H Saito1, T Tanimoto2, M Kami3, Y Suzuki4, T Morita5, M Morita3, K Yamamoto3, Y Shimada6, M Tsubokura5, M Endo7. 1. Department of Gastroenterology, Sendai Kousei Hospital, Sendai, Miyagi, Japan. Electronic address: h.saito0515@gmail.com. 2. Department of Internal Medicine, Navitas Clinic, Tachikawa, Tokyo, Japan. 3. Medical Governance Research Institute, Minato-ku, Tokyo, Japan. 4. Department of Obstetrics and Gynecology, Tone Central Hospital, Numata, Gunma, Japan. 5. Department of Internal Medicine, Soma Central Hospital, Soma, Fukushima, Japan. 6. Department of Neurosurgery, Minamisoma Municipal General Hospital, Minamisoma, Fukushima, Japan. 7. Support Office for Medical Education and Trainings, Sendai Kousei Hospital, Sendai, Miyagi, Japan.
Abstract
OBJECTIVES: The problem of uneven distribution of medical services and inequitable distribution of physicians is drawing much attention worldwide. Revealing how changes in the specialty training system in Japan have affected the distribution of doctors could help us understand this problem. In 2018, a new and standardized specialty training system was implemented by the Japanese Medical Specialty Board, which is recognized by the Ministry of Health, Labor and Welfare. The purpose of this study was to investigate how this new system has affected the geographical distribution of doctors commencing specialty training (trainees) and choice of specialty in Japan. STUDY DESIGN: Retrospective observational study. METHODS: The change in the number of trainees between the control period (2012-2014) and 2018 was investigated, taking into account the prefecture and specialty selected. Population, the proportion of residents aged 65 years or older (aging rate), and the total number of overall doctors in each prefecture were considered as the background characteristics of each prefecture. We created a Lorenz curve and calculated the Gini coefficient for the distribution of trainees. RESULTS: In 2018, the number of trainees per 100,000 population increased to 6.6 nationwide compared with 5.5 during the control period. The number of trainees per 100,000 population in 2018 increased in prefectures with a large population of ≧ 2,000,000, a low aging rate (<27%), and a high doctor density (≧ 250 doctors per 100,000 population). The Gini coefficient showed an increase to 0.226 in 2018 compared with only 0.160 during the control period. CONCLUSIONS: After the implementation of the new training system, there was an increase in the number of doctors enrolling in specialty programs, and the specialties other than internal medicine and surgery have attracted more trainees. Inequality in the distribution of doctors between urban and rural prefectures worsened. This indicates the need to explore new ways of balancing distribution while maintaining optimal opportunities for specialist training.
OBJECTIVES: The problem of uneven distribution of medical services and inequitable distribution of physicians is drawing much attention worldwide. Revealing how changes in the specialty training system in Japan have affected the distribution of doctors could help us understand this problem. In 2018, a new and standardized specialty training system was implemented by the Japanese Medical Specialty Board, which is recognized by the Ministry of Health, Labor and Welfare. The purpose of this study was to investigate how this new system has affected the geographical distribution of doctors commencing specialty training (trainees) and choice of specialty in Japan. STUDY DESIGN: Retrospective observational study. METHODS: The change in the number of trainees between the control period (2012-2014) and 2018 was investigated, taking into account the prefecture and specialty selected. Population, the proportion of residents aged 65 years or older (aging rate), and the total number of overall doctors in each prefecture were considered as the background characteristics of each prefecture. We created a Lorenz curve and calculated the Gini coefficient for the distribution of trainees. RESULTS: In 2018, the number of trainees per 100,000 population increased to 6.6 nationwide compared with 5.5 during the control period. The number of trainees per 100,000 population in 2018 increased in prefectures with a large population of ≧ 2,000,000, a low aging rate (<27%), and a high doctor density (≧ 250 doctors per 100,000 population). The Gini coefficient showed an increase to 0.226 in 2018 compared with only 0.160 during the control period. CONCLUSIONS: After the implementation of the new training system, there was an increase in the number of doctors enrolling in specialty programs, and the specialties other than internal medicine and surgery have attracted more trainees. Inequality in the distribution of doctors between urban and rural prefectures worsened. This indicates the need to explore new ways of balancing distribution while maintaining optimal opportunities for specialist training.