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Observational Study
. 2022 Jul 13;12(7):e055459.
doi: 10.1136/bmjopen-2021-055459.

Accuracy of algorithms to identify patients with a diagnosis of major cancers and cancer-related adverse events in an administrative database: a validation study in an acute care hospital in Japan

Takashi Fujiwara  1   2 , Takashi Kanemitsu  3 , Kosei Tajima  4 , Akinori Yuri  5 , Masahiro Iwasaku  1 , Yasuyuki Okumura  6 , Hironobu Tokumasu  7   6
Affiliations
Observational Study

Accuracy of algorithms to identify patients with a diagnosis of major cancers and cancer-related adverse events in an administrative database: a validation study in an acute care hospital in Japan

Takashi Fujiwara et al. BMJ Open. .

Abstract

Objectives: Validation studies in oncology are limited in Japan. This study was conducted to evaluate the accuracy of diagnosis and adverse event (AE) definitions for specific cancers in a Japanese health administrative real-world database (RWD).

Design and setting: Retrospective observational validation study to assess the diagnostic accuracy of electronic medical records (EMRs) and claim coding regarding oncology diagnosis and AEs based on medical record review in the RWD. The sensitivity and positive predictive value (PPV) with 95% CIs were calculated.

Participants: The validation cohort included patients with lung (n=2257), breast (n=1121), colorectal (n=1773), ovarian (n=216) and bladder (n=575) cancer who visited the hospital between January 2014 and December 2018, and those with prostate cancer (n=3491) visiting between January 2009 and December 2018, who were identified using EMRs.

Outcomes: Key outcomes included primary diagnosis, deaths and AEs.

Results: For primary diagnosis, sensitivity and PPV for the respective cancers were as follows: lung, 100.0% (96.6 to 100.0) and 81.0% (74.9 to 86.2); breast, 100.0% (96.3 to 100.0) and 74.0% (67.3 to 79.9); colorectal, 100.0% (96.6 to 100.0) and 80.5% (74.3 to 85.8); ovarian, 89.8% (77.8 to 96.6) and 75.9% (62.8 to 86.1); bladder, 78.6% (63.2 to 89.7) and 67.3% (52.5 to 0.1); prostate, 100.0% (93.2 to 100.0) and 79.0% (69.7 to 86.5). Sensitivity and PPV for death were as follows: lung, 97.0% (84.2 to 99.9) and 100.0% (84.2 to 100.0); breast, 100.0% (1.3 to 100.0) and 100.0% (1.3 to 100.0); colorectal, 100.0% (28.4 to 100.0) and 100.0% (28.4 to 100.0); ovarian, 100.0% (35.9 to 100.0) and 100.0% (35.9 to 100.0); bladder, 100.0% (9.4-100.0) and 100.0% (9.4 to 100.0); prostate, 75.0% (19.4 to 99.4) and 100.0% (19.4 to 100.0). Overall, PPV tended to be low, with the definition based on International Classification of Diseases, 10th revision alone for AEs.

Conclusion: Diagnostic accuracy was not so high, and therefore needs to be further investigated.

Trial registration number: University Hospital Medical Information Network (UMIN) Clinical Trials Registry (UMIN000039345).

Keywords: Adult oncology; Breast tumours; Gynaecological oncology; Respiratory tract tumours; Urological tumours.

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Conflict of interest statement

Competing interests: TK, KT and AY are employees of Chugai Pharmaceutical Co. TF reports personal fee for statistical analysis from Real World Data Co during the conduct of the study; personal fee for collaborative research from Chugai Pharmaceutical Co; and personal fee for statistical analysis from Real World Data Co outside the submitted work. MI has nothing to disclose. YO is an employee of Real World Data Co and reports personal fees from MSD K.K., Otsuka Pharmaceutical and Kurashiki Central Hospital, outside the submitted work. HT reports personal fees for lecture from AYUMI Pharmaceutical Corporation and Chugai Pharmaceutical Co, outside the submitted work and is an employee of Kurashiki Central Hospital and the Director of Real World Data Co.

Figures

Figure 1
Figure 1
Health, Clinic, and Education Information Evaluation Institute/real-world database. EMR, electronic medical record; HCEI, Health, Clinic, and Education Information Evaluation Institute; KCH, Kurashiki Central Hospital; RWD, real-world database.
Figure 2
Figure 2
Diagnosis definitions with high* accuracy. *All accuracy values included for a definition are approximately 70% or more. NPV, negative predictive value; PPV, positive predictive value.
Figure 3
Figure 3
Death definitions with high* accuracy. *All accuracy values included for a definition are >70%. NPV, negative predictive value; PPV, positive predictive value
See this image and copyright information in PMC

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