Medical big data are accumulated daily by medical staff in clinical settings. We developed a formulary in 2016 using medical big data from eight hospitals affiliated with Showa University, Japan (3200 beds). In 2019, we revised the procedure from the perspective of authenticity, reproducibility, and clarity to develop a medicine formulary with unbiased data. Briefly, we organized two teams of expert physicians. Team 1 was a systematic review team that conducted a literature search using systematic review. Team 2 was a medical big data team that conducted the analysis using medical big data. Both teams developed a bisphosphonate formulary. First and second team recommendations were alendronic acid and minodronic acid, and alendronic acid and risedronic acid, respectively. Discussion between the two teams yielded alendronic acid only in the bisphosphonate formulary. We developed reports for the bisphosphonate formulary that included conflicts of interest, the role of each staff member in developing the formulary, and the process for determining the formulary. To use our formulary in a community context, we updated the formulary on our website. We tried to substantiate our bisphosphonate formulary and make a recommendation to change the bisphosphonates according to our formulary. The formulary is focused on controlling the economic burden of medical expenses. We believe that the formulary needs to represent authenticity, reproducibility, and clarity in the procedure and conflicts of interest, with unbiased data to preclude context (hospital)-convenient decisions.
CITATION STYLE
Momo, K. (2022). Evidence for Proper Use of Medicines Using Medical Big Data: Formulary in a Clinical Setting Using Medical Big Data. In Yakugaku Zasshi (Vol. 142, pp. 327–330). Pharmaceutical Society of Japan. https://doi.org/10.1248/yakushi.21-00178-2
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