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Category Archives: Multimorbidity methods

Assessing and measuring chronic multimorbidity in the older population

By Amaia Calderón-Larrañaga and Davide L Vetrano
Multimorbidity is one of the main challenges facing health systems worldwide. While its definition as “the simultaneous presence of two or more chronic diseases” is well established, its operationalization is not yet agreed. This study aimed to provide a clinically-driven comprehensive list of chronic conditions to be included when measuring multimorbidity.
Based on a consensus definition of chronic disease, all codes from the International Classification of Diseases 10th revision (ICD-10) were classified as chronic or not by an international team of physicians and epidemiologists specialized in geriatrics and family medicine, and were subsequently grouped into broader categories. Last, we showed proof of concept by applying the classification to older adults from the Swedish National study of Aging and Care in Kungsholmen (SNAC-K).
An initial number of 918 chronic ICD-10 codes were identified and grouped into 60 chronic disease categories. In SNAC-K, 88.6% had ≥2 of these 60 disease categories, 73.2% had ≥3, and 55.8% had ≥4. Once validated, this operational measure of multimorbidity may enable the advancement and evolution of conceptual and theoretical aspects of multimorbidity that will eventually lead to better care.
The publication can be found in the following link:

Methods for identifying 30 chronic conditions: application to administrative data

By Marcello Tonelli

From a list of 40 common chronic conditions, we identified validated algorithms that use ICD-9 CM/ICD-10 data for 30 of these [1]. Algorithms with both positive predictive value and sensitivity ≥70% were graded as “high validity”; those with positive predictive value ≥70% and sensitivity <70% were graded as “moderate validity”. Of the 40 morbidities, we identified 30 that could be identified with high to moderate validity. We then applied the algorithms to a large cohort of Alberta residents to show proof of concept. In our opinion, using a standard set of algorithms could facilitate the study and surveillance of multimorbidity across jurisdictions. We encourage other groups to consider using this scheme in their studies.

1. Marcello Tonelli et al. Methods for identifying 30 chronic conditions: application to administrative data. BMC Medical Informatics and Decision Making. 2015;15:31.