scholarly journals 1123. Specificity of Diagnosis Codes and Adequacy of Supportive Documentation for Common Acute Pediatric Infections: Implications for Ambulatory Stewardship

2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S399-S399
Author(s):  
Zachary Willis ◽  
Elizabeth Walters
Keyword(s):  
Acute Otitis Media ◽  
Antibiotic Prescribing ◽  
National Guidelines ◽  
Laboratory Findings ◽  
Healthcare Settings ◽  
Diagnosis Codes ◽  
Icd 10 ◽  
Pediatric Infections ◽  
Data Elements ◽  
Physical Findings

Abstract Background Assessing the appropriateness of antibiotic prescribing in ambulatory care generally relies on the accuracy of diagnosis codes, which is uncertain. It is also uncertain if documented history and physical findings support antibiotic indications (AI). We completed a retrospective study of pediatric primary care (PPC) encounters to determine: A) if documented findings supported documented AI; and B) whether diagnosis codes captured documented AI (figure). Methods We conducted point-prevalence audits of the 9 PPC clinics in our healthcare system, randomly selecting one weekday per month to review all visits between 9/2017 and 4/2018. We included only encounters with antibiotic prescribing. We reviewed clinician notes, orders, laboratory results, and ICD-10 diagnosis codes. We recorded demographics; visit date/location; AI as documented in notes; history, examination, and laboratory findings; and diagnosis codes. We used national guidelines to determine whether documentation supported AI. We calculated the sensitivity of diagnosis codes using documented AI as the gold standard. Results The sample included 452 encounters. The most common AI were acute otitis media (AOM), pharyngitis, and sinusitis. For AOM, 163 of 168 encounters (97.0%) had an appropriate diagnosis code; for pharyngitis, 127 of 138 (92.0%); and for sinusitis, 68 of 75 (90.7%). For AOM, 160 of 168 encounters (95.2%) had adequate documentation of supportive findings. For sinusitis, 44 of 75 encounters had adequate supporting history and/or examination findings (58.7%). For pharyngitis, while 135 of 139 (97.1%) had a positive streptococcal test, 104 of 139 (74.8%) had history and examination findings to support testing. Conclusion By chart review, we identified each AI and evaluated whether findings supported those AI. The sensitivity of diagnosis codes for AI ranged from 90.7–97.0% for common conditions; this result can inform the design of ambulatory stewardship programs. Only 74.8% of children treated for pharyngitis and 58.7% of children treated for sinusitis had sufficient supporting documentation. Use of discrete data elements alone (Figure 1) may result in overestimates of the proportion of children for whom antibiotics are appropriate. Further research is needed across healthcare settings. Disclosures All authors: No reported disclosures

scholarly journals Appropriateness of outpatient antibiotic prescribing among privately insured US patients: ICD-10-CM based cross sectional study

BMJ ◽  
2019 ◽  
pp. k5092 ◽  
Author(s):  
Kao-Ping Chua ◽  
Michael A Fischer ◽  
Jeffrey A Linder
Keyword(s):  
Classification Scheme ◽  
Antibiotic Prescription ◽  
Antibiotic Prescribing ◽  
Diagnosis Code ◽  
Diagnosis Codes ◽  
The Us ◽  
Look Back ◽  
Icd 10 ◽  
Recent Diagnosis ◽  
Privately Insured

