title: Quality performance measurement using the text of electronic medical records.
abstract: BACKGROUND
  Annual foot examinations (FE) constitute a critical component of care for diabetes. Documented evidence of FE is central to quality-of-care reporting; however, manual abstraction of electronic medical records (EMR) is slow, expensive, and subject to error. The objective of this study was to test the hypothesis that text mining of the EMR results in ascertaining FE evidence with accuracy comparable to manual abstraction.
  
  
  METHODS
  The text of inpatient and outpatient clinical reports was searched with natural-language (NL) queries for evidence of neurological, vascular, and structural components of FE. A manual medical records audit was used for validation. The reference standard consisted of 3 independent sets used for development (n=200 ), validation (n=118), and reliability (n=80).
  
  
  RESULTS
  The reliability of manual auditing was 91% (95% confidence interval [CI]= 85-97) and was determined by comparing the results of an additional audit to the original audit using the records in the reliability set. The accuracy of the NL query requiring 1 of 3 FE components was 89% (95% CI=83-95). The accuracy of the query requiring any 2 of 3 components was 88% (95% CI=82-94). The accuracy of the query requiring all 3 components was 75% (95% CI= 68- 83).
  
  
  CONCLUSIONS
  The free text of the EMR is a viable source of information necessary for quality of health care reporting on the evidence of FE for patients with diabetes. The low-cost methodology is scalable to monitoring large numbers of patients and can be used to streamline quality-of-care reporting.
authors.affiliation: Department of Pharmaceutical Care and Health Systems, University of Minnesota Rochester, Rochester, MN, USA.
authors.forename: Serguei
authors.initials: S
authors.lastname: Pakhomov
authors.forename: Susan
authors.initials: S
authors.lastname: Bjornsen
authors.forename: Penny
authors.initials: P
authors.lastname: Hanson
authors.forename: Steven
authors.initials: S
authors.lastname: Smith
mesh_terms: D003133:Commission on Professional and Hospital Activities; D017719:Diabetic Foot / Q000175:diagnosis*; D006801:Humans; D016247:Information Storage and Retrieval; D016347:Medical Records Systems, Computerized; D010808:Physical Examination; D019984:Quality Indicators, Health Care