Clinical Research Using the Large Health Insurance Claims Database

被引:1
|
作者
Takekuma, Yoh [1 ]
Imai, Shungo [2 ]
Sugawara, Mitsuru [1 ,2 ]
机构
[1] Hokkaido Univ Hosp, Dept Pharm, Kita Ku, Kita 14 Jo,Nishi 5 Chome, Sapporo, Hokkaido 0608648, Japan
[2] Hokkaido Univ, Fac Pharmaceut Sci, Kita Ku, Kita 12 Jo,Nishi 6 Chome, Sapporo, Hokkaido 0600812, Japan
关键词
big data; clams database; pharmacoepidemiology;
D O I
10.1248/yakushi.21-00178-3
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
The JMDC Claims Database (R) 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 (R) seems to be the investigation of actual prescriptions. However, the research topics that pharmacists are interested in are probably comparisons of drug effects, drug-drug interactions, or causal analysis of drugs and side effects. 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 effects. In this review, we introduce our studies performed by using JMDC Claims Database (R) 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.
引用
收藏
页码:331 / 336
页数:6
相关论文
共 50 条
  • [21] Linking male parents to pregnancies and infants in a health insurance claims database
    Bertoia, Monica
    Pernar, Claire
    Doherty, Michael C.
    Seeger, John
    [J]. PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, 2022, 31 : 248 - 248
  • [22] Survival analysis of posterior restorations using an insurance claims database
    Bogacki, RE
    Hunt, RJ
    del Aguila, M
    Smith, WR
    [J]. OPERATIVE DENTISTRY, 2002, 27 (05) : 488 - 492
  • [23] Identifying Idiopathic Pulmonary Fibrosis in a US Health Insurance Claims Database
    Esposito, Daina B.
    Donneyong, Macarius
    Holick, Crystal N.
    Lanes, Stephan
    [J]. PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, 2015, 24 : 420 - 420
  • [24] Analysis of Patient Exposure for Enbrel Using Insurance Claims Database
    Xue, Fei
    Yuan, Jason
    Gastanaga, Victor
    Stryker, Scott
    Hughes, Gail
    McCroskery, Peter
    Zhao, Sean
    [J]. PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, 2010, 19 : S176 - S177
  • [25] Characteristics of patients with a lipoprotein(a) assessment - a health insurance claims database analysis
    Laufs, U.
    Schorr, J.
    Klebs, S.
    [J]. EUROPEAN HEART JOURNAL, 2021, 42 : 2519 - 2519
  • [26] Characteristics of patients with lipoprotein(a) assessment: a health insurance claims database analysis
    Stuerzebecher, P. E.
    Schorr, J.
    Klebs, S.
    Laufs, U.
    [J]. EUROPEAN HEART JOURNAL, 2022, 43 : 2308 - 2308
  • [27] Comparing the efficacy of anti-seizure medications using matched cohorts on a large insurance claims database
    Kan-Tor, Yoav
    Ness, Lior
    Szlak, Liran
    Benninger, Felix
    Ravid, Sivan
    Chorev, Michal
    Rosen-Zvi, Michal
    Shimoni, Yishai
    Fisher, Robert S.
    [J]. EPILEPSY RESEARCH, 2024, 201
  • [28] Household Transmission of Tinea Infections: Analysis of a Large Commercial Health Insurance Claims Database, United States, 2021
    Benedict, Kaitlin
    Lipner, Shari R.
    Caplan, Avrom S.
    Gold, Jeremy A. W.
    [J]. OPEN FORUM INFECTIOUS DISEASES, 2024, 11 (07):
  • [29] Polypharmacy in primary care practices: an analysis using a large health insurance database
    Grimmsmann, Thomas
    Himmel, Wolfgang
    [J]. PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, 2009, 18 (12) : 1206 - 1213
  • [30] Early experience with ocrelizumab: patient characteristics from a large insurance claims database
    Engmann, N. J.
    Yang, E.
    Julian, L.
    Yeh, W. S.
    Whiteley, J.
    [J]. MULTIPLE SCLEROSIS JOURNAL, 2018, 24 : 963 - 964