Development and Internal Validation of an Emergency Department Admission Intensity Measure Using Data From a National Group

Ann Emerg Med. 2023 Sep;82(3):316-325. doi: 10.1016/j.annemergmed.2022.12.011. Epub 2023 Jan 18.

Abstract

Study objective: We develop and assess variation in an emergency department (ED) admission intensity measure intended for value-based payment models. The measure includes ED diagnoses amenable to evidence-based protocols and where admission decisions vary based on physician discretion.

Methods: Measure International Classification of Diseases (ICD)-10 codes were selected by face validity by 3 emergency physicians using expertise and administrative data. Feedback was sought from a separate technical panel. Using data from a national group (2018 to 2019), we assessed measure stability at the physician and facility level by quarter using descriptive plots, multilevel linear probability models, and intraclass correlation coefficients (ICC).

Results: A total of 535 ICD-10 measure codes were selected from 23,590 codes. Across 127 EDs, facility-quarter admission rates averaged 26.1% (95% confidence interval [CI] 24.5 to 27.7). Between- and within-facility standard deviations were 9.2 (95% CI 8.2 to 10.5) and 2.9 (95% CI 2.7 to 3.0), respectively, with an ICC of 0.91. Most ED-quarters (749/961) fell within 2.5% of their facility's average. Among 2,398 physicians, quarterly rates averaged 29.1% (95% CI 28.6 to 29.6). The between- and within-physician standard deviation was 6.3 (95% CI 6.1 to 6.5) and 5.3 (95% CI 5.3 to 5.4), respectively, with an ICC of 0.58; 220 physicians (9.2%) had an admission rate consistently higher than average and 193 (8.0%) consistently lower.

Conclusion: This set of ICD-10 diagnoses demonstrates face validity and stability for quarterly admission rates at the facility and physician levels. The measure may be useful to monitor facility admission rates in value-based models and reliably identify high and low admitters within facilities to manage admission variation.

MeSH terms

  • Emergency Service, Hospital*
  • Hospitalization
  • Humans
  • International Classification of Diseases
  • Patient Admission
  • Physicians*
  • Retrospective Studies