ArticlePaediatrics & child health2025
Development of a medical chart extraction tool to identify children with medical complexity in the Maritime Provinces of Canada.
Article in Paediatrics & child health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
16 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: Children with medical complexity (CMC) are a population in need of policy and practice reform within the Canadian healthcare system. They are generally characterized as sharing four predominant characteristics: (1) one or more complex chronic condition(s), (2) functional limitations, (3) high health resources use, and (4) family-identified needs. There is currently no standard method to identify the CMC population in Canada. The aim of this research was to establish a clear method to select the best way to identify this population. This was done by developing a medical chart extraction tool specific to the Maritimes' population of CMC. Methods: This study was conducted in the Canadian Maritimes. The work was conducted in two phases; first, a consensus meeting was held to develop a Maritime-specific conceptual definition with a multidisciplinary group of experts. Second, a smaller expert team used the Maritime-specific definition to co-design a medical chart extraction tool. Ethical approval for this project was granted by IWK Health. Results: The consensus meeting involved a total of 57 relevant stakeholders from all three Maritime provinces. The definition developed through consensus included four constructs (functional limitations, chronic disease, health care use, and family-identified needs) and 12 descriptors (2 to 5 per construct). The medical chart extraction tool queried 22 items and 84 sub-items. Conclusions: The consensus process developed a strong and comprehensive medical chart extraction tool that can be applied to select the best-fit method for identifying CMC at a population level.
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