Multi-Institutional Implementation of Quality Decisions: a Clinical Decision Support Analytics Tool to Drive Outcomes

项目总结/文摘

Project Summary/Abstract Phrase Health is a clinical decision support (CDS) analytics company that empowers health systems to deliver high value clinical care through data-driven improvements of CDS. CDS enhances health‐related decisions and actions with pertinent, organized clinical knowledge, and patient information. For example, physicians may have trouble remembering to order all guideline-recommended care for sepsis. CDS delivered via an order set in the electronic health record (EHR) can simplify this process and reduce mortality by bundling the recommended diagnostic and therapeutic orders together. However, CDS may fail to improve outcomes because: (1) the CDS tool is underutilized; (2) the user may not follow the recommended action from the CDS; (3) the recommended action may not lead to the appropriate evidence-based practice (EBP); and/or (4) the EBP may not translate to the expected outcome in a novel population. Healthcare organizations need an efficient, rigorous, and scalable process evaluation method to diagnose when and why CDS is not leading to the intended improvements. In Phase 1, our team demonstrated the technical feasibility and usability of a new software product, Quality Decisions, that guides quality improvement (QI) advocates of all experience levels to (1) rigorously evaluate the impact of CDS on clinical outcomes and (2) convert data-driven insights into action. In this Phase 2 proposal, we will use the RE-AIM framework to evaluate implementation of Quality Decisions at three diverse health systems (Children’s Healthcare of Atlanta, Children’s Hospital of Philadelphia, and The University of Vermont Health Network). In Aim 1 of this proposal, we will evaluate the implementation effectiveness of Quality Decisions. Our primary outcome will be how often the software leads to (1) new QI or CDS intervention(s), (2) increased confidence in CDS effectiveness, or (3) changes in cohort or measure definitions. Using mixed methods including surveys, log data, and focus groups, we will evaluate implementation efficacy, adoption, and fidelity. We will also assess implementation barriers and facilitators using the Consolidated Framework for Implementation Research. In Aim 2, we will determine the customer resources required to implement Quality Decisions at scale. In a pilot phase, each health system will implement the software for a limited number of CPGs and collect hours of work required to get the software up and running. In an expansion phase, we will estimate the number of institutional CPGs that could feasibly be incorporated into the software and the number actually built in one year. At the end of this project, we will have collected the primary data required to commercialize our software to potential customers including (1) a description of the customer resource requirements to use the software across CPGs in a health system and (2) implementation outcomes demonstrating that users use the software frequently as intended and gain meaningful insights. These data will demonstrate value for future cust omers and investors, allowing us accelerate the translation of knowledge into better health outcomes.