{"id":739147,"date":"2021-05-20T08:52:13","date_gmt":"2021-05-20T15:52:13","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-blog-post&p=739147"},"modified":"2021-05-20T08:53:39","modified_gmt":"2021-05-20T15:53:39","slug":"case-study-covid-19-vaccine-eligibility-bot","status":"publish","type":"msr-blog-post","link":"https:\/\/www.microsoft.com\/en-us\/research\/articles\/case-study-covid-19-vaccine-eligibility-bot\/","title":{"rendered":"Case Study: Covid-19 Vaccine Eligibility Bot"},"content":{"rendered":"
As Covid-19 vaccine rollouts began in January 2021, it became clear that the phased eligibility approach in use by the United States was causing widespread confusion. The question of eligibility has been a complex topic, with rules and qualifications differing state-by-state \u2013 and sometimes differing at county and city levels. In states like Arizona and Massachusetts, we observed eligibility differences from county to county. In Los Angeles and Chicago, eligibility criteria were different between large cities and their surrounding counties. In North Dakota, the vaccine eligibility criteria even varied between pharmacies and vaccinating locations.<\/p>\n
Because of the technical complexity in navigating this information space, there is a healthcare equity concern as to the ability of different groups to access vaccination resources. Qualifying individuals in hard-hit communities are underserved compared to the well-connected and technically savvy. This is often due to a gap between the information that exists and the ability of people to access it \u2013 on their own terms, in a form they understand, and in their own language.<\/p>\n
Our goal with this project was to create a conversational chatbot to streamline the determination of vaccine eligibility in the United States, aggregating policies across regions and policy updates over time. Users would interact with the bot via a simple workflow of Yes or No questions to determine their current eligibility and be directed towards authoritative sources for confirmation. We designed this bot to be accessible across a range of communication channels (e.g., web, SMS, and WhatsApp), with localizations available for communities that may otherwise be disadvantaged due to low levels of English proficiency.<\/p>\n
A risk we identified right away was that inaccurate or out-of-date data could become a source of misinformation and confusion. We engaged with partners in the healthcare space \u2013 MITRE (opens in new tab)<\/span><\/a> and The Fight Is In Us (opens in new tab)<\/span><\/a> \u2013 to mitigate this risk, curating and auditing these criteria as they changed over the course of the pandemic.<\/p>\n One key decision we made in the early stages of this project was to develop it in the open. We wanted this to be an opportunity to build trust \u2013 not just with our partners and their stakeholders, but with the open-source developer community and potential hosts of adapted bots around the world. To achieve this goal, we used GitHub as the central repository of all information relating to vaccine eligibility in our target deployment context (i.e., the United States). To support rapid updates and adaptation to other contexts, we developed a simple data schema that could capture a hierarchy of regional policies using the familiar nested filesystem model.<\/p>\n One of our goals with this system was to make it accessible to non-developers. GitHub is traditionally a platform used for software engineering, and the partners using this platform would not necessarily be familiar with version control systems such as git developed for source code. We therefore built a Data Management Portal that uses GitHub\u2019s API to interact with the knowledge repository automatically, on behalf of the party deploying the bot. This approach gave us the ability to build on top of GitHub\u2019s trusted infrastructure and workflows to provide data editing tools for a non-developer audience.<\/p>\nBot deployment<\/h2>\n