The sustainability of the Japanese healthcare system is questionable because of a huge fiscal debt. One of the solutions is to improve the efficiency of healthcare. The purpose of this study is to determine what factors are predictive of surgeons' efficiency scores. The authors collected data from all the surgical procedures performed at Teikyo University Hospital from April 1 through September 30 in 2013-2015. Output-oriented Charnes-Cooper-Rhodes model of data envelopment analysis was employed to calculate each surgeon's efficiency score. Seven independent variables that may predict their efficiency scores were selected: experience, medical school, surgical volume, gender, academic rank, surgical specialty, and the surgical fee schedule. Multiple regression analysis using random-effects Tobit model was used for our panel data. The data from total 8722 surgical cases were obtained in 18-month study period. The authors analyzed 134 surgeons. The only statistically significant coefficients were surgical specialty and surgical fee schedule (p = 0.000 and p = 0.016, respectively). Experience had some positive association with efficiency scores but did not reach statistical significance (p = 0.062). The other coefficients were not statistically significant. These results demonstrated that the surgical reimbursement system, not surgeons' personal characteristics, is a significant predictor of surgeons' efficiency.
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 11 April 2017.
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#19,049,051
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Outputs from Health Services Management Research
#171
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#171,290
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Outputs of similar age from Health Services Management Research
#6
of 10 outputs
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