Abstract Objective To assess the appropriateness of outpatient antibiotic prescribing for privately insured children and non-elderly adults in the US using a comprehensive classification scheme of diagnosis codes in ICD-10-CM (international classification of diseases-clinical modification, 10th revision), which replaced ICD-9-CM in the US on 1 October 2015. Design Cross sectional study. Setting MarketScan Commercial Claims and Encounters database, 2016. Participants 19.2 million enrollees aged 0-64 years. Main outcome measures A classification scheme was developed that determined whether each of the 91 738 ICD-10-CM diagnosis codes “always,” “sometimes,” or “never” justified antibiotics. For each antibiotic prescription fill, this scheme was used to classify all diagnosis codes in claims during a look back period that began three days before antibiotic prescription fills and ended on the day fills occurred. The main outcome was the proportion of fills in each of four mutually exclusive categories: “appropriate” (associated with at least one “always” code during the look back period, “potentially appropriate” (associated with at least one “sometimes” but no “always” codes), “inappropriate” (associated only with “never” codes), and “not associated with a recent diagnosis code” (no codes during the look back period). Results The cohort (n=19 203 264) comprised 14 571 944 (75.9%) adult and 9 935 791 (51.7%) female enrollees. Among 15 455 834 outpatient antibiotic prescription fills by the cohort, the most common antibiotics were azithromycin (2 931 242, 19.0%), amoxicillin (2 818 939, 18.2%), and amoxicillin-clavulanate (1 784 921, 11.6%). Among these 15 455 834 fills, 1 973 873 (12.8%) were appropriate, 5 487 003 (35.5%) were potentially appropriate, 3 592 183 (23.2%) were inappropriate, and 4 402 775 (28.5%) were not associated with a recent diagnosis code. Among the 3 592 183 inappropriate fills, 2 541 125 (70.7%) were written in office based settings, 222 804 (6.2%) in urgent care centers, and 168 396 (4.7%) in emergency departments. In 2016, 2 697 918 (14.1%) of the 19 203 264 enrollees filled at least one inappropriate antibiotic prescription, including 490 475 out of 4 631 320 children (10.6%) and 2 207 173 out of 14 571 944 adults (15.2%). Conclusions Among all outpatient antibiotic prescription fills by 19 203 264 privately insured US children and non-elderly adults in 2016, 23.2% were inappropriate, 35.5% were potentially appropriate, and 28.5% were not associated with a recent diagnosis code. Approximately 1 in 7 enrollees filled at least one inappropriate antibiotic prescription in 2016. The classification scheme could facilitate future efforts to comprehensively measure outpatient antibiotic appropriateness in the US, and it could be adapted for use in other countries that use ICD-10 codes.

scholarly journals 1632. Non-Visit-Based and Non-Infection-Related Ambulatory Antibiotic Prescribing

2018 ◽  
Vol 5 (suppl_1) ◽  
pp. S43-S43 ◽  
Author(s):  
Jeffrey A Linder ◽  
Tiffany Brown ◽  
Ji Young Lee ◽  
Kao-Ping Chua ◽  
Michael A Fischer
Keyword(s):  
Nurse Practitioners ◽  
Physician Assistants ◽  
Antibiotic Prescribing ◽  
Face To Face ◽  
Health Delivery ◽  
Online Portal ◽  
Diagnosis Codes ◽  
Icd 10 ◽  
Primary Care Clinicians ◽  
Attending Physicians

Abstract Background Many studies have examined or intervened on ambulatory antibiotic prescribing based on infection-related diagnosis codes. However, clinicians may prescribe antibiotics without seeing patients face-to-face or without documenting an infection-related diagnosis. Methods We measured the prevalence of non-visit-based and non-infection-related oral, antibacterial–antibiotic prescribing between November 2015 and October 2017 using the EHR of an integrated health delivery system. We examined the visit type (in-person vs. other) and classified prescriptions into 3 mutually exclusive groups based on same-day diagnosis codes: (1) infection-related for prescriptions associated with at least one of 21,730 ICD-10 codes that may signify infection; (2) non-infection-related for prescriptions only associated with the 72,519 ICD-10 codes that do not signify infections; and (3) associated with no diagnosis. Results There were 509,534 antibiotic prescriptions made to 279,169 unique patients by 2,413 clinicians in 514 clinics. Patients had a mean age of 43 years old, were 60% women, and 75% white. Clinicians were 54% women; were 63% attending physicians, 18% residents/fellows, 10% nurse practitioners, and 7% physician assistants; and were 41% medical specialists, 21% primary care clinicians, and 7% surgical specialists. The most common antibiotic classes were penicillins (30%), macrolides (23%), cephalosporins (14%), fluoroquinolones (11%), tetracyclines (10%), and sulfonamides (6%). Clinicians prescribed 20% of antibiotics outside of an in-person visit; prescription encounters were in-person (80%), telephone (10%), order-only (4%), refill (4%), and online portal (1%). Clinicians prescribed 46% of antibiotics without an infection-related diagnosis: 54% of antibiotic prescriptions were infection-related, 29% were non-infection-related, and 17% were associated with no diagnosis. Various look-back and look-forward durations for diagnosis codes changed the results only slightly. Conclusion Clinicians prescribed 20% of antibiotics outside of in-person visits and 46% of antibiotics without an infection-related diagnosis. Interventions that target visit-based, diagnosis-specific prescriptions miss a large share of antibiotic prescribing. Disclosures All authors: No reported disclosures.

