Am J Cardiovasc Dis 2012;2(3):184-191
Original Article
Choices in the use of ICD-9 codes to identify stroke risk factors can affect
the apparent population-level risk factor prevalence and distribution of
CHADS2 scores
James A Rothendler, Adam J Rose, Joel I Reisman, Dan R Berlowitz, Lewis E Kazis
Center for Health Quality, Outcomes and Economic Research, Health Services Research and Development, Bedford VA
Medical Center, Bedford, MA, USA; Department of Health Policy and Management, Boston University School of Public
Health, Boston, MA, USA; Department of Medicine, Section of General Internal Medicine, Boston University School of
Medicine, Boston, MA, USA
Received May 18, 2012; Accepted June 10, 2012; Epub July 25, 2012; Published August 15, 2012
Abstract: While developed for managing individuals with atrial fibrillation, risk stratification schemes for stroke, such as
CHADS2, may be useful in population-based studies, including those assessing process of care. We investigated how
certain decisions in identifying diagnoses from administrative data affect the apparent prevalence of CHADS2-associated
diagnoses and distribution of scores. Two sets of ICD-9 codes (more restrictive/ more inclusive) were defined for each
CHADS2-associated diagnosis. For stroke/transient ischemic attack (TIA), the more restrictive set was applied to only
inpatient data. We varied the number of years (1-3) in searching for relevant codes, and, except for stroke/TIA, the number
of instances (1 vs. 2) that diagnoses were required to appear. The impact of choices on apparent disease prevalence
varied by type of choice and condition, but was often substantial. Choices resulting in substantial changes in prevalence
also tended to be associated with more substantial effects on the distribution of CHADS2 scores. (AJCD1205003)
Keywords: Stroke, atrial fibrillation, risk stratification, CHADS2, ICD-9-CM codes
Address all correspondence to:
Dr. Lewis E Kazis
Pharmaceutical Effectiveness Program
Center for Health Quality
Outcomes and Economic Research (CHQOER)
200 Springs Rd. (152), Building 70
Bedford, MA 01730-1114, USA.
Tel: 781-687-2860
E-mail: lek@bu.edu
Original Article
Choices in the use of ICD-9 codes to identify stroke risk factors can affect
the apparent population-level risk factor prevalence and distribution of
CHADS2 scores
James A Rothendler, Adam J Rose, Joel I Reisman, Dan R Berlowitz, Lewis E Kazis
Center for Health Quality, Outcomes and Economic Research, Health Services Research and Development, Bedford VA
Medical Center, Bedford, MA, USA; Department of Health Policy and Management, Boston University School of Public
Health, Boston, MA, USA; Department of Medicine, Section of General Internal Medicine, Boston University School of
Medicine, Boston, MA, USA
Received May 18, 2012; Accepted June 10, 2012; Epub July 25, 2012; Published August 15, 2012
Abstract: While developed for managing individuals with atrial fibrillation, risk stratification schemes for stroke, such as
CHADS2, may be useful in population-based studies, including those assessing process of care. We investigated how
certain decisions in identifying diagnoses from administrative data affect the apparent prevalence of CHADS2-associated
diagnoses and distribution of scores. Two sets of ICD-9 codes (more restrictive/ more inclusive) were defined for each
CHADS2-associated diagnosis. For stroke/transient ischemic attack (TIA), the more restrictive set was applied to only
inpatient data. We varied the number of years (1-3) in searching for relevant codes, and, except for stroke/TIA, the number
of instances (1 vs. 2) that diagnoses were required to appear. The impact of choices on apparent disease prevalence
varied by type of choice and condition, but was often substantial. Choices resulting in substantial changes in prevalence
also tended to be associated with more substantial effects on the distribution of CHADS2 scores. (AJCD1205003)
Keywords: Stroke, atrial fibrillation, risk stratification, CHADS2, ICD-9-CM codes
Address all correspondence to:
Dr. Lewis E Kazis
Pharmaceutical Effectiveness Program
Center for Health Quality
Outcomes and Economic Research (CHQOER)
200 Springs Rd. (152), Building 70
Bedford, MA 01730-1114, USA.
Tel: 781-687-2860
E-mail: lek@bu.edu
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