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Context: Naturally occurring retirement communities (NORCs) are unplanned communities with a high proportion of older residents. Mapping NORCs and understanding their unique sociodemographic characteristics and health utilization patterns can assist primary care teams in supporting older adults by: i) identifying geographical areas of high service need and, ii) developing neighborhood based programs. Study Design and Analysis Observational Design: Descriptive analysis identifying proportions of communities in the province of Ontario, Canada with [greater than or equal to] 40% of persons with >55 years of age (NORCs) and the sociodemographic characteristics (e.g., Ontario Marginalization Index), health utilization and primary care enrollment models were displayed in a series of maps. Maps offered a visual presentation of provincial patterns of high density of older adults . The forward sortation areas, geographical units based on the first 3 characters of the Canadian postal code, from the 2016 census year were used. Dataset: Linked administrative data at ICES, an independent, non-profit research institute that routinely collects sociodemographic and healthcare information for the residents in Ontario, Canada. Population: All resident of Ontario >55 years of age as of March 31, 2021 (N=4,663,813). Intervention/Instrument: Maps to depict the distribution of NORCs and the patterns of health. Outcome Measure: Geographical patterns of NORCs in Ontario, Canada. Results: The regional distribution of NORCs varies across the province, with a greater number of NORCs identified in the Eastern and Northern regions of Ontario. The majority of NORCs had high proportion of older adults enrolled in team based models of primary care. Patterns of health use and frailty varied across the province. Conclusions: This is the first known study to map health use and primary care enrollment in NORCs in a province and highlights the complex and varied patterns of regional distribution. Mapping NORCs is an important resource for decision makers and planners to leverage primary care in supporting older adults to age in their communities., Presenters Eliot Frymire, MA, BEd, Vincent DePaul, Peter Gozdyra, MA, Paul Nguyen, PhD, Catherine Donnelly, [...]

This paper presents the main findings from a collaborative community/university research project in Canada. The goal of the project was to improve access to community health information, and in so doing, enhance our knowledge of the development of community health information resources and community/university collaboration. The project built on a rich history of community/university collaboration in Southeast Toronto (SETO), and employed an interdisciplinary applied research and action design. Specific project objectives were to: (1) develop via active community/university collaboration a geographic information system (GIS) for ready access to routinely collected health data, and to study logistical, conceptual and technical problems encountered during system development; and (2) to document and analyze issues that can emerge in the process of community/university research collaboration. System development involved iteration through community user assessment of need, development or refinement of the GIS, and assessment of the GIS by community users. Collaborative process assessment entailed analysis of archival material, interviews with investigators and participant observation. Over the course of the project, a system was successfully developed, and favorably assessed by users. System development problems fell into four main areas: maintaining user involvement in system development, understanding and integrating data, bringing disparate data sources together, and making use of assembled data. Major themes emerging from the community/university collaborative research process included separate community and university cultures, time as an important issue for all involved, and the impact of uncertainty and ambiguity on the collaborative process. Keywords: Community health; Research collaboration; Community/university partnership; Interdisciplinary; Geographic information systems; Medical informatics; Canada