Synthesis, Expansion, and Iteration

We’ve been busy over the past month. Team members have presented their machine learning tool at a conference in Nashville, organized a panel discussion on “Engineering Innovation for Clinical Impact,” been part of a multi-stakeholder symposium on data sharing; talked to over a dozen different individuals from industry, government, academia, and nonprofits; and paid site visits to various stakeholders in three different cities. In addition, throughout October, the team systematically organized and summarized all the project notes from interviews, meetings, and studios that we have gathered over the course of the project thus far.

What is abundantly clear is that the amount of complexity and information present in the system can become overwhelming very quickly. In our interviews, stakeholders have talked repeatedly about the complexity of the system, and the tendency to move from issue to issue without finding an end to each thread. Our challenge is to manage this complexity so that we avoid getting lost in the system ourselves; to make real change.

Recently, we attended a talk by Peter Pronovost on using engineering in healthcare, and he made a very astute observation: doctors are trained to solve puzzles and engineers are trained to solve problems. We would agree! The engineers in our group remember working through hundreds, sometimes thousands of problems a week to really understand the mathematical material.

Pronovost points out that doctors are specifically trained to figure out what is wrong with the patient. They are trained repeatedly in puzzles: given a case study, they are asked to perform diagnoses on different patients. Pattern recognition coupled with experience and an eye for humanity is what drives medicine.

Our team has been very lucky to have both sets of minds either as members or as advisers. But when faced with a complex systems challenge, the mindset of solving puzzles and/or problems can lead us down frustrating rabbit holes that seem to have no end. Sometimes we search for puzzles and problems to go after: a hammer looking for nails, or a puzzle piece which matches shape but not orientation of the board. So how do we get around this?

The third piece of the puzzle (pun intended) for our project has been to invoke design in the face of the multitude of puzzles and problems that the system presents. Keeping with Pronovost’s terminology, someone who can solve crossword puzzles is incredibly skillful, but the person who designs those puzzles has a different skillset. They think at a higher level of intentionality, making the problem-solver focus on the problem at hand and apply their skills in a useful way.

Helping Us Design the Puzzles and Problems we Need to Solve

In early November, we brought our research synthesis along with identified opportunities and future directions to our Social Innovation Fellows from the Center for Social Design at the Maryland Institute and College of Art (MICA). They took our ideas and led us through a series of exercises that cycled through the breaking down and rebuilding of our ideas/concepts in an effort to clarify and target our thinking; to clearly identify the problems we want to solve.

It was an invigorating experience, where we started off with themes around data, culture, and money and ended up with creative definitions of the critical issues within the system. This method of zooming in and out to tune out distraction and gain clarity is second nature to designers, and we are grateful that our team can utilize this thinking to avoid getting tangled in complexity.

The Design Process

In the next month, we intend to finish this process as a framework for developing recommendations. It is an exciting time. Mostly because once this is over, the other team members can move forward with what they do best: solving problems and puzzles.