Accelerating Analytics for Clinical Pathways to Drive Cost Reduction and Quality Improvement

摘要

Healthcare systems in the United States are under extreme pressure to simultaneously lower costs and improve patient outcomes. There is no global approach to achieve this. Instead, the most successful methodology is to establish quality standards of care and protocols specific to each acute disease. The challenge with this approach is that there is significant level of effort and time required to design and develop each protocol, adjust workflows, gather and aggregate the data and create analytics dashboards to monitor performance and drive improvement. We have found that it takes twelve weeks or more to extract the data and develop the analytics dashboards for a clinical pathway for one disease. This is an extremely worthwhile exercise which we have performed for high-volume and high-risk disease cohorts, but it is simply untenable to do this for all acute diseases. In this project, we provide a solution to accelerate the creation of clinical pathways, acute disease metrics and analytics dashboards. We use data analysis and upfront data processing, producing a solution that is data-driven rather than tool-driven. This solution allows us to create acute care quality programs and analytics dashboards more rapidly with less work effort. Additionally, we can use the same data analysis to help define better programs, rather than simply measure pre-defined protocol metrics.