title: Leveraging electronic medical records for surveillance of surgical site infection in a total joint replacement population.
abstract: OBJECTIVE
  To evaluate whether a hybrid electronic screening algorithm using a total joint replacement (TJR) registry, electronic surgical site infection (SSI) screening, and electronic health record (EHR) review of SSI is sensitive and specific for SSI detection and reduces chart review volume for SSI surveillance.
  
  
  METHODS
  Validation study.
  
  
  METHODS
  A large health maintenance organization (HMO) with 8.6 million members.
  
  
  METHODS
  Using codes for infection, wound complications, cellullitis, procedures related to infections, and surgeon-reported complications from the International Classification of Diseases, Ninth Revision, Clinical Modification, we screened each TJR procedure performed in our HMO between January 2006 and December 2008 for possible infections. Flagged charts were reviewed by clinical-content experts to confirm SSIs. SSIs identified by the electronic screening algorithm were compared with SSIs identified by the traditional indirect surveillance methodology currently employed in our HMO. Positive predictive values (PPVs), negative predictive values (NPVs), and specificity and sensitivity values were calculated. Absolute reduction of chart review volume was evaluated.
  
  
  RESULTS
  The algorithm identified 4,001 possible SSIs (9.5%) for the 42,173 procedures performed for our TJR patient population. A total of 440 case patients (1.04%) had SSIs (PPV, 11.0%; NPV, 100.0%). The sensitivity and specificity of the overall algorithm were 97.8% and 91.5%, respectively.
  
  
  CONCLUSIONS
  An electronic screening algorithm combined with an electronic health record review of flagged cases can be used as a valid source for TJR SSI surveillance. The algorithm successfully reduced the volume of chart review for surveillance by 90.5%.
authors: Surgical Outcomes and Analysis Unit of Clinical Analysis, Kaiser Permanente, San Diego, California 92109, USA. maria.cs.inacio@kp.org
authors: Maria C S
authors: MC
authors: Inacio
authors: Elizabeth W
authors: EW
authors: Paxton
authors: Yuexin
authors: Y
authors: Chen
authors: Jessica
authors: J
authors: Harris
authors: Enid
authors: E
authors: Eck
authors: Sue
authors: S
authors: Barnes
authors: Robert S
authors: RS
authors: Namba
authors: Christopher F
authors: CF
authors: Ake
mesh_terms: D000465:Algorithms; D019644:Arthroplasty, Replacement, Hip / Q000009:adverse effects* / Q000706:statistics & numerical data; D019645:Arthroplasty, Replacement, Knee / Q000009:adverse effects* / Q000706:statistics & numerical data; D002140:California / Q000453:epidemiology; D057286:Electronic Health Records / Q000706:statistics & numerical data*; D005188:False Negative Reactions; D005189:False Positive Reactions; D006801:Humans; D011159:Population Surveillance / Q000379:methods*; D011237:Predictive Value of Tests; D012042:Registries / Q000706:statistics & numerical data*; D013530:Surgical Wound Infection / Q000453:epidemiology* / Q000209:etiology