scholarly journals Digital Care Providers Antibiotic Prescribing Compared to Traditional Primary Healthcare: A Retrospective Database Study of 332,987 Healthcare Visits in Sweden.

2021 ◽  
Author(s):  
Justyna Ivarsson ◽  
Thorne Wallman ◽  
Andy Wallman
Keyword(s):  
Primary Healthcare ◽  
Antibiotic Prescription ◽  
Personal Information ◽  
Antibiotic Prescribing ◽  
Care Providers ◽  
Place Of Residence ◽  
Diagnosis Codes ◽  
Icd 10 ◽  
Virtual Visits ◽  
Retrospective Database

Abstract ObjectivesThe aim of this study was to examine if there was a difference in antibiotic prescribing between private digital care providers, and traditional primary healthcare, and to investigate if the prescriptions differed regarding diagnosis between virtual visits and physical visits adjusted for age, sex, and place of residence for patients seeking care digitally and in person.MethodsAntibiotic prescribing based on ATC-codes during the period of two months in 2020 was studied. Prescriptions issued by online doctors and by physicians working within PHC Sörmland County, Sweden were considered. Information about healthcare provider, date of the visit, staff category that patient had contact with, ICD-10-diagnosis codes, ATC-codes of prescribed medicines and personal information such as: age, sex, and place of residence were used. Statistical analysis and logistic regression were performed.ResultsAltogether 332,987 healthcare visits were registered. Of all visits to physicians at PHC in Region Sörmland, antibiotics were prescribed in 5.9% of cases, and 3.9% of all visits to online doctors. The total number of visits that led to infection diagnosis was 112,354. Within physical visits at PHC 21.5% infection visits ended with antibiotic prescription, while within online visits the corresponding percentage was 10.1%. Additionally, the study focused on seventeen infection diagnoses.ConclusionThis study has shown that private digital care providers do not prescribe more antibiotics than doctors at PHC. Probability of receiving antibiotic prescription during digital visits was 4.88 times lower compared to physical visits.

scholarly journals Predicting the 14-Day Hospital Readmission of Patients with Pneumonia Using Artificial Neural Networks (ANN)

2021 ◽  
Vol 18 (10) ◽  
pp. 5110
Author(s):  
Shu-Farn Tey ◽  
Chung-Feng Liu ◽  
Tsair-Wei Chien ◽  
Chin-Wei Hsu ◽  
Kun-Chen Chan ◽  
...  
Keyword(s):  
Neural Network ◽  
Early Stage ◽  
Characteristic Curve ◽  
Patient Discharge ◽  
Ann Model ◽  
Healthcare Settings ◽  
High Area ◽  
Icd 10 ◽  
Artificial Neural ◽  
Artificial Neural Network Ann

Unplanned patient readmission (UPRA) is frequent and costly in healthcare settings. No indicators during hospitalization have been suggested to clinicians as useful for identifying patients at high risk of UPRA. This study aimed to create a prediction model for the early detection of 14-day UPRA of patients with pneumonia. We downloaded the data of patients with pneumonia as the primary disease (e.g., ICD-10:J12*-J18*) at three hospitals in Taiwan from 2016 to 2018. A total of 21,892 cases (1208 (6%) for UPRA) were collected. Two models, namely, artificial neural network (ANN) and convolutional neural network (CNN), were compared using the training (n = 15,324; ≅70%) and test (n = 6568; ≅30%) sets to verify the model accuracy. An app was developed for the prediction and classification of UPRA. We observed that (i) the 17 feature variables extracted in this study yielded a high area under the receiver operating characteristic curve of 0.75 using the ANN model and that (ii) the ANN exhibited better AUC (0.73) than the CNN (0.50), and (iii) a ready and available app for predicting UHA was developed. The app could help clinicians predict UPRA of patients with pneumonia at an early stage and enable them to formulate preparedness plans near or after patient discharge from hospitalization.

