Design Thinking

Learning Launch Tool Applied to Pop-up COVID-19 Testing Sites

Challenge

Before March 2020, my day job was managing a team of biotech program managers. The  cross-functional teams they lead, create novel medical platforms that help people who suffer  from disease live happier and healthier lives. That all changed in early 2020 as COVID-19 was  classified as a pandemic. My company called a code red (all hands on deck). We wanted to  focus all of our resources on the global public health crisis and my team needed to rapidly pivot.  We have some of the worlds best clinicians, scientists, hardware and software engineers who  created a clinical studies platform for remote clinical trial management. This was typically used  for multi-year drug trials not time sensitive pandemics and we never operated any public facing  health clinics. Some of the questions we faced were: How are we going to leverage our existing  infrastructure to help with COVID-19? Could we use our clinical studies platform to screen the  public to see if they qualified for testing? How would we physically test people? How could we  do all of this and fast enough to help?

Tool Selection

Design thinking was well suited for us because we faced very human-centered problems.  People were scared, this strain of the virus was not well understood nor how to solve it, there  were many unknowns, and specific data was not fully analyzed. Several design thinking tools  were used, but I chose learning launch because we needed to quickly and cheaply test and  iterate on our idea. We hypothesized that given the limitations of our current healthcare systems  and testing supply constraints, public health departments needed a faster way to systematically  test communities for COVID-19. We thought there had to be a better solution to testing the  public than having them wait in lines for hours only to be turned away if they ultimately didn't  meet the screening criteria. Our idea was to leverage our existing clinical studies platform and  have people register at home then fill out the CDC COVID-19 testing questionnaire. Once filled  out, they could immediately know if they qualified for testing and then schedule a testing  appointment all within the software platform.

Application

My team quickly added COVID-19 as a new ‘study’ to our clinical platform and began work to  replicate the CDC screener questions. In parallel, our government relations and business  development teams reached out to public health officials to let them know we were working on a  possible solution. We set up a pilot COVID-19 testing site in the parking lot of our office building  using pop-up tents and simple a-frames to use for traffic directions and instructions. We  launched the pilot study to a limited number of people to begin. We staffed the experimental  testing site with our own employee volunteers, used our existing clinical laboratory partners,

health care providers, and physicians network to automatically have a doctor's order created if  the screening criteria was met. Participants had pass the screening criteria and had an  appointment scheduled through the website before being allowed to come on site for a test. We  began testing only a limited number of people per day (< 50 or 5-6 per hour) and would stop  testing every couple days to analyze the data, incorporate learnings, and relaunch with the  improvements.

Insights

We immediately began to iterate and make the service better for the end users. We would test  for a couple days with very limited numbers of people, stop testing, make modifications, and  resume testing - like mini-experiments. We began to understand the pain points and bottlenecks  in our process. We learned quickly which workflows needed improvement, which health care  worker and participant instructions needed refinement, we added training and informational  videos so people knew what to expect at their testing appointment. We added hand signage so  people would better understand what they needed to do without rolling down their windows,  better containing the spread of the virus and reducing risk to our site staff. Based on the data,  we knew those who were the highest risk were being tested first. We were able to take our  clinical study platform and COVID-19 pilot data to private retail partners and key public health  officials and in partnership with them go into production with a free community COVID-19 testing  program. The initial pilot site ramped from 50 per day during the learning launch phase to more  than 500 per day. We scaled rapidly from there, expanding to more than 150 testing sites in 15  states, and today have conducted more than 500,000 COVID-19 tests.    In this case, the learning launch tool helped us confirm our assumptions that our current  healthcare system was ill prepared for a pandemic of this magnitude, testing supplies were  limited and needed to go to the highest risk people first (those who passed the screening  questionnaire), people would be unhappy waiting in line for hours then being turned away like in  many cities at most testing sites, offering appointments made for a quick, efficient, and safe  testing process that had most participants in and out of the testing site within 10 minutes.

Approach

The learning launch tool was essential to our success by allowing us to conduct experiments to  quickly test our hypothesis, find the truth, and solve for real problems mentioned in the previous  section. If I were to do this again, I would still choose the learning launch tool as an approach to  solve this problem.


