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.
- geriatric medicine
- health services administration & management
- statistics & research methods
ASJC Scopus subject areas