Variation In Risk-adjusted Rates Research Articles

Variation in Risk-Adjusted Ventilator-Associated Pneumonia Days Within a Quality Collaborative

IntroductionVentilator-associated pneumonia (VAP) is associated with increased mortality, prolonged mechanical ventilation, and longer intensive care unit stays. The rate of VAP (VAPs per 1000 ventilator days) within a hospital is an important quality metric. Despite adoption of preventative strategies, rates of VAP in injured patients remain high in trauma centers. Here, we report variation in risk-adjusted VAP rates within a statewide quality collaborative. MethodsUsing Michigan Trauma Quality Improvement Program data from 35 American College of Surgeons–verified Level I and Level II trauma centers between November 1, 2020 and January 31, 2023, a patient-level Poisson model was created to evaluate the risk-adjusted rate of VAP across institutions given the number of ventilator days, adjusting for injury severity, physiologic parameters, and comorbid conditions. Patient-level model results were summed to create center-level estimates. We performed observed-to-expected adjustments to calculate each center's risk-adjusted VAP days and flagged outliers as hospitals whose confidence intervals lay above or below the overall mean. ResultsWe identified 538 VAP occurrences among a total of 33,038 ventilator days within the collaborative, with an overall mean of 16.3 VAPs per 1000 ventilator days. We found wide variation in risk-adjusted rates of VAP, ranging from 0 (0-8.9) to 33.0 (14.4-65.1) VAPs per 1000 d. Several hospitals were identified as high or low outliers. ConclusionsThere exists significant variation in the rate of VAP among trauma centers. Investigation of practices and factors influencing the differences between low and high outlier institutions may yield information to reduce variation and improve outcomes.

Variation in Incidence of Pneumothorax Complications After Percutaneous Lung Biopsies Among Veterans Health Administration Hospitals

Variation in Incidence of Pneumothorax Complications After Percutaneous Lung Biopsies Among Veterans Health Administration Hospitals

Hospital-level variation in rates of postpartum hemorrhage in California.

To examine the extent of hospital-level variation in risk-adjusted rates of postpartum hemorrhage (PPH). We performed a cross-sectional study examining live births in 257 California hospitals between 2011 and 2015 using linked birth certificate and maternal discharge data. PPH was measured using International Classification of Diseases Codes version 9. Mixed-effects logistic regression models were used to examine the presence and extent of hospital-level variation in PPH before and after adjustment for patient-level risk factors and select hospital characteristics (teaching status and annual delivery volume). Risk-adjusted rates of PPH were estimated for each hospital. The extent of hospital variation was evaluated using the median odds ratio (MOR) and intraclass correlation coefficient (ICC). Our study cohort comprised 1,904,479 women who had a live birth delivery hospitalization at 247 hospitals. The median, lowest, and highest hospital-specific rates of PPH were 3.48%, 0.54%, and 12.0%, respectively. Similar rates were observed after adjustment for patient and hospital factors (3.44%, 0.60%, and 11.48%). After adjustment, the proportion of the total variation in PPH rates attributable to the hospital was low, with a MOR of 2.02 (95% confidence interval [CI]: 1.89-2.15) and ICC of 14.3% (95% CI: 11.9%-16.3%). Wide variability exists in the rate of PPH across hospitals in California, not attributable to patient factors, hospital teaching status, and hospital annual delivery volume. Determining whether differences in hospital quality of care explain the unaccounted-for variation in hospital-level PPH rates should be a public health priority.

Evaluation of readmissions due to surgical site infections: A potential target for quality improvement

IntroductionReadmissions have become a focus of pay-for-performance programs. Surgical site infections (SSI) are the reason for most readmissions. Readmissions for SSI could be a unique target for quality improvement. MethodsReadmission risk for SSI were evaluated for patients undergoing colectomies from 2013 to 2014. Hazard models were developed to examine factors associated with and hospital-level variation in risk-adjusted rates of readmission for SSI. ResultsAmong 59,088 patients at 525 hospitals, the rate of readmissions for SSI ranged from 1.45% to 6.34%. Characteristics associated with a greater likelihood of SSI readmissions include male gender, smoking, open surgery and hospitals with increased socioeconomically-disadvantaged patients. After risk adjustment, there was little correlation between hospital performance with SSI readmission rate and performance with overall SSI or total readmission rate (r2 = 0.29, r2 = 0.14). ConclusionsReadmission for SSI represents a unique aspect of quality beyond that offered by measuring only SSI or readmission rates alone, and may provide actionable quality improvement.

Sources of Inefficiency in Healthcare and Education.

Healthcare and education exhibit wide variation in spending that is loosely associated with outcomes. We study supply-side explanations for such variation in in healthcare, and extend this discussion to how it might apply to education. In both sectors, variation in risk-adjusted rates could arise from some providers or educators doing too much (overuse) or others are using too little (underuse). Alternatively, the production function varies across providers and educators, so that hospitals and educators with higher returns to treatment deliver more because of comparative advantage. We discuss how a prototypical Roy model can separate these explanations.

764: Variation in risk-adjusted rates of adverse obstetric outcomes across hospitals nationwide

764: Variation in risk-adjusted rates of adverse obstetric outcomes across hospitals nationwide

Return to theatre for elective hip and knee replacements: what is the relative importance of patient factors, surgeon and hospital?

The aim of this study was to define return to theatre (RTT) rates for elective hip and knee replacement (HR and KR), to describe the predictors and to show the variations in risk-adjusted rates by surgical team and hospital using national English hospital administrative data. We examined information on 260 206 HRs and 315 249 KRs undertaken between April 2007 and March 2012. The 90-day RTT rates were 2.1% for HR and 1.8% for KR. Male gender, obesity, diabetes and several other comorbidities were associated with higher odds for both index procedures. For HR, hip resurfacing had half the odds of cement fixation (OR = 0.58, 95% confidence intervals (CI) 0.47 to 0.71). For KR, unicondylar KR had half the odds of total replacement (OR = 0.49, 95% CI 0.42 to 0.56), and younger ages had higher odds (OR = 2.23, 95% CI 1.65 to 3.01) for ages < 40 years compared with ages 60 to 69 years). There were more funnel plot outliers at three standard deviations than would be expected if variation occurred on a random basis. Hierarchical modelling showed that three-quarters of the variation between surgeons for HR and over half the variation between surgeons for KR are not explained by the hospital they operated at or by available patient factors. We conclude that 90-day RTT rate may be a useful quality indicator for orthopaedics.