title: Understanding caseload and practice through analysis of therapeutic state transitions.
abstract: Increasing uptake of electronic medical records (EMRs) offers opportunities for analysis and quality assurance of clinical practice; but making appropriate inferences about chronic disease management is non-trivial. We propose a state-transition model for analysis of chronic disease therapy by community practices based on clinical practice guidelines. We abstract guideline recommendations to key therapeutic states, and map electronic prescribing data into a series of states and transitions, which can then be interpreted with respect to the recommendations of the guideline. By applying our approach to a patient cohort diagnosed with both hypertension and diabetes mellitus, we demonstrate that the method identifies cases at risk of suboptimal care, deserving further review by General Practitioners (GPs).
authors.affiliation: Advanced Computing Reseach Centre, University of South Australia.
authors.forename: Jim
authors.initials: J
authors.lastname: Warren
authors.forename: Svetla
authors.initials: S
authors.lastname: Gadzhanova
authors.forename: Jan
authors.initials: J
authors.lastname: Stanek
authors.forename: Ivan
authors.initials: I
authors.lastname: Iankov
mesh_terms: D001315:Australia; D019090:Case Management; D003627:Data Interpretation, Statistical; D048909:Diabetes Complications / Q000188:drug therapy; D003920:Diabetes Mellitus / Q000188:drug therapy*; D004358:Drug Therapy / Q000706:statistics & numerical data*; D004359:Drug Therapy, Combination; D005194:Family Practice / Q000592:standards*; D006801:Humans; D006973:Hypertension / Q000150:complications / Q000188:drug therapy*; D016347:Medical Records Systems, Computerized; D017410:Practice Guidelines as Topic; D010818:Practice Patterns, Physicians' / Q000592:standards / Q000706:statistics & numerical data*; D011785:Quality Assurance, Health Care; D019035:Rural Health Services