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

BMJ 2019; 364 doi: (Published 16 January 2019) Cite this as: BMJ 2019;364:k5092

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The challenges of developing healthcare quality measures based on ICD-10-CM codes

  1. Kao-Ping Chua, assistant professor of pediatrics1,
  2. Michael A Fischer, associate professor of medicine2,
  3. Jeffrey A Linder, professor of medicine3
  1. 1Department of Pediatrics, Child Health Evaluation and Research Center, University of Michigan Medical School, 300 N Ingalls Street, SPC 5456 Room 6E18, Ann Arbor, MI 48109-5456, USA
  2. 2Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
  3. 3Division of General Internal Medicine and Geriatrics, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
  1. Correspondence to: K-P Chua chuak{at} (or @kaopingchua on Twitter)
  • Accepted 13 November 2018


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.


  • Contributors: KC, MAF, and JAL conceived and designed the study. KC acquired the data. KC, MAF, and JAL analyzed and interpreted the data. KC drafted the manuscript. KC, MAF, and JAL critically revised the manuscript for important intellectual content. KC was responsible for the statistical analysis. JAL supervised the study. KC is the guarantor. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted.

  • Funding: JAL and MAF are supported by a grant from the Agency for Healthcare Research and Quality (R01HS024930). JAL is supported by a contract from the Agency for Healthcare Research and Quality (HHSP233201500020I). The funding source played no role in the design of the study; the collection, analysis, and interpretation of the data; and the decision to approve publication of the finished manuscript.

  • Competing interests: All authors have completed the ICMJE uniform disclosure form at and declare: no support from any organization for the submitted work; no financial relationships with any organizations that might have an interest in the submitted work in the previous three years; and no other relationships or activities that could appear to have influenced the submitted work.

  • Ethical approval: Owing to the use of deidentified data, the institutional review board of the University of Michigan Medical School exempted this study from human subjects review.

  • Data sharing: Programming code is available from the corresponding author at The data used in this study are proprietary and cannot be shared.

  • Transparency: The lead author (KC) affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned (and, if relevant, registered) have been explained.

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