Dataset Information

Identifying patients with diagnosed cirrhosis in administrative health databases: a validation study.

ABSTRACT:

Objectives

Case ascertainment algorithms were developed and validated to identify people living with cirrhosis in administrative health data in Manitoba, Canada using primary care electronic medical records (EMR) to define the reference standards.

Methods

We linked provincial administrative health data to primary care EMR data. The validation cohort included 116,675 Manitobans aged >18 years with at least one primary care visit between April 1998 and March 2015. Hospital records, physician billing claims, vital statistics, and prescription drug data were used to develop and test 93 case-finding algorithms. A validated case definition for primary care EMR data was the reference standard. We estimated sensitivity, specificity, positive and negative predictive values (PPV, NPV), Youden's index, area under the receiver operative curve, and their 95% confidence intervals (CIs).

Results

A total of 116,675 people were in the validation cohort. The prevalence of cirrhosis was 1.4% (n = 1593). Algorithm sensitivity estimates ranged from 32.5% (95% CI 32.2-32.8) to 68.3% (95% CI 68.0-68.9) and PPV from 17.4% (95% CI 17.1-17.6) to 23.4% (95% CI 23.1-23.6). Specificity (95.5-98.2) and NPV (approximately 99%) were high for all algorithms. The algorithms had slightly higher sensitivity estimates among men compared with women, and individuals aged ≥45 years compared to those aged 18-44 years.

Conclusion

Cirrhosis algorithms applied to administrative health data had moderate validity when a validated case definition for primary care EMRs was the reference standard. This study provides algorithms for identifying diagnosed cirrhosis cases for population-based research and surveillance studies.

SUBMITTER: Faisal N

PROVIDER: S-EPMC10946181 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature

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Publications

Identifying patients with diagnosed cirrhosis in administrative health databases: a validation study.

Faisal Nabiha N Lix Lisa M LM Walld Randy R Singer Alexander A Renner Eberhard E Singh Harminder H Kosowan Leanne L Mahar Alyson A

Canadian liver journal 20240226 1

<h4>Objectives</h4>Case ascertainment algorithms were developed and validated to identify people living with cirrhosis in administrative health data in Manitoba, Canada using primary care electronic medical records (EMR) to define the reference standards.<h4>Methods</h4>We linked provincial administrative health data to primary care EMR data. The validation cohort included 116,675 Manitobans aged >18 years with at least one primary care visit between April 1998 and March 2015. Hospital records, ...[more]

PMID: 38505786

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Project description:Validation of algorithms for selecting patients from healthcare administrative databases (HAD) is recommended. This PATHFINDER study section is aimed at testing algorithms to select rheumatoid arthritis (RA) patients from Tuscan HAD (THAD) and assessing RA diagnosis time interval between the medical chart date and that of THAD. A population was extracted from THAD. The information of the medical charts at the Rheumatology Unit of Pisa University Hospital represented the reference. We included first ever users of biologic disease modifying anti-rheumatic drugs (bDMARDs) between 2014 and 2016 (index date) with at least a specialist visit at the Rheumatology Unit of the Pisa University Hospital recorded from 2013 to the index date. Out of these, we tested four index tests (algorithms): (1) RA according to hospital discharge records or emergency department admissions (ICD-9 code, 714*); (2) RA according to exemption code from co-payment (006); (3) RA according to hospital discharge records or emergency department admissions AND RA according to exemption code from co-payment; (4) RA according to hospital discharge records or emergency department admissions OR RA according to exemption code from co-payment. We estimated sensitivity, specificity, positive and negative predicted values (PPV and NPV) with 95% confidence interval (95% CI) and the RA diagnosis median time interval (interquartile range, IQR). Two sensitivity analyses were performed. Among 277 reference patients, 103 had RA. The fourth algorithm identified 96 true RA patients, PPV 0.78 (95% CI 0.70-0.85), sensitivity 0.93 (95% CI 0.86-0.97), specificity 0.84 (95% CI 0.78-0.90), and NPV 0.95 (95% CI 0.91-0.98). The sensitivity analyses confirmed performance. The time measured between the actual RA diagnosis date recorded in medical charts and that assumed in THAD was 2.2 years (IQR 0.5-8.4). In conclusion, this validation showed the fourth algorithm as the best. The time interval elapsed between the actual RA diagnosis date in medical charts and that extrapolated from THAD has to be considered in the design of future studies.

Dataset Information

Identifying patients with diagnosed cirrhosis in administrative health databases: a validation study.

Objectives

Methods

Results

Conclusion

Publications

Identifying patients with diagnosed cirrhosis in administrative health databases: a validation study.

Similar Datasets

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