Medicare Switching: Patterns Of Enrollment Growth In Medicare Advantage, 2006-22.

Medicare Advantage (MA) has grown rapidly over the course of the past two decades and is projected to continue to grow. We examined sources of new enrollment in MA and analyzed the switching patterns between MA and traditional fee-for-service Medicare, using more recent and more detailed data than in previous analyses. We found that switching from fee-for-service Medicare to MA more than tripled between 2006 and 2022, whereas switching from MA to fee-for-service Medicare decreased, with the change rates accelerating since 2019. The share of switchers among all new MA enrollees rose from 61 percent in 2011 to 80 percent in 2022. Black, dual-eligible, and disabled beneficiaries had higher odds of switching in both directions, whereas younger and healthier beneficiaries had higher odds of switching from fee-for-service Medicare to MA but lower odds of switching from MA to fee-for-service Medicare. Two-thirds of annual switching between MA and fee-for-service Medicare in 2022 occurred in January, likely reflecting the open enrollment period.

Concentration of Physician Services Across Insurers and Effects on Quality: Early Evidence From Medicare Advantage.

BACKGROUND: A growing proportion of Medicare beneficiaries is covered by private insurers through Medicare Advantage, yet little is known about how these plans are structured in terms of relationships with physicians and implications for quality of care. OBJECTIVE: The objective of this study was to assess whether greater physician concentration of services across insurers was associated with higher quality in Medicare Advantage (MA), overall and particularly among MA insurers serving a high proportion of vulnerable enrollees. RESEARCH DESIGN: A retrospective cohort design with regression analysis. DATA SOURCES: The primary dataset was 2014 MA encounter records submitted by insurers to the Centers for Medicare and Medicaid Services, covering 600,329 physicians across 119 insurers. These data were merged with Centers for Medicare and Medicaid Services data on MA contract quality rating as well as physician characteristics in the Medicare Data on Provider Practice and Specialty file. MEASURES: Two measures were generated to capture the concentration of physician services across insurers: the percentage of a physician's Medicare services which was through MA (MA penetration); and the percentage of a physician's MA services with a specific insurer (insurer share of MA services). RESULTS: Greater MA penetration and insurer share of MA services were each associated with higher MA plan quality. The relationship between insurer share and quality was stronger in contracts with a relatively high percentage of disabled enrollees. CONCLUSION: Greater physician concentration of services across MA insurers was associated with a higher quality of care overall and especially among vulnerable enrollees.

Town and Gown Differences Among the 100 Largest Medical Groups in the United States.

PURPOSE: The authors undertook a study to determine whether large academic and community-based medical groups differ in terms of their financial stake in Medicare Advantage or Medicare Accountable Care Organizations (ACOs) and whether their participation in these alternative payment models is related to their size, specialty mix, and Medicare physician market share in their local area. METHOD: The authors used the 2013 Medicare Data on Provider Practice and Specialty database and a national database of ACOs to conduct a cross-sectional descriptive study of the 100 largest medical groups in the United States. Medical groups were categorized as academic or community based on matches of their name with a list of U.S. medical schools or the results of a series of Internet search procedures. RESULTS: Sixty-eight of the 100 largest groups were academic, and 32 were community based. On average, community-based groups had more than twice the percentage of primary care physicians as academic groups (mean, 38.4%; 95% CI, 34.7%-42.0%; vs. 18.3%; 95% CI, 17.0%-19.6%). Community groups were significantly (P < .001) more likely than academic groups to have a financial stake in a Medicare ACO or Medicare Advantage plan, but this difference was no longer significant when the percentage of primary care physicians in the group was added to the model. CONCLUSIONS: The specialty mix within academic medical groups may hinder their ability to transform themselves into organizations that can manage the financial responsibilities of caring for a patient population through a Medicare ACO or Medicare Advantage.

Measuring coding intensity in the Medicare Advantage program.

BACKGROUND: In 2004, Medicare implemented a system of paying Medicare Advantage (MA) plans that gave them greater incentive than fee-for-service (FFS) providers to report diagnoses. DATA: Risk scores for all Medicare beneficiaries 2004-2013 and Medicare Current Beneficiary Survey (MCBS) data, 2006-2011. MEASURES: Change in average risk score for all enrollees and for stayers (beneficiaries who were in either FFS or MA for two consecutive years). Prevalence rates by Hierarchical Condition Category (HCC). RESULTS: Each year the average MA risk score increased faster than the average FFS score. Using the risk adjustment model in place in 2004, the average MA score as a ratio of the average FFS score would have increased from 90% in 2004 to 109% in 2013. Using the model partially implemented in 2014, the ratio would have increased from 88% to 102%. The increase in relative MA scores appears to largely reflect changes in diagnostic coding, not real increases in the morbidity of MA enrollees. In survey-based data for 2006-2011, the MA-FFS ratio of risk scores remained roughly constant at 96%. Intensity of coding varies widely by contract, with some contracts coding very similarly to FFS and others coding much more intensely than the MA average. Underpinning this relative growth in scores is particularly rapid relative growth in a subset of HCCs. DISCUSSION: Medicare has taken significant steps to mitigate the effects of coding intensity in MA, including implementing a 3.4% coding intensity adjustment in 2010 and revising the risk adjustment model in 2013 and 2014. Given the continuous relative increase in the average MA risk score, further policy changes will likely be necessary.

Proportion of physicians in large group practices continued to grow in 2009-11.

