Background: Antibiotics are frequently prescribed in nursing homes; national data describing facility-level antibiotic use are lacking. The objective of this analysis was to describe variability in antibiotic use in nursing homes across the United States using electronic health record orders. Methods: A retrospective cohort study of antibiotic orders for 309,884 residents in 1,664 US nursing homes in 2016 were included in the analysis. Antibiotic use rates were calculated as antibiotic days of therapy (DOT) per 1,000 resident days and were compared by type of stay (short stay ≤100 days vs long stay >100 days). Prescribing indications and the duration of nursing home-initiated antibiotic orders were described. Facility-level correlations of antibiotic use, adjusting for resident health and facility characteristics, were assessed using multivariate linear regression models. Results: In 2016, 54% of residents received at least 1 systemic antibiotic. The overall rate of antibiotic use was 88 DOT per 1,000 resident days. The 3 most common antibiotic classes prescribed were fluoroquinolones (18%), cephalosporins (18%), and urinary anti-infectives (9%). Antibiotics were most frequently prescribed for urinary tract infections, and the median duration of an antibiotic course was 7 days (interquartile range, 5–10). Higher facility antibiotic use rates correlated positively with higher proportions of short-stay residents, for-profit ownership, residents with low cognitive performance, and having at least 1 resident on a ventilator. Available facility-level characteristics only predicted a small proportion of variability observed (Model R2 version 0.24 software). Conclusions: Using electronic health record orders, variability was found among US nursing-home antibiotic prescribing practices, highlighting potential opportunities for targeted improvement of prescribing practices.
BackgroundAntibiotics are frequently prescribed in nursing homes (NH). National data describing facility-level antibiotic use (AU) in NH are lacking. The objectives of this analysis were to use NH electronic health records (EHR) to describe AU in NH and variability in AU rates across NH.MethodsWe analyzed antibiotic orders for 309,884 residents in 1,664 US NHs using one EHR company in 2016. We calculated AU rates as antibiotic days-of-therapy (DOT) per 1,000 resident-days and compared by the type of stay (short-stay (SS) ≤ 100 days vs. long-stay (LS) >100 days). We also examined prescribing indications and the duration of nursing home-initiated antibiotic orders. We assessed facility-level correlates of AU using resident health and NH facility characteristics publically available through NH Compare and LTCfocus using a univariate linear regression.ResultsIn 2016, 57% of NH residents received at least one systemic antibiotic; overall rate of AU was 90 DOT/1,000 resident-days. The median facility-level AU rate was 64 DOT/1,000 resident-days (IQR 36–104). The median proportion of SS residents at a facility was 74% (IQR 60–84%). The SS and LS AU rates were 241 DOT/1,000 resident-days (IQR 173–342) and 24 DOT/1,000 resident-days (IQR 14–37), respectively. Overall, the three most common antibiotic classes prescribed were fluoroquinolones (18%), cephalosporins (18%), and extended-spectrum β-lactams (10%). Antibiotics were most frequently prescribed for urinary tract infections, and the mean duration of an antibiotic order was 9 days (range 1–365). Higher facility AU rate correlated positively with the following facility characteristics; proportion of SS residents, urban location, proportion of residents with mild cognitive impairment and lower activities of daily living scores, presence of ventilator beds, proportion of LS residents with urinary catheters or pressure ulcers, facility case-mix index, and not-for-profit ownership and multiorganization facilities.ConclusionSignificant variability in NH AU rates exist, and SS residents have higher AU rates. Identifying NH with high rates of AU after adjusting for facility-level predictors of AU may identify opportunities for targeting efforts to improve prescribing practices.Disclosures All Authors: No reported Disclosures.
