First Resort: Building a smart intake and referral system at DC Public Library

The constellation of social service and legal aid organizations, each already facing operational strain, are insufficiently interconnected to form a coherent safety net. For clients, even those assisted by existing social workers and agencies, this means that every additional service needed is a foray into the unknown, as there is scant capacity to get a rigorous sense of the quality and appropriateness of the referral being made. Conversely, service providers must contend with receiving referrals of uncertain quality, which are time-consuming to process or turn away, and weight, which means that it is difficult to predict whether an organization has capacity to accept a referral. Taken together, this leads to a system marked by early-stage chaos, where individuals and organizations are suboptimally matched, increasing the search cost for both. 
 
For many, libraries are the first resource for finding social and legal services. Matching a potential client with a suitable organization from the constellation of small service providers remains a difficult task, one that libraries are not necessarily equipped to deal with. 
 
DC Public Library, Open Referral Initiative, and Social Impact Lab are collaborating on a Knight Prototype Grant to build a smart intake and referral system designed to be housed at libraries. On the foundation of Open211 and other service data, we're building a coded classification system of service needs, so that new providers can easily identify which services they do and do not fulfill. Then, we're combining existing intake and interview flows with the aim not of eliminating potential clients from consideration, but matching them to the best-fit service in the fewest number of questions. Finally, we're building a framework that will allow others to build on our work, contributing to a common taxonomy and logic that can be adapted across geographies.
 
SIMLab has been using this project as a model to develop other similar projects in different geographies with different topical focus areas. Our end goal is to build flexible, integrated interview and logic flows that terminate in service codes, which can be used across multiple geographies. Multiple systems, expert organizations, and localities can contribute to and adapt this common, foundational classification system and interview logic, resulting in a stronger product than any single entity would be able to produce individually. In this way, other geographies beyond our selected project partners can benefit from the initial classification work done, rigorously integrate locality-specific services and questions, and match local service provider capabilities to the corresponding service codes. Organizations that participate in this intake flow can then not only be sure that referrals produced by the system are an appropriate match for their capabilities, but can also more confidently refer clients to outside organizations for additional services.  Taken together, this will hopefully minimize false referrals and repetitive intake and search processes for end clients and providers alike. 
 
In this session, SIMLab will present progress on the prototype, projects that are in development related to the prototype, such as an eligibility fingerprint system, and detail how other organizations can be involved and contribute to the framework.
 
Keith Porcaro is a lawyer and technologist with a background in helping organizations and individuals optimize around shifting systems. Keith leads SIMLab’s Legal and Land work, where he works to make legal systems more accessible and efficient. Keith’s background sits at the intersection of law and technology: prior to joining SIMLab, he advised technology startups on legal and operational issues, worked as legal counsel and content strategist for Reboot, a service design firm, and freelanced as a web developer. Keith has a J.D. from Duke University, where he was the Technical Editor for the Duke Law & Technology Review and a BSFS in International Politics from Georgetown University’s School of Foreign Service. He is proficient in Mandarin, Ruby, and JavaScript, and is licensed to practice law in California.