Statewide data infrastructure supports population health management: diabetes case study.

OBJECTIVES: To understand how a statewide data infrastructure, including clinical and multipayer claims data, can inform preventive care and reduce medical expenditures for patients with diabetes. STUDY DESIGN: A retrospective 1-year cross-sectional analysis of claims linked to clinical data for 6719 patients with diabetes in 2014 to evaluate impacts of comorbidities on the total cost of care. METHODS: Initially, variation in healthcare expenditures was examined versus a measure of disease control (most recent glycated hemoglobin [A1C] test results). Multivariable linear regression calculated the relative impact of a series of risk factors on medical expenditures. Poisson regression estimated the relative impact on inpatient hospital admissions. Possible savings were estimated with a reduction in potentially avoidable hospital admissions. RESULTS: No linear relationship was found between A1C and same-year medical expenditures. Comorbidities in the population with diabetes with the largest relative impact on expenditures and inpatient hospital admissions were renal failure, congestive heart failure, chronic obstructive pulmonary disease, and discordant blood pressure. Diabetes plus congestive heart failure had the highest cost per inpatient admission; diabetes plus body mass index (BMI) ≥35 had the highest aggregate costs and potential savings. CONCLUSIONS: A statewide data infrastructure can be used to identify criteria for outreach and population management of diabetes. The selection criteria are applicable across a statewide population and are associated with a higher relative impact on near-term expenditures than recent A1C test results. Whole-population data aggregation can be used to develop actionable information that is particularly relevant as independent organizations work together under alternative payment model arrangements.

Synthesis Of Research On Patient-Centered Medical Homes Brings Systematic Differences Into Relief.

The patient-centered medical home (PCMH) model emphasizes comprehensive, coordinated, patient-centered care, with the goals of reducing spending and improving quality. To evaluate the impact of PCMH initiatives on utilization, cost, and quality, we conducted a meta-analysis of methodologically standardized findings from evaluations of eleven major PCMH initiatives. There was significant heterogeneity across individual evaluations in many outcomes. Across evaluations, PCMH initiatives were not associated with changes in the majority of outcomes studied, including primary care, emergency department, and inpatient visits and four quality measures. The initiatives were associated with a 1.5 percent reduction in the use of specialty visits and a 1.2 percent increase in cervical cancer screening among all patients, and a 4.2 percent reduction in total spending (excluding pharmacy spending) and a 1.4 percent increase in breast cancer screening among higher-morbidity patients. These associations were significant. Identification of the components of PCMHs likely to improve outcomes is critical to decisions about investing resources in primary care.

Risk-adjustment methods for all-payer comparative performance reporting in Vermont.

BACKGROUND: As the emphasis in health reform shifts to value-based payments, especially through multi-payer initiatives supported by the U.S. Center for Medicare & Medicaid Innovation, and with the increasing availability of statewide all-payer claims databases, the need for an all-payer, "whole-population" approach to facilitate the reporting of utilization, cost, and quality measures has grown. However, given the disparities between the different populations served by Medicare, Medicaid, and commercial payers, risk-adjustment methods for addressing these differences in a single measure have been a challenge. METHODS: This study evaluated different levels of risk adjustment for primary care practice populations - from basic adjustments for age and gender to a more comprehensive "full model" risk-adjustment method that included additional demographic, payer, and health status factors. It applied risk adjustment to populations attributed to patient-centered medical homes (283,153 adult patients and 78,162 pediatric patients) in the state of Vermont that are part of the Blueprint for Health program. Risk-adjusted expenditure and utilization outcomes for calendar year 2014 were reported in 102 adult and 56 pediatric primary-care comparative practice profiles. RESULTS: Using total expenditures as the dependent variable for the adult population, the r2 for the model adjusted for age and gender was 0.028. It increased to 0.265 with the additional adjustment for 3M Clinical Risk Groups and to 0.293 with the full model. For the adult population at the practice level, the no-adjustment model had the highest variation as measured by the coefficient of variation (18.5) compared to the age and gender model (14.8); the age, gender, and CRG model (13.0); and the full model (11.7). Similar results were found for the pediatric population practices. CONCLUSIONS: Results indicate that more comprehensive risk-adjustment models are effective for comparing cost, utilization, and quality measures across multi-payer populations. Such evaluations will become more important for practices, many of which do not distinguish their patients by payer type, and for the implementation of incentive-based or alternative payment systems that depend on "whole-population" outcomes. In Vermont, providers, accountable care organizations, policymakers, and consumers have used Blueprint profiles to identify priorities and opportunities for improving care in their communities.

Impact of Medication-Assisted Treatment for Opioid Addiction on Medicaid Expenditures and Health Services Utilization Rates in Vermont.

