States Encouraging Value-Based Payment: Lessons From CMS's State Innovation Models Initiative.

Policy Points Six states received $250 million under the federal State Innovation Models (SIM) Initiative Round 1 to increase the proportion of care delivered under value-based payment (VBP) models aligned across multiple payers. Multipayer alignment around a common VBP model occurred within the context of state regulatory and purchasing policies and in states with few commercial payers, not through engaging many stakeholders to act voluntarily. States that made targeted infrastructure investments in performance data and electronic hospital event notifications, and offered grants and technical assistance to providers, produced delivery system changes to enhance care coordination even where VBP models were not multipayer. CONTEXT: In 2013, six states (Arkansas, Massachusetts, Maine, Minnesota, Oregon, and Vermont) received $250 million in Round 1 State Innovation Models (SIM) awards to test how regulatory, policy, purchasing, and other levers available to state governments could transform their health care system by implementing value-based payment (VBP) models that shift away from fee-for-service toward payment based on quality and cost. METHODS: We gathered and analyzed qualitative data on states' implementation of their SIM Initiatives between 2014 and 2018, including interviews with state officials and other stakeholders; consumer and provider focus groups; and review of relevant state-produced documents. FINDINGS: State policymakers leveraged existing state law, new policy development, and federal SIM Initiative funds to implement new VBP models in Medicaid. States' investments promoted electronic health information going from hospitals to primary care providers and collaboration across care team members within practices to enhance care coordination. Multipayer alignment occurred where there were few commercial insurers in a state, or where a state law or state contracting compelled commercial insurer participation. Challenges to health system change included commercial payer reluctance to coordinate on VBP models, cost and policy barriers to establishing bidirectional data exchange among all providers, preexisting quality measurement requirements across payers that impede total alignment of measures, providers' perception of their limited ability to influence patients' behavior that puts them at financial risk, and consumer concerns with changes in care delivery. CONCLUSIONS: The SIM Initiative's test of the power of state governments to shape health care policy demonstrated that strong state regulatory and purchasing policy levers make a difference in multipayer alignment around VBP models. In contrast, targeted financial investments in health information technology, data analytics, technical assistance, and workforce development are more effective than policy alone in encouraging care delivery change beyond that which VBP model participation might manifest.

Medicare part D data: major changes on the horizon.

BACKGROUND: The 3 primary administrative data sets developed by the Centers for Medicare and Medicaid services (CMS) to support the Medicare Part D program implementation represent a valuable source of data for health services researchers. This paper describes the structure of the Medicare Part D program and the related databases, and discusses their utilization for research purposes. RESULTS: The Medicare Part D administrative data include information on plan benefits (integrated into the Health Plan Management System), beneficiary enrollment files, and prescription drug event (PDE) claims-type data. The enrollment data may be of use in investigating the benefits and plan types that appeal to beneficiaries, but their application is limited by the fact that, although individual beneficiaries' enrollment choices are recorded, only summary enrollment data are currently publicly available. PDE data are likely to be of most interest to researchers as they are detailed (including beneficiary identifiers, contract identifiers pharmacy provider information on drugs provided, drug cost, and insurance status), beneficiary-specific (allowing them to be linked to beneficiary characteristics), and an unusual output for a program reimbursed under a capitation-based system. Because PDE data are highly sensitive, only summary data on the number of Part D prescriptions filled are publicly available. CONCLUSIONS: Although the data collected in relation to the Medicare Part D program could be applied to many questions of interest to health services researchers, their utility is limited by the sensitive natures of many of these data, making it difficult currently to obtain access for research purposes.

Patient casemix classification for medicare psychiatric prospective payment.

OBJECTIVE: For a proposed Medicare prospective payment system for inpatient psychiatric facility treatment, the authors developed a casemix classification to capture differences in patients' real daily resource use. METHOD: Primary data on patient characteristics and daily time spent in various activities were collected in a survey of 696 patients from 40 inpatient psychiatric facilities. Survey data were combined with Medicare claims data to estimate intensity-adjusted daily cost. Classification and Regression Trees (CART) analysis of average daily routine and ancillary costs yielded several hierarchical classification groupings. Regression analysis was used to control for facility and day-of-stay effects in order to compare hierarchical models with models based on the recently proposed payment system of the Centers for Medicare & Medicaid Services. RESULTS: CART analysis identified a small set of patient characteristics strongly associated with higher daily costs, including age, psychiatric diagnosis, deficits in daily living activities, and detox or ECT use. A parsimonious, 16-group, fully interactive model that used five major DSM-IV categories and stratified by age, illness severity, deficits in daily living activities, dangerousness, and use of ECT explained 40% (out of a possible 76%) of daily cost variation not attributable to idiosyncratic daily changes within patients. A noninteractive model based on diagnosis-related groups, age, and medical comorbidity had explanatory power of only 32%. CONCLUSIONS: A regression model with 16 casemix groups restricted to using "appropriate" payment variables (i.e., those with clinical face validity and low administrative burden that are easily validated and provide proper care incentives) produced more efficient and equitable payments than did a noninteractive system based on diagnosis-related groups.

Measures and predictors of Medicare knowledge: a review of the literature.

As the Medicare Program evolves, adding new insurance options like regional preferred provider organizations (PPOs) and prescription drug benefits, beneficiaries have an even greater need to understand the program. However, past research suggests that many beneficiaries have limited understanding of Medicare and related health insurance options. While improvements in beneficiary understanding of Medicare may be feasible, driven by new and varied efforts to provide the Medicare population with educational opportunities, is there evidence of factors that predict knowledge limitations? This article seeks to address this question by a thorough review of the literature on the measures and factors that influence beneficiary knowledge.