This presentation illustrates the concept of clinical measurement and the connection between measurement and providers, using illustrations to show the design of moving information from measuring to point-of-care providers responsible for patient care. Analysis of clinical measures identifies the drivers of outcomes. Presentation of these drivers is designed to accommodate the point of view of the care provider, at a frequency that allows timely changes in the delivery of care in order to improve outcomes. An example of this comes from the Partnership for Patients initiative to reduce readmissions.Methods/process/procedures
How we present data, at what frequency, to whom (1) when the measure is an outcome, these measures are reported quarterly. This gives the clinical leaders’ time to react, investigate, and implement a plan before the next wave comes crashing down. (2) Deep dive measurement (regression analyses, special studies, etc) focuses on drivers of the outcomes in order to understand where the daily and weekly focus should be. (3) Daily and weekly, clinical leaders and clinicians see the drivers, focusing on the items that are meaningful in terms of influencing outcomes. These daily/weekly dashboards help them know in near real time if they are hitting the target so they can course correct and ultimately change the outcome.Results
Example: Readmissions study. The state of readmissions was examined, broken out by condition. Regression analysis revealed that having a medical index admission, older age, and most importantly a lack of follow-up appointment after discharge had a much higher likelihood of readmission. These data indicate the need to create a dashboard/dynamic report that tracks the highest-risk patients to make sure they get follow-up. The highest rate of readmission was for a small sample of patients with a high likelihood of readmission. This is a population that should be specifically called out in the clinical measures presentation, at a frequency that allows for timely intervention.Discussion/outcomes
Clinical measures make the greatest difference in optimizing clinical care delivery when the measures are presented in a timeframe that allows clinical leaders time to react, investigate, and implement a plan. In-depth analysis of clinical measures should identify the drivers of outcomes. Those drivers should be presented near real time to clinical leaders and clinicians, with special attention to specific populations at highest risk for harm. With accurate and timely feedback on the drivers of outcomes, care delivery can be adjusted to optimize outcomes and minimize harm.