Suchergebnisse

Intro -- Title Page -- Copyright -- Dedication -- Contents -- Introduction -- Chapter 1: Alarm Bells -- Chapter 2: Beyond Robots and Foreigners -- Chapter 3: Not Just Any Jobs -- Chapter 4: Box Jumps and Other Barriers -- Chapter 5: Keep Working Blokes Working -- Chapter 6: (Some) Blue-Collar Jobs of the Future -- Conclusion -- Acknowledgements -- Notes -- Back Cover.

Title Page -- Copyright -- Dedication -- Contents -- Introduction -- Chapter 1 : Work (getting in) -- Chapter 2 : Work (getting on) -- Chapter 3 : Wealth -- Chapter 4 : Debt -- Chapter 5 : Wellbeing -- Chapter 6 : So now what? -- Conclusion -- Acknowledgments -- Notes -- Back Cover

IntroductionDeveloping decision support tools using data from a health care organization, to support care within that organization, is a promising paradigm to improve care delivery and population health. Descriptive epidemiology may be a valuable supplement to stakeholder input towards selection of potential initiatives and to inform methodological decisions throughout tool development. We additionally propose that to properly characterize complex populations in large-scale descriptive studies, both simple statistical and machine learning techniques can be useful.
ObjectiveTo describe sociodemographic, clinical, and health care use characteristics of primary care clients served by the Alliance for Healthier Communities, which provides team-based primary health care through Community Health Centres (CHCs) across Ontario, Canada.
MethodsWe used electronic health record data from adult ongoing primary care clients served by CHCs in 2009-2019. We performed traditional table-based summaries for each characteristic; and applied three unsupervised learning techniques to explore patterns of common condition co-occurrence, care provider teams, and care frequency.
ResultsThere were 221,047 eligible clients. Sociodemographics: We described 13 characteristics, stratified by CHC type and client multimorbidity status. Clinical characteristics: Eleven-year prevalence of 24 investigated conditions ranged from 1% (Hepatitis C) to 63% (chronic musculoskeletal problem) with non-uniform risk across the care history; multimorbidity was common (81%) with variable co-occurrence patterns. Health care use characteristics: Most care was provided by physician and nursing providers, with heterogeneous combinations of other provider types. A subset of clients had many issues addressed within single-visits and there was within- and between-client variability in care frequency. In addition to substantive findings, we discuss methodological considerations for future decision support initiatives.
ConclusionsWe demonstrated the use of methods from statistics and machine learning, applied with an epidemiological lens, to provide an overview of a complex primary care population and lay a foundation for stakeholder engagement and decision support tool development.

Objective/ApproachThe Black Health Equity Working Group's Applied Health Research Question aimed to compare cancer screening rates and surgical wait times between community health centre (CHC) clients based on race-related data and non-CHC clients.
CHC client data was categorized by self-identified racial groups, with Black self-identification compared to non-Black racialized, White, and missing racial self-identification, and non-CHC clients. Health card numbers were encrypted to link individuals to the Primary Care Population dataset for breast, cervical, and colorectal cancer screening rates. Surgical wait time indicators, such as the number of patients undergoing surgery and average wait times for initial consultation and completed surgeries, were derived from the Wait Time Information System. Assessments were conducted semi-annually from fiscal year 2018 to 2021.
ResultsFollowing the onset of COVID-19, CHC clients self-identifying as Black experienced the most significant decrease (6.8%) in colorectal screenings compared to other groups. Mammogram screenings remained consistently higher for CHC clients self-identifying as Black pre- and post-pandemic. Average cervical cancer screening rates were approximately 8% higher among CHC clients compared to non-CHC clients, irrespective of racial self-identification. However, due to small sample sizes and missing data among self-identified racial groups, trends in surgical wait times for both CHC and non-CHC clients were unstable.
Conclusion/ImplicationsTailored interventions targeting Black CHC clients can enhance cancer screening rates, particularly colorectal screenings. The analysis of CHC data offers valuable insights into race-based disparities in health outcomes. Improved data completeness is essential for accurately assessing health outcome variations among different racial groups.