Payers and advocates for improved health care quality are raising expectations for greater care coordination and accountability for care delivery, and physician groups may be responding by becoming larger. We used Medicare claims from the period 2009-11, merged with information from the Medicare provider enrollment database, to measure whether physician group sizes have been increasing over time and in association with physician characteristics. All US physicians serving Medicare fee-for-service patients in any practice setting were included. The percentage of physicians in groups of more than fifty increased from 30.9 percent in 2009 to 35.6 percent in 2011. This shift occurred across all specialty categories, both sexes, and all age groups, although it was more prominent among physicians under age forty than those age sixty or older. The movement of physicians into groups is not a new phenomenon, but our data suggest that the groups are larger than surveys have previously indicated. Questions for future studies include whether there are significant cost savings or quality improvements associated with increased practice size.

Antihypertensive drug use by children: are the drugs labeled and indicated?

As a result of the Food and Drug Administration (FDA) Modernization Act and the Best Pharmaceuticals for Children Act, the number of medications with FDA-approved pediatric labeling has increased. To assess the success of these initiatives, we examined whether antihypertensive drugs used by children with hypertension in 2008 had FDA-approved pediatric labeling and indications. Using a nationwide commercial insurer database, 2915 children with primary (n=2607) and secondary (n=308) hypertension were identified. Drug user rate and days of supply were calculated from pharmacy claims. Drugs were categorized based on pediatric labeling and indication and whether they were recommended for pediatric use. Antihypertensive drugs were used by 889 (34%) children with primary hypertension and 200 children (65%) with secondary hypertension. User rates were 44.3% in hypertensive children younger than 6 years, 30.9% in those 6 years to older than 12 years, and 38.1% in those 12 years to older than 18 years. Seven percent of drugs were neither labeled for pediatric use nor considered recommended for use in children. In children younger than 6 years, 29% of drugs used were not indicated for use in that age group. Despite recent legislative initiatives, many drugs used by hypertensive children still lack pediatric labeling. Additional efforts are needed to close the gap between the availability of drugs that are labeled and indicated for pediatric use and actual drug usage in children.

Electronic health records in four community physician practices: impact on quality and cost of care.

OBJECTIVE: To assess the impact of the electronic health record (EHR) on cost (i.e., payments to providers) and process measures of quality of care. STUDY DESIGN: Retrospective before-after-study-control. From the database of a large managed care organization (MCO), we obtained the claims of patients from four community physician practices that implemented the EHR and from about 50 comparison practices without the EHR in the same counties. The diverse patient and practice populations were chosen to be a sample more representative of typical private practices than has previously been studied. MEASUREMENTS: For four chronic conditions, we used commercially-available software to analyze cost per episode over a year and the rate of adherence to clinical guidelines as a measure of quality. RESULTS: The implementation of the EHR had a modest positive impact on the quality measure of guideline adherence for hypertension and hyperlipidemia, but no significant impact for diabetes and coronary artery disease. No measurable impact on the short-term cost per episode was found. Discussions with the study practices revealed that the timing and comprehensiveness of EHR implementation varied across practices, creating an intervention variable that was heterogeneous. CONCLUSIONS: Guideline adherence increased across practices without EHRs and slightly faster in practices with EHRs. Measuring the impact of EHRs on cost per episode was challenging, because of the difficulty of completely capturing the long-term episodic costs of a chronic condition. Few practices associated with the study MCO had implemented EHRs in any form, much less utilizing standardized protocols.

Management tools for Medicaid and State Children's Health Insurance Program (SCHIP).

Medicaid and the State Children's Health Insurance Program need analytic tools to manage their programs. Drawing upon extensive discussions with experts in states, this article describes the state of the art in tool use, making several observations: (1) Several states have linked Medicaid/State Children's Health Insurance Program administrative data to other data (eg, birth and death records) to measure access to care. (2) Several states use managed care encounter data to set payment rates. (3) The analysis of pharmacy claims data appears widespread. The article also describes "lessons learned" regarding building capacity and improving data to support the implementation of management tools.

Outpatient encounter data for risk adjustment: strategic issues for Medicare and Medicaid.

Payers are increasingly using diagnostic data from outpatient encounter records to adjust the payment to health plans. Although much has been written about the ability of such data to predict health care costs, little has been written about the data itself--its quality and availability. Fee-for-service (FFS) data face several threats to their validity, including the possibility that they may seriously underreport diagnoses. Because the systems and incentives that yield FFS and managed care diagnosis data are quite different, they may not be comparable, depending on circumstances such as audit rules. The next generation of risk adjustment models should be designed around the capabilities and potentialities of plans' information systems.

Disease management practices of health plans.

OBJECTIVE: To investigate how health plans manage chronic diseases. STUDY DESIGN: Health plan medical directors were surveyed regarding the disease management (DM) practices of their plans. METHODS: We took a stratified random sample of 65 plans, all members of the American Association of Health Plans. Forty-five plans responded. Results were weighted to be representative of the industry (including nonmember plans). Medical directors were asked to consider that they had a DM program only if 2 things were true: (1) A majority of a plan's enrollees could not be ineligible for a DM program for non-clinical reasons (eg, geographic location); and (2) a DM program had to have at least 6 of the 8 components of a DM program as defined by the Disease Management Association of America. RESULTS: The 3 diseases most likely to be the focus of DM programs were diabetes, asthma, and congestive heart failure. For each of these diseases, at least one quarter of Americans were enrolled in plans offering a DM program. Medical directors perceived their DM programs to be highly effective in reducing mortality and morbidity and in improving the functional status of patients, and perceived them to be effective in lowering cost. The greatest challenge in implementing DM programs involves information technology. These results yield insights into the future of treatment of chronic disease in the United States. CONCLUSION: Health plans have made a significant investment in programs to improve care for chronic illness. The almost universality of DM programs highlight the need for scholarly evaluations of their effectiveness and cost effectiveness.