Arteriovenous Fistula Use in the United States and Dialysis Facility-Level Comorbidity Burden.

RATIONALE & OBJECTIVE: Patients with multiple comorbid conditions are less likely to use an arteriovenous fistula (AVF) for hemodialysis vascular access. Some dialysis facilities have high rates of AVF placement despite having patients with many comorbid conditions. This study describes variation in facility-level use of AVFs across the facility-level burden of patient comorbid conditions. STUDY DESIGN: Retrospective cohort study. SETTING & PARTICIPANTS: Medicare patients receiving hemodialysis for 1 year or more in US dialysis facilities. PREDICTORS: Facility-level burden of patient comorbid conditions; patient characteristics. OUTCOMES: Odds of AVFs versus other access types; facility-level use of AVFs. ANALYTICAL APPROACH: Facility-level comorbidity burden was calculated by summing individual comorbid conditions, determining the average per patient, then defining 11 groups based on facility percentile ranking. Generalized estimating equations with a logit link were used to estimate the odds of AVF placement at the patient level. For the facility-level analysis, a generalized estimating equation model with the identity link was fit to characterize the percentage of AVF use at each facility. RESULTS: Overall, AVF use was 65.8% in 315,919 prevalent hemodialysis patients among 5,813 facilities. After adjustment for patient characteristics, AVF use was 0.27, 0.30, 1.05, and 1.74 percentage points lower than the median among facilities in the 61st to 70th, 71st to 80th, 81st to 90th, and 91st to 99th percentiles of comorbidity, respectively, and 0.42, 0.63, 1.34, and 1.90 percentage points higher than the median among facilities in the 31st to 40th, 21st to 30th, 11th to 20th, and 1st to 10th percentiles of comorbidity, respectively. Facilities in the greater than 99th percentile of comorbidity burden had AVF use that was 3.47 percentage points lower than the median. Facilities in the less than 1st percentile of comorbidity burden had AVF use that was 2.64 percentage points greater than the median. LIMITATIONS: Limited to Medicare dialysis-dependent patients treated for 1 year or more. CONCLUSIONS: After adjustment for patient characteristics, we found small differences in facility rates of AVF use except in the extremes of high or low levels of comorbidity burden. Our study demonstrates that dialysis facilities with a relatively high patient comorbidity burden can achieve similar fistula rates as facilities with healthier patients. Although high comorbidity burden does not explain low facility AVF use, additional study is needed to understand differences in AVF use rates between facilities with similar comorbidity burdens.

Comparing national point prevalence surveys of healthcare-associated infection and antimicrobial prescribing: a methodological approach to adjust for differences in case-mix.

BACKGROUND: National point prevalence surveys (PPS) of healthcare-associated infection (HAI) and antimicrobial prescribing in hospitals were conducted in 2011 and 2016 in Scotland. When comparing results of PPS, it is important to adjust for any differences in patient case-mix that may confound the comparison. AIM: To describe the methodology used to compare prevalence for the two surveys and illustrate the importance of taking case-mix (patient and hospital stay characteristics) into account. METHODS: Multivariate models (clustered logistic regression) that adjusted for differences in patient case-mix were used to describe the difference in prevalence of six outcomes (HAI, antimicrobial prescribing and four devices: central vascular catheter, peripheral vascular catheter, urinary catheterisation and intubation) between the 2011 and 2016 PPS. Univariate models that did not adjust for these differences were also developed for comparison to show the importance of adjusting for confounders. RESULTS: Without adjustment for case-mix, HAI and intubation prevalence estimates were not significantly different in 2016 compared with 2011 although with adjustment, the prevalence of both was significantly lower (P=0.03 and P=0.02, respectively). These associations were only identified after adjustment for confounding by case-mix. CONCLUSIONS: While prevalence surveys do not provide intelligence on temporal trends as an incidence-based surveillance system would, if limitations and caveats are acknowledged, it is possible to compare two prevalence surveys to describe changing epidemiology. Adjusting for differences in case-mix is essential for robust comparisons. This methodology may be useful for other countries that are conducting large, repeated prevalence surveys.

A pilot study of risk adjustment for benchmarking antibiotic use between hospitals in Sweden.

There is no established standard for comparing overall antibiotic use between hospitals taking patient characteristics into account. The objective of this study was to investigate whether there is a correlation between surrogate markers for patient morbidity, namely case mix index (CMI), mean length of hospital stay (LoS) and mean cost per admission, and antibiotic use in a sample of Swedish hospitals. All primary and secondary hospitals in three counties with high and three counties with low consumption of antibiotics were selected. Data from 16 hospitals were included. A regression analysis was used to evaluate whether there was a linear trend between defined daily doses (DDD) of antibiotics per 100 bed-days and the surrogate markers for morbidity. No correlation could be found between any of the measures of morbidity and total antibiotic consumption. However, a correlation was found between CMI and the proportion of narrow-spectrum antibiotics: the higher the CMI, the lower the proportional use of ß-lactamase-sensitive penicillins. In conclusion, it was found that CMI, mean LoS and mean cost per admission did not appears to be useful factors to adjust for when comparing antibiotic use in this subset of primary and secondary care hospitals. Based on this limited study, we suggest that DDD/100 bed-days can still be used as an appropriate metric to benchmark antibiotic use in primary and secondary hospitals until a better marker for variation of patients and activities is identified.