Infection Control & Hospital Epidemiology In this study, we quantified the prevalence and characteristics
of patients prescribed antibiotics upon discharge from an acute- care hospital to LTCFs. We also quantified the association between receiving an antibiotic prescription upon discharge to an LTCF and healthcare utilization including 30-day hospital read- mission, 30-day emergency department (ED) visits, and C. difficile- associated hospital readmission or ED visit within 60 days of discharge. These outcomes result in considerable burden on LTCF residents, their family members, and facility staff. Furthermore, if receiving antibiotics upon discharge to LTCFs is associated with an increased frequency of hospital readmission, this may provide a financial incentive for both hospitals and LTCFs to improve antibiotic prescribing in this patient population.
Methods Study design and patient population
Prior to study commencement, the Oregon Health & Science University (OHSU) Institutional Review Board approved this study. This was a retrospective cohort study of adult (≥18-year- old) inpatients discharged from OHSU Hospital to an LTCF between February 1, 2012, and June 30, 2016. During the study period, OHSU Hospital was a 576-bed academic, quaternary-care facility in Portland, Oregon. Furthermore, during the study per- iod, there was no formal policy for review and management of antibiotic prescribed upon discharge. Observation patients and those discharged from the ED were excluded.
Data collection and variable definitions
Study data were collected from the Pharmacy Data Repository (PHARR), a longitudinal repository of patient healthcare data created in partnership with the Oregon Clinical and Translational Institute (OCTRI) research data warehouse. These data have been previously used in epidemiologic studies of medication prescrib- ing upon discharge.20–22 Our primary outcome of interest was receiving an outpatient prescription for an antibiotic upon discharge from acute care to an LTCF. In addition, we identified the potential infectious indication for each antibiotic prescription. Given our large sample size and that all infection types are not routinely cultured, we initially used diagnosis codes (ie, International Classification of Diseases, Ninth or Tenth Revision [ICD-9 or ICD-10]) for bac- terial infections during the index encounter. Among patients who lacked a diagnosis code for a bacterial infection, we assessed whether patients had a positive clinical culture for a bacterial organism or a positive C. difficile toxin assay or polymerase chain reaction (PCR) test. For patients lacking both a diagnosis code and a positive bacterial culture or C. difficile toxin assay or PCR test, we reviewed a 20% random sample of discharge summaries to discern the possible indication for the antibiotic prescription. Other exposures of interest included patient demographics (eg, age and sex), inpatient encounter diagnosis-related groups, indi- vidual (based on ICD-9 or -10 diagnosis code) and aggregate comorbidity burden (defined using the Charlson comorbidity index), and length of stay during the index hospital admission. We also quantified the association between receiving an
antibiotic prescription upon discharge to an LTCF and healthcare utilization. Outcomes of interest for this analysis included having an ED visit or being readmitted to OHSU Hospital within 30 days of discharge. Additionally, we determined the prevalence of a new
19
diagnosis code or positive C. difficile toxin or PCR assay on an ED visit or readmission to OHSU Hospital within 60 days of discharge.
Statistical analysis
We used descriptive statistics including means, standard devia- tions, frequencies, and percentages to describe the study popu- lation and distributions of antibiotic classes prescribed and potential infectious indications. We used logistic regression to examine the unadjusted and adjusted associations between receiving a prescription for antibiotics upon discharge and 30-day hospital readmission, 30-day ED visits at the index facility, and C. difficile infection during a readmission or ED visit at the index within 60 days of discharge. We used best subsets selection with Akaike information criterion (AIC) optimization with forced inclusion of our exposure of interest (ie, receiving a prescription for antibiotics upon discharge) to determine candidate models. We then evaluated the confounding effect of all unselected vari- ables and included them in the final model if their inclusion in the final model changed the measure of association between our exposure of interest and outcome by at least 10%. Results from the logistic regression models are presented as odds ratios (ORs) and 95% confidence intervals (CIs). All analyses were performed using SAS statistical software, version 9.2 (SAS Institute, Cary, NC).
Results
There were 6,701 adult discharges to an LTCF from OHSU Hospital during the study period. Patient characteristics are dis- played in Table 1. Approximately 36.0% of the patients dis- charged were <65 years of age; 11.7% were 86 years or older; and 49.7% were male. The median inpatient length of stay on the index hospital admission was 7 days (interquartile range [IQR], 4–12 days). The primary admission diagnosis (MS-DRG) was most frequently surgery- or procedure-related at 64.0%, and the median Charlson comorbidity index was 3 (IQR, 1–5). Of the 6,701 patients discharged to an LTCF, 1,532 patients
(22.9%) had an outpatient prescription for an antibiotic upon discharge, of whom 24.7% had >1 antibiotic prescription. In addition, of the 1,532 patients who received antibiotics upon discharge, only 160 (10.4%) had an infectious diseases consulta- tion during their index admission (data not shown). The distribution of antibiotics prescribed upon discharge is
displayed in Table 2. The most frequently prescribed antibiotics were cephalosporins (20.4%), fluoroquinolones (19.1%), and penicillins (16.7%). Of the 1,906 antibiotics prescribed upon dis- charge, 508 (26.7%) were parenteral antibiotics (data not shown). Among 1,532 patients discharged who received an antibiotic prescription upon discharge to an LTCF, 1,334 patient records (87.1%) included evidence of a potential infectious indication using a diagnosis code for a bacterial infection, a positive clinical culture for a bacterial organism, or a positive C. difficile toxin assay or polymerase chain reaction (PCR) test during the index admission. Most records of patients discharged (82.1%) had a diagnosis code for a bacterial infection among which the most prevalent diagnoses were for urinary tract infections (UTIs, 35.9%), bloodstream infection/endocarditis (26.9%), and “other bacterial diseases” (19.7%) (Table 3). Within the “other bacterial diseases” group, 66 patient records (26.7%) had an additional
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44 |
Page 45 |
Page 46 |
Page 47 |
Page 48 |
Page 49 |
Page 50 |
Page 51 |
Page 52 |
Page 53 |
Page 54 |
Page 55 |
Page 56 |
Page 57 |
Page 58 |
Page 59 |
Page 60 |
Page 61 |
Page 62 |
Page 63 |
Page 64 |
Page 65 |
Page 66 |
Page 67 |
Page 68 |
Page 69 |
Page 70 |
Page 71 |
Page 72 |
Page 73 |
Page 74 |
Page 75 |
Page 76 |
Page 77 |
Page 78 |
Page 79 |
Page 80 |
Page 81 |
Page 82 |
Page 83 |
Page 84 |
Page 85 |
Page 86 |
Page 87 |
Page 88 |
Page 89 |
Page 90 |
Page 91 |
Page 92 |
Page 93 |
Page 94 |
Page 95 |
Page 96 |
Page 97 |
Page 98 |
Page 99 |
Page 100 |
Page 101 |
Page 102 |
Page 103 |
Page 104 |
Page 105 |
Page 106 |
Page 107 |
Page 108 |
Page 109 |
Page 110 |
Page 111 |
Page 112 |
Page 113 |
Page 114 |
Page 115 |
Page 116 |
Page 117 |
Page 118 |
Page 119 |
Page 120 |
Page 121 |
Page 122 |
Page 123 |
Page 124 |
Page 125 |
Page 126 |
Page 127 |
Page 128 |
Page 129 |
Page 130 |
Page 131 |
Page 132 |
Page 133 |
Page 134 |
Page 135 |
Page 136
