Abstract: Based on experience with clinical decision support (CDS) linked to electronic health record (EHR) data and appearing within clinical workflow, we will discuss possibilities for making use of extensive clinical data available electronically. EHR patient data may be linked with CDS systems external to the EHR to process complex conclusions about the state of the patient and to make recommendations for next steps in therapy that can be returned for presentation within the EHR for real-time CDS individualized to the patient whose record is being viewed. The core systems with clinical knowledge encoded for automated application to electronic patient data could also be used, with different interfaces, for direct-to-patient applications. EHR data may also be used in analyses across health care systems for quality monitoring. While some types of EHR data are in structured, computable formats (diagnoses, lab values, prescriptions, etc.), large amounts of EHR data are in unstructured free text. This session will present an example CDS (ATHENA-CDS) and example projects processing EHR free-text data. We will discuss ways in which integrating EHR data with CDS and with quality measures may transform clinical practice not only by providing alerts and reminders, but by linking multiple threads for complex disease management and opening the way for rapid-cycle quality assessment/improvement. We will also discuss the possibility of integrating patient preferences to enhance shared decision-making. We will briefly discuss potential applications of risk prediction tools and future incorporation of genomic dtaa. We will also discuss challenges to effective use of CDS, including alert fatigue and the cognitive cost of interruptions, and related issues of EHR design.

mgoldstein-abstract.txt · Last modified: 2013/08/25 23:26 by stuo
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