scholarly journals A Descriptive Analysis of Outpatient Antimicrobial Use for Urinary Tract Infections in Virginia

2020 ◽  
Vol 41 (S1) ◽  
pp. s453-s454
Author(s):  
Hasti Mazdeyasna ◽  
Shaina Bernard ◽  
Le Kang ◽  
Emily Godbout ◽  
Kimberly Lee ◽  
...  
Keyword(s):  
Urinary Tract ◽  
Urinary Tract Infections ◽  
Private Insurance ◽  
Geographic Region ◽  
Study Cohort ◽  
Antibiotic Prescribing ◽  
Prescribing Trends ◽  
Icd 10 ◽  
Tract Infections ◽  
Insurance Payer

Background: Data regarding outpatient antibiotic prescribing for urinary tract infections (UTIs) are limited, and they have never been formally summarized in Virginia. Objective: We describe outpatient antibiotic prescribing trends for UTIs based on gender, age, geographic region, insurance payer and International Classification of Disease, Tenth Revision (ICD-10) codes in Virginia. Methods: We used the Virginia All-Payer Claims Database (APCD), administered by Virginia Health Information (VHI), which holds data for Medicare, Medicaid, and private insurance. The study cohort included Virginia residents who had a primary diagnosis of UTI, had an antibiotic claim 0–3 days after the date of the diagnosis and who were seen in an outpatient facility in Virginia between January 1, 2016, and December 31, 2016. A diagnosis of UTI was categorized as cystitis, urethritis or pyelonephritis and was defined using the following ICD-10 codes: N30.0, N30.00, N30.01, N30.9, N30.90, N30.91, N39.0, N34.1, N34.2, and N10. The following antibiotics were prescribed: aminoglycosides, sulfamethoxazole/trimethoprim (TMP-SMX), cephalosporins, fluoroquinolones, macrolides, penicillins, tetracyclines, or nitrofurantoin. Patients were categorized based on gender, age, location, insurance payer and UTI type. We used χ2 and Cochran-Mantel-Haenszel testing. Analyses were performed in SAS version 9.4 software (SAS Institute, Cary, NC). Results: In total, 15,580 patients were included in this study. Prescriptions for antibiotics by drug class differed significantly by gender (P < .0001), age (P < .0001), geographic region (P < .0001), insurance payer (P < .0001), and UTI type (P < .0001). Cephalosporins were prescribed more often to women (32.48%, 4,173 of 12,846) than to men (26.26%, 718 of 2,734), and fluoroquinolones were prescribed more often to men (53.88%, 1,473 of 2,734) than to women (47.91%, 6,155 of 12,846). Although cephalosporins were prescribed most frequently (42.58%, 557 of 1,308) in northern Virginia, fluoroquinolones were prescribed the most in eastern Virginia (50.76%, 1677 of 3,304). Patients with commercial health insurance, Medicaid, and Medicare were prescribed fluoroquinolones (39.31%, 1,149 of 2,923), cephalosporins (56.33%, 1,326 of 2,354), and fluoroquinolones (57.36%, 5,910 of 10,303) most frequently, respectively. Conclusions: Antibiotic prescribing trends for UTIs varied by gender, age, geographic region, payer status and UTI type in the state of Virginia. These data will inform future statewide antimicrobial stewardship efforts.Funding: NoneDisclosures: Michelle Doll reports a research grant from Molnlycke Healthcare.

scholarly journals 143. Initial Impact of COVID-19 on Ambulatory Antibiotic Prescribing for Respiratory Viral Infections

