The transition from paper to digital health care records promises a significantly enhanced ability to leverage claims and clinical data for secondary uses – uses beyond that for which the health data was originally collected, such as research, public health surveillance, or fraud prevention. Done properly, these secondary uses of data that were originally collected for treatment or payment can aid the creation of a more effective, information-driven health care system. For example, researchers are using digital claims data to provide the public with comparisons of the quality and cost effectiveness of treatment for particular conditions among plans or health care facilities in a given market.
Patient privacy and data security are among the first considerations of agencies establishing such programs, and many agencies have instituted strong technical controls (such as de-identifying the data) and policy frameworks to protect the confidentiality and integrity of the data. Although a strong policy framework is essential, the technical architecture of information exchange is another important factor. This week, the Center for Democracy & Technology (CDT) released a report challenging the prevailing centralized model of health data analysis and urging Dept. of Health and Human Services (HHS) to explore distributed systems for secondary use programs. The paper comes at the same time that the Centers for Medicare and Medicaid (CMS) issued a final rule for its risk adjustment program – mandated by the Affordable Care Act of 2010 – that would use a distributed system as a default, changing course from the proposed rule, which would have required a centralized model.