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A Classification Method for General Medicine Physicians to Advance Field Research in Japan
Masaki Tago1, Risa Hirata1, Kiyoshi Shikino2,3
1Department of General Medicine, Saga University Hospital, Saga, Japan.
Purpose:
General medicine physicians in Japan play diverse roles depending on their work environments; however, there is no clear definition. In the United States, the establishment of a definition for "hospitalists" has contributed to the accumulation of evidence. To develop research in general medicine and build evidence in Japan, there is an urgent need to establish a systematic classification method for general medicine physicians.
Methods:
Based on discussions with six hospital-based general medicine physicians with over 10 years of experience at an academic conference in 2024 and a literature review, we proposed a classification method for general medicine physicians.
Results:
The proposed classification method was based on four indicators: physician maldistribution index, inpatient care contribution index (the contribution of one general medicine physician to inpatient care across all beds in the hospital), clinical content (home medical care, outpatient care, emergency response, inpatients management, and critical inpatients management), and education (medical students, clinical residents, and senior residents). These indicators were established by considering physician characteristics, target population, social environment, and hospital environment, enabling an objective evaluation of factors contributing to the practice of general medicine physicians.
Conclusion:
This classification method may serve as a foundation for research that makes it easier to understand the characteristics of general medicine physicians under study and allows for the comparison of roles according to regional characteristics and hospital size. Future validation and continuous improvement of this classification method are expected to advance the accumulation of evidence related to general medicine physicians. In this paper, we present a proposal for a classification method; future validation of this classification is necessary.
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