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S82-S82
Author(s):  
Zahra Kassamali Escobar ◽  
Todd Bouchard ◽  
Jose Mari Lansang ◽  
Scott Thomassen ◽  
Joanne Huang ◽  
...  
Keyword(s):  
Primary Care ◽  
Viral Infections ◽  
Respiratory Infections ◽  
Urgent Care ◽  
Antibiotic Prescribing ◽  
Specific Rate ◽  
Inclusion Criteria ◽  
Diagnosis Codes ◽  
Control And Prevention ◽  
Viral Respiratory Infections

Abstract Background Between 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. Methods This 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. Results Pre 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. Conclusion Rates 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. Disclosures All Authors: No reported disclosures

Antibiotic Prescribing in Adults Presenting with Pharyngitis Pre- and Post-Implementation of a Rapid Group A Streptococcus Test

2021 ◽  
pp. 001857872110323
Author(s):  
Preeyaporn Sarangarm ◽  
Timothy A. Huerena ◽  
Tatsuya Norii ◽  
Carla J. Walraven
Keyword(s):  
Group A Streptococcus ◽  
Intervention Group ◽  
Urgent Care ◽  
Antibiotic Prescribing ◽  
Care Clinic ◽  
Rapid Antigen Detection Test ◽  
Appropriate Prescribing ◽  
Icd 10 ◽  
Group A

Background: Group A Streptococcus (GAS) pharyngitis is the most common bacterial cause of acute pharyngitis and is often over treated with unnecessary antibiotics. The purpose was to evaluate if implementation of a rapid antigen detection test (RADT) for GAS would reduce the number of inappropriately prescribed antibiotics for adult patients presenting with symptoms of pharyngitis. Methods: This was a retrospective cohort study of adult urgent care clinic patients pre- and post-implementation of a GAS RADT. We included patients who had a diagnosis of GAS identified via ICD-10 codes and either a throat culture, GAS RADT, or antibiotic prescribed for GAS. Antibiotic prescribing was assessed as appropriate or inappropriate based on testing and IDSA guideline recommendations. Thirty-day follow-up visits related to pharyngitis or the prescribed antibiotics was also evaluated. Results: A total of 1734 patients were included; 912 and 822 in the pre- and post-implementation groups, respectively. Following implementation of the GAS RADT, there was an increase in the number of antibiotics prescribed for GAS (43.4% vs 59.1%, P < .001) as well as an increase in appropriate prescribing (67.6% vs 77.5%, P < .001). More 30-day pharyngitis-related follow-up visits were seen in the pre-intervention group (12.5% vs 9.3%, P = .03). Conclusion: Implementation of a RADT for GAS pharyngitis was associated with an increase in both the overall number of antibiotic prescriptions for GAS and the proportion of appropriately prescribed antibiotics. There was also a reduction in follow up visits related to GAS pharyngitis, however educational efforts to further increase appropriate prescribing is needed.

scholarly journals Inappropriate Azithromycin Use in Nine Primary-Care Clinics Before and After Implementation of Provider Guidance in the EMR

2020 ◽  
Vol 41 (S1) ◽  
pp. s292-s293
Author(s):  
Alexandria May ◽  
Allison Hester ◽  
Kristi Quairoli ◽  
Sheetal Kandiah
Keyword(s):  
Primary Care ◽  
Retrospective Chart Review ◽  
Antibiotic Prescribing ◽  
Upper Respiratory Tract ◽  
National Guidelines ◽  
Targeted Interventions ◽  
Primary Care Clinics ◽  
Before And After ◽  
Upper Respiratory ◽  
Tract Infections

