Evaluating Hospital Readmission Rates After Discharge From Inpatient Rehabilitation.

OBJECTIVE: To examine facility-level rates of all-cause, unplanned hospital readmissions for 30 days after discharge from inpatient rehabilitation facilities (IRFs). DESIGN: Observational design. SETTING: Inpatient rehabilitation facilities. PARTICIPANTS: Medicare fee-for-service beneficiaries (N=567,850 patient-stays). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: The outcome is all-cause, unplanned hospital readmission rates for IRFs. We adapted previous risk-adjustment and statistical approaches used for acute care hospitals to develop a hierarchical logistic regression model that estimates a risk-standardized readmission rate for each IRF. The IRF risk-adjustment model takes into account patient demographic characteristics, hospital diagnoses and procedure codes, function at IRF admission, comorbidities, and prior hospital utilization. We presented national distributions of observed and risk-standardized readmission rates and estimated confidence intervals to make statistical comparisons relative to the national mean. We also analyzed the number of days from IRF discharge until hospital readmission. RESULTS: The national observed hospital readmission rate by 30 days postdischarge from IRFs was 13.1%. The mean unadjusted readmission rate for IRFs was 12.4%±3.5%, and the mean risk-standardized readmission rate was 13.1%±0.8%. The C-statistic for our risk-adjustment model was .70. Nearly three-quarters of IRFs (73.4%) had readmission rates that were significantly different from the mean. The mean number of days to readmission was 13.0±8.6 days and varied by rehabilitation diagnosis. CONCLUSIONS: Our results demonstrate the ability to assess 30-day, all-cause hospital readmission rates postdischarge from IRFs and the ability to discriminate between IRFs with higher- and lower-than-average hospital readmission rates.

Development of Episode-Based Cost Measures for the US Medicare Merit-based Incentive Payment System.

Importance: The Merit-based Incentive Payment System (MIPS), established as part of the Quality Payment Program, is a Medicare value-based payment program that evaluates clinicians' performance across 4 categories: quality, cost, promoting interoperability, and improvement activities. The cost category includes novel episode-based measures designed for targeted evaluation of the resource use of specific conditions. This report describes the development of episode-based cost measures and their role in the shift from volume-based to value-based purchasing. Objectives: Episode-based cost measures focus on resource use related to the treatment of a specific condition or procedure. The measures exclude health care costs unrelated to the condition or procedure of focus. The episode-based cost measures provide a nuanced examination of resource use that can be used alongside quality metrics to identify opportunities to improve the value by capturing costs that are clinically related to the care being delivered within a given patient-clinician relationship of care delivered to patients. These measures were developed with the input of clinical committees composed of over 320 clinicians from 127 specialty societies and stakeholder organizations. The MIPS program currently evaluates clinician cost category performance based on 2 population-based cost measures (Medicare spending per beneficiary and total per capita costs) in addition to 18 episode-based cost measures. Additional episode-based cost measures are currently under development. Conclusions and Relevance: The transition to value-based payment requires an accurate assessment of clinician effect on health care quality and cost. The use of episode-based cost measures to assess clinician influence on health care costs for high-priority conditions and procedures is an important step. The Centers for Medicare & Medicaid Services is introducing MIPS Value Pathways that will align episode-based cost measures with related quality measures to further incentivize the transition from fee-for-service to value-based care.

Evaluating national trends in outcomes after implementation of a star rating system: Results from dialysis facility compare.

OBJECTIVE: To examine which factors are driving improvement in the Dialysis Facility Compare (DFC) star ratings and to test whether nonclinical facility characteristics are associated with observed longitudinal changes in the star ratings. DATA SOURCES: Data were collected from eligible patients in over 6,000 Medicare-certified dialysis facilities from three annual star rating and individual measure updates, publicly released on DFC in October 2015, October 2016, and April 2018. STUDY DESIGN: Changes in the star rating and individual quality measures were investigated across three public data releases. Year-to-year changes in the star ratings were linked to facility characteristics, adjusting for baseline differences in quality measure performance. DATA COLLECTION: Data from publicly reported quality measures, including standardized mortality, hospitalization, and transfusion ratios, dialysis adequacy, type of vascular access for dialysis, and management of mineral and bone disease, were extracted from annual DFC data releases. PRINCIPAL FINDINGS: The proportion of four- and five-star facilities increased from 30.0% to 53.4% between October 2015 and April 2018. Quality improvement was driven by the domain of care containing the dialysis adequacy and hypercalcemia measures. Additionally, independently owned facilities and facilities belonging to smaller dialysis organizations had significantly lower odds of year-to-year improvement than facilities belonging to either of the two large dialysis organizations (Odds Ratio [OR]: 0.736, 95% Confidence Interval [CI]: 0.631-0.856 and OR: 0.797, 95% CI: 0.723-0.879, respectively). CONCLUSIONS: The percentage of four- and five-star facilities has increased markedly over a three-year time period. These changes were driven by improvement in the specific quality measures that may be most directly under the control of the dialysis facility.