Design Thinking Learning Launch Tool Applied to Pop - up COVID-19 Testing Sites Challenge Before March 2020 , my day job was managing a team of biotech program managers . The cross - functional teams they lead , create novel medical platforms that help people who suffer from disease live happier and healthier lives . That all changed in early 2020 as COVID-19 was classified as a pandemic . My company called a code red ( all hands on deck ) . We wanted to focus all of our resources on the global public health crisis and my team needed to rapidly pivot . We have some of the worlds best clinicians , scientists , hardware and software engineers who created a clinical studies platform for remote clinical trial management . This was typically used for multi - year drug trials not time sensitive pandemics and we never operated any public facing health clinics . Some of the questions we faced were : How are we going to leverage our existing infrastructure to help with COVID-19 ? Could we use our clinical studies platform to screen the public to see if they qualified for testing ? How would we physically test people ? How could we do all of this and fast enough to help ? Tool Selection Design thinking was well suited for us because we faced very human - centered problems . People were scared , this strain of the virus was not well understood nor how to solve it , there were many unknowns , and specific data was not fully analyzed . Several design thinking tools were used , but I chose learning launch because we needed to quickly and cheaply test and iterate on our idea . We hypothesized that given the limitations of our current healthcare systems and testing supply constraints , public health departments needed a faster way to systematically test communities for COVID-19 . We thought there had to be a better solution to testing the public than having them wait in lines for hours only to be turned away if they ultimately did n't meet the screening criteria . Our idea was to leverage our existing clinical studies platform and have people register at home then fill out the CDC COVID-19 testing questionnaire . Once filled out , they could immediately know if they qualified for testing and then schedule a testing appointment all within the software platform . Application My team quickly added COVID-19 as a new ‘ study ’ to our clinical platform and began work to replicate the CDC screener questions . In parallel , our government relations and business development teams reached out to public health officials to let them know we were working on a possible solution . We set up a pilot COVID-19 testing site in the parking lot of our office building using pop - up tents and simple a - frames to use for traffic directions and instructions . We launched the pilot study to a limited number of people to begin . We staffed the experimental testing site with our own employee volunteers , used our existing clinical laboratory partners , health care providers , and physicians network to automatically have a doctor 's order created if the screening criteria was met . Participants had pass the screening criteria and had an appointment scheduled through the website before being allowed to come on site for a test . We began testing only a limited number of people per day ( < 50 or 5 - 6 per hour ) and would stop testing every couple days to analyze the data , incorporate learnings , and relaunch with the improvements . Insights We immediately began to iterate and make the service better for the end users . We would test for a couple days with very limited numbers of people , stop testing , make modifications , and resume testing - like mini - experiments . We began to understand the pain points and bottlenecks in our process . We learned quickly which workflows needed improvement , which health care worker and participant instructions needed refinement , we added training and informational videos so people knew what to expect at their testing appointment . We added hand signage so people would better understand what they needed to do without rolling down their windows , better containing the spread of the virus and reducing risk to our site staff . Based on the data , we knew those who were the highest risk were being tested first . We were able to take our clinical study platform and COVID-19 pilot data to private retail partners and key public health officials and in partnership with them go into production with a free community COVID-19 testing program . The initial pilot site ramped from 50 per day during the learning launch phase to more than 500 per day . We scaled rapidly from there , expanding to more than 150 testing sites in 15 states , and today have conducted more than 500,000 COVID-19 tests . In this case , the learning launch tool helped us confirm our assumptions that our current healthcare system was ill prepared for a pandemic of this magnitude , testing supplies were limited and needed to go to the highest risk people first ( those who passed the screening questionnaire ) , people would be unhappy waiting in line for hours then being turned away like in many cities at most testing sites , offering appointments made for a quick , efficient , and safe testing process that had most participants in and out of the testing site within 10 minutes . Approach The learning launch tool was essential to our success by allowing us to conduct experiments to quickly test our hypothesis , find the truth , and solve for real problems mentioned in the previous section . If I were to do this again , I would still choose the learning launch tool as an approach to solve this problem .