The Most Urgent Matter Facing Designers Today: Data in Healthcare
I was honored to contribute to an article in the Fast Company Innovation by Design 2021 Issue, talking about what I think is the most urgent matter facing designers today: The design of data in healthcare
If there is anything that the COVID-19 pandemic has taught us, it is that data is critical for healthcare decision-making and public health planning. There isn’t a day when every major website or news publication doesn’t present the latest statistics on COVID-19 disease rates and vaccine uptake. The availability of this data provides the unique opportunity for artificial intelligence to make significant contributions to health and health outcomes, but AI is only as good as the quality of data on which its algorithms are developed, and what we have witnessed is a struggling public health data pipeline as the pandemic continues to persist. What have we observed about this struggle for data?
First, there is no universal health information technology system for public health, given the lack of funding and investment over the last two decades. As a result, public health agencies, healthcare systems, and laboratories struggle on a daily basis to share information on COVID-19 cases, hospitalizations, deaths and vaccine uptake. There are 47 metrics that hospitals, laboratories, and acute care facilities are mandated to report on a daily basis to the federal government, such as the number of adult and pediatric cases of COVID-19, hospital occupancy, or the availability of ventilators. Because the technology systems are not connected and cannot seamlessly talk to each other, the work of reporting and integrating this data is manual, burdensome, and prone to generating inaccurate data. I can only imagine the reliance on fax, e-mail, paper and manual entry into excel spreadsheets by beleaguered health professionals that has occurred since this pandemic started.
To address this lack of data infrastructure, government-funded information technology solutions were created, but the results were disastrous. The Centers for Disease Control and Prevention spent $44 million on a website designed by the consulting firm Deloitte called VAMS (Vaccine Administration Management System) to help states with vaccine supply tracking, appointment scheduling, and vaccine uptake. Unfortunately, the software and user experience were dismal: ‘It won’t work on Internet Explorer; it only works in Chrome. The ‘Next’ button is all the way down and to the right, so if you’re on a cell phone, you literally can’t see it,’ one user said. ‘In the first round, people using VAMS mostly had advanced degrees. If you’re 75 and someone asks you to log into VAMS, there is zero way it’ll happen without help.’ Because of the terrible design, some states actually decided to drop VAMS (which was free to use) and decided to pay extra money for alternative technology systems that functioned more effectively. Worse yet, some entities decided to track everything by paper instead and then ironically had to find volunteers to sit in a room and copy all the information into VAMS. If a technology system is so hard to use that individuals revert to paper, that does not bode well for data availability, quality, and accuracy.
Public health agencies and states explored public-private partnerships to acquire access to more modern technology but this came with unintended consequences. For example, at the beginning of the pandemic, Google secured $55 million in contracts with the state of California to support COVID-19 testing (which included symptom screening, appointment booking, and test result reporting). However, enrollment was exclusively online with no ability to talk to an agent on the phone, and there were delays in real-time reporting about testing site locations, which would disproportionately impact underserved communities who had a higher numbers of pop-up testing sites. Furthermore, individuals were required to sign up for Gmail accounts and had to give permission to Google share personal data with third party entities, raising privacy concerns. The partnership was eventually terminated, but if the design of the platform leads to the inadvertent exclusion of certain types of individuals, such as those who may be older, sicker, and less technology-savvy, there will be implicit bias in the data, no matter how amazing the user experience or technology is.
Finally, these data barriers don’t even capture the most important next steps needed, which includes the integration, viewing, and deeper exploration of this imperfect and messy health data, and most critically, the need to effectively translate the data into a compelling call to action for Americans who are reluctant to get vaccinated.
Click here for information about creative commons licensing. Disclosures: Medical Advisory Board of GoodRx.