In the face of increasing rates of overdose deaths, escalating health care costs, and the tremendous social costs of opioid addiction, policy makers are asked to address the questions of whether and how to expand access to treatment services. In response to an upward trend in opioid abuse and adverse outcomes, Vermont is investing in statewide expansion of a medication-assisted therapy program delivered in a network of community practices and specialized treatment centers (Hub & Spoke Program). This study was conducted to test the rationale for these investments and to establish a pre-Hub & Spoke baseline for evaluating the additive impact of the program. Using a serial cross-sectional design from 2008 to 2013 to evaluate medical claims for Vermont Medicaid beneficiaries with opioid dependence or addiction (6158 in the intervention group, 2494 in the control group), this study assesses the treatment and medical service expenditures for those receiving medication-assisted treatment compared to those receiving substance abuse treatment without medication. Results suggest that medication-assisted therapy is associated with reduced general health care expenditures and utilization, such as inpatient hospital admissions and outpatient emergency department visits, for Medicaid beneficiaries with opioid addiction. For state Medicaid leaders facing similar decisions on approaches to opioid addiction, these results provide early support for expanding medication-assisted treatment services rather than relying only on psychosocial, abstinence, or detoxification interventions.

Vermont's Community-Oriented All-Payer Medical Home Model Reduces Expenditures and Utilization While Delivering High-Quality Care.

Patient-centered medical home programs using different design and implementation strategies are being tested across the United States, and the impact of these programs on outcomes for a general population remains unclear. Vermont has pursued a statewide all-payer program wherein medical home practices are supported with additional staffing from a locally organized shared resource, the community health team. Using a 6-year, sequential, cross-sectional methodology, this study reviewed annual cost, utilization, and quality outcomes for patients attributed to 123 practices participating in the program as of December 2013 versus a comparison population from each year attributed to nonparticipating practices. Populations are grouped based on their practices' stage of participation in a calendar year (Pre-Year, Implementation Year, Scoring Year, Post-Year 1, Post-Year 2). Annual risk-adjusted total expenditures per capita at Pre-Year for the participant group and comparison group were not significantly different. The difference-in-differences change from Pre-Year to Post-Year 2 indicated that the participant group's expenditures were reduced by -$482 relative to the comparison (95% CI, -$573 to -$391; P < .001). The lower costs were driven primarily by inpatient (-$218; P < .001) and outpatient hospital expenditures (-$154; P < .001), with associated changes in inpatient and outpatient hospital utilization. Medicaid participants also had a relative increase in expenditures for dental, social, and community-based support services ($57; P < .001). Participants maintained higher rates on 9 of 11 effective and preventive care measures. These results suggest that Vermont's community-oriented medical home model is associated with improved outcomes for a general population at lower expenditures and utilization. (Population Health Management 2016;19:196-205).

Evaluating health care delivery reform initiatives in the face of "cost disease".

The authors analyzed historical claims data from 2007 to 2011 from the Vermont All-Payer Claims database for all individuals covered by commercial insurance and Medicaid to determine per capita inpatient expenditures, cost per discharge, and cost per inpatient day. The authors further evaluated the proportion of all health care expenditure allocated to mental health, maternity care, surgical services, and medical services. Although utilization of inpatient services declined during the study period, cost per discharge and cost per inpatient day increased in a compensatory manner. Although the utilization of inpatient services by the Medicaid population decreased by 8%, cost per discharge increased by 84%. Among the commercially insured, discharges per 1000 members were essentially unchanged during the study period and inpatient cost per discharge increased by a relatively modest 32%. The relative utilization of mental health, maternity care, surgical services, and medical services was unchanged during the study period. The significant increase in the cost of inpatient services increased the proportion of total expenditure on surgical services from 21% in 2007 to 33% in 2011. The authors conclude that although health care providers are increasingly being assessed on their ability to control health care costs while achieving better outcomes, there are many cost drivers that are outside of their control. Efforts to assess initiatives, such as patient-centered medical homes, should be focused on utilization trends and outcomes rather than cost or, at a minimum, reflect cost drivers that physicians and other providers cannot influence.

Tracking spending among commercially insured beneficiaries using a distributed data model.

OBJECTIVES: To explore the feasibility of using a distributed data model for ongoing reporting of local healthcare spending, specifically to investigate the contribution of utilization and pricing to geographic variation and trends in reimbursements for commercially insured beneficiaries younger than 65 years. STUDY DESIGN: Retrospective descriptive analysis. METHODS: Commercial claims were obtained for beneficiaries in 5 states for the years 2008 to 2010 using a distributed data model. Claims were aggregated to the hospital service area (HSA) level and healthcare utilization was quantified using a novel, National Quality Forum-endorsed measure that is independent of price and allows for the calculation of resource use across all services in standardized units. We examined trends in utilization, prices, and reimbursements over time. To examine geographic variation, we mapped resource use by HSA in the 3 states from which we had data from multiple insurers. We calculated the correlation between commercial and Medicare reimbursements and utilization. Medicare claims were obtained from the Dartmouth Atlas. RESULTS: We found that much of the recent growth in reimbursements for the commercially insured from 2008 to 2010 was due to increases in prices, particularly for outpatient services. As in the Medicare population, resource use by this population varied by HSA. While overall resource use patterns in the commercially insured did not mirror those among Medicare beneficiaries, we observed a strong correlation in inpatient hospital use. CONCLUSIONS: This research demonstrates the feasibility and value of public reporting of standardized area-level utilization and price data using a distributed data model to understand variation and trends in reimbursements.