Assessing surgical quality using administrative and clinical data sets: A direct comparison of the university healthsystem consortium clinical database and the national surgical quality improvement program data set

Daniel L. Davenport, Clyde W. Holsapple, Joseph Conigliaro

Research output: Contribution to journalArticlepeer-review

119 Scopus citations

Abstract

The use of "clinical" versus "administrative" data sets for health care quality assessment continues to be debated. This study directly compares the University HealthSystem Consortium Clinical Database (UHC CDB) and the National Surgical Quality Improvement Program (NSQIP) in terms of their assessment of complications and death for 26 322 surgery patients using analyses of variance, correlation, and multivariable logistic regression. The NSQIP had more variables with significant correlation with outcomes. The NSQIP was better at predicting death (c-index 0.94 vs 0.90, <.05) and complications (c-index 0.78 vs 0.76, P<=.07), especially for higher risk patients. The UHC CDB missed and misclassified several major complications. The data sets are similar in their explanatory power relative to outcomes, but the clinical data set is better, particularly at identifying higher risk patients and specific complications. It should prove more useful for initiating and monitoring clinical process improvements because of more clinically relevant variables.

Original languageEnglish
Pages (from-to)395-402
Number of pages8
JournalAmerican Journal of Medical Quality
Volume24
Issue number5
DOIs
StatePublished - Sep 10 2009

Keywords

  • Contextual data quality
  • National Surgical Quality Improvement Program
  • Surgical morbidity and mortality
  • Surgical quality assessment
  • University HealthSystem Consortium

ASJC Scopus subject areas

  • Health Policy

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