DOCUMENTS

papers

HMO family physicians: men and women differ in their work

Published: December 1, 1995
Category: Papers
Authors: Boiko P, Feeny D, Weyrauch KF
Country: United States
Language: null
Types: Care Management, Performance Analysis
Setting: Hospital

HMO Pract 9:155-161.

Group Health Cooperative of Puget Sound, Seattle, WA, USA

OBJECTIVE: The goal was to identify differences in the type of work and amount of work performed by male and female family HMO physicians.

DESIGN: Data were collected by self-administered physician surveys, retrospective analysis of encounter forms, ambulatory care group (ACG) analysis of physicians’ patient panels, and participant observation.

SETTING: A large HMO-based clinical facility.

PARTICIPANTS. Family practitioners (n = 21) at one HMO clinic.

MAIN OUTCOME MEASURES: Measures included patient encounters/day, self-assessed and encounter-form-based workload, ambulatory care group panel evaluation and qualitative observation of practice patterns and team functioning.

RESULTS: These data show that the kind of work male and female physicians did at this site differed, when compared on the basis of encounter-form-based diagnoses, ambulatory care group panel assessments and participant observation. However, the amount of work performed by each gender did not appear to different when evaluated by age-sex-adjusted panel size, patient encounters per unit time, a subjective magnitude estimation workload questionnaire and an encounter-form-based workload assessment.

CONCLUSION: In this study, multiple measures for evaluating physician workload revealed distinct differences in the kind of clinical work performed by male and female HMO family physicians. These findings have implications for clinicians, managers, planners, researchers and educators.

PMID: 10170166

Practice Patterns Comparison,Human Resources,Performance Assessment,Process Measures,United States,Adult,Ambulatory Care/manpower,Data Collection,Gender,Middle Aged,Physicians,Women/statistics & numerical data,Practice Patterns,Physicians’/statistics & numerical data,Sex Factors

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