TS-PASS: Methodology to Help Reduce Health Costs and Improve Outcome Effectiveness
A goal of the Military Health System (MHS) is to recapture patients presently lost to the network. In order to meet this goal, the MHS must be able to adequately and safely deal with the increased patient volume. We believe that better management of the entire Healthcare Team’s time is crucial to meet this goal. Factoring cognitive capacity offers a unique way of ensuring task execution – making sure critical work is done to keep the patients safer and healthier with the limited time and resources available in the MHS while paving the way for Accountable Care.
The Tri-Service Patient Acuity and Staff Scheduling (TS-PASS) team initially focused on technologies as a solution to workload management. A recent review of health systems and clinical literature revealed a process methodology that has led to the reduction of hospital readmissions and staff workload in the civilian sector. The methodology harnesses cognitive load balancing and ties available physical resources to patient care requirements in order to improve staff-workload management while also improving care quality, patient safety and satisfaction, and reducing readmissions. This perfectly complements the MHS goals of reducing per capita costs and improving the experience of care. Funded by an award administered by the Telemedicine and Advanced Technology Research Center (TATRC), this project team is applying the methodology in the Naval Medical Center San Diego’s (NMCSD) Pediatric clinic. They are accomplishing this by conducting a careful analysis of historical workload data from Pediatrics and applying this information to improve task execution of the newly integrated Medical Home Team preventing readmissions and lowering resource utilization.
The key tool is the cognitive load balancing concept that would address the assignment of resources (for a physical resource model) to meet patient care demands. Using cognitive load modeling and balancing, the current workload management process transitions the solution to a cognitive resource model to maximize clinical effectiveness and efficiency.
The project team is currently supporting a retrospective quality improvement project in NMCSD’s Pediatric Clinic. Since the project could scale very quickly, we would plan to expand to a research project that would utilize concurrent data to optimize resource allocation proactively. A concurrent analysis of data using existing information systems would complement the present review of retrospective data. The team could be ready to start the concurrent model within two months of launch and provide the “load balancing” capabilities within three months after that. Initial results should be ready to review within ten months.
The initial costs for this project include the cost of deploying a team to teach the key methods and implement the methodology. Specific costs would be based on the team size and budget parameters, along with the level of research desired. The cost estimates would range from $2 million to $7 million. The annual training cost is $240,000 per inpatient facility and $60,000 per outpatient facility. However, please note that based on sizable anticipated cost savings (with an ROI of 500% based on a project business case already developed).