Search

Objective: To develop outcome measures that are more sensitive than current measures for evaluating primary or transitional care after hospitalizations, emergency department (ED) visits, or observation stays.Data Sources: Medicare claims data from January 1, 2015, to October 31, 2017, for 1 261 707 Medicare fee-for-service beneficiaries served by (a) primary care practices participating in Track 1 of the Comprehensive Primary Care Plus (CPC+) initiative, and (b) their matched comparison practices.Study Design: Given the poor statistical power in many studies to detect effects on readmissions, we developed two novel claims-based measures of unplanned acute care (UAC) following an index acute care event. The first measure assesses the proportion of hospitalizations followed by an unplanned readmission, ED visit, or observation stay within 30 days of discharge; the second assesses the proportion of ED visits and observation stays followed by a hospitalization, ED visit, or observation stay within 30 days. We calculate minimum detectable effects (MDEs) for both measures and for a conventional measure of 30-day unplanned readmissions, using CPC+ data.Principal Findings: Repeat UAC events are common among Medicare beneficiaries served by the CPC+ practices. In 2017, 22% of discharges and 21% of ED visits and observation stays had a UAC event within 30 days. Readmissions were the most common UAC event following discharge, whereas ED visits were most common following index ED visits or observation stays. MDEs are 25%-40% lower for the new measures than for the standard 30-day readmissions measure, indicating better statistical power to detect impacts of primary or transitional care interventions.Conclusions: This study introduces two new claims-based measures to assess quality of care during a patient's vulnerable period following acute care. The new measures complement existing measures, covering a broader range of UAC events than the standard 30-day readmissions measure, and yielding greater statistical power. [ABSTRACT FROM AUTHOR]

Objective: To develop an automated, reproducible method for delineating hospital service areas (HSAs).Data Sources/setting: Discharge data from all Swiss acute care hospitals for the years 2013 to 2016.Study Design: We derived HSAs and hospital referral regions for Switzerland using a newly developed flow-based, automated, objective, and reproducible method using all discharge data. We compared our method to the classical, partially subjective approach used to delineate the Swiss Health Care Atlas by delineating four sets of intervention-specific HSAs.Principal Findings: Based on 4 105 885 discharges, the fully automated method delineated 63 HSAs. Comparison with existing HSAs reveals good overlap and comparable measures of health utilization between the methods and shows that in the Swiss setting, our method outperforms a cluster-based approach to defining HSAs. While the classical method potentially takes an entire day to delineate the regions, our method took approximately 10 minutes.Conclusions: Hospital service areas are used to analyze differences in use of health care that may indicate underuse and overuse. Our new, fully automated, objective, and reproducible method provides a useful tool for hospital services researchers that will enable them to delineate and update patient-flow-based HSAs. [ABSTRACT FROM AUTHOR]

Objective: To quantify the impact of two approaches (directed and query-based) to health information exchange (HIE) on potentially avoidable use of health care services.Data Sources/study Setting: Data on ambulatory care providers' adoption of HIE were merged with Medicare fee-for-service claims from 2008 to 2014. Providers were from 13 counties in New York served by the Rochester Regional Health Information Organization (RHIO).Study Design: Linear regression models with provider and year fixed effects were used to estimate changes in the probability of utilization outcomes for Medicare beneficiaries attributed to providers adopting directed and/or query-based HIE compared with beneficiaries attributed to providers who had not adopted HIE.Data Collection: Providers' HIE adoption status was determined through Rochester RHIO registration records. RHIO and claims data were linked via National Provider Identifiers.Principal Findings: Query-based HIE adoption was associated with a 0.2 percentage point reduction in the probability of an ambulatory care sensitive hospitalization and a 1.1 percentage point decrease in the likelihood of an unplanned readmission. Directed HIE adoption was not associated with any outcome.Conclusions: The Centers for Medicare & Medicaid Services' (CMS) EHR certification criteria includes requirements for directed HIE, but not query-based HIE. Pending further research, certification criteria should place equal weight on facilitating query-based and directed exchange. [ABSTRACT FROM AUTHOR]

