BACKGROUND:The 2010 Patient Protection and Affordable Care Act reformed the individual and small group health insurance markets and established a risk adjustment program to create a level playing field for competition. A new set of predictive models for measuring enrollee risk across plans was developed for the Patient Protection and Affordable Care Act-reformed markets, referred to as the Department of Health and Human Services Hierarchical Condition Category (HHS-HCC) models. Beginning in 2018, selected prescription drug classes were added to the models as risk markers.OBJECTIVE:We describe the motivations, concerns, methodology, and results of adding prescription drug utilization to the HHS-HCC models.METHODS:Separate HHS-HCC models are estimated by enrollee age and plan actuarial value. We defined and added 10 prescription drug classes, called RXCs, to the HHS-HCC adult models.RESULTS:Using selected RXCs alongside demographic and diagnostic indicators yielded modest overall improvement in HHS-HCC models' predictive power. Also, adding RXCs captures the higher costs of enrollees taking certain expensive pharmaceuticals and allows imputation of diagnoses for enrollees utilizing a drug but lacking the associated diagnosis.CONCLUSIONS:Including selected drugs in risk adjustment improved the models' predictive power. In addition, inclusion of selected drugs may discourage insurers from using formulary and drug benefit design to avoid enrollment of patients taking high-cost drugs, such as for HIV, multiple sclerosis, and rheumatoid arthritis, and improve access for enrollees taking these drugs. Adding RXCs also may improve plan risk measurement for plans with less complete diagnosis reporting.

Background: The Patient Protection and Affordable Care Act (PPACA) established new parameters for the individual and small group health insurance markets starting in 2014. We study these 2 reformed markets by comparing health risk and costs to the more mature large employer market. Study Data: For 2017, claims data for all enrollees in PPACA-compliant individual and small group market plans as well as claims data from a sample of large employer market enrollees. Variables and Methodology: Risk scores and total (unadjusted and risk-adjusted) per-member-per-month (PMPM) allowed charges. Differences across markets in enrollment duration, age, and geographic distribution are addressed. The analysis is descriptive. Results: Compared with large employer market enrollees, health risk was 3% lower among PPACA small group market enrollees and 20% higher among PPACA individual market enrollees. After adjusting for differences in health risk, enrollees in the PPACA individual market had 27% lower PMPM allowed charges than enrollees in the large employer market and enrollees in the PPACA small group market had 12% lower PMPM allowed charges than enrollees in the large employer market. Conclusions: On average, the PPACA individual market enrolls sicker individuals than the 2 group markets. But this does not translate to higher health costs; in fact, enrollees in the PPACA individual market accumulate lower allowed charges than enrollees in the large employer market. Lower-income enrollees particularly accumulate lower allowed charges. Narrower networks and increased enrollee cost-sharing among individual market plans, though they may reduce the value of coverage, likely significantly reduce allowed charges.

Background Clinical characteristics driving variations in Medicare outpatient physical therapy expenditures are inadequately understood. Objective The objectives of this study were to examine variations in annual outpatient physical therapy expenditures of Medicare fee-for-service beneficiaries by primary diagnosis and baseline functional mobility, and to assess whether case mix groups based on primary diagnosis and functional mobility scores would be useful for expenditure differentiation. Design This was an observational, longitudinal study. Methods Volunteer providers in community settings participated in data collection with Continuity Assessment Record and EvaluationCommunity (CARE-C) assessments for Medicare fee-for-service beneficiaries. Annual outpatient physical therapy expenditures were calculated using allowed charges on Medicare claims; primary diagnosis and baseline functional mobility were obtained from CARE-C assessments. Whether annual expenditures varied significantly across primary diagnosis groups and within diagnosis groups by functional mobility was examined. Results Data for 4210 patients (mean [SD] age = 72.9 [9.9] years; 64.6% women) from 127 providers were included. Mean expenditures differed significantly across 12 primary diagnosis groups created from CARE-C clinician-reported diagnoses (F = 12.73; df = 11). Twenty-five pairwise differences in 66 pairwise diagnosis group comparisons were statistically significant. Within 8 diagnosis groups, expenditures were significantly higher for low-mobility subgroups than for high-mobility subgroups; borderline significance was achieved for 1 diagnosis group. Limitations The small convenience sample limited the statistical power and the generalizability of the results. Conclusions Significant variations in physical therapy expenditures based on primary diagnosis and baseline functional mobility support the use of these variables in predicting outpatient physical therapy expenditures. Although Medicare's annual therapy spending cap was repealed effective January 2018, the data from this study provide an initial foundation to inform any future policy efforts, such as targeted medical review, risk-adjusted therapy payments, or case mix groups as potential payment alternatives. Additional research with larger samples is needed to further develop and test case mix groups and improve generalizability to the national population. Refined case mix groups could also help providers prognosticate physical therapy expenditures based on patient profiles.

