In this blog post, we have thrown light on how healthcare organizations can fast-track the Optimization of Cost-Quality Equation and enhance Consumer Engagement by leveraging modern technology solutions correctly.
How Technology Drives Your VBC Goals of Cost-Quality Equation Optimization and Consumer Engagement Enhancement
- Performing calculations for drug dosing
- Identification of the reportable condition by analyzing the inputs from EHR
- Evaluating the guidelines for drug formulations
- Initiating automated reminders for medication or appointments
- Analyzing the severity index for different diseases to suggest treatment.
- Yale and Mayo Clinic developed a specialized CDSS application for patients with head injuries. The application evaluated the severity of the injury and significantly reduced the number of unnecessary CT scans.
- The Department of Veteran Affairs site in Indiana without lowering the quality of the healthcare reduced unnecessary lab tests by over 11% which saved the patients as much as $150,000 – thanks to the CDSS tools it implemented.
- Provider benchmarking
- Site of Care (SOC) optimization
- Reports related to care navigation and point-of-care delivery
- Reports related to patient outcomes
- Gap Analysis,
- Evaluation of Performance-based KPIs,
- Timely Intervention,
- Efficient Patient Engagement,
- Thereby, Achieve Better Patient Care Outcomes.
Here’s an interesting story of how a leading healthcare provider utilized technology to achieve better outcomes.
Challenge: The provider had been facing challenges around decreasing the length of hospital stay for patients undergoing hip and knee replacement surgeries.
Technology Adoption: The organization leveraged existing research and a validated prediction model to capture presurgery records from the physician’s offices. The propensity score was put into the clinical workflow so all providers could use it in their preoperative patient discussions.
Results: The program successfully decreased hospital stay length, cutting costs and improving patient experience scores in the HCAPHS Care Transition measures.
- Appointment scheduling
- Patient record entry and management
- Insurance verification
- Consent forms management
- Staff activities and roster management
- Billing management
- Multilingual support and more.
Image recognition and deep learning models within AI are also enabling providers to make intelligent predictions such as forecasting high-cost claims events for corrective actions. This is yielding better patient outcomes and helping healthcare organizations meet their value-based care goals.
- Mayo Clinic investigators demonstrated how predictive analytics could be leveraged to accurately predict long-term survival outcomes of patients diagnosed with borderline or locally advanced pancreatic cancer prior to their surgeries.
- The University of Chicago Medical Center (UCMC) used predictive analytics to tackle the problem of operating room delays. It combined real-time data with a complex-event processing algorithm to improve workflows, create notifications, and streamline the handoffs from one team to the next for each step of the Operating Room process. The effort decreased turnover time 15% to 20% (four minutes per room), which was expected to save the hospital up to $600,000 annually.