Abstract
OBJECTIVE: To assess the validity of the US Department of Health and Human Services (DHHS) definition of multimorbidity using International Classification of Diseases, ninth edition (ICD-9) codes from administrative data. DESIGN: Cross-sectional comparison of two ICD-9 billing code algorithms to data abstracted from medical records. SETTING: Olmsted County, Minnesota, USA. PARTICIPANTS: An age-stratified and sex-stratified random sample of 1509 persons ages 40-84 years old residing in Olmsted County on 31 December 2010. STUDY MEASURES: Seventeen chronic conditions identified by the US DHHS as important in studies of multimorbidity were identified through medical record review of each participant between 2006 and 2010. ICD-9 administrative billing codes corresponding to the 17 conditions were extracted using the Rochester Epidemiology Project records-linkage system. Persons were classified as having each condition using two algorithms: at least one code or at least two codes separated by more than 30 days. We compared the ICD-9 code algorithms with the diagnoses obtained through medical record review to identify persons with multimorbidity (defined as ≥2, ≥3 or ≥4 chronic conditions). RESULTS: Use of a single code to define each of the 17 chronic conditions resulted in sensitivity and positive predictive values (PPV) ≥70%, and in specificity and negative predictive values (NPV) ≥70% for identifying multimorbidity in the overall study population. PPV and sensitivity were highest in persons 65-84 years of age, whereas NPV and specificity were highest in persons 40-64 years. The results varied by condition, and by age and sex. The use of at least two codes reduced sensitivity, but increased specificity. CONCLUSIONS: The use of a single code to identify each of the 17 chronic conditions may be a simple and valid method to identify persons who meet the DHHS definition of multimorbidity in populations with similar demographic, socioeconomic, and health care characteristics.