Dataset Information

Value-based payment in implementing evidence-based care: the Mental Health Integration Program in Washington state.

ABSTRACT: To assess the role of value-based payment (VBP) in improving fidelity and patient outcomes in community implementation of an evidence-based mental health intervention, the Collaborative Care Model (CCM).Retrospective study based on a natural experiment.We used the clinical tracking data of 1806 adult patients enrolled in a large implementation of the CCM in community health clinics in Washington state. VBP was initiated in year 2 of the program, creating a natural experiment. We compared implementation fidelity (measured by 3 process-of-care elements of the CCM) between patient-months exposed to VBP and patient-months not exposed to VBP. A series of regressions were estimated to check robustness of findings. We estimated a Cox proportional hazard model to assess the effect of VBP on time to achieving clinically significant improvement in depression (measured based on changes in depression symptom scores over time).Estimated marginal effects of VBP on fidelity ranged from 9% to 30% of the level of fidelity had there been no exposure to VBP (P <.05 for every fidelity measure). Improvement in fidelity in response to VBP was greater among providers with a larger patient panel and among providers with a lower level of fidelity at baseline. Exposure to VBP was associated with an adjusted hazard ratio of 1.45 (95% confidence interval, 1.04-2.03) for achieving clinically significant improvement in depression.VBP improved fidelity to key elements of the CCM, both directly incentivized and not explicitly incentivized by the VBP, and improved patient depression outcomes.

SUBMITTER: Bao Y

PROVIDER: S-EPMC5559616 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

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Value-based payment in implementing evidence-based care: the Mental Health Integration Program in Washington state.

Bao Yuhua Y McGuire Thomas G TG Chan Ya-Fen YF Eggman Ashley A AA Ryan Andrew M AM Bruce Martha L ML Pincus Harold Alan HA Hafer Erin E Unützer Jürgen J

The American journal of managed care 20170101 1

<h4>Objectives</h4>To assess the role of value-based payment (VBP) in improving fidelity and patient outcomes in community implementation of an evidence-based mental health intervention, the Collaborative Care Model (CCM).<h4>Study design</h4>Retrospective study based on a natural experiment.<h4>Methods</h4>We used the clinical tracking data of 1806 adult patients enrolled in a large implementation of the CCM in community health clinics in Washington state. VBP was initiated in year 2 of the pro ...[more]

PMID: 28141930

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Project description:Background:When risk adjustment is inadequate and incentives are weak, pay-for-performance programs, such as the Value-Based Payment Modifier (Value Modifier [VM]) implemented by the Centers for Medicare & Medicaid Services, may contribute to health care disparities without improving performance on average. Objective:To estimate the association between VM exposure and performance on quality and spending measures and to assess the effects of adjusting for additional patient characteristics on performance differences between practices serving higher-risk and those serving lower-risk patients. Design:Exploiting the phase-in of the VM on the basis of practice size, regression discontinuity analysis and 2014 Medicare claims were used to estimate differences in practice performance associated with exposure of practices with 100 or more clinicians to full VM incentives (bonuses and penalties) and exposure of practices with 10 or more clinicians to partial incentives (bonuses only). Analyses were repeated with 2015 claims to estimate performance differences associated with a second year of exposure above the threshold of 100 or more clinicians. Performance differences were assessed between practices serving higher- and those serving lower-risk patients after standard Medicare adjustments versus adjustment for additional patient characteristics. Setting:Fee-for-service Medicare. Patients:Random 20% sample of beneficiaries. Measurements:Hospitalization for ambulatory care-sensitive conditions, all-cause 30-day readmissions, Medicare spending, and mortality. Results:No statistically significant discontinuities were found at the threshold of 10 or more or 100 or more clinicians in the relationship between practice size and performance on quality or spending measures in either year. Adjustment for additional patient characteristics narrowed performance differences by 9.2% to 67.9% between practices in the highest and those in the lowest quartile of Medicaid patients and Hierarchical Condition Category scores. Limitation:Observational design and administrative data. Conclusion:The VM was not associated with differences in performance on program measures. Performance differences between practices serving higher- and those serving lower-risk patients were affected considerably by additional adjustments, suggesting a potential for Medicare's pay-for-performance programs to exacerbate health care disparities. Primary Funding Source:The Laura and John Arnold Foundation and National Institute on Aging.

