title: Enabling claims-based decision support through non-interruptive capture of admission diagnoses and provider billing codes.
abstract: The patient problem list, like administrative claims data, has become an important source of data for decision support, patient cohort identification, and alerting systems. A two-fold intervention to increase capture of problems on the problem list automatically - with minimal disruption to admitting and provider billing workflows - is described. For new patients with no prior data in the electronic health record, the intervention resulted in a statistically significant increase in the number of problems recorded to the problem list (3.8 vs 2.9 problems post-and pre-intervention respectively, p value 2×10(-16)). The majority of problems were recorded in the first 24 hours of admission. The proportion of patients with at least one problem coded to the problem list within the first 24 hours increased from 94% to 98% before and after intervention (chi square 344, p value 2×10(-16)). ICD9 "V codes" connoting circumstances beyond disease were captured at a higher rate post intervention than before. Deyo/Charlson comorbidities derived from problem list data were more similar to those derived from claims data after the intervention than before (Jaccard similarity 0.3 post- vs 0.21 pre-intervention, p value 2×10(-16)). A workflow-sensitive, non-interruptive means of capturing provider-entered codes early in admission can improve both the quantity and content of problems on the patient problem list.
authors.affiliation: Department of Biomedical Informatics, Columbia University, New York, NY ; Department of Medicine, Columbia University, New York, NY.
authors.forename: Colin G
authors.initials: CG
authors.lastname: Walsh
authors.affiliation: Department of Biomedical Informatics, Columbia University, New York, NY ; Department of Information Technology, NewYork-Presbyterian Hospital, New York, NY.
authors.forename: David K
authors.initials: DK
authors.lastname: Vawdrey
authors.affiliation: Department of Medicine, Columbia University, New York, NY ; Department of Biomedical Informatics, Columbia University, New York, NY.
authors.forename: Peter D
authors.initials: PD
authors.lastname: Stetson
authors.affiliation: Department of Information Technology, NewYork-Presbyterian Hospital, New York, NY.
authors.forename: Matthew R
authors.initials: MR
authors.lastname: Fred
authors.affiliation: Department of Biomedical Informatics, Columbia University, New York, NY.
authors.forename: George
authors.initials: G
authors.lastname: Hripcsak
mesh_terms: D059019:Clinical Coding; D057286:Electronic Health Records; D006801:Humans; D007344:Insurance Claim Reporting; D038801:International Classification of Diseases; D008501:Medical Records, Problem-Oriented; D010343:Patient Admission; D014584:User-Computer Interface; D057188:Workflow