In its brief history on the payer space, Social Determinants of Health (SDOH) efforts served as drivers for helping all parties in the care continuum to enhance population health. Typically, sharing this data with patients was not a common practice \u2013 until today.<\/p>\n
Blue Shield of California recently launched an effort<\/a> to make SDOH data universally available. Called the Neighborhood Health Dashboard generator, this solution allows anyone \u2013 even if they are not a Blue Shield of California member or a resident of California \u2013 to access data about any zip code or address.<\/p>\n \u201cBy making the data publicly available, anyone can gain a deeper understanding of the unmet social needs in their community and serve the population with increased knowledge about issues that have an impact on people\u2019s health and wellbeing,\u201d said Peter Long, SVP at Blue Shield of California, in this recent Health Payer Intelligence <\/em>article.<\/a><\/p>\n With other payers most likely to replicate this kind of effort, they will be expanding their health data management and analytic capabilities. A big part of this will be considering the options between schema\/structured and data lake environments for making datasets more actionable and valuable to their SDOH efforts.<\/p>\n Both options have their opportunities and challenges, and below is a quick summary.<\/p>\n The schema\/structured environment<\/strong> serves as a more traditional storage mechanism (i.e., SQL and NoSQL). Essentially, they are built around the data elements that a payer is interested in accessing. This makes it easy to plan, normalize and standardize the data to drive analytics and make key decisions.<\/p>\n In the data lakes environment<\/strong>, the data is stored in a raw form without any really known parameters for indexing and accessing this data. The convenience is that you have a wider-range of data to access. Though accessing this data requires a high-cost of computing, hardware and infrastructure, where many technologies need to work in data to build structure for data on the fly.<\/p>\n