Clinicians’ Reasons for Non-Visit-Based, No-Infectious-Diagnosis-Documented Antibiotic Prescribing: A Sequential Mixed-Methods Study

BackgroundPrevious studies have reported high levels of inappropriate ambulatory antibiotic prescribing in the United States. This population-based cohort study examines temporal trends in appropriateness of ambulatory antibiotic prescribing in South Carolina.MethodsAggregated pharmacy claims data for oral antibiotic prescriptions among South Carolina residents < 65 years old were matched with primary diagnosis codes from medical claims within 14 days of the pharmacy claim from 2012–2017. Appropriateness of antibiotics was defined as maybe indicated or not indicated based on diagnosis codes. Chi-square tests were used to examine overall temporal trend in appropriateness and the trends across age group and gender.ResultsDuring the 6-year period, 3,133,379 prescriptions were identified. Overall, 25.6% of antibiotic prescriptions filled were not indicated. This decreased from 27.9% in 2012 to 22.7% in 2017 (p < 0.001). The most common not indicated conditions were viral upper respiratory infections (39.1%), bronchitis (26.7%), and serous otitis (10.9%). The most common maybe indicated conditions were bacterial otitis (27.5%), acute bacterial tonsillitis (24.8%), and sinusitis (23.6%). While females filled more antibiotic prescriptions, they were less likely than males to have a not indicated condition (24.7% vs. 27.1%, p < 0.001). Prescribing for not indicated conditions was more likely in adults aged 40–64 (33.7%) than those aged 18–39 (23.5%) and < 18 (24.2%).ConclusionThe observed decline in inappropriate ambulatory antibiotic prescribing from 2012 to 2017 in South Carolina represents welcomed news. Further improvements in ambulatory antibiotic stewardship efforts are needed particularly in men ≥ 40 years old with acute respiratory infections.DisclosuresJulie Ann Justo, PharmD, MS, BCPS-AQ ID, bioMerieux (Speaker’s Bureau)TRC Healthcare (Speaker’s Bureau)

Behavioral Economics and Ambulatory Antibiotic Stewardship: A Narrative Review

Electronic medical record (EMR) prescription data may identify high antibiotic prescribers in primary care. However, practitioners doubt that population differences between providers and delayed antibiotic prescriptions are adequately accounted for in EMR-derived prescription rates. This study assessed the validity of using EMR prescription data to produce antibiotic prescription rates, accounting for these factors. The study was a secondary analysis of antimicrobial prescriptions collected from 4 primary care clinics from 2015 to 2017. For adults with selected respiratory and urinary infections, EMR diagnostic codes, prescription data, clinical diagnoses and demographics were abstracted. Overall and delayed prescription rates were produced for EMR diagnostic codes, clinical diagnoses, by clinic, and types of infection. Direct standardization was used to adjust for case mix differences by clinic. High antibiotic prescribers, above the 75th percentile for prescriptions, were compared with low antibiotic prescribers. Of 3108 EMR visits, there were 2577 (85.4%) eligible visits with a clinical diagnosis and prescription information. Overall antibiotic prescription rates were similar utilizing EMR records (31.6%) or clinical diagnoses (32.6%, P = .40). When delayed prescriptions were removed, prescribing rates were lower (22.4%, P < .01). EMR data overestimated prescribing rates for conditions where antibiotics are usually not indicated (17.7% EMR vs 7.6% clinical diagnoses, P < .001). High antibiotic prescribers saw more cases where antibiotics are usually indicated (23.4%) compared to low prescribers (16.8%; P = .001). Electronic medical record prescribing rates are similar to those using clinical diagnoses overall, but overestimate prescribing by clinicians for conditions usually not needing antibiotics. EMR prescription rates do not account for delayed antibiotic prescriptions or differences in infection case-mix.

