ArticleBMC medical informatics and decision making2021
Characteristics of hospital differences in missing of clinical laboratory test results in a multi-hospital observational database contributing to MID-NET® in Japan.
Article in BMC medical informatics and decision making, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Dealing with missing data in laboratory test results used as a baseline covariate: results of multi-hospital cohort studies utilizing a database system contributing to MID-NETBMC medical informatics and decision making · 2023Article
- Regulatory Approval With Real-World Data From Regulatory Science Perspective in Japan.Frontiers in medicine · 2022Article
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6 authors.
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Abstract
backgroundIn Japan, a multiple-hospital observational database system, the Medical Information Database Network (MID-NET®), was launched for post-marketing drug safety assessments. These assessments will be based on datasets with missing laboratory results. The characteristics of missing data considering hospital differences have not been evaluated. We assessed the missing proportion and the association between missingness and a factor through case studies using a database system, a part of MID-NET®.
methodsSeven scenarios using laboratory results before the prescription of the assessed drug as baseline covariates and data from 10 hospitals of Tokushukai Medical Group were used. The missing proportion and the association between missingness and patient background were investigated per hospital. The associations were assessed using the log of adjusted odds ratio (log-aOR). Additionally, an ad hoc survey was conducted to explore other factors affecting the missingness.
resultsFor some laboratory tests, missing proportions varied among hospitals, such as 7.4-44.4% of alkaline phosphatase (ALP) and 8.1-31.2% of triglyceride (TG) among statin users. The association between missingness and affecting factors also differed among hospitals for some factors; example, the log-aOR of hospitalization associated with missingness of TG was - 0.41 (95% CI, - 1.06 to 0.24) in hospital 3 and 1.84 (95% CI, 1.34 to 2.34) in hospital 4. In the ad hoc survey focusing on ALP, hospital-dependent differences in the ordering system settings were observed.
conclusionsHospital differences in missing data appeared in some laboratory tests in our multi-hospital observational database, which could be attributed to the affecting factors, including the patient background.
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