket costs in a plan, which serves as a measure of the generosity of plan benefits, and a $0.11 to $0.16 reduction in premiums. As expected, coding intensity's effect on bids was substantially larger in counties with higher levels of MA competition than in less competitive counties. CONCLUSIONS: While coding intensity increases taxpayers' costs of the MA program, enrollees and plans both benefit but with larger gains for plans. The adoption of policies to more completely adjust for coding intensity would likely affect both beneficiaries and plan profits.

Health Insurance Mandates for Nonpharmacological Pain Treatments in 7 US States.

This cross-sectional study examines the extent to which states have introduced or enacted mandates for coverage of nonpharmacological pain treatments and characterizes the variation in such mandates.

The response of small businesses to variation in the price of health insurance: results from a randomized controlled trial.

There is substantial interest in attempts to reduce the number of uninsured persons by providing subsidies to small businesses. To measure the responsiveness of small businesses to offers of subsidized coverage, the authors conducted a randomized controlled trial in which selected groups of San Diego businesses were offered the opportunity to purchase coverage at prices ranging from $20 to $100 per month for an employee-only policy. At $20 per month, an estimated 40% of eligible businesses purchased insurance; at $100 per month, 13% purchased insurance. Small businesses not currently offering insurance to employees are not very responsive to large reductions in the price of coverage. Programs to subsidize insurance for small businesses and their employees are unlikely to substantially reduce the number of uninsured persons.

Getting What We Pay For: How Do Risk-Based Payments to Medicare Advantage Plans Compare with Alternative Measures of Beneficiary Health Risk?

OBJECTIVE: To estimate the relative health risk of Medicare Advantage (MA) beneficiaries compared to those in Traditional Medicare (TM). DATA SOURCES/STUDY SETTING: Medicare claims and enrollment records for the sample of beneficiaries enrolled in Part D between 2008 and 2015. STUDY DESIGN: We assigned therapeutic classes to Medicare beneficiaries based on their prescription drug utilization. We then regressed nondrug health spending for TM beneficiaries in 2015 on demographic and therapeutic class identifiers for 2014 and used coefficients from this regression to predict relative risk of both MA and TM beneficiaries. PRINCIPAL FINDINGS: Based on prescription drug utilization data, beneficiaries enrolled in MA in 2015 had 6.9 percent lower health risk than beneficiaries in TM, but differences based on coded diagnoses suggested MA beneficiaries were 6.2 percent higher risk. The relative health risk based on drug usage of MA beneficiaries compared to those in TM increased by 3.4 p.p. from 2008 to 2015, while the relative risk using diagnoses increased 9.8 p.p. CONCLUSIONS: Our results add to a growing body of evidence suggesting MA receives favorable, or, at worst, neutral selection. If MA beneficiaries are no healthier and no sicker than similar beneficiaries in TM, then payments to MA plans exceed what is warranted based on their health status.

Beyond The ACA: Paths To Universal Coverage In California.

California has long sought to achieve universal health insurance coverage for its residents. The state's uninsured population was dramatically reduced as a result of the Affordable Care Act (ACA). However, faced with federal threats to the ACA, California is exploring how it might take greater control over the financing of health care. In 2017 the state Senate passed the Healthy California Act, SB-562, calling for California to adopt a single-payer health care system. The state Assembly did not vote on the bill but held hearings on a range of options to expand coverage. These hearings highlighted the many benefits of unified public financing, whether a single- or multipayer system (which would retain health plans as intermediaries). The hearings also identified significant challenges to pooling financial resources, including the need for federal cooperation and for new state taxes to replace employer and employee payments. For now, California's single-payer legislation is stalled, but the state will establish a task force to pursue unified public financing to achieve universal health insurance. California's 2018 gubernatorial and legislative elections will provide a forum for further health policy debate and, depending on election outcomes, may establish momentum for more sweeping change.