Inferring 'Therapeutic States' of Patients from Community Electronic Prescribing Data

Jim Warren, Jan Stanek, Svetla Gadzhanova, Ivan Iankov, Gary Misan
2006 Journal of Health Informaticsnet   unpublished
We set out to devise a method for analysis of chronic disease therapeutic decision making with specific emphasis on practice patterns across multiple consultations and providers within a single community-based practice. We examine treatment by abstracting each patient's therapeutic state at any given time as a vector of n Boolean state variables, each representing a key decision in the domain under examination. We illustrate the method where the state variables are inferred from electronic
more » ... rom electronic prescribing data for treatment of hypertension at a rural practice. We find that graphs of therapeutic state transitions, at various levels of granularity, can provide an overview of prescribing practice or help to identify cohorts of patients that warrant further examination. The graphs, however, are sensitive to heuristic interpretation of the data. A direction for further research is to identify the principles for inference of therapeutic state that are adequately sophisticated for accurate classification of cases and yet interpretable for clinical audit.