Validity of diagnoses of respiratory diseases recorded in a Japanese administrative database.


Journal

Respiratory investigation
ISSN: 2212-5353
Titre abrégé: Respir Investig
Pays: Netherlands
ID NLM: 101581124

Informations de publication

Date de publication:
May 2023
Historique:
received: 04 12 2022
revised: 14 01 2023
accepted: 17 01 2023
medline: 24 4 2023
pubmed: 4 3 2023
entrez: 3 3 2023
Statut: ppublish

Résumé

Validating the information recorded in administrative databases is essential. However, no study has comprehensively validated the accuracy of Japanese Diagnosis Procedure Combination (DPC) data on various respiratory diseases. Therefore, this study aimed to evaluate the validity of diagnoses of respiratory diseases in the DPC database. We conducted chart reviews of 400 patients hospitalized in the departments of respiratory medicine in two acute-care hospitals in Tokyo, between April 1, 2019 and March 31, 2021, and used them as reference standards. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of DPC data on 25 respiratory diseases were determined. Sensitivity ranged from 22.2% (aspiration pneumonia) to 100% (chronic eosinophilic pneumonia and malignant pleural mesothelioma) and was <50% for eight diseases, while specificity was >90% for all diseases. PPV ranged from 40.0% (aspiration pneumonia) to 100% (coronavirus disease 2019, bronchiectasis, chronic eosinophilic pneumonia, pulmonary hypertension, squamous cell carcinoma, small cell carcinoma, lung cancer of other histological types, and malignant pleural mesothelioma) and was >80% for 16 diseases. Except for chronic obstructive pulmonary disease (82.9%) and interstitial pneumonia (other than idiopathic pulmonary fibrosis) (85.4%), NPV was >90% for all diseases. These validity indices were similar in both hospitals. The validity of diagnoses of respiratory diseases in the DPC database was high in general, thereby providing an important basis for future studies.

Sections du résumé

BACKGROUND BACKGROUND
Validating the information recorded in administrative databases is essential. However, no study has comprehensively validated the accuracy of Japanese Diagnosis Procedure Combination (DPC) data on various respiratory diseases. Therefore, this study aimed to evaluate the validity of diagnoses of respiratory diseases in the DPC database.
METHODS METHODS
We conducted chart reviews of 400 patients hospitalized in the departments of respiratory medicine in two acute-care hospitals in Tokyo, between April 1, 2019 and March 31, 2021, and used them as reference standards. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of DPC data on 25 respiratory diseases were determined.
RESULTS RESULTS
Sensitivity ranged from 22.2% (aspiration pneumonia) to 100% (chronic eosinophilic pneumonia and malignant pleural mesothelioma) and was <50% for eight diseases, while specificity was >90% for all diseases. PPV ranged from 40.0% (aspiration pneumonia) to 100% (coronavirus disease 2019, bronchiectasis, chronic eosinophilic pneumonia, pulmonary hypertension, squamous cell carcinoma, small cell carcinoma, lung cancer of other histological types, and malignant pleural mesothelioma) and was >80% for 16 diseases. Except for chronic obstructive pulmonary disease (82.9%) and interstitial pneumonia (other than idiopathic pulmonary fibrosis) (85.4%), NPV was >90% for all diseases. These validity indices were similar in both hospitals.
CONCLUSIONS CONCLUSIONS
The validity of diagnoses of respiratory diseases in the DPC database was high in general, thereby providing an important basis for future studies.

Identifiants

pubmed: 36868080
pii: S2212-5345(23)00018-7
doi: 10.1016/j.resinv.2023.01.009
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

314-320

Informations de copyright

Copyright © 2023 The Japanese Respiratory Society. Published by Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Conflict of Interest The authors declare no conflicts of interest.

Auteurs

Nobuyasu Awano (N)

Department of Respiratory Medicine, Japanese Red Cross Medical Center, Tokyo, Japan. Electronic address: awanobu0606@hotmail.co.jp.

Hirokazu Urushiyama (H)

Department of Respiratory Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.

Hayato Yamana (H)

Data Science Center, Jichi Medical University, Tochigi, Japan; Department of Clinical Epidemiology and Health Economics, School of Public Health, The University of Tokyo, Tokyo, Japan.

Akira Yokoyama (A)

Department of Respiratory Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.

Takahiro Ando (T)

Department of Respiratory Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.

Takehiro Izumo (T)

Department of Respiratory Medicine, Japanese Red Cross Medical Center, Tokyo, Japan.

Minoru Inomata (M)

Department of Respiratory Medicine, Japanese Red Cross Medical Center, Tokyo, Japan.

Yu Ito (Y)

Department of Respiratory Medicine, Japanese Red Cross Medical Center, Tokyo, Japan.

Taisuke Jo (T)

Department of Respiratory Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan; Department of Health Services Research, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.

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