Hospital Readmission in Total Hip Replacement Patients in 2009 and 2014

Cost-DALY comparison of hip replacement care in 12 Belgian hospitals

BACKGROUND

In view of the expected increase in expenditure on hip replacement treatment in Belgium, the complication rate and potential waste reduction, as estimated by the Organisation for Economic Cooperation and Development, we are not yet in a position to assess the efficiency of hip replacement treatment in Belgian hospitals. This objective study uses a cost-disability-adjusted life years (DALYs) ratio to propose a comparison of hip replacement surgery among 12 Belgian hospitals.

METHODS

Our study seeks to innovate by proposing an interhospital comparison that simultaneously integrates the weighting of quality indicators and the costs of managing a patient. To this end, we associated a DALY impact with each patient safety indicator, readmission and mortality outcome. We then compared hospitals using both costs and DALYs adjusted to their case mix index. The adjusted values (costs and DALYs) were obtained by relating the observed value to the predicted value obtained from the linear regression model.

RESULTS

We registered a total of 246.5 DALYs for the 12 hospital institutions, the average cost (SD) of a stay being €8013 (€4304). Our model allowed us to identify hospitals with observed values higher than those predicted. Out of the 12 hospitals evaluated, 4 need to reduce costs and DALYs impacts, 6 have to improve one of the two factors and 2 appear to have good results. The costs for the worst performing hospitals can rise to over €150 000.

CONCLUSION

Evaluating the rates of patient safety indicators, associated with cost, is a prerequisite for quality and cost improvement efforts on the part of managers and practitioners. However, it appears essential to evaluate the entire care chain using a comparable unit of measurement. The hospital's case mix index must also be considered in benchmarking to avoid drawing the wrong conclusions. In addition, other indicators, such as the patient's perception of the actual results, should be added to our study.

Causes and Predictors of 30-Day Readmission in Patients With Syncope/Collapse: A Nationwide Cohort Study

Background Syncope accounts for 0.6% to 1.5% of hospitalizations in the United States. We sought to determine the causes and predictors of 30-day readmission in patients with syncope. Methods and Results We identified 323 250 encounters with a primary diagnosis of syncope/collapse in the 2013-2014 Nationwide Readmissions Database. We excluded patients younger than 18 years, those discharged in December, those who died during hospitalization, hospital transfers, and those whose length of stay was missing. We used multivariable logistic regression analysis to evaluate the association between baseline characteristics and 30-day readmission. A total of 282 311 syncope admissions were included. The median age was 72 years (interquartile range, 58-83), 53.9% were women, and 9.3% had 30-day readmission. The most common cause of 30-day readmissions was syncope/collapse, followed by cardiac, neurological, and infectious causes. Characteristics associated with 30-day readmissions were age 65 years and older (odds ratio [OR], 0.7; 95% confidence interval [ CI ], 0.6-0.7), female sex (OR, 0.9; 95% CI, 0.8-0.9), congestive heart failure (OR, 1.5; 95% CI, 1.2-1.9), atrial fibrillation/flutter (OR, 1.3; 95% CI, 1.3-1.4), diabetes mellitus (OR, 1.2; 95% CI, 1.2-1.3), coronary artery disease (OR, 1.2; 95% CI, 1.2-1.3), anemia (OR, 1.4; 95% CI, 1.4-1.5), chronic obstructive pulmonary disease (OR, 1.4; 95% CI, 1.3-1.4), home with home healthcare disposition (OR, 1.5; 95% CI, 1.5-1.6), leaving against medical advice (OR, 1.7; 95% CI, 1.6-1.9), length of stay of 3 to 5 days (OR, 1.5; 95% CI, 1.4-1.6) or >5 days (OR, 2; 95% CI, 1.8-2), and having private insurance (OR, 0.6; 95% CI, 0.6-0.7). Conclusions The 30-day readmission rate after syncope/collapse was 9.3%. We identified causes and risk factors associated with readmission. Future prospective studies are needed to derive risk-stratification models to reduce the high burden of readmissions.