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Background <p>Rural physician shortages persist globally, with professional isolation a major barrier. Traditional incentives have limited effects on long-term retention.</p> Aim <p>To describe the decentralized, academically integrated training model at Shimane University General Medicine Center (SGMC) and evaluate recruitment and retention outcomes.</p> Setting <p>Shimane Prefecture, a rural, aging region in Japan.</p> Participants <p>Forty-two General Practice residents (2018–2025).</p> Program Description <p>SGMC implemented a prefecture-wide “Neural GP Network” community of practice and a “Virtual Office” using Slack and Zoom. Residents completed longitudinal rural placements in local care teams.</p> Program Evaluation <p>Annual recruitment averaged 15.8% of specialty trainees, significantly exceeding the national average (2.6%; <i>P</i> &lt; 0.001). As of January 2026, 88.1% (37/42) remained in the prefectural network, exceeding estimates for rural Japan (~ 50%). The Virtual Office generated 26,787 messages and 6803 files (Feb 2024–Jan 2025). Since 2021, affiliates published 58 English-language papers.</p> Discussion <p>Over 8 years, this hybrid model integrating digital networking with longitudinal training was associated with strong workforce stability, representing a promising approach to strengthen rural primary care.</p>

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A Decentralized, Academically Integrated Training Model for Rural General Practice in Japan: A Descriptive Program Evaluation

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月20日

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  • Kota Sakaguchi,
  • Takeshi Endo,
  • Yoshihiko Shiraishi,
  • Makoto Kaneko,
  • Takashi Watari

摘要

Background

Rural physician shortages persist globally, with professional isolation a major barrier. Traditional incentives have limited effects on long-term retention.

Aim

To describe the decentralized, academically integrated training model at Shimane University General Medicine Center (SGMC) and evaluate recruitment and retention outcomes.

Setting

Shimane Prefecture, a rural, aging region in Japan.

Participants

Forty-two General Practice residents (2018–2025).

Program Description

SGMC implemented a prefecture-wide “Neural GP Network” community of practice and a “Virtual Office” using Slack and Zoom. Residents completed longitudinal rural placements in local care teams.

Program Evaluation

Annual recruitment averaged 15.8% of specialty trainees, significantly exceeding the national average (2.6%; P < 0.001). As of January 2026, 88.1% (37/42) remained in the prefectural network, exceeding estimates for rural Japan (~ 50%). The Virtual Office generated 26,787 messages and 6803 files (Feb 2024–Jan 2025). Since 2021, affiliates published 58 English-language papers.

Discussion

Over 8 years, this hybrid model integrating digital networking with longitudinal training was associated with strong workforce stability, representing a promising approach to strengthen rural primary care.