Care Model 101
07/10
Care models powered by a modern tech stack offer unprecedented data about clinical pathways and outcomes, operational efficiencies, and user experience. Today’s care models are truly apples to oranges when comparing them to oral conversations in exam rooms all documented by billing systems designed to maximize revenue from insurance companies. But this opportunity also comes with complications. A big fat hairy question involves measuring an individual clinician’s efficiency and throughput. Do we measure individual clinicians on speedy response times? Or how frequently they use standardizations, assuming we’re standardizing for the most evidence-based clinical pathways, assuming quality stems from standardizations? How do we avoid Goodheart’s Law which states “when a measure becomes a target, it ceases to be a good measure.” And once we have defined the data we’ll use to measure the care team, who is responsible for acting on the data and changing human behaviors to optimize the model?
And, for patients, how do they define success? Is it clinical improvement? Or is it preventing decline? Are they ecstatic about our service and singing our praises online or…not? How do we engage with patients around released features to see if they are performing as expected? And how do we solicit ideas from users?
If we have employer or payor clients, how do we choose which metrics to share with them to ensure they focus on the right concepts that prove our value? Both oversharing and under-sharing can cause real heartache over time.
Examples of questions we’ll tackle when considering this component of the care model are:
- What off the shelf tools do we use to view our internal data?
- What reports are needed, when, and who needs them?
- How do we create actionable next steps from our data so our users can actively see improvements in the service?
- How do we know what data to focus on vs. creating reports for creating reports sake?
- How do metrics and targets change as our care model matures over time?
Next: Clinical Proof ⇢