Neural transfer learning for assigning diagnosis codes to EMRs

BackgroundAmbulatory antibiotic prescriptions without a clinic visit or without documentation of infection could represent overuse and contribute to adverse outcomes. We aim to describe US ambulatory antibiotic prescribing, including those without an associated visit or infection diagnosis.MethodsWe conducted an observational cohort study using data of all patients receiving antibacterial, antibiotic prescriptions from 04/01/2016 to 06/30/2018 in a large US private health insurance plan. We identified outpatient antibiotic prescriptions as (1) associated with a clinician visit and an infection-related diagnosis; (2) associated with a clinician visit but no infection-related diagnosis; or (3) not associated with an in-person clinician visit in the 7 days before the prescription (non-visit-based). We then assessed whether non-visit-based antibiotic prescriptions (NVBAPs) differed from visit-based antibiotics by patient, clinician, or antibiotic characteristics using multivariable models.ResultsThe cohort included 8.6M enrollees who filled 22.3M antibiotic prescriptions. NVBAP accounted for 31% (6.9M) of fills, and non-infection-related prescribing accounted for 22% (4.9M). NVBAP rates were lower for children than for adults (0–17 years old, 16%; 18–64 years old, 33%; >65 years old, 34%). Among most commonly prescribed antibiotic classes, NVBAP was highest for penicillins (36%) and lowest for cephalosporins (25%) and macrolides (25%). Specialist physicians had the highest rate of NVBAP (38%), followed by internists (28%), family medicine (20%), and pediatricians (10%). In multivariable models, NVBAP was associated with increasing age, and NVBAP was less likely for patients in the South, those with more baseline clinical visits, or those with chronic lung disease.ConclusionsOver half of ambulatory antibiotic use was either non-visit-based or non-infection-related. Particularly given health care changes due to the coronavirus disease 2019 pandemic, efforts to improve antibiotic prescribing must account for non-visit-based and non-infection-related prescribing.

BackgroundBetween 15–50% of patients seen in ambulatory settings are prescribed an antibiotic. At least one third of this usage is considered unnecessary. In 2019, our institution implemented the MITIGATE Toolkit, endorsed by the Centers for Disease Control and Prevention to reduce inappropriate antibiotic prescribing for viral respiratory infections in emergency and urgent care settings. In February 2020 we identified our first hospitalized patient with SARS-CoV(2). In March, efforts to limit person-to-person contact led to shelter in place orders and substantial reorganization of our healthcare system. During this time we continued to track rates of unnecessary antibiotic prescribing.MethodsThis was a single center observational study. Electronic medical record data were accessed to determine antibiotic prescribing and diagnosis codes. We provided monthly individual feedback to urgent care prescribers, (Sep 2019-Mar 2020), primary care, and ED providers (Jan 2020 – Mar 2020) notifying them of their specific rate of unnecessary antibiotic prescribing and labeling them as a top performer or not a top performer compared to their peers. The primary outcome was rate of inappropriate antibiotic prescribing.ResultsPre toolkit intervention, 14,398 patient visits met MITIGATE inclusion criteria and 12% received an antibiotic unnecessarily in Jan-April 2019. Post-toolkit intervention, 12,328 patient visits met inclusion criteria and 7% received an antibiotic unnecessarily in Jan-April 2020. In April 2020, patient visits dropped to 10–50% of what they were in March 2020 and April 2019. During this time the unnecessary antibiotic prescribing rate doubled in urgent care to 7.8% from 3.6% the previous month and stayed stable in primary care and the ED at 3.2% and 11.8% respectively in April compared to 4.6% and 10.4% in the previous month.ConclusionRates of inappropriate antibiotic prescribing were reduced nearly in half from 2019 to 2020 across 3 ambulatory care settings. The increase in prescribing in April seen in urgent care and after providers stopped receiving their monthly feedback is concerning. Many factors may have contributed to this increase, but it raises concerns for increased inappropriate antibacterial usage as a side effect of the SARS-CoV(2) pandemic.DisclosuresAll Authors: No reported disclosures

Electronic Health Records: Can Promise Be Fulfilled?

