Identification of in-hospital complications from claims data. Is it valid?

Med Care. 2000 Aug;38(8):785-95. doi: 10.1097/00005650-200008000-00003.


Objectives: This study examined the validity of the Complications Screening Program (CSP) by testing whether (1) ICD-9-CM codes used to identify a complication are coded completely and accurately and (2) the CSP algorithm successfully separates conditions present on admission from those occurring in the hospital.

Methods: We compared diagnosis and procedure codes contained in the Medicare claim with codes abstracted from an independent re-review of more than 1,200 medical records from Connecticut and California.

Results: Eighty-nine percent of the surgical cases and 84% of the medical cases had their CSP trigger codes corroborated by re-review of the medical record. For 13% of the surgical cases and 58% of the medical cases, the condition represented by the code was judged to be present on admission rather than occurring in-hospital. The positive predictive value of the claim was greater than 80% for the surgical risk pool, suggesting the value of the CSP as a screening tool.

Conclusions: The CSP has validity as a screen for most surgical complications but only for 1 medical complication. The CSP does not have validity as a "stand-alone" tool to identify more than a few in-hospital surgery-related events. The addition of an indicator to the Medicare claim to capture the timing of secondary diagnoses would improve the validity of the CSP for identifying both surgical and medical in-hospital events.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Aged
  • California / epidemiology
  • Connecticut / epidemiology
  • Female
  • Hospitals / standards*
  • Humans
  • Iatrogenic Disease*
  • Insurance Claim Review / classification*
  • Male
  • Medical Audit / methods*
  • Medical Records / classification
  • Medicare / standards
  • Patient Discharge
  • Postoperative Complications / classification
  • Postoperative Complications / epidemiology
  • Professional Review Organizations
  • Quality Indicators, Health Care / classification*
  • Reproducibility of Results
  • Risk Factors
  • United States