Objective: To conduct an analysis of Medicare outpatient therapy episodes of care and associated payment implications.Design: Retrospective observational design using Medicare claims data. To descriptively analyze the composition of outpatient therapy episodes, both variable- and fixed-length episodes are explored. The variable-length episode definition organizes services into episodes based on the time pattern of therapy service utilization, using 60-day clean periods. Fixed-length episodes are also examined, beginning with the first therapy utilization in calendar year 2010 and extending 30, 60, and 90 days.Setting: The study is focused on community-dwelling users of outpatient therapy.Participants: The sample includes all Medicare patients who used outpatient therapy beginning at any point in 2010.Interventions: Not applicable.Main Outcome Measures: Mean episode payments and episode lengths in calendar days.Results: Variable -length outpatient therapy episodes have a mean payment of $881. On average, outpatient therapy episodes last 43 calendar days. Mean therapy durations for the 30-, 60-, and 90 -day fixed-length episodes are 20, 31, and 38 calendar days, respectively. The 30-, 60-, and 90 -day fixed-length initial episodes account for 40%, 55%, and 63%, respectively, of total Medicare payments. Simulations of episode-based payment illustrate the difficulty of avoiding a large number of substantial underpayments, because of the right-skewed distribution of total actual payments.Conclusions: A strength of episode payment is that it reduces cost and potentially wasteful variation within episodes. Given the substantial variation in therapy episode expenditures, absent improvements in available data and in predictive information, a pure lump sum episode payment would result in substantial revenue changes for many episodes. Additional data are needed to better explain the wide variation in episode expenditures. (C) 2016 by the American Congress of Rehabilitation Medicine

Background A Medicare beneficiary's annual outpatient therapy expenditures that exceed congressionally established caps are subject to extra documentation and review requirements. In 2011, these caps were $1,870 for physical therapy and speech-language pathology combined and $1,870 for occupational therapy separately. Objective This article considers the distributional effects of replacing current cap policy with equal caps by therapy discipline (physical therapy, occupational therapy, and speech-language pathology) or a single combined cap, and risk adjusting the physical therapy cap using beneficiary characteristics and functional status. Methods Alternative therapy cap policies are simulated with 100% Medicare claims for 2011 therapy users (N=4.9 million). A risk-adjusted cap for annual physical therapy expenditures is calculated from a quantile regression estimated on a sample of physical therapy users with diagnoses and clinician assessments of functional ability merged to their claims (n=4,210). Results Equal discipline-specific caps of $1,710 each for physical therapy, occupational therapy, and speech-language pathology result in the same aggregate Medicare expenditures above the caps as 2011 cap policy. A single combined-disciplines cap of $2,485 also results in the same aggregate expenditures above the cap. Risk adjustment varies the physical therapy cap by as much as 5 to 1 across beneficiaries and equalizes the probability of exceeding the physical therapy cap across diagnosis and functional status groups. Limitations One limitation of the study was the assumption of no behavioral response on the part of beneficiaries or providers to a change in cap policy. Additionally, analysis of risk adjusting the therapy caps was limited by sample size. Conclusions Equal discipline-specific caps for physical therapy, occupational therapy, and speech-language pathology are more equitable to high users of both physical therapy and speech-language pathology than current cap policy. Separating the physical therapy and speech-language pathology caps is a change that policy makers could consider. Risk adjustment of the therapy caps is a first step in incorporating beneficiary need for services into Medicare outpatient therapy payment policy.

