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The purpose of this paper is to examine from the viewpoint of resource utilization the Japanese surgical payment system which was revised in April 2016.

The authors collected data from surgical records in the Teikyo University electronic medical record system from April 1 till September 30, 2016. The authors defined the decision-making unit as a surgeon with the highest academic rank in the surgery. Inputs were defined as the number of medical doctors who assisted surgery, and the time of operation from skin incision to closure. An output was defined as the surgical fee. The authors calculated each surgeon’s efficiency score using output-oriented Charnes–Cooper–Rhodes model of data envelopment analysis. The authors compared the efficiency scores of each surgical specialty using the Kruskal–Wallis and the Steel method.

The authors analyzed 2,558 surgical procedures performed by 109 surgeons. The difference in efficiency scores was significant (p = 0.000). The efficiency score of neurosurgery was significantly greater than obstetrics and gynecology, general surgery, orthopedics, emergency surgery, urology, otolaryngology and plastic surgery (p<0.05).

The authors demonstrated that the surgeons’ efficiency was significantly different among their specialties. This suggests that the Japanese surgical reimbursement scales fail to reflect resource utilization despite the revision in 2016.

The sustainability of the Japanese healthcare system is in question because the government has had a huge fiscal debt. Despite an enormous effort to cut the deficit, our healthcare expenditure is increasing every year because of the rapidly aging population. One of the solutions for this problem is to improve the productivity of healthcare. The purpose of this paper is to determine the factors that change surgeons’ productivity in one year.

The authors collected data of all surgical procedures performed at Teikyo University Hospital from April 1 through September 30 in 2014 and 2015, and computed the surgeons’ Malmquist index (MI), efficiency change (EC) and technical change (TC) using non-radial and non-oriented Malmquist model under the constant returns-to-scale assumptions. The authors then divided the surgeons into two groups; one whose productivity progressed and the other whose productivity regressed. These two groups were compared to identify factors that may influence their MI.

The only significant difference between the two groups was ECs (p < 0.0001). The other factors, such as TC, experience, surgical volume, emergency cases, surgical specialty, academic ranks, medical schools and gender, were not significantly different between the two groups.

EC is a major determinant of surgeons’ productivity change. The best way to improve surgeons’ productivity may be to enhance their efficiency regardless of their surgical volume and personal backgrounds.