Objective: To characterize the nature and degree of hospitals' efforts to collaborate with skilled nursing facilities (SNFs) and associated patient outcomes.Data Sources/study Setting: Qualitative data were collected through 138 interviews with staff in 16 hospitals and 25 SNFs in eight markets across the United States in 2015. Quantitative data include Medicare claims data for the 290,603 patients discharged from those 16 hospitals between 2008 and 2015.Study Design/data Collection: Semi-structured interviews with hospital and SNF staff were coded and used to classify hospitals' collaboration efforts with SNFs into high versus low collaboration hospitals, and risk-adjusted, claims-based hospital readmission rates from SNF were compared.Principal Findings: Hospital collaboration efforts were defined as establishing SNF partners, transition management initiatives, and hospital staff visits to SNFs. High collaboration hospitals were more likely to send patients to SNFs (as opposed to home, home with home health, or other PAC settings), sent a higher share of patients to high quality SNFs, and had fewer hospital readmissions from SNF sooner than did low collaboration hospitals.Conclusions: Although collaboration with SNF requires significant administrative and clinical time investment, it is associated with positive patient outcomes. [ABSTRACT FROM AUTHOR]

Objective: To assess whether provider organizations exhibit distinct profiles of low-value service provision.Data Sources: 2007-2011 Medicare fee-for-service claims and enrollment data.Study Design: Use of 31 services that provide minimal clinical benefit was measured for 4,039,733 beneficiaries served by 3,137 provider organizations. Variation across organizations, persistence within organizations over time, and correlations in use of different types of low-value services within organizations were estimated via multilevel modeling, with adjustment for beneficiary sociodemographic and clinical characteristics.Principal Findings: Organizations provided 45.6 low-value services per 100 beneficiaries on average, with considerable variation across organizations (90th/10th percentile ratio, 1.78; 95 percent CI, 1.72-1.84), including substantial between-organization variation within hospital referral regions (90th/10th percentile ratio, 1.66; 95 percent CI, 1.60-1.71). Low-value service use within organizations was highly correlated over time (r, 0.98; 95 percent CI, 0.97-0.99) and positively correlated between 13 of 15 pairs of service categories (average r, 0.26; 95 percent CI, 0.24-0.28), with the greatest correlation between low-value imaging and low-value cardiovascular testing and procedures (r, 0.54).Conclusions: Use of low-value services in provider organizations exhibited substantial variation, high persistence, and modest consistency across service types. These findings are consistent with organizations shaping the practice patterns of affiliated physicians. [ABSTRACT FROM AUTHOR]

Objective: To improve the predictions provided by Medicare's Hospital Compare (HC) to facilitate better informed decisions regarding hospital choice by the public.Data Sources/setting: Medicare claims on all patients admitted for Acute Myocardial Infarction between 2009 through 2011.Study Design: Cohort analysis using a Bayesian approach, comparing the present assumptions of HC (using a constant mean and constant variance for all hospital random effects), versus an expanded model that allows for the inclusion of hospital characteristics to permit the data to determine whether they vary with attributes of hospitals, such as volume, capabilities, and staffing. Hospital predictions are then created using directly standardized estimates to facilitate comparisons between hospitals.Data Collection/extraction Methods: Medicare fee-for-service claims.Principal Findings: Our model that included hospital characteristics produces very different predictions from the current HC model, with higher predicted mortality rates at hospitals with lower volume and worse characteristics. Using Chicago as an example, the expanded model would advise patients against seeking treatment at the smallest hospitals with worse technology and staffing.Conclusion: To aid patients when selecting between hospitals, the Centers for Medicare and Medicaid Services (CMS) should improve the HC model by permitting its predictions to vary systematically with hospital attributes such as volume, capabilities, and staffing. [ABSTRACT FROM AUTHOR]

Objective: To examine the relationship between Magnet recognition, an indicator of nursing excellence, and patients' experience with their hospitalization reported in the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey.Data Sources: This secondary analysis includes cross-sectional data from the 2010 HCAHPS survey, the American Hospital Association, and the American Nurses Credentialing Center.Study Design: We conducted a retrospective observational study.Data Collection: Using common hospital identifiers, we created a matched set of 212 Magnet hospitals and 212 non-Magnet hospitals.Principal Findings: Patients in Magnet hospitals gave their hospitals higher overall ratings, were more likely to recommend their hospital, and reported more positive care experiences with nurse communication.Conclusions: Magnet recognition is associated with better patient care experiences, which may positively enhance reimbursement for hospitals. [ABSTRACT FROM AUTHOR]