OBJECTIVE:To examine the impact of the Medicare Physician Group Practice (PGP) demonstration on expenditure, utilization, and quality outcomes.DATA SOURCE:Secondary data analysis of 2001-2010 Medicare claims for 1,776,387 person years assigned to the ten participating provider organizations and 1,579,080 person years in the corresponding local comparison groups.STUDY DESIGN:We used a pre-post comparison group observational design consisting of four pre-demonstration years (1/01-12/04) and five demonstration years (4/05-3/10). We employed a propensity-weighted difference-in-differences regression model to estimate demonstration effects, adjusting for demographics, health status, geographic area, and secular trends.PRINCIPAL FINDINGS:The ten demonstration sites combined saved $171 (2.0%) per assigned beneficiary person year (p<0.001) during the five-year demonstration period. Medicare paid performance bonuses to the participating PGPs that averaged $102 per person year. The net savings to the Medicare program were $69 (0.8%) per person year. Demonstration savings were achieved primarily from the inpatient setting. The demonstration improved quality of care as measured by six of seven claims-based process quality indicators.CONCLUSIONS:The PGP demonstration, which used a payment model similar to the Medicare Accountable Care Organization (ACO) program, resulted in small reductions in Medicare expenditures and inpatient utilization, and improvements in process quality indicators. Judging from this demonstration experience, it is unlikely that Medicare ACOs will initially achieve large savings. Nevertheless, ACOs paid through shared savings may be an important first step toward greater efficiency and quality in the Medicare fee-for-service program.

The Affordable Care Act provides for a program of risk adjustment in the individual and small group health insurance markets in 2014 as Marketplaces are implemented and new market reforms take effect. The purpose of risk adjustment is to lessen or eliminate the influence of risk selection on the premiums that plans charge. The risk adjustment methodology includes the risk adjustment model and the risk transfer formula. This article is the third of three in this issue of the Medicare & Medicaid Research Review that describe the ACA risk adjustment methodology and focuses on the risk transfer formula. In our first companion article, we discussed the key issues and choices in developing the methodology. In our second companion paper, we described the risk adjustment model that is used to calculate risk scores. In this article we present the risk transfer formula. We first describe how the plan risk score is combined with factors for the plan allowable premium rating, actuarial value, induced demand, geographic cost, and the statewide average premium in a formula that calculates transfers among plans. We then show how each plan factor is determined, as well as how the factors relate to each other in the risk transfer formula. The goal of risk transfers is to offset the effects of risk selection on plan costs while preserving premium differences due to factors such as actuarial value differences. Illustrative numerical simulations show the risk transfer formula operating as anticipated in hypothetical scenarios.

The traditional Medicare fee-for-service program may be able to purchase clinical laboratory test services at a lower cost through competitive bidding. Demonstrations of competitive bidding for clinical laboratory tests have been twice mandated or authorized by Congress but never implemented. This article provides a summary and review of the final design of the laboratory competitive bidding demonstration mandated by the Medicare Modernization Act of 2003. The design was analogous to a sealed bid (first price), clearing price auction. Design elements presented include covered laboratory tests and beneficiaries, laboratory bidding and payment status under the demonstration, composite bids, determining bidding winners and the demonstration fee schedule, and quality under the demonstration. Expanded use of competitive bidding in Medicare, including specifically for clinical laboratory tests, has been recommended in some proposals for Medicare reform. The presented design may be a useful point of departure if Medicare clinical laboratory competitive bidding is revived in the future.

Beginning in 2014, individuals and small businesses will be able to purchase private health insurance through competitive marketplaces.The Affordable Care Act (ACA) provides for a program of risk adjustment in the individual and small group markets in 2014 as Marketplaces are implemented and new market reforms take effect.The purpose of risk adjustment is to lessen or eliminate the influence of risk selection on the premiums that plans charge and the incentive for plans to avoid sicker enrollees.This article -the first of three in the Medicare & Medicaid Research Review-describes the key program goal and issues in the Department of Health and Human Services (HHS) developed risk adjustment methodology, and identifies key choices in how the methodology responds to these issues.The goal of the HHS risk adjustment methodology is to compensate health insurance plans for differences in enrollee health mix so that plan premiums reflect differences in scope of coverage and other plan factors, but not differences in health status.The methodology includes a risk adjustment model and a risk transfer formula that together address this program goal as well as three issues specific to ACA risk adjustment: 1) new population; 2) cost and rating factors; and 3) balanced transfers within state/market.The risk adjustment model, described in the second article, estimates differences in health risks taking into account the new population and scope of coverage (actuarial value level).The transfer formula, described in the third article, calculates balanced transfers that are intended to account for health risk differences while preserving permissible premium differences.

