Suchergebnisse

Family health history is a well-established risk factor for many health conditions but the systematic collection of health histories, particularly for multiple generations and multiple family members, can be challenging. Routinely-collected electronic databases in a select number of sites worldwide offer a powerful tool to conduct multigenerational health research for entire populations. At these sites, administrative and healthcare records are used to construct familial relationships and objectively-measured health histories. We review and synthesize published literature to compare the attributes of routinely-collected, linked databases for three European sites (Denmark, Norway, Sweden) and three non-European sites (Canadian province of Manitoba, Taiwan, Australian state of Western Australia) with the capability to conduct population-based multigenerational health research. Our review found that European sites primarily identified family structures using population registries, whereas non-European sites used health insurance registries (Manitoba and Taiwan) or linked data from multiple sources (Western Australia). Information on familial status was reported to be available as early as 1947 (Sweden); Taiwan had the fewest years of data available (1995 onwards). All centres reported near complete coverage of familial relationships for their population catchment regions. Challenges in working with these data include differentiating biological and legal relationships, establishing accurate familial linkages over time, and accurately identifying health conditions. This review provides important insights about the benefits and challenges of using routinely-collected, population-based linked databases for conducting population-based multigenerational health research, and identifies opportunities for future research within and across the data-intensive environments at these six sites.

IntroductionMajor osteoporotic fractures (MOF) are associated with significant morbidity and healthcare system burden.
Objectives and ApproachWe aimed to determine whether sibling fracture history is associated with MOF risk amongst individuals from a population-based cohort using objectively-ascertained measures of fracture history. This retrospective cohort study used administrative databases from the province of Manitoba, Canada, which has a universal healthcare system. The cohort included individuals aged 40 years and older between 1997 and 2015 with linkage to at least one sibling. The exposure was MOF diagnosis occurring at age 40 years or older in a randomly selected sibling. The outcome was incident clinically-diagnosed MOF (hip, wrist, humerus or spine) identified in hospital and physician records using established case definitions. A multivariable Cox proportional hazards regression was used to test the association of sibling fracture history with the risk of MOF in individuals after adjustment for known fracture risk factors.
ResultsThe cohort included 217,519 individuals; 92% were linked to full siblings (i.e., same mother/father) and 49% were females. During a median follow-up of 11 years (IQR 5 -15), 7274 (3.3%) incident MOF cases were identified. Sibling MOF history was associated with increased risk of MOF (HR 1.71, 95% CI 1.48–1.97). The risk was elevated in both men (HR 1.63, 95% CI 1.29-2.06) and women (HR 1.78, 95% CI 1.48-2.13) but was higher among sisters (HR 2.08, 95% CI 1.65-2.61) compared to brothers (HR 1.67, 95% CI 1.20-2.32). In a secondary analysis of sibling fracture site, the highest risk was observed with diagnosis of wrist followed by spine fractures (HR 1.86, 95% CI 1.57-2.21 and HR 1.46, 95% CI 1.08-1.98, respectively).
ConclusionSibling fracture history is associated with increased MOF risk in individuals and should be considered as a candidate risk factor for improving fracture risk prediction.

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.