Background: According to the CDC Core Elements of Outpatient Stewardship, the first step in optimizing outpatient antibiotic use the identification of high-priority conditions in which antibiotics are commonly used inappropriately. Azithromycin is a broad-spectrum antimicrobial commonly used inappropriately in clinical practice for nonspecific upper respiratory infections (URIs). In 2017, a medication use evaluation at Grady Health System (GHS) revealed that 81.4% of outpatient azithromycin prescriptions were inappropriate. In an attempt to optimize outpatient azithromycin prescribing at GHS, a tool was designed to direct the prescriber toward evidence-based therapy; it was implemented in the electronic medical record (EMR) in January 2019. Objective: We evaluated the effect of this tool on the rate of inappropriate azithromycin prescribing, with the goal of identifying where interventions to improve prescribing are most needed and to measure progress. Methods: This retrospective chart review of adult patients prescribed oral azithromycin was conducted in 9 primary care clinics at GHS between February 1, 2019, and April 30, 2019, to compare data with that already collected over a 6-month period in 2017 before implementation of the antibiotic prescribing guidance tool. The primary outcome of this study was the change in the rate of inappropriate azithromycin prescribing before and after guidance tool implementation. Appropriateness was based on GHS internal guidelines and national guidelines. Inappropriate prescriptions were classified as inappropriate indication, unnecessary prescription, excessive or insufficient treatment duration, and/or incorrect drug. Results: Of the 560 azithromycin prescriptions identified during the study period, 263 prescriptions were included in the analysis. Overall, 181 (68.8%) of azithromycin prescriptions were considered inappropriate, representing a 12.4% reduction in the primary composite outcome of inappropriate azithromycin prescriptions. Bronchitis and unspecified upper respiratory tract infections (URI) were the most common indications where azithromycin was considered inappropriate. Attending physicians prescribed more inappropriate azithromycin prescriptions (78.1%) than resident physicians (37.0%) or midlevel providers (37.0%). Also, 76% of azithromycin prescriptions from nonacademic clinics were considered inappropriate, compared with 46% from academic clinics. Conclusions: Implementation of a provider guidance tool in the EMR lead to a reduction in the percentage of inappropriate outpatient azithromycin prescriptions. Future targeted interventions and stewardship initiatives are needed to achieve the stewardship program’s goal of reducing inappropriate outpatient azithromycin prescriptions by 20% by 1 year after implementation.Funding: NoneDisclosures: None

scholarly journals Development of an Electronic Algorithm to Target Outpatient Antimicrobial Stewardship Efforts for Acute Bronchitis

2020 ◽  
Vol 41 (S1) ◽  
pp. s32-s32
Author(s):  
Ebbing Lautenbach ◽  
Keith Hamilton ◽  
Robert Grundmeier ◽  
Melinda Neuhauser ◽  
Lauri Hicks ◽  
...  
Keyword(s):  
Antimicrobial Stewardship ◽  
Predictive Value ◽  
Gold Standard ◽  
Chart Review ◽  
Acute Bronchitis ◽  
Antibiotic Use ◽  
Antibiotic Prescribing ◽  
Diagnostic Codes ◽  
Icd 10 ◽  
The Impact

Background: Antibiotic resistance has increased at alarming rates, driven predominantly by antibiotic overuse. Although most antibiotic use occurs in outpatients, antimicrobial stewardship programs have primarily focused on inpatient settings. A major challenge for outpatient stewardship is the lack of accurate and accessible electronic data to target interventions. We sought to develop and validate an electronic algorithm to identify inappropriate antibiotic use for outpatients with acute bronchitis. Methods: This study was conducted within the University of Pennsylvania Health System (UPHS). We used ICD-10 diagnostic codes to identify encounters for acute bronchitis at any outpatient UPHS practice between March 15, 2017, and March 14, 2018. Exclusion criteria included underlying immunocompromising condition, other comorbidity influencing the need for antibiotics (eg, emphysema), or ICD-10 code at the same visit for a concurrent infection (eg, sinusitis). We randomly selected 300 (150 from academic practices and 150 from nonacademic practices) eligible subjects for detailed chart abstraction that assessed patient demographics and practice and prescriber characteristics. Appropriateness of antibiotic use based on chart review served as the gold standard for assessment of the electronic algorithm. Because antibiotic use is not indicated for this study population, appropriateness was assessed based upon whether an antibiotic was prescribed or not. Results: Of 300 subjects, median age was 61 years (interquartile range, 50–68), 62% were women, 74% were seen in internal medicine (vs family medicine) practices, and 75% were seen by a physician (vs an advanced practice provider). On chart review, 167 (56%) subjects received an antibiotic. Of these subjects, 1 had documented concern for pertussis and 4 had excluding conditions for which there were no ICD-10 codes. One received an antibiotic prescription for a planned dental procedure. Thus, based on chart review, 161 (54%) subjects received antibiotics inappropriately. Using the electronic algorithm based on diagnostic codes, underlying and concurrent conditions, and prescribing data, the number of subjects with inappropriate prescribing was 170 (56%) because 3 subjects had antibiotic prescribing not noted based on chart review. The test characteristics of the electronic algorithm (compared to gold standard chart review) for identification of inappropriate antibiotic prescribing were the following: sensitivity, 100% (161 of 161); specificity, 94% (130 of 139); positive predictive value, 95% (161 of 170); and negative predictive value, 100% (130 of 130). Conclusions: For outpatients with acute bronchitis, an electronic algorithm for identification of inappropriate antibiotic prescribing is highly accurate. This algorithm could be used to efficiently assess prescribing among practices and individual clinicians. The impact of interventions based on this algorithm should be tested in future studies.Funding: NoneDisclosures: None