Payer (insurer) sharing of savings is a way of motivating providers of medical services to reduce cost growth. A Medicare shared savings program is established for accountable care organizations in the 2010 Patient Protection and Affordable Care Act. However, savings created by providers cannot be distinguished from the normal (random) variation in medical claims costs, setting up a classic principal-agent problem. To lessen the likelihood of paying undeserved bonuses, payers may pay bonuses only if observed savings exceed minimum levels. We study the trade-off between two types of errors in setting minimum savings requirements: paying bonuses when providers do not create savings and not paying bonuses when providers create savings.

Introduction:The continued success of the Medicare Part D program is contingent on appropriate Medicare payment adjustments for the projected drug costs of Part D plan enrollees. This article describes a major revision of these “risk adjustments,” intended to more accurately match payments to costs, especially for high-cost, disadvantaged populations. Methods:For the first time actual Part D data are used to calibrate risk adjustment. The sample is Medicare beneficiaries with fee-for-service enrollment in 2007 and Part D standalone prescription drug plan enrollment in 2008 (N=14,224,301). Part D plan liability expenditures are predicted using demographic and diagnostic factors in a weighted least squares regression. Models for Medicare subpopulations are analyzed. The predictive accuracy of risk adjustment models is evaluated using R2 and predictive ratio statistics. Results:Based on differences in both mean expenditures and incremental expenditures by diagnosis, separate Part D risk adjustment models are calibrated for 5 Medicare subpopulations: aged not low income; aged low income; nonaged not low income; nonaged low income; and institutionalized. The variation in plan liability drug expenditures (R2) explained by these models ranges from 13% to 29%. The 5 separate models accurately predict mean plan liability expenditures ranging from $967 to $1762 across subpopulations and account for differences in incremental disease coefficients by subpopulation. Conclusions:The refined Part D risk adjustment model represents a significant improvement in the accuracy and fairness of payment to Part D plans. The new model provides greater incentives for drug plans to compete for low-income and institutionalized enrollees.

Current Medicare payment policy for outpatient laboratory services is outdated. Future reforms, such as competitive bidding, should consider the characteristics of the laboratory market. To inform payment policy, we analyzed the structure of the national market for Medicare Part B clinical laboratory testing, using a 5-percent sample of 2006 Medicare claims data. The independent laboratory market is dominated by two firms--Quest Diagnostics and Laboratory Corporation of America. The hospital outreach market is not as concentrated as the independent laboratory market. Two subgroups of Medicare beneficiaries, those with end-stage renal disease and those residing in nursing homes, are each served in separate laboratory markets. Despite the concentrated independent laboratory market structure, national competitive bidding for non-patient laboratory tests could result in cost savings for Medicare.

This book provides a balanced assessment of pay for performance (P4P), addressing both its promise and its shortcomings. P4P programs have become widespread in health care in just the past decade and have generated a great deal of enthusiasm in health policy circles and among legislators, despite limited evidence of their effectiveness. On a positive note, this movement has developed and tested many new types of health care payment systems and has stimulated much new thinking about how to improve quality of care and reduce the costs of health care. The current interest in P4P echoes earlier enthusiasms in health policy—such as those for capitation and managed care in the 1990s—that failed to live up to their early promise. The fate of P4P is not yet certain, but we can learn a number of lessons from experiences with P4P to date, and ways to improve the designs of P4P programs are becoming apparent. We anticipate that a “second generation” of P4P programs can now be developed that can have greater impact and be better integrated with other interventions to improve the quality of care and reduce costs.

This book provides a balanced assessment of pay for performance (P4P), addressing both its promise and its shortcomings. P4P programs have become widespread in health care in just the past decade and have generated a great deal of enthusiasm in health policy circles and among legislators, despite limited evidence of their effectiveness. On a positive note, this movement has developed and tested many new types of health care payment systems and has stimulated much new thinking about how to improve quality of care and reduce the costs of health care.

CMS has had a continuing interest in exploring ways to incorporate frailty adjustment into the CMS Hierarchical Condition Categories (CMS-HCC) risk adjustment methodology for Medicare Advantage and other Medicare private organizations. In this article we present research results for Medicare risk adjustment of the frail elderly since the adoption of frailty adjustment for Program of All-Inclusive Care for the Elderly (PACE) organizations in 2004. In particular, we present results on the revised frailty adjuster that is being phased in for PACE organizations between 2008 and 2012.