Clinical guidelines discourage antibiotic prescribing for many acute respiratory infections (ARIs), especially for non-antibiotic appropriate diagnoses. Electronic health record (EHR)-based clinical decision support has the potential to improve antibiotic prescribing for ARIs. We randomly assigned 27 primary care clinics to receive an EHR-integrated, documentation-based clinical decision support system for the care of patients with ARIs - the ARI Smart Form - or to offer usual care. The primary outcome was the antibiotic prescribing rate for ARIs in an intent-to-intervene analysis based on administrative diagnoses. During the intervention period, patients made 21 961 ARI visits to study clinics. Intervention clinicians used the ARI Smart Form in 6% of 11 954 ARI visits. The antibiotic prescribing rate in the intervention clinics was 39% versus 43% in the control clinics (odds ratio (OR), 0.8; 95% confidence interval (CI), 0.6-1.2, adjusted for clustering by clinic). For antibiotic appropriate ARI diagnoses, the antibiotic prescribing rate was 54% in the intervention clinics and 59% in the control clinics (OR, 0.8; 95% CI, 0.5-1.3). For non-antibiotic appropriate diagnoses, the antibiotic prescribing rate was 32% in the intervention clinics and 34% in the control clinics (OR, 0.9; 95% CI, 0.6-1.4). When the ARI Smart Form was used, based on diagnoses entered on the form, the antibiotic prescribing rate was 49% overall, 88% for antibiotic appropriate diagnoses and 27% for non-antibiotic appropriate diagnoses. In an as-used analysis, the ARI Smart Form was associated with a lower antibiotic prescribing rate for acute bronchitis (OR, 0.5; 95% CI, 0.3-0.8). The ARI Smart Form neither reduced overall antibiotic prescribing nor significantly improved the appropriateness of antibiotic prescribing for ARIs, but it was not widely used. When used, the ARI Smart Form may improve diagnostic accuracy compared to administrative diagnoses and may reduce antibiotic prescribing for certain diagnoses.

This study aimed to describe the pattern of prescription and laboratory use in the management of infectious acute gastroenteritis (AGE) in children seen in a rural service delivery network (SDN) and to determine their adherence to the 2019 Clinical Practice Guidelines on the Management of Acute Infectious Diarrhea in Children and Adults from the Department of Health (DOH). A descriptive retrospective study was done using the electronic medical records (EMR) of patients less than 19 years old seen by the rural SDN from April 2019-2021 and diagnosed with infectious AGE. Data were extracted on diagnostic and therapeutic management. Adherence to strong CPG recommendations focusing on rehydration, zinc supplementation, rational laboratory use, and antibiotic prescription was chosen as indicator of quality of care. Adherence of less than 70% was defined as low. There were 227 infectious AGE cases, with 72% diagnosed under non-specific infectious AGE. Fifty two percent (52%) were prescribed with low-osmolarity oral rehydration solutions (ORS), while 74% were given zinc. Stool analysis was done in 25% of cases while CBC was done in 20%. Top antibiotics given were metronidazole at 44% and cotrimoxazole at 33%. There was low adherence to prescribing low-osmolarity ORS for rehydration (52%) and to deferring routine antibiotic prescription for non-specific infectious AGE cases (24%). Adherence to deferring routine stool analysis and CBC were relatively high at 73% and 70%, respectively while adherence to antibiotic use for indicated cases was high at 95%. Frequency of diagnostics ordered were low resulting to high adherence rates to recommendations concerning judicious laboratory use. Prescription frequency of appropriate antibiotics and interventions for AGE were low, leading to low adherence rates to recommendations concerning rational antibiotic use and prescription of cornerstone therapies for infectious AGE.

