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Statistical methods for provider profiling are designed to measure healthcare quality and create incentives for low-quality providers to improve. While most existing healthcare quality metrics assess the overall treatment delivered to providers' entire patient populations, widespread racial and sociodemographic disparities in health outcomes highlight the need to evaluate providers' healthcare quality across patient subgroups. Disparity measure development at the healthcare provider level is a nascent research area, and existing measures have lacked the statistical rigor and clear definitions of performance benchmarks that are characteristic of traditional provider profiling methodology. In response to these gaps, we propose a formal disparity model for provider evaluations, which can be used to construct null hypotheses and test statistics for concepts such as systemic disparities, equality in performance, and equity in performance. For each of these topics, we define the appropriate performance benchmark in terms of statistical parameters, and describe its relationship with the existing literature. These arguments also shed light on the long standing debate regarding social risk adjustments in assessments of overall healthcare quality. Finally, we develop an assessment chart to easily visualize disparity patterns and identify the most culpable providers. These methods are demonstrated through analyses of racial disparities in access to transplantation among End-Stage Renal Disease patients. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

To assess the quality of health care, patient outcomes associated with medical providers (eg, dialysis facilities) are routinely monitored in order to identify poor (or excellent) provider performance. Given the high stakes of such evaluations for payment as well as public reporting of quality, it is important to assess the reliability of quality measures. A commonly used metric is the inter‐unit reliability (IUR), which is the proportion of variation in the measure that comes from inter‐provider differences. Despite its wide use, however, the size of the IUR has little to do with the usefulness of the measure for profiling extreme outcomes. A large IUR can signal the need for further risk adjustment to account for differences between patients treated by different providers, while even measures with an IUR close to zero can be useful for identifying extreme providers. To address these limitations, we propose an alternative measure of reliability, which assesses more directly the value of a quality measure in identifying (or profiling) providers with extreme outcomes. The resulting metric reflects the extent to which the profiling status is consistent over repeated measurements. We use national dialysis data to examine this approach on various measures of dialysis facilities. [ABSTRACT FROM AUTHOR]

Background: To assure and improve the quality and safety of care provided by dialysis facilities, federal oversight has been conducted through periodic survey assessment. However, with the growing number of individuals living with ESRD and dialysis facilities, state survey agencies have faced challenges in time and resources to complete survey activities. Therefore, the survey process (‘Basic Survey’ used prior to 2013) was redesigned in order to develop a more efficient process (‘Core Survey’ newly implemented since 2013). The purpose of this analysis was to evaluate and compare dialysis facility survey outcomes between the Core and Basic Survey processes, using a causal inference technique. The survey outcomes included condition-level citations, total citations (condition- and standard-level), and citation rate per survey-hour. Methods: For comparisons of non-randomly assigned survey types, propensity score matching was used. Data were drawn from CMS’ Quality Improvement Evaluation System (QIES) database from January 1, 2013 through July 31, 2014. Covariates available included survey type, facility characteristics (state, urban, practices catheter reuse, dialysis modalities offered, number of patients, mortality, hospitalization, infection) and survey-related characteristics (number of surveyors, time since last survey). Results: Compared to the Basic Survey, the Core Survey identified 10% more total citations (P = 0.001) and identified condition-level citations more frequently, although the latter finding did not reach statistical significance. These findings suggest an increase of 10% in citation rate (i.e. ratio between citations and survey time) with the Core survey process (P = 0.002). Conclusions: Greater efficiency has implications for attenuating the time-intensive burden of the state survey process, and improving the safety and quality of care provided by dialysis facilities. [ABSTRACT FROM AUTHOR]

Discusses the challenges of field/archival research confronted during the investigation of the Black Panther Party (BPP) in the U.S. Empirical legacy of the BPP; Lack of comprehensive analysis on the party within the literature on social movement; Substantial costs of hiring, training and keeping research assistants.