title: Assessment of algorithms to identify patients with thrombophilia following venous thromboembolism.
abstract: BACKGROUND
  Routine testing for thrombophilia following venous thromboembolism (VTE) is controversial. The use of large datasets to study the clinical impact of thrombophilia testing on patterns of care and patient outcomes may enable more efficient analysis of this practice in a wide range of settings. We set out to examine how accurately algorithms using International Classification of Diseases 9th Revision (ICD-9) codes and/or pharmacy data reflect laboratory-confirmed thrombophilia diagnoses.
  
  
  METHODS
  A random sample of adult Kaiser Permanente Colorado patients diagnosed with unprovoked VTE between 1/2004 and 12/2010 underwent medical record abstraction of thrombophilia test results. Algorithms using "ICD-9" (positive if a thrombophilia ICD-9 code was present), "Extended anticoagulation (AC)" (positive if AC therapy duration was >6 months), and "ICD-9 & Extended AC" (positive for both) criteria to identify possible thrombophilia cases were tested. Using positive thrombophilia laboratory results as the gold standard, the sensitivity, specificity, positive predictive value (PPV), and negative predictive value of each algorithm were calculated, along with 95% confidence intervals (CIs).
  
  
  RESULTS
  In our cohort of 636 patients, sensitivities were low (<50%) for each algorithm. "ICD-9" yielded the highest PPV (41.5%, 95% CI 26.3-57.9%) and a high specificity (95.9%, 95% CI 94.0-97.4%). "Extended AC" had the highest sensitivity but lowest specificity, and "ICD-9 & Extended AC" had the highest specificity but lowest sensitivity.
  
  
  CONCLUSIONS
  ICD-9 codes for thrombophilia are highly specific for laboratory-confirmed cases, but all algorithms had low sensitivities. Further development of methods to identify thrombophilia patients in large datasets is warranted.
authors.affiliation: Department of Clinical Pharmacy, Kaiser Permanente Colorado, 16601 East Centretech Parkway, Aurora, CO 80011, USA; Department of Pharmacy, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado, Denver, 12850 East Montview Boulevard, Aurora, CO 80045, USA. Electronic address: tom.delate@kp.org.
authors.forename: Thomas
authors.initials: T
authors.lastname: Delate
authors.affiliation: Keck School of Medicine, University of Southern California, 1975 Zonal Avenue, Los Angeles, CA 90033, USA. Electronic address: wendy.hsiao@usc.edu.
authors.forename: Wendy
authors.initials: W
authors.lastname: Hsiao
authors.affiliation: Division of Hematology/Oncology, Department of Medicine, University of California, 505 Parnassus Avenue, M1286, Box 1270, San Francisco, CA 94143, USA. Electronic address: Benjamin.Kim@ucsf.edu.
authors.forename: Benjamin
authors.initials: B
authors.lastname: Kim
authors.affiliation: Department of Clinical Pharmacy, Kaiser Permanente Colorado, 16601 East Centretech Parkway, Aurora, CO 80011, USA; Department of Pharmacotherapy, University of Utah College of Pharmacy, 30 South 2000 East, Room 4926, Salt Lake City, UT 84112, USA. Electronic address: dan.witt@pharm.utah.edu.
authors.forename: Daniel M
authors.initials: DM
authors.lastname: Witt
authors.affiliation: Department of Clinical Pharmacy, Kaiser Permanente Colorado, 16601 East Centretech Parkway, Aurora, CO 80011, USA. Electronic address: melissa.r.meyer@kp.org.
authors.forename: Melissa R
authors.initials: MR
authors.lastname: Meyer
authors.affiliation: Division of Research, Kaiser Permanente of Northern California, 2000 Broadway, Oakland, CA 94612, USA; Departments of Epidemiology, Biostatistics, and Medicine, University of California, 550 16th Street, 2nd floor, San Francisco, CA 94158, USA; Department of Health Research and Policy, Stanford University School of Medicine, 150 Governor's Lane, Stanford, CA 94305, USA. Electronic address: Alan.S.Go@nsmtp.kp.org.
authors.forename: Alan S
authors.initials: AS
authors.lastname: Go
authors.affiliation: Division of Hospital Medicine, Department of Medicine, University of California, 533 Parnassus Avenue, Box 0131, Room U135, San Francisco, CA 94143, USA. Electronic address: mfang@medicine.ucsf.edu.
authors.forename: Margaret C
authors.initials: MC
authors.lastname: Fang
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D000925:Anticoagulants / Q000008:administration & dosage; D001780:Blood Coagulation Tests / Q000706:statistics & numerical data*; D003120:Colorado / Q000453:epidemiology; D015897:Comorbidity; D020000:Decision Support Systems, Clinical; D003936:Diagnosis, Computer-Assisted / Q000379:methods; D005260:Female; D006801:Humans; D015994:Incidence; D038801:International Classification of Diseases / Q000706:statistics & numerical data*; D008297:Male; D008875:Middle Aged; D015995:Prevalence; D015203:Reproducibility of Results; D018570:Risk Assessment / Q000379:methods; D012680:Sensitivity and Specificity; D019851:Thrombophilia / Q000175:diagnosis* / Q000453:epidemiology / Q000517:prevention & control*; D054556:Venous Thromboembolism / Q000175:diagnosis / Q000453:epidemiology / Q000628:therapy*
chemical_list: D000925:Anticoagulants
keywords: Algorithms; Dataset; Sensitivity; Specificity; Thrombophilia; Venous thromboembolism