Health systems are moving to implement comprehensive electronic medical record (EMR) systems, or significant pieces of them, in the belief that EMR can be integrated into clinical practice and lead to improved patient outcomes and enhanced safety. There are substantial roadblocks to implementing EMR, including significant cost, the competency needed to implement, the political environment, organization infrastructure and culture, and how organization leaders understand return on investment. Complicating factors include the drive to implement EMR to meet meaningful use standards to qualify for a federal incentive program and recently publicized studies that question the value equation of the EMR as it relates to patient care improvements. We offer our experiences on the successful implementation of the EMR across the large health systems we lead. We offer practical advice and tips on how to achieve successful implementation, evidence that successful implementations improve patient care and safety, and a glimpse of how EMR is a significant foundation in a future of collaborative models that provide continuum-based care.

BackgroundDepending on the population of interest, it is not always feasible to acquire electronic health record (EHR) data for antibiotic prescribing in longitudinal outpatient studies. Even when available, EHR algorithms are limited to only capturing in-network prescriptions. Thus, there is value in learning more about the reliability of parent-reported data to see whether this approach can be validated for epidemiologic research.MethodsWe examined antibiotic prescribing in the MAGIC (Microbiome, Antibiotics, and Growth Infant Cohort) Study, a longitudinal birth cohort of healthy newborns followed through 2 years of life. An informatics algorithm within an EHR platform was developed such that the study team received a text message alert every time a study participant who sought care in the Children’s Hospital of Philadelphia (CHOP) Care Network was prescribed an antibiotic. Families were also asked every 3 months whether their child had been prescribed an antibiotic in the past 3 months. We compared parent-reported antibiotic use with antibiotic use that generated an alert in the EHR.ResultsAmong the 104 EHR-documented antibiotic exposures in 3-month spans, 52 (50%) were reported by parents at the relevant time point. Of the 52 nonreported antibiotic prescriptions that generated alerts, 4 (4%) were explicitly not reported by families and the remaining 48 exposures (46%) were not reported because the family did not answer the question at the relevant time point. There were 11 total exposures that were patient-reported without documented EHR alerts.ConclusionIn this longitudinal birth cohort, only half of in-network, EHR-generated alerts for antibiotic prescriptions were reported by parents, and parent-reported antibiotic exposures occurred outside of the pediatric network that, by definition, could not generate EHR-based alerts. These results suggest that the most effective method for quantifying antibiotic use may be using EHR data supplemented with parent-reported data.DisclosuresAll authors: No reported disclosures.

Urgent Care (UC) encounters result in more inappropriate antibiotic prescriptions than other outpatient setting. Few stewardship interventions have focused on UC. To evaluate the effectiveness of an antibiotic stewardship initiative to reduce antibiotic prescribing for respiratory conditions in a UC network. This quality improvement study conducted in a UC network with 38 UC clinics and 1 telemedicine clinic included 493 724 total UC encounters. The study compared the antibiotic prescribing rates of all UC clinicians who encountered respiratory conditions for a 12-month baseline period (July 1, 2018, through June 30, 2019) with an intervention period (July 1, 2019, through June 30, 2020). A sustainability period (July 1, 2020, through June 30, 2021) was added post hoc. Stewardship interventions included (1) education for clinicians and patients, (2) electronic health record (EHR) tools, (3) a transparent clinician benchmarking dashboard, and (4) media. Occurring independently but concurrent with the interventions, a stewardship measure was introduced by UC leadership into the quality measures, including a financial incentive. The primary outcome was the percentage of UC encounters with an antibiotic prescription for a respiratory condition. Secondary outcomes included antibiotic prescribing when antibiotics were not indicated (tier 3 encounters) and first-line antibiotics for acute otitis media, sinusitis, and pharyngitis. Interrupted time series with binomial generalized estimating equations were used to compare periods. The baseline period included 207 047 UC encounters for respiratory conditions (56.8% female; mean [SD] age, 30.0 [21.4] years; 92.0% White race); the intervention period included 183 893 UC encounters (56.4% female; mean [SD] age, 30.7 [20.8] years; 91.2% White race). Antibiotic prescribing for respiratory conditions decreased from 47.8% (baseline) to 33.3% (intervention). During the initial intervention month, a 22% reduction in antibiotic prescribing occurred (odds ratio [OR], 0.78; 95% CI, 0.71-0.86). Antibiotic prescriptions decreased by 5% monthly during the intervention (OR, 0.95; 95% CI, 0.94-0.96). Antibiotic prescribing for tier 3 encounters decreased by 47% (OR, 0.53; 95% CI, 0.44-63), and first-line antibiotic prescriptions increased by 18% (OR, 1.18; 95% CI, 1.09-1.29) during the initial intervention month. Antibiotic prescriptions for tier 3 encounters decreased by an additional 4% each month (OR, 0.96; 95% CI, 0.94-0.98), whereas first-line antibiotic prescriptions did not change (OR, 1.00; 95% CI, 0.99-1.01). Antibiotic prescribing for respiratory conditions remained stable in the sustainability period. The findings of this quality improvement study indicated that a UC antibiotic stewardship initiative was associated with decreased antibiotic prescribing for respiratory conditions. This study provides a model for UC antibiotic stewardship.

