- Traditional Change Models
- Disparate Change Groups
- Uncontained Change
- No Standard Change Approach
- Tools Focus
- Reliance on Benchmarking
- Changes Are Not Based On Data, Good Data, Or The Right Data
- Changes Made Based On Symptoms, Not Causes
- Systems Versus Processes
- Focus On People, Not On Process
- Lack of Context for Solutions
- Adding Versus Subtracting (Patching)
- Poor Implementation
- No Emphasis On Control
- Management Versus Leadership
Changes Made Based On Symptoms, Not Causes
The majority of metrics in healthcare are lagging indicators of performance, merely symptoms of the process versus true process metrics closely tied to the real-time performance of the process—for example, mortality, morbidity, ventilator-associated pneumonia or VAP rates, falls, and employee engagement. Many metrics are composite metrics, made up of many drivers—for example, patient satisfaction and physician satisfaction.
When improvement (or decline) occurs in lagging or composite metrics, it’s very difficult, sometimes impossible, to relate it back to any changes made.
Finally, lagging data captured in the process is often used as a control for ensuring that the process consistently meets performance requirements. Such metrics are almost useless as control metrics, being captured monthly or even quarterly or annually when context is not available and not much could be done to react even if the cause were known. When trying to drive improvement in processes, if the measures used are just symptoms and not real process metrics, it’s just a matter of “track and hope” at best.