title: Data-driven approach for assessing utility of medical tests using electronic medical records.
abstract: OBJECTIVE
  To precisely define the utility of tests in a clinical pathway through data-driven analysis of the electronic medical record (EMR).
  
  
  METHODS
  The information content was defined in terms of the entropy of the expected value of the test related to a given outcome. A kernel density classifier was used to estimate the necessary distributions. To validate the method, we used data from the EMR of the gastrointestinal department at a university hospital. Blood tests from patients undergoing surgery for gastrointestinal surgery were analyzed with respect to second surgery within 30 days of the index surgery.
  
  
  RESULTS
  The information content is clearly reflected in the patient pathway for certain combinations of tests and outcomes. C-reactive protein tests coupled to anastomosis leakage, a severe complication show a clear pattern of information gain through the patient trajectory, where the greatest gain from the test is 3-4 days post index surgery.
  
  
  CONCLUSIONS
  We have defined the information content in a data-driven and information theoretic way such that the utility of a test can be precisely defined. The results reflect clinical knowledge. In the case we used the tests carry little negative impact. The general approach can be expanded to cases that carry a substantial negative impact, such as in certain radiological techniques.
authors.affiliation: Norwegian Centre for Integrated Care and Telemedicine, University Hospital of North Norway, Tromsø, Norway; IBM Thomas J. Watson Research Center, Yorktown Heights, New York, USA. Electronic address: stein.olav.skrovseth@telemed.no.
authors.forename: Stein Olav
authors.initials: SO
authors.lastname: Skrøvseth
authors.affiliation: Norwegian Centre for Integrated Care and Telemedicine, University Hospital of North Norway, Tromsø, Norway; Department of Gastrointestinal Surgery, University Hospital of North Norway, Tromsø, Norway; Department of Surgery, University Hospitals Case Medical Center, Case Western Reserve University, Cleveland, OH, USA.
authors.forename: Knut Magne
authors.initials: KM
authors.lastname: Augestad
authors.affiliation: IBM Thomas J. Watson Research Center, Yorktown Heights, New York, USA.
authors.forename: Shahram
authors.initials: S
authors.lastname: Ebadollahi
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D000714:Anastomosis, Surgical; D001005:Anus Neoplasms / Q000601:surgery; D002097:C-Reactive Protein / Q000378:metabolism; D003110:Colonic Neoplasms / Q000601:surgery; D013505:Digestive System Surgical Procedures; D057286:Electronic Health Records; D005260:Female; D005767:Gastrointestinal Diseases / Q000097:blood; D006403:Hematologic Tests; D006801:Humans; D008297:Male; D008490:Medical Informatics / Q000379:methods*; D008875:Middle Aged; D012004:Rectal Neoplasms / Q000601:surgery; D013997:Time Factors; D055815:Young Adult
chemical_list: D002097:C-Reactive Protein
keywords: Colorectal surgery; Electronic medical records; Information theory; Medical informatics; Pattern recognition