Validity of operative information in Japanese administrative data: a chart review-based analysis of 1221 cases at a single institution

Konishi, Takaaki; Yoshimoto, Takako; Fujiogi, Michimasa; Yamana, Hayato; Tanabe, Masahiko; Seto, Yasuyuki; Yasunaga, Hideo

doi:10.1007/s00595-022-02521-8

Cited by 38 publications

(26 citation statements)

References 33 publications

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“…42 Another study published after our search period also validated operative information. 55 These studies would contribute to promoting detailed clinical epidemiology research using the data available in the administrative databases.…”

Section: Discussionmentioning

confidence: 99%

Validation studies of Japanese administrative health care data: A scoping review

Yamana

Konishi

Yasunaga

2023

Pharmacoepidemiology and Drug

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Purpose Large‐scale administrative health care databases are increasingly being utilized for research. However, there has not been much literature that validated administrative data in Japan; a previous review identified six validation studies published between 2011 and 2017. We conducted a literature review of studies that assessed the validity of Japanese administrative health care data. Methods We searched for studies published by March 2022 that compared individual‐level administrative data with a reference standard from another data source, as well as studies that validated administrative data using other data within the same database. The eligible studies were also summarized based on characteristics which included data types, settings, reference standard used, numbers of patients, and conditions validated. Results There were 36 eligible studies, including 29 that used external reference standard and seven that validated administrative data using other data within the same database. Chart review was the reference standard in 21 studies (range of the numbers of patients, 72–1674; 11 studies conducted in single institutions and nine studies in 2–5 institutions). Five studies used a disease registry as the reference standard. Diagnoses of cardiovascular diseases, cancer, and diabetes were frequently evaluated. Conclusions Validation studies are being conducted at an increasing rate in Japan, although most of them are small scale. Further large‐scale comprehensive validation studies are necessary to effectively utilize the databases for research.

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Section: Discussionmentioning

confidence: 99%

Validation studies of Japanese administrative health care data: A scoping review

Yamana

Konishi

Yasunaga

2023

Pharmacoepidemiology and Drug

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“…To the best of our knowledge, this multicenter cross-sectional study is the first to develop and validate definitions to identify the cause of death in Japanese claims data. Although several studies have evaluated the validity of information such as diagnosis [ 14 – 17 ], procedure [ 14 , 18 ], prescription [ 19 ], and discharge information [ 20 , 21 ] in Japanese claims data, there has been limited information regarding the method used to identify the cause of death. The major finding of this study was that the cause of death due to cancer and cerebrovascular disease in Japanese claims could be satisfactorily identified using definitions where PPVs were 89%-96% in cancer and 71%-90% in cerebrovascular disease.…”

Section: Discussionmentioning

confidence: 99%

“…In contrast, because the National Database (NDB), which stores claims data for all Japanese citizens, is restricted from being linked to external databases, we cannot ascertain the cause of death from the NDB. Several studies have evaluated the validity of Japanese claims data, including information related to diagnosis [14][15][16][17], procedure [14,18], prescription [19], and discharge [20,21].…”

Section: Introductionmentioning

confidence: 99%

Validation study on definition of cause of death in Japanese claims data

et al. 2023

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Identifying the cause of death is important for the study of end-of-life patients using claims data in Japan. However, the validity of how cause of death is identified using claims data remains unknown. Therefore, this study aimed to verify the validity of the method used to identify the cause of death based on Japanese claims data. Our study population included patients who died at two institutions between January 1, 2018 and December 31, 2019. Claims data consisted of medical data and Diagnosis Procedure Combination (DPC) data, and five definitions developed from disease classification in each dataset were compared with death certificates. Nine causes of death, including cancer, were included in the study. The definition with the highest positive predictive values (PPVs) and sensitivities in this study was the combination of “main disease” in both medical and DPC data. For cancer, these definitions had PPVs and sensitivities of > 90%. For heart disease, these definitions had PPVs of > 50% and sensitivities of > 70%. For cerebrovascular disease, these definitions had PPVs of > 80% and sensitivities of> 70%. For other causes of death, PPVs and sensitivities were < 50% for most definitions. Based on these results, we recommend definitions with a combination of “main disease” in both medical and DPC data for cancer and cerebrovascular disease. However, a clear argument cannot be made for other causes of death because of the small sample size. Therefore, the results of this study can be used with confidence for cancer and cerebrovascular disease but should be used with caution for other causes of death.

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“…Following previous validation studies, we defined diagnosis based on chart reviews as the reference standard 11,13,19,20. Because the quality of the descriptions in the charts affects the quality of the chart reviews, we took 2 measures.…”

Section: Discussionmentioning

confidence: 99%

Validity of Algorithms to Identify Patients With Glaucoma Using the Japanese Claims Data

Fujita

Aoyama

Yamana

et al. 2022

Journal of Glaucoma

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Précis: Diagnostic or antiglaucoma drug records in the Japanese claims data showed a high validity in identifying glaucoma patients. Specific subtypes were identified with high specificity and negative predictive values but low sensitivity and positive predictive values. Purpose: Despite the widespread use of administrative claims data in epidemiological research on glaucoma, only a few studies have investigated the validity of the methods in defining patients with glaucoma using diagnoses and drug records. We aimed to evaluate the validity of these algorithms in identifying patients with glaucoma using the Japanese claims data. Methods: Two ophthalmologists independently reviewed the medical charts and administrative claims data of 500 randomly selected patients who visited the Department of Ophthalmology of an academic hospital in 2019. We constructed 12 algorithms to identify patients with any type and specific subtypes of glaucoma using the claims records of diagnosis, antiglaucoma drugs, and visual field tests. We regarded the diagnosis of glaucoma based on the medical charts as the reference standard and calculated the sensitivity, specificity, and positive and negative predictive values of each algorithm based on the claims data. Results: The algorithms of ≥1 diagnostic record per year and ≥1 antiglaucoma drug record per year exhibited sensitivities of 94.6% and 89.2%, respectively, and specificities of 88.9% and 98.3%, respectively. An increase in the frequency of records resulted in a decreased sensitivity and slightly increased specificity. The addition of visual field tests did not improve the validity. The algorithms for specific subtypes of glaucoma exhibited high specificity and relatively low sensitivity. Conclusion: Diagnostic or antiglaucoma drug records in the Japanese claims data were useful for identifying patients with glaucoma. Researchers should select identification algorithms based on the study design.

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Validity of operative information in Japanese administrative data: a chart review-based analysis of 1221 cases at a single institution

Cited by 38 publications

References 33 publications

Validation studies of Japanese administrative health care data: A scoping review

Validation studies of Japanese administrative health care data: A scoping review

Validation study on definition of cause of death in Japanese claims data

Validity of Algorithms to Identify Patients With Glaucoma Using the Japanese Claims Data

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