Thomas Delate1, Wendy Hsiao2, Benjamin Kim3, Daniel M Witt4, Melissa R Meyer5, Alan S Go6, Margaret C Fang7. 1. 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. 2. Keck School of Medicine, University of Southern California, 1975 Zonal Avenue, Los Angeles, CA 90033, USA. Electronic address: wendy.hsiao@usc.edu. 3. 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. 4. 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. 5. Department of Clinical Pharmacy, Kaiser Permanente Colorado, 16601 East Centretech Parkway, Aurora, CO 80011, USA. Electronic address: melissa.r.meyer@kp.org. 6. 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. 7. 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.
Abstract
INTRODUCTION: 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. MATERIALS AND 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.
INTRODUCTION: 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. MATERIALS AND 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 thrombophiliapatients in large datasets is warranted.
Authors: Clive Kearon; Elie A Akl; Anthony J Comerota; Paolo Prandoni; Henri Bounameaux; Samuel Z Goldhaber; Michael E Nelson; Philip S Wells; Michael K Gould; Francesco Dentali; Mark Crowther; Susan R Kahn Journal: Chest Date: 2012-02 Impact factor: 9.410
Authors: Inna Tsoran; Gleb Saharov; Benjamin Brenner; Manuel Barrón; Valentín Valdés; María de la Roca Toda; Manuel Monreal Journal: Thromb Res Date: 2010-07-11 Impact factor: 3.944