title: On the efficacy of programmatic searching of medical claims for the occurrence of hospital admissions for coronary artery disease.
abstract: This study was conducted in order to test the proposition that medical claim records, when searched electronically, can be reliably used to locate individual, disease-specific hospital admissions. For the study, admissions for coronary artery disease (CAD), self-reported by employer-sponsored recipients of chronic disease management (DM) services, were verified against physician-compiled medical records. Confirmed events were then subjected to electronic searching of the corresponding medical claim records using a variety of conditional requirements for included types of evidence. At maximum sensitivity (92.6%), the search algorithm positively identified 126 of 136 verified admissions while falsely identifying 1,025 others. At maximum specificity (98.7%), the algorithm positively identified 55 of 136 while falsely identifying 13. The maximum value of the true positive to false positive ratio was 4.47. The maximum Youden index value was obtained by requiring that the diagnostic intensity (proportion of event-related claims having a CAD-related diagnosis code) have a minimum value of 0.20. The study concluded that an admission search algorithm applied to typical commercial medical claims generated results that are unsatisfactory for the determination of admission incidence in the CAD population. While the methods may be sound, they fail to overcome the weaknesses of the searched data.
authors.affiliation: Cardium Health, Farmington, Connecticut 06030, USA. jnestor@cardiumhealth.com
authors.forename: James R
authors.initials: JR
authors.lastname: Nestor
authors.forename: Janet G
authors.initials: JG
authors.lastname: Knecht
mesh_terms: D000465:Algorithms; D003324:Coronary Artery Disease / Q000601:surgery; D019468:Disease Management; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D007345:Insurance Claim Review / Q000458:organization & administration*; D016347:Medical Records Systems, Computerized; D010343:Patient Admission / Q000639:trends; D014481:United States