Project description:ImportanceMedicare recently launched the Physician Value-Based Payment Modifier (PVBM) Program, a mandatory pay-for-performance program for physician practices. Little is known about performance by practices that serve socially or medically high-risk patients.ObjectiveTo compare performance in the PVBM Program by practice characteristics.Design, setting, and participantsCross-sectional observational study using PVBM Program data for payments made in 2015 based on performance of large US physician practices caring for fee-for-service Medicare beneficiaries in 2013.ExposuresHigh social risk (defined as practices in the top quartile of proportion of patients dually eligible for Medicare and Medicaid) and high medical risk (defined as practices in the top quartile of mean Hierarchical Condition Category risk score among fee-for-service beneficiaries).Main outcomes and measuresQuality and cost z scores based on a composite of individual measures. Higher z scores reflect better performance on quality; lower scores, better performance on costs.ResultsAmong 899 physician practices with 5 189 880 beneficiaries, 547 practices were categorized as low risk (neither high social nor high medical risk) (mean, 7909 beneficiaries; mean, 320 clinicians), 128 were high medical risk only (mean, 3675 beneficiaries; mean, 370 clinicians), 102 were high social risk only (mean, 1635 beneficiaries; mean, 284 clinicians), and 122 were high medical and social risk (mean, 1858 beneficiaries; mean, 269 clinicians). Practices categorized as low risk performed the best on the composite quality score (z score, 0.18 [95% CI, 0.09 to 0.28]) compared with each of the practices categorized as high risk (high medical risk only: z score, -0.55 [95% CI, -0.77 to -0.32]; high social risk only: z score, -0.86 [95% CI, -1.17 to -0.54]; and high medical and social risk: -0.78 [95% CI, -1.04 to -0.51]) (P < .001 across groups). Practices categorized as high social risk only performed the best on the composite cost score (z score, -0.52 [95% CI, -0.71 to -0.33]), low risk had the next best cost score (z score, -0.18 [95% CI, -0.25 to -0.10]), then high medical and social risk (z score, 0.40 [95% CI, 0.23 to 0.57]), and then high medical risk only (z score, 0.82 [95% CI, 0.65 to 0.99]) (P < .001 across groups). Total per capita costs were $9506 for practices categorized as low risk, $13 683 for high medical risk only, $8214 for high social risk only, and $11 692 for high medical and social risk. These patterns were associated with fewer bonuses and more penalties for high-risk practices.Conclusions and relevanceDuring the first year of the Medicare Physician Value-Based Payment Modifier Program, physician practices that served more socially high-risk patients had lower quality and lower costs, and practices that served more medically high-risk patients had lower quality and higher costs.

Project description:ObjectiveThis study examines the relationship between evidence-based appropriateness criteria for neurologic imaging procedures and Medicare payment determinations. The primary research question is whether Medicare is more likely to pay for imaging procedures as the level of appropriateness increases.Data sourcesThe American College of Radiology Appropriateness Criteria (ACRAC) for neurological imaging, ICD-9-CM codes, CPT codes, and payment determinations by the Medicare Part B carrier for Florida and Connecticut.Study designCross-sectional study of appropriateness criteria and Medicare Part B payment policy for neurological imaging. In addition to descriptive and bivariate statistics, multivariate logistic regression on payment determination (yes or no) was performed.Data collection methodsThe American College of Radiology Appropriateness Criteria (ACRAC) documents specific to neurological imaging, ICD-9-CM codes, and CPT codes were used to create 2,510 medical condition/imaging procedure combinations, with associated appropriateness scores (coded as low/middle/high).Principal findingsAs the level of appropriateness increased, more medical condition/imaging procedure combinations were payable (low = 61 percent, middle = 70 percent, and high = 74 percent). Logistic regression indicated that the odds of a medical condition/imaging procedure combination with a middle level of appropriateness being payable was 48 percent higher than for an otherwise similar combination with a low appropriateness score (95 percent CI on odds ratio=1.19-1.84). The odds ratio for being payable between high and low levels of appropriateness was 2.25 (95 percent CI: 1.66-3.04).ConclusionsMedicare could improve its payment determinations by taking advantage of existing clinical guidelines, appropriateness criteria, and other authoritative resources for evidence-based practice. Such an approach would give providers a financial incentive that is aligned with best-practice medicine. In particular, Medicare should review and update its payment policies to reflect current information on the appropriateness of alternative imaging procedures for the same medical condition.

Dataset Information

Value-based payment in implementing evidence-based care: the Mental Health Integration Program in Washington state.

Publications

Value-based payment in implementing evidence-based care: the Mental Health Integration Program in Washington state.

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