Data Challenges and Opportunities
State health and human services (HHS) enterprises encompass a diverse range of divisions that cover child and adult health, behavioral health, juvenile justice, and more. Although separate, these divisions overlap in the populations they serve. Data, particularly the ability to analyze and share data, can enable these different divisions to work together to improve outcomes. However, there are still obstacles to making different divisions’ IT systems interoperable, including challenges with data collection, governance, privacy, and finances. Furthermore, there are substantial limitations with current solutions that only use structured data when the majority of data is unstructured, in the form of images, case notes, and journal articles. Unstructured data can provide a more holistic account of an individual and inform more targeted, focused, and effective policies. Leveraging unstructured data requires new types of solutions, such as artificial intelligence, that include cognitive computing and machine learning systems. To understand the challenges states face and some of the efforts currently underway, we conducted interviews with officials in five states: Utah, Oklahoma, Washington, Colorado, and Idaho. These states represent varying degrees of progress along the continuum of leveraging data and pursuing interoperability to inform state policies and improve outcomes. This paper also examines how artificial intelligence solutions can provide states with significantly more insight into the populations they serve and have the potential to help states develop programs and policies to address a range of issues from improving population health and decreasing costs, to reducing substance use disorders, unemployment, and homelessness.