Canadian Data Platform: Developing an Algorithm Inventory for Health and Social Measures

IntroductionThe SPOR (Strategy for Patient-Oriented Research) Canadian Data Platform aims to facilitate multi-jurisdictional research through a variety of activities, including the development of standardized algorithms for health conditions, health service use, and the determinants of health. An initial step towards standardization was to identify existing health measures that have been validated or assessed for feasibility of implementation in multi-jurisdictional research, document features of these measures, and describe the methods used to validate or assess feasibility.\r\nObjectives and ApproachWe constructed an inventory of published algorithms to measure population health, health services use, and the determinants of health. A systematic review of published literature identified algorithms from validation or feasibility studies in two or more Canadian provinces/territories. The search strategy was applied to Medline, Embase, and Scopus. The Algorithms and Harmonized Data Working Group of the Canadian Data Platform identified relevant fields for data extraction, including study type, population characteristics, data source, jurisdictions, and algorithm details. A searchable online resource was created to maintain and share the algorithms.\r\nResultsOf the 2758 articles retrieved, 1998 articles underwent title and abstract review and 60 articles were selected for full review. A total of 8 validation and 26 feasibility studies were assessed; they contributed over 140 algorithms. Chronic physical health conditions, such as diabetes, depression, hypertension and dementia, were most often represented in the algorithms. British Columbia and Manitoba were the jurisdictions most frequently represented in the studies. Methods to facilitate automated searching of the on-line resource are under development.\r\nConclusion / ImplicationsOur inventory of algorithms provides valuable information for researchers interested in conducting multi-jurisdictional studies, and reveals gaps where further algorithm development could be undertaken. This comprehensive collection of existing algorithms will support future studies aimed at improving population health and monitoring health service use in Canada.