Calculation and public use of the unit-specific standardized mortality ratio

Comparing dialysis centre mortality outcomes across Australia and New Zealand: identifying unusually performing centres 2008-2013

BACKGROUND

Comparing the mortality profiles of dialysis centres is important to ensure that high standards of care are maintained. We compare the performance of dialysis centres in Australia and New Zealand in their treatment of haemodialysis patients, accounting for the competing risks of kidney transplantation and transfer to peritoneal dialysis.

METHODS

Observational cohort study. We included data from all adult patients (5574 patients) commencing haemodialysis at home or in a facility between 2008 and 2010 across 62 dialysis centres, from the Australia and New Zealand Dialysis and Transplant Registry. Standardised mortality ratios were calculated by estimating mortality probabilities from a pooled random effects logistic regression model, accounting for the competing risk of transplantation using an inverse probability weighting approach. Models were adjusted for patient comorbidities, sex, height, weight, late referral to a nephrologist, age, race, primary kidney disease, smoking status, and serum creatinine (μmol/l).

RESULTS

Two dialysis centres were found to have relatively higher levels of risk-adjusted mortality lying outside the prediction intervals for "usual" performance. Risk adjusted mortality rates were not associated with centres' compliance with guidelines for vascular access and biochemical and haematological targets.

CONCLUSIONS

We demonstrate that standardised mortality ratios are useful to identify facilities that have statistically outlying mortality risk. Our criterion for determining whether a centre has better or worse performance than expected is statistical, and thus analyses such as ours can serve only as a screening tool, and are only one aspect of assessment of "quality" of performance.

Risk Adjustment and the Assessment of Disparities in Dialysis Mortality Outcomes

Standardized mortality ratios (SMRs) reported by Medicare compare mortality at individual dialysis facilities with the national average, and are currently adjusted for race. However, whether the adjustment for race obscures or clarifies disparities in quality of care for minority groups is unknown. Cox model-based SMRs were computed with and without adjustment for patient race for 5920 facilities in the United States during 2010. The study population included virtually all patients treated with dialysis during this period. Without race adjustment, facilities with higher proportions of black patients had better survival outcomes; facilities with the highest percentage of black patients (top 10%) had overall mortality rates approximately 7% lower than expected. After adjusting for within-facility racial differences, facilities with higher proportions of black patients had poorer survival outcomes among black and non-black patients; facilities with the highest percentage of black patients (top 10%) had mortality rates approximately 6% worse than expected. In conclusion, accounting for within-facility racial differences in the computation of SMR helps to clarify disparities in quality of health care among patients with ESRD. The adjustment that accommodates within-facility comparisons is key, because it could also clarify relationships between patient characteristics and health care provider outcomes in other settings.

Dialysis practices that distinguish facilities with below- versus above-expected mortality

BACKGROUND AND OBJECTIVES

Mortality rates vary widely among dialysis facilities even after adjustment with standardized mortality ratios (SMRs). This variation may occur because top-performing facilities use practices not shared by others, because the SMR fails to capture key patient characteristics, or both. Practices were identified that distinguish top- from bottom-performing facilities by SMR.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

A cross-sectional survey was performed of staff across three organizations. Staff members rated the perceived quality of their units' patient-, provider-, and facility-level practices using a six-point Likert scale. Facilities were divided into those with above- versus below-expected mortality on the basis of SMRs from U.S. Renal Data Service facility reports. Mean Likert scores were computed for each practice using t tests. Practices that were statistically significant (P ≤ 0.05) and achieved at least a medium effect size of ≥0.4 were reported. Significant predictors were entered into a linear regression model.

RESULTS

Dialysis facilities with below-expected mortality reported that patients in their unit were more activated and engaged, physician communication and interpersonal relationships were stronger, dieticians were more resourceful and knowledgeable, and overall coordination and staff management were superior versus facilities with above-expected mortality. Staff ratings of these practices explained 31% of the variance in SMRs.

CONCLUSIONS

Patient-, provider-, and facility-level practices partly explain SMR variation among facilities. Improving SMRs may require processes that reflect a coordinated, multidisciplinary environment (i.e., no one group, practice, or characteristic will drive facility-level SMRs). Understanding and improving SMRs will require a holistic view of the facility.