Objectives: Vaccine preventable diseases significantly lead to high under 5 mortality in sub-Saharan Africa. Much attention is given to immunization coverage, but little is known about the population of never-vaccinated children (those that have not received any dose of the WHO recommended immunizations) in Ethiopia. This study aims to (i) Describe the prevalence of never-vaccinated children in Ethiopia and (ii) Examine the effects of individual and contextual factors on non-vaccination of Ethiopian children. Methods: We conducted a secondary analysis using pooled cross-sectional data from 2000-2016 Ethiopia Demographic Health Survey. Analyses were restricted to children aged 12-59 months. A two-level multilevel regression analysis model was built with individuals (level 1) nested within communities (level 2). Results: A total of 20,212 children aged 12-59 months nested within 520 clusters were included in the analysis. Approximately 19% (n=3,943) of the study sample had never been vaccinated. Prevalence of non-vaccination was higher among mothers who delivered at home (86%), with no formal education (62%). In the fully adjusted model, the odds of not being vaccinated reduced for children whose mothers attended high school (adjusted odds ratio [aOR] = 0.35; 95% confidence interval [CI] =0.14-0.84), had employment (aOR, 0.74; 95% CI, 0.59-0.92) and delivered in the hospital (aOR, 0.68; 95% CI, 0.52-0.91). As wealth index increases, the odds of a child not being vaccinated decreased (aOR, 0.63; 95%CI, 0.42-0.93). The odds of being unvaccinated were higher among children whose mother lived in rural area (aOR, 1.76; 95% CI, 1.07-2.89), Somali region (aOR, 13.16; 95% CI, and Affar region (aOR, 8.28; 95% CI, 5.04-13.61) compare to those who lived in urban area or Addis Ababa. Conclusions: Both individual and contextual factors contributed to non-vaccination of children in Ethiopia. Interventions to improve childhood vaccination could benefit from putting these factors responsible for non-vaccination of under 5 children into consideration.
Background: Antibiotics are frequently prescribed in nursing homes, often inappropriately. Data sources are needed to facilitate measurement and reporting of antibiotic use to inform antibiotic stewardship efforts. Previous analyses have shown that the type of nursing-home stay, that is, short stay (<100 days), is a strong predictor of high antibiotic use compared to longer nursing-home stays. The study objective was to compare 2 different data sources, electronic health record (EHR) and long-term care (LTC) pharmacy data, for surveillance of antibiotic use and type of nursing-home stay. Methods: EHR and pharmacy data during 2017 were included from 1,933 and 1,348 US-based nursing homes, respectively. We compared data elements available in each data source for antibiotic use reporting. In each data set, we attempted to describe antibiotic use as the proportion of residents on an antibiotic, days-of-therapy (DOT) per 1,000 resident days (RD), and distribution of antibiotic course duration, overall and at the facility level. Facility proportion of short-stay and long-stay (>100 days) nursing-home residents were calculated using admission dates and census data in the EHR data set and a payor variable in the pharmacy data set (Figure 1). The 2 data sources also provided antibiotic characteristics, including antibiotic class, agent, and route of administration. The deidentified nature of facility data prevented direct comparison of antibiotic use measures between facilities. Results: The EHR and pharmacy data sets contained 381,382 and 326,713 residents, respectively (Table 1). Within the EHR, 51% of residents were prescribed an antibiotic in 2017, at a median rate of 77 DOT per 1,000 RD. In the LTC pharmacy, 46% of residents were prescribed an antibiotic at a median rate of 79 DOT per 1,000 RD (Table 1). Short-stay residents contributed a smaller proportion of total RDs in the EHR relative to the pharmacy cohort (21% vs 50%, respectively). Conclusions: Nursing-home antibiotic use data obtained from EHR and pharmacy vendors can be used for calculating antibiotic use measures, which is important for antibiotic use reporting and facility-level tracking to identify opportunities for improving prescribing practices and provide facility-level benchmarks. Further validation of both data sources in the same facilities is needed to compare antibiotic use rates and to determine the most appropriate proxy for type of nursing-home stay for facility-level risk adjustment of antibiotic use rates.Funding: NoDisclosures: None
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