scholarly journals 23. Regional Variation in Outpatient Antibiotic Prescribing in a Commercially-insured Population, United States, 2017

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S12-S12
Author(s):  
Destani J Bizune ◽  
Danielle Palms ◽  
Laura M King ◽  
Monina Bartoces ◽  
Ruth Link-Gelles ◽  
...  
Keyword(s):  
United States ◽  
Otitis Media ◽  
Acute Otitis Media ◽  
Urgent Care ◽  
Antibiotic Prescribing ◽  
Tier 2 ◽  
Regional Variability ◽  
Patient Age ◽  
Patient Âgé ◽  
Tier 3

Abstract Background Studies have shown that the Southern United States has higher rates of outpatient antibiotic prescribing compared to other regions in the country, but reasons for this variation are unclear. We aimed to determine whether the regional variability in outpatient antibiotic prescribing for respiratory diagnoses can be explained by differences in patient age, care setting, comorbidities, and diagnosis in a commercially-insured population. Methods We analyzed the 2017 IBM® MarketScan® Commercial Database of commercially-insured individuals aged &lt; 65 years. We included visits with acute respiratory tract infection (ARTI) diagnoses from retail clinics, urgent care centers, emergency departments, and physician offices. ARTI diagnoses were categorized as: Tier 1, antibiotics are almost always indicated (pneumonia); Tier 2, antibiotics are sometimes indicated (sinusitis, acute otitis media, pharyngitis); and Tier 3, antibiotics are not indicated (asthma, allergy, bronchitis, bronchiolitis, influenza, nonsuppurative otitis media, viral upper respiratory infections, viral pneumonia). We calculated risk ratios and 95% confidence intervals (CI) stratified by US Census region and ARTI tier using log-binomial models controlling for patient age, comorbidities (Elixhauser and Complex Chronic Conditions for Children), and setting of care, with Tier 3 visits in the West, the strata with the lowest antibiotic prescription rate, as the reference for all strata. Results A total of 100,104,860 visits were analyzed. In multivariable modeling, ARTI visits in the South and Midwest were highly associated with receiving an antibiotic for Tier 2 conditions vs. patients in other regions (Figure 1). Figure 1. Multivariable model comparing risk of receiving an antibiotic for an ARTI by region and diagnostic tier in urgent care, retail health, emergency department, and office visits, MarketScan® 2017, United States Conclusion Regional variability in outpatient antibiotic prescribing for Tier 2 and 3 ARTIs remained even after controlling for patient age, comorbidities, and setting of care. It is likely that this variability is in part due to non-clinical factors such as regional differences in clinicians’ prescribing habits and patient expectations. Targeted and enhanced public health stewardship interventions are needed to address cultural factors that affect antibiotic prescribing in outpatient settings. Disclosures All Authors: No reported disclosures

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