Population segments as a tool for health care performance reporting: an exploratory study in the Canadian province of British Columbia.

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  • Additional Information
    • Source:
      Publisher: BioMed Central Country of Publication: England NLM ID: 100967792 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2296 (Electronic) Linking ISSN: 14712296 NLM ISO Abbreviation: BMC Fam Pract Subsets: MEDLINE
    • Publication Information:
      Original Publication: London : BioMed Central, [2000-2021]
    • Subject Terms:
      Patient Care Management*/methods ; Patient Care Management*/organization & administration ; Patient Care Management*/statistics & numerical data ; Primary Health Care*/organization & administration ; Primary Health Care*/standards ; Quality of Health Care*/organization & administration ; Quality of Health Care*/standards; Community Health Planning/*methods ; Health Care Costs/*statistics & numerical data; British Columbia/epidemiology ; Cross-Sectional Studies ; Female ; Humans ; Male ; Middle Aged ; Needs Assessment/organization & administration ; Patient Acceptance of Health Care/statistics & numerical data ; Process Assessment, Health Care/methods ; Risk Management
    • Abstract:
      Background: Primary care serves all age groups and individuals with health states ranging from those with no chronic conditions to those who are medically complex, or frail and approaching the end of life. For information to be actionable and guide planning, there must be some population disaggregation based on differences in expected needs for care. Promising approaches to segmentation in primary care reflect both the breadth and severity of health states, the types and amounts of health care utilization that are expected, and the roles of the primary care provider. The purpose of this study was to assess population segmentation as a tool to create distinct patient groups for use in primary care performance reporting.
      Methods: This cross-sectional study used administrative data (patient characteristics, physician and hospital billings, prescription medicines data, emergency department visits) to classify the population of British Columbia (BC), Canada into one of four population segments: low need, multiple morbidities, medically complex, and frail. Each segment was further classified using socioeconomic status (SES) as a proxy for patient vulnerability. Regression analyses were used to examine predictors of health care use, costs and selected measures of primary care attributes (access, continuity, coordination) by segment.
      Results: Average annual health care costs increased from the low need ($ 1460) to frail segment ($10,798). Differences in primary care cost by segment only emerged when attributes of primary care were included in regression models: accessing primary care outside business hours and discontinuous primary care (≥5 different GP's in a given year) were associated with higher health care costs across all segments and higher continuity of care was associated with lower costs in the frail segment (cost ratio = 0.61). Additionally, low SES was associated with higher costs across all segments, but the difference was largest in the medically complex group (cost ratio = 1.11).
      Conclusions: Population segments based on expected need for care can support primary care measurement and reporting by identifying nuances which may be lost when all patients are grouped together. Our findings demonstrate that variables such as SES and use of regression analyses can further enhance the usefulness of segments for performance measurement and reporting.
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    • Grant Information:
      TTF-128265 Canada CIHR; PT-CPH-00001-134 International Michael Smith Foundation for Health Research
    • Contributed Indexing:
      Keywords: Administrative data; Health care costs; Performance measurement; Population segmentation; Primary care; Risk adjustment
    • Publication Date:
      Date Created: 20200602 Date Completed: 20210709 Latest Revision: 20240729
    • Publication Date:
      20250114
    • Accession Number:
      PMC7262753
    • Accession Number:
      10.1186/s12875-020-01141-w
    • Accession Number:
      32475339