title: Using a diabetes data mart in individualizing diabetes management.
abstract: Constantly changing diabetes care standards makes it challenging to deliver care adapted to the unique condition of the individual patient. The availability of large amounts of data from patient's electronic medical records makes it possible to individualize diabetes management. Initial design of a "patient-specific" hybrid system (physiological-causal probabilistic) of adaptive diabetes models and insulin treatment algorithms will be presented. The system is uniquely derived and tested using a diabetes data mart of about 33,000 patients.
authors.affiliation: Department of Biomedical Informatics, School of Medicine, University of Utah, SLC, UT, USA.
authors.forename: Youssef T
authors.initials: YT
authors.lastname: Al-sheikh
authors.forename: Peter J
authors.initials: PJ
authors.lastname: Haug
authors.forename: Anthony
authors.initials: A
authors.lastname: Wong
authors.forename: Homer R
authors.initials: HR
authors.lastname: Warner
authors.forename: Alan H
authors.initials: AH
authors.lastname: Morris
authors.forename: Katherine
authors.initials: K
authors.lastname: Sward
mesh_terms: D020000:Decision Support Systems, Clinical; D003920:Diabetes Mellitus / Q000188:drug therapy*; D004360:Drug Therapy, Computer-Assisted / Q000379:methods*; D007328:Insulin / Q000627:therapeutic use*; D016347:Medical Records Systems, Computerized / Q000706:statistics & numerical data*; D018802:Patient-Centered Care / Q000379:methods; D057285:Precision Medicine / Q000379:methods*; D014589:Utah
chemical_list: D007328:Insulin