title: [Predictive Bayesian network model using electronic patient records for prevention of hospital-acquired pressure ulcers].
abstract: OBJECTIVE
  The study was designed to determine the discriminating ability of a Bayesian network (BN) for predicting risk for pressure ulcers.
  
  
  METHODS
  Analysis was done using a retrospective cohort, nursing records representing 21,114 hospital days, 3,348 patients at risk for ulcers, admitted to the intensive care unit of a tertiary teaching hospital between January 2004 and January 2007. A BN model and two logistic regression (LR) versions, model-I and -II, were compared, varying the nature, number and quality of input variables. Classification competence and case coverage of the models were tested and compared using a threefold cross validation method.
  
  
  RESULTS
  Average incidence of ulcers was 6.12%. Of the two LR models, model-I demonstrated better indexes of statistical model fits. The BN model had a sensitivity of 81.95%, specificity of 75.63%, positive and negative predictive values of 35.62% and 96.22% respectively. The area under the receiver operating characteristic (AUROC) was 85.01% implying moderate to good overall performance, which was similar to LR model-I. However, regarding case coverage, the BN model was 100% compared to 15.88% of LR.
  
  
  CONCLUSIONS
  Discriminating ability of the BN model was found to be acceptable and case coverage proved to be excellent for clinical use.
authors.affiliation: Department of Nursing, Inha University, Incheon, Korea. insook.cho@inha.ac.kr
authors.forename: In Sook
authors.initials: IS
authors.lastname: Cho
authors.forename: Eunja
authors.initials: E
authors.lastname: Chung
mesh_terms: D000328:Adult; D000368:Aged; D019540:Area Under Curve; D001499:Bayes Theorem; D015331:Cohort Studies; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008499:Medical Records; D008875:Middle Aged; D011237:Predictive Value of Tests; D003668:Pressure Ulcer / Q000453:epidemiology / Q000517:prevention & control*; D012189:Retrospective Studies; D018570:Risk Assessment