A METHOD FOR IDENTIFYING PATIENTS WITH CHRONIC ANGINA FROM ADMINISTRATIVE CLAIMS DATA
Author(s)
Watson JB1, Lee DW2, Kadlubek PJ2, Haberman M2, Goldberg GA2, 1 CV Therapeutics, Palo Alto, CA, USA; 2 Constella Health Strategies, Herndon, VA, USA
OBJECTIVE: Administrative claims data are widely used to study disease treatment patterns and costs. A valid, claims-based definition method is needed to identify patients with chronic angina (CA) from these data. METHODS: Five cardiologists and one internist with claims-coding expertise developed an initial series of increasingly specific, claims-based definitions of CA. Claims data from 2001 to 2002 were used to determine the number and demographic characteristics of patients who met these criteria. This information was used to determine a final definition for patients with CA that has acceptable levels of qualitatively assessed sensitivity and specificity. RESULTS: The panel reviewed relative patient count and demographic information and developed the following claims-based definition for CA: Patients aged °Ý 35 years who were: a) diagnosed at least twice with CA (ICD-9-CM codes 413.xx) and filled two nitrate, beta-blocker or calcium channel blocker prescriptions with at least 30 days between prescriptions; b) filled two nitrate prescriptions, were diagnosed with chest pain (ICD-9-CM 786.50, 786.51 or 786.59), and were either diagnosed with coronary artery disease (CAD) or had a CAD-related procedure; or c) filled two nitrate prescriptions with at least 30 days between prescriptions, were diagnosed with CAD and had one CA claim. CONCLUSION: Patients with CA can be identified from administrative claims data with different levels of specificity and sensitivity. More studies are needed to confirm criteria validity of these criteria and to examine the clinical and economic impact of CA in contemporary medical practice.
Conference/Value in Health Info
2004-10, ISPOR Europe 2004, Hamburg, Germany
Value in Health, Vol. 7, No. 6 (November/December 2004)
Code
PCV74
Topic
Real World Data & Information Systems
Topic Subcategory
Health & Insurance Records Systems
Disease
Cardiovascular Disorders