Addressing Scaleability of New Models of Care

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About this Client
Our client is a non-profit medical research organization that pioneers new and smarter technologies, policies, and practices to make high-quality healthcare more accessible at a lower cost to all Americans.

Executive Summary
Our client wanted to explore how they could invest in research that would have deeper impact.  Could they move beyond just studying healthcare and publishing papers on their results, and delve into designing potential solutions?  They discovered a geriatric practice that was testing a new Medicare payment model called Independence at Home (IAH).  The aim of IAH is to share savings stemming from keeping high cost frail, elderly patients out of the hospital and stable in their homes. The practice did this by making housecalls to their patients, which was effective at delivery quality care but inefficient and costly.  Our client engaged Inceodia to use a design approach to discover solutions that could enable the geriatric team to address inefficiencies that were preventing them from scaling their practice.

The Challenge
The practice provides care to 600 geriatric patients in their homes in a large metro area.  The doctors, nurse practitioners and social workers drive to an average of 5 – 6 patient’s homes in a day.  In a fee-for-service payment model, this was not enough visits to pay the salaries and overhead of the practice.  Including the office paper work, many of the providers were spending 10 hours a day supporting their patients.  There was a long waitlist of patients who really needed their services.  Traffic had intensified in the last few years, increasing the amount of time the providers spent driving.  And the practice had a desire to expand to new neighboring communities yet their operational processes had grown organically so they were struggling with how to duplicate the service they offered.

The Solution
Our client engaged a human-centered design team from Inceodia to use a design thinking approach to discovering the frustrations and workarounds the practice was encountering and finding potential solutions that would enable them to scale.  We observed the teams in the field as they visited patients and documented their journeys, which allowed us to develop empathy for the things that mattered to them as they delivered their services.  This uncovered the “secret sauce” that made them effective at keeping their patients out of the hospital, key to allowing the practice to replicate in new areas.  We also observed the teams in the office to see understand the support processes that enabled or inhibited their inefficiencies.  This discovery approach uncovered some pain points and areas of inefficiencies such as urgent visits that took practitioners across town and a lack of tools to help dispatch providers, for better scheduling and routing of their days.

We held bi-weekly co-design sessions with the physicians, which allowed us to find better design ideas that addressed their needs for autonomy while working in the field.  Before deploying any solutions, we did a 6-week time analysis of their days using a combination of surveys, GPS tracking and patient billing records to create a baseline view of their current scheduling and routing process.  We then introduced a solution that allowed them to see their daily tracks and the office to use a dispatch view of the entire practice to better deploy practitioners when urgent calls came in.  We iterated and refined the solution, continuing to test and compare against the baseline data to ensure we were continuing to make efficiency improvements.

To address one of the biggest time sinks of the physician’s day, the administrative paperwork, we brought in a coding expert who could take a holistic view of their documenting practices.  The coder worked with the practitioners to create templates that would standardize their documentation, creating a consistent approach that could be replicated when new practices were started.  The coder then coached the practitioners on the implementation and refined on the process so that it worked well in their current practice.

Our baseline data revealed that practitioners were seeing an average of 5 patients per day which typically took about 6 hours.  And they spent another 4 hours in care coordination and charting.  By improving their urgent dispatch, we were able to add another .5 patient visits.  By further improving the scheduling process to better distribute patient visits geographically, we saw a potential to add another 1 patient visit per day.  The time spent on documentation decreased somewhat but by studying other practices we discovered much broader improvements that could be made by adding in more support for care coordination.

On a more human level, we were able to decrease the stress and isolation of the physicians who were working in the field by enabling them to easily see where their colleagues were throughout the day.  Our client found that only 15% of the frail, elderly homebound patients in the US were receiving the care they needed.  Building workforce capacity and developing more practices that could do this kind of work is key to enabling scalability of the housecall model.  This discovery of approaches that could help build a cohesive workforce was the real breakthrough of our work, enabling much broader impact of our client’s research than had been previously achieved.