title: Predictive Analytics In Healthcare: Medications as a Predictor of Medical Complexity.
abstract: Children with special healthcare needs (CSHCN) require health and related services that exceed those required by most hospitalized children. A small but growing and important subset of the CSHCN group includes medically complex children (MCCs). MCCs typically have comorbidities and disproportionately consume healthcare resources. To enable strategic planning for the needs of MCCs, simple screens to identify potential MCCs rapidly in a hospital setting are needed. We assessed whether the number of medications used and the class of those medications correlated with MCC status. Retrospective analysis of medication data from the inpatients at Seattle Children's Hospital found that the numbers of inpatient and outpatient medications significantly correlated with MCC status. Numerous variables based on counts of medications, use of individual medications, and use of combinations of medications were considered, resulting in a simple model based on three different counts of medications: outpatient and inpatient drug classes and individual inpatient drug names. The combined model was used to rank the patient population for medical complexity. As a result, simple, objective admission screens for predicting the complexity of patients based on the number and type of medications were implemented.
authors.affiliation: 1 Bioinformatics and High-Throughput Data Analysis Laboratory, Seattle Children's Research Institute , Seattle, Washington.|2 Predictive Analytics, Seattle Children's Hospital , Seattle, Washington.|3 Data Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington.
authors.forename: Roger
authors.initials: R
authors.lastname: Higdon
authors.affiliation: 1 Bioinformatics and High-Throughput Data Analysis Laboratory, Seattle Children's Research Institute , Seattle, Washington.|3 Data Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington.
authors.forename: Elizabeth
authors.initials: E
authors.lastname: Stewart
authors.affiliation: 4 Institute for Systems Biology , Seattle, Washington.
authors.forename: Jared C
authors.initials: JC
authors.lastname: Roach
authors.affiliation: 5 The Information School, University of Washington , Seattle, Washington.
authors.forename: Caroline
authors.initials: C
authors.lastname: Dombrowski
authors.affiliation: 1 Bioinformatics and High-Throughput Data Analysis Laboratory, Seattle Children's Research Institute , Seattle, Washington.|2 Predictive Analytics, Seattle Children's Hospital , Seattle, Washington.|3 Data Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington.
authors.forename: Larissa
authors.initials: L
authors.lastname: Stanberry
authors.affiliation: 6 Center for Children with Special Needs , Seattle Children's Research Institute, Seattle, Washington.
authors.forename: Holly
authors.initials: H
authors.lastname: Clifton
authors.affiliation: 2 Predictive Analytics, Seattle Children's Hospital , Seattle, Washington.|3 Data Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington.
authors.forename: Natali
authors.initials: N
authors.lastname: Kolker
authors.affiliation: 7 Departments of Biostatistics and Environmental and Occupational Health Sciences, University of Washington , Seattle, Washington.
authors.forename: Gerald
authors.initials: G
authors.lastname: van Belle
authors.affiliation: 8 Department of Pediatrics, University of Washington , Seattle, Washington.|9 Medical Affairs, Seattle Children's Hospital , Seattle, Washington.|10 Department of Biomedical Informatics & Medical Education, University of Washington , Seattle, Washington.
authors.forename: Mark A
authors.initials: MA
authors.lastname: Del Beccaro
authors.affiliation: 1 Bioinformatics and High-Throughput Data Analysis Laboratory, Seattle Children's Research Institute , Seattle, Washington.|2 Predictive Analytics, Seattle Children's Hospital , Seattle, Washington.|3 Data Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington.|8 Department of Pediatrics, University of Washington , Seattle, Washington.|10 Department of Biomedical Informatics & Medical Education, University of Washington , Seattle, Washington.
authors.forename: Eugene
authors.initials: E
authors.lastname: Kolker