TY - JOUR
T1 - 大規模レセプトデータベースを用いた臨床研究
AU - Takekuma, Yoh
AU - Imai, Shungo
AU - Sugawara, Mitsuru
N1 - Publisher Copyright:
© 2022 The Pharmaceutical Society of Japan
PY - 2022
Y1 - 2022
N2 - The JMDC Claims Database®contains completely anonymized receipt information on the insured members of health insurance associations. The number of registered users is approximately 9.6 million (6% of the population) as of May 2020. In this database, it is possible to track even outpatient treatment, even if the patient changes the medical facility, as long as the insurer of the subscriber's health insurance does not change, so that long-term medical treatment could be targeted as a research theme. However, as the data do not contain medical record information, it is not possible to obtain laboratory values, although it is possible to know whether clinical tests have been performed. For pharmaceutics-related research, the most suitable use of the receipt database like JMDC Claims Database®seems to be the investigation of actual prescriptions. However, the research topics that pharmacists are interested in are probably comparisons of drug eŠects, drug-drug interactions, or causal analysis of drugs and side eŠects. However, laboratory data for evaluating drug efficacy is not available in the receipt database, and the accuracy of the disease name in the database becomes problematic when using the disease name as information indicating the occurrence of side eŠects. In this review, we introduce our studies performed by using JMDC Claims Database®and how to manage the above-described problems. We hope that this study will be helpful to those who are going to engage in research using medical big data.
AB - The JMDC Claims Database®contains completely anonymized receipt information on the insured members of health insurance associations. The number of registered users is approximately 9.6 million (6% of the population) as of May 2020. In this database, it is possible to track even outpatient treatment, even if the patient changes the medical facility, as long as the insurer of the subscriber's health insurance does not change, so that long-term medical treatment could be targeted as a research theme. However, as the data do not contain medical record information, it is not possible to obtain laboratory values, although it is possible to know whether clinical tests have been performed. For pharmaceutics-related research, the most suitable use of the receipt database like JMDC Claims Database®seems to be the investigation of actual prescriptions. However, the research topics that pharmacists are interested in are probably comparisons of drug eŠects, drug-drug interactions, or causal analysis of drugs and side eŠects. However, laboratory data for evaluating drug efficacy is not available in the receipt database, and the accuracy of the disease name in the database becomes problematic when using the disease name as information indicating the occurrence of side eŠects. In this review, we introduce our studies performed by using JMDC Claims Database®and how to manage the above-described problems. We hope that this study will be helpful to those who are going to engage in research using medical big data.
KW - big data
KW - clams database
KW - pharmacoepidemiology
UR - http://www.scopus.com/inward/record.url?scp=85127462357&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85127462357&partnerID=8YFLogxK
U2 - 10.1248/yakushi.21-00178-3
DO - 10.1248/yakushi.21-00178-3
M3 - Article
C2 - 35370187
AN - SCOPUS:85127462357
VL - 142
SP - 331
EP - 336
JO - Yakugaku zasshi : Journal of the Pharmaceutical Society of Japan
JF - Yakugaku zasshi : Journal of the Pharmaceutical Society of Japan
SN - 0031-6903
IS - 4
ER -