Dataset Information

Validation of algorithms to identify colorectal cancer patients from administrative claims data of a Japanese hospital.

ABSTRACT:

Background

Administrative claims data are a valuable source for clinical studies; however, the use of validated algorithms to identify patients is essential to minimize bias. We evaluated the validity of diagnostic coding algorithms for identifying patients with colorectal cancer from a hospital's administrative claims data.

Methods

This validation study used administrative claims data from a Japanese university hospital between April 2017 and March 2019. We developed diagnostic coding algorithms, basically based on the International Classification of Disease (ICD) 10th codes of C18-20 and Japanese disease codes, to identify patients with colorectal cancer. For random samples of patients identified using our algorithms, case ascertainment was performed using chart review as the gold standard. The positive predictive value (PPV) was calculated to evaluate the accuracy of the algorithms.

Results

Of 249 random samples of patients identified as having colorectal cancer by our coding algorithms, 215 were confirmed cases, yielding a PPV of 86.3% (95% confidence interval [CI], 81.5-90.1%). When the diagnostic codes were restricted to site-specific (right colon, left colon, transverse colon, or rectum) cancer codes, 94 of the 100 random samples were true cases of colorectal cancer. Consequently, the PPV increased to 94.0% (95% CI, 87.2-97.4%).

Conclusion

Our diagnostic coding algorithms based on ICD-10 codes and Japanese disease codes were highly accurate in detecting patients with colorectal cancer from this hospital's claims data. The exclusive use of site-specific cancer codes further improved the PPV from 86.3 to 94.0%, suggesting their desirability in identifying these patients more precisely.

SUBMITTER: Hirano T

PROVIDER: S-EPMC10029250 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

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Publications

Validation of algorithms to identify colorectal cancer patients from administrative claims data of a Japanese hospital.

Hirano Takahiro T Negishi Makiko M Kuwatsuru Yoshiki Y Arai Masafumi M Wakabayashi Ryozo R Saito Naoko N Kuwatsuru Ryohei R

BMC health services research 20230321 1

<h4>Background</h4>Administrative claims data are a valuable source for clinical studies; however, the use of validated algorithms to identify patients is essential to minimize bias. We evaluated the validity of diagnostic coding algorithms for identifying patients with colorectal cancer from a hospital's administrative claims data.<h4>Methods</h4>This validation study used administrative claims data from a Japanese university hospital between April 2017 and March 2019. We developed diagnostic c ...[more]

PMID: 36944932

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Project description:ObjectivePressure ulcer development is a quality of care indicator, as pressure ulcers are potentially preventable. Yet pressure ulcer is a leading cause of morbidity, discomfort and additional healthcare costs for inpatients. Methods are lacking for accurate surveillance of pressure ulcer in hospitals to track occurrences and evaluate care improvement strategies. The main study aim was to validate hospital discharge abstract database (DAD) in recording pressure ulcers against nursing consult reports, and to calculate prevalence of pressure ulcers in Alberta, Canada in DAD. We hypothesised that a more inclusive case definition for pressure ulcers would enhance validity of cases identified in administrative data for research and quality improvement purposes.SettingA cohort of patients with pressure ulcers were identified from enterostomal (ET) nursing consult documents at a large university hospital in 2011.ParticipantsThere were 1217 patients with pressure ulcers in ET nursing documentation that were linked to a corresponding record in DAD to validate DAD for correct and accurate identification of pressure ulcer occurrence, using two case definitions for pressure ulcer.ResultsUsing pressure ulcer definition 1 (7 codes), prevalence was 1.4%, and using definition 2 (29 codes), prevalence was 4.2% after adjusting for misclassifications. The results were lower than expected. Definition 1 sensitivity was 27.7% and specificity was 98.8%, while definition 2 sensitivity was 32.8% and specificity was 95.9%. Pressure ulcer in both DAD and ET consultation increased with age, number of comorbidities and length of stay.ConclusionDAD underestimate pressure ulcer prevalence. Since various codes are used to record pressure ulcers in DAD, the case definition with more codes captures more pressure ulcer cases, and may be useful for monitoring facility trends. However, low sensitivity suggests that this data source may not be accurate for determining overall prevalence, and should be cautiously compared with other prevalence studies.

Dataset Information

Validation of algorithms to identify colorectal cancer patients from administrative claims data of a Japanese hospital.

Background

Methods

Results

Conclusion

Publications

Validation of algorithms to identify colorectal cancer patients from administrative claims data of a Japanese hospital.

Similar Datasets

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