Christine Baumgartner1, Alan S Go2, Dongjie Fan3, Sue Hee Sung4, Daniel M Witt5, John R Schmelzer6, Marc S Williams7, Steven H Yale8, Jeffrey J VanWormer9, Margaret C Fang10. 1. Department of General Internal Medicine, Inselspital, Bern University Hospital, University of Bern, Freiburgstrasse, CH-3010 Bern, Switzerland; University of California, San Francisco, 533 Parnassus Ave., Box 0131, room U135, San Francisco, CA 94143, United States of America.. Electronic address: christine.baumgartner@insel.ch. 2. Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA 94612-2304, United States of America; Departments of Epidemiology, Biostatistics and Medicine, University of California, San Francisco, United States of America; Departments of Medicine, Health Research and Policy, Stanford University School of Medicine, Palo Alto, CA, United States of America. Electronic address: Alan.S.Go@kp.org. 3. Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA 94612-2304, United States of America. Electronic address: Dongjie.J.Fan@kp.org. 4. Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA 94612-2304, United States of America. Electronic address: sue.hee.sung@kp.org. 5. Department of Pharmacotherapy, University of Utah College of Pharmacy, 30 South 2000 East, Salt Lake City, UT 84112, United States of America. Electronic address: dan.witt@pharm.utah.edu. 6. Marshfield Clinic Research Institute, 1000 North Oak Ave., Marshfield, WI 54449, United States of America. Electronic address: Schmelzer.John@marshfieldresearch.org. 7. Genomic Medicine Institute, Geisinger, 100 N Academy Ave. Danville, PA 17822-2620, United States of America. Electronic address: mswilliams1@geisinger.edu. 8. Department of Medicine, University of Central Florida College of Medicine, 6850 Lake Nona Blvd., Orlando, FL 32827, United States of America. Electronic address: Steven.Yale.md@gmail.com. 9. Marshfield Clinic Research Institute, 1000 North Oak Ave., Marshfield, WI 54449, United States of America. Electronic address: vanwormer.jeffrey@marshfieldresearch.org. 10. University of California, San Francisco, 533 Parnassus Ave., Box 0131, room U135, San Francisco, CA 94143, United States of America.. Electronic address: Margaret.Fang@ucsf.edu.
Abstract
BACKGROUND: Studies using administrative data commonly rely on diagnosis codes to identify venous thromboembolism (VTE) events. Our objective was to assess the validity of using International Classification of Disease, 9th Revision (ICD-9) codes in identifying recurrent VTE. MATERIALS AND METHODS: Among 5497 adults with confirmed incident VTE from four healthcare delivery systems in the Cardiovascular Research Network (CVRN), we identified all subsequent inpatient, emergency department (ED), and ambulatory clinical encounters associated with an ICD-9 code for VTE (combined with relevant radiology procedure codes for inpatient/ED VTE codes in the secondary discharge position or outpatient codes) during the follow-up period. Medical records were reviewed using standardized diagnostic criteria to assess for the presence of new, recurrent VTE. The positive predictive value (PPV) of codes was calculated as the number of valid events divided by total encounters. RESULTS: We identified 2397 encounters that were considered potential recurrent VTE by ICD-9 codes. However, only 31.1% (95%CI: 29.3-33.0%) of encounters were verified by reviewers as true recurrent VTE. Hospital or ED encounters with VTE codes in the primary position were more likely to represent valid recurrent VTE (PPV 61.3%, 95%CI: 56.7-66.3%) than codes in secondary positions (PPV 35.4%, 95%CI: 31.9-39.3%), or outpatient codes (PPV 20.3%, 95%CI: 18.3-22.5%). PPV was low for all VTE types (29.9% for pulmonary embolism, 38.3% for lower and 37.7% for upper extremity deep venous thrombosis, and 14.1% for other VTE). CONCLUSIONS: ICD-9 codes do not accurately identify new VTE events in patients with a prior history of VTE.
BACKGROUND: Studies using administrative data commonly rely on diagnosis codes to identify venous thromboembolism (VTE) events. Our objective was to assess the validity of using International Classification of Disease, 9th Revision (ICD-9) codes in identifying recurrent VTE. MATERIALS AND METHODS: Among 5497 adults with confirmed incident VTE from four healthcare delivery systems in the Cardiovascular Research Network (CVRN), we identified all subsequent inpatient, emergency department (ED), and ambulatory clinical encounters associated with an ICD-9 code for VTE (combined with relevant radiology procedure codes for inpatient/ED VTE codes in the secondary discharge position or outpatient codes) during the follow-up period. Medical records were reviewed using standardized diagnostic criteria to assess for the presence of new, recurrent VTE. The positive predictive value (PPV) of codes was calculated as the number of valid events divided by total encounters. RESULTS: We identified 2397 encounters that were considered potential recurrent VTE by ICD-9 codes. However, only 31.1% (95%CI: 29.3-33.0%) of encounters were verified by reviewers as true recurrent VTE. Hospital or ED encounters with VTE codes in the primary position were more likely to represent valid recurrent VTE (PPV 61.3%, 95%CI: 56.7-66.3%) than codes in secondary positions (PPV 35.4%, 95%CI: 31.9-39.3%), or outpatient codes (PPV 20.3%, 95%CI: 18.3-22.5%). PPV was low for all VTE types (29.9% for pulmonary embolism, 38.3% for lower and 37.7% for upper extremity deep venous thrombosis, and 14.1% for other VTE). CONCLUSIONS: ICD-9 codes do not accurately identify new VTE events in patients with a prior history of VTE.
Keywords:
Deep vein thrombosis; Electronic health record; International Classification of Diseases, 9th Revision; Pulmonary embolism; Venous thromboembolism
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