The protocol of improving safe antibiotic prescribing in telehealth: A randomized trial

Background Cefalexin is a commonly prescribed oral antibiotic, with a similar side chain to amoxicillin. The objectives of this study were to (1) describe the frequency and nature of previously recorded cefalexin adverse reaction (AR) labels in the electronic medical record (EMR) in a medical inpatient cohort, (2) evaluate the accuracy of these labels and (3) examine the association between a cefalexin allergy label and the antibiotics prescribed during an inpatient admission. Methods Consecutive admissions under general medicine in a tertiary hospital over a 1-year period were included in this retrospective cohort study. Data regarding cefalexin adverse reaction (AR) history, and antibiotics prescribed during admission were collected from the EMR. Cefalexin allergy descriptions were reviewed using expert criteria to determine whether the described reaction was most consistent with allergy or intolerance. Results The number of admissions included in this study was 12,134. Of the 224 (1.9%) admissions with a recorded cefalexin AR, 196 (87.5%) had a label of allergy and 28 (12.5%) of intolerance. Following the application of expert criteria, 43 (21.9%) of cefalexin allergy labels were found to be consistent with intolerance. The presence of a low-risk cefalexin allergy was associated with an increased likelihood of receiving non-penicillin antibiotics including clindamycin and ciprofloxacin. Conclusion Cefalexin AR are common, and frequently incorrectly classified in the electronic medical record with consequences for in-hospital antibiotic prescribing and antimicrobial stewardship.

Estimating population-level obesity rates is important for informing policy and targeting treatment. The current gold standard for obesity measurement in the United States-the National Health and Nutrition Examination Survey (NHANES)-samples <0.1% of the population and does not target state-level or health system-level measurement. To assess the feasibility of using body mass index (BMI) data from the electronic health record (EHR) to assess rates of overweight and obesity and compare these rates to national NHANES estimates. Using outpatient data from 42 clinics, we studied 388,762 patients in a large health system with at least 1 primary care visit in 2011-2012. We compared crude and adjusted overweight and obesity rates by age category and ethnicity (white, black, Hispanic, Other) between EHR and NHANES participants. Adjusted overweight (BMI≥25) and obesity rates were calculated by a 2-step process. Step 1 accounted for missing BMI data using inverse probability weighting, whereas step 2 included a poststratification correction to adjust the EHR population to a nationally representative sample. Adjusted rates of obesity (BMI≥30) for EHR patients were 37.3% [95% confidence interval (95% CI), 37.1-37.5] compared with 35.1% (95% CI, 32.3-38.1) for NHANES patients. Among the 16 different obesity class, ethnicity, and sex strata that were compared between EHR and NHANES patients, 14 (87.5%) contained similar obesity estimates (ie, overlapping 95% CIs). EHRs may be an ideal tool for identifying and targeting patients with obesity for implementation of public health and/or individual level interventions.