Suchergebnisse

ObjectivesValidation of algorithms to identify health conditions (e.g., diabetes) or service use (e.g., high-cost users) in administrative data is time-consuming and expensive. Many algorithms are only assessed in a single jurisdiction, which may limit generalizability. Our study described the characteristics of multi-jurisdiction algorithms from a Canadian algorithm repository.
ApproachWe summarized algorithms captured in the open-access Algorithms Inventory developed by Health Data Research Network (HDRN) Canada. This inventory contains published algorithms identified through a series of systematic reviews of peer-reviewed research. Algorithms included in the inventory were validated or assessed for feasibility of implementation in two or more provinces/territories; they encompass measures of population health, health service use, and determinants of health. Descriptive statistics were used to characterize the study data on such features as year and discipline of the study journal, algorithm topic area, jurisdictions included in the study, validation source data, and algorithm elements (i.e., diagnosis codes).
ResultsThe HDRN Canada Algorithms Inventory currently contains 166 algorithms from 63 published articles. The majority of articles were published in 2010 or later (89%) and more than half (56%) of the articles were found in journals with a clinical focus. Feasibility studies (79%) were conducted more often than validation studies (21%). Most algorithms used data from the provinces of British Columbia, Manitoba, Ontario, and Nova Scotia. The majority of algorithms (72%) measured population health concepts, such as chronic physical health conditions (63%; e.g., hypertension) and mental health conditions (14%; e.g., depression). Algorithms about the determinants of health (17%) mostly focused on measures of socioeconomic status (37%) derived from census data. Multi-jurisdiction algorithms about health service use were least common (11%).
ConclusionThis synthesis revealed few Canadian multi-jurisdiction validation studies have been conducted and not all provinces/territories are equally represented. New validation studies, particularly about health service use and determinants of health, will increase the consistency and accuracy of Canadian research. Reusing published algorithms from this inventory will facilitate research reproducibility.

IntroductionAdministrative health data capture diagnoses using the International Classification of Diseases (ICD), which has multiple versions over time. To facilitate longitudinal investigations using these data, we aimed to map diagnoses identified in three ICD versions – ICD-8 with adaptations (ICDA-8), ICD-9 with clinical modifications (ICD-9-CM), and ICD-10 with Canadian adaptations (ICD-10-CA) – to mutually exclusive chronic health condition categories adapted from the open source Clinical Classifications Software (CCS).
MethodsWe adapted the CCS crosswalk to 3-digit ICD-9-CM codes for chronic conditions and resolved the one-to-many mappings in ICD-9-CM codes. Using this adapted CCS crosswalk as the reference and referring to existing crosswalks between ICD versions, we extended the mapping to ICDA-8 and ICD-10-CA. Each mapping step was conducted independently by two reviewers and discrepancies were resolved by consensus through deliberation and reference to prior research. We report the frequencies, agreement percentages and 95% confidence intervals (CI) from each step.
ResultsWe identified 354 3-digit ICD-9-CM codes for chronic conditions. Of those, 77 (22%) codes had one-to-many mappings; 36 (10%) codes were mapped to a single CCS category and 41 (12%) codes were mapped to combined CCS categories. In total, the codes were mapped to 130 adapted CCS categories with an agreement percentage of 92% (95% CI: 86%–98%). Then, 321 3-digit ICDA-8 codes were mapped to CCS categories with an agreement percentage of 92% (95% CI: 89%–95%). Finally, 3583 ICD-10-CA codes were mapped to CCS categories; 111 (3%) had a fair or poor mapping quality; these were reviewed to keep or move to another category (agreement percentage=77% [95% CI: 69%–85%]).
ConclusionsWe developed crosswalks for three ICD versions (ICDA-8, ICD-9-CM, and ICD-10-CA) to 130 clinically meaningful categories of chronic health conditions by adapting the CCS classification. These crosswalks will benefit chronic disease studies spanning multiple decades of administrative health data.