DOCUMENTS

papers

Patient poverty and workload in primary care: study of prescription drug benefit recipients in community health centres

Published: April 1, 2013
Category: Papers
Authors: Dahrouge S, Muldoon L, Rayner J
Country: Canada
Language: null
Type: Population Health
Setting: Hospital

Can Fam Physician 59:384-390.

Lamont Primary Health Care Research Centre, Bruyère Research Institute, Ottawa, ON, Canada

Erratum in: Can Fam Physician. 2013 Jun;59(6):612.

OBJECTIVE: To determine if patient poverty is associated with increased workload for primary care providers (PCPs).

DESIGN: Linkage of administrative data identifying patient poverty and comorbidity with survey data about the organizational structure of community health centres (CHCs).

SETTING: Ontario’s 73 CHCs.

PARTICIPANTS: A total of 64 CHC sites (N=63 included in the analysis).

MAIN OUTCOME MEASURES: Patient poverty was determined in 2 different ways: based on receipt of Ontario Drug Benefits (identifying recipients of welfare, provincial disability support, and low-income seniors’ benefits) or residence in low-income neighbourhoods. Patient comorbidities were determined through administrative diagnostic data from the CHCs and the Institute for Clinical Evaluative Sciences. Primary care workload was determined by examining PCP panel size (the number of patients cared for by a full-time-equivalent PCP during a 2-year interval).

RESULTS: The CHCs with higher proportions of poor patients had smaller panel sizes. The smaller panel sizes were entirely explained by the medical comorbidity profile of the poor patients.

CONCLUSION: Poor patients generate a higher workload for PCPs in CHCs; however, this is principally because they are sicker than higher-income patients are. Further information is required about the spectrum of services used by poor patients in CHCs.

PMID: 23585609
PMCID: PMC3625088

Population Markers,Prescription Drugs and Expenditures,Targeted Program,Co-morbidity,Canada,Adolescent,Adult,Aged,Community Health Centers/statistics & numerical data,Databases,Factual,Linear Models,Gender,Middle Aged,Ontario,Primary Health Care/manpower,Young Adult

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