Data are an asset and a public good (McGinnis, Olsen, & Goodby, 2010). Health data (e.g., clinical, claims, and administrative) hold the potential to transform the health care industry into a learning health system (LHS) through the application and integration of bidirectional discoveries of actionable knowledge for research and health care practice (Friedman, Wong, & Blumenthal, 2010; Greene, Reid, & Larson, 2012). Theoretically, people benefit because a LHS is likely to increase safety (avoiding misuse and harm from care) and promote effectiveness (avoidance of overuse or underuse and care grounded in evidence; Berwick, 2009; Kohn, Corrigan, & Donaldson, 2000).
Justification for learning in health care originates from a morally essential feature of the health care system (Faden, Beauchamp, & Kass, 2011). Morally essential health rests on two empirical assumptions. First, a just health care system cannot be secured without continuous commitment to improving quality and efficiency of person-centered health services. Second, honoring this commitment depends on efficiently integrating into clinical service delivery a wide range of learning activities, including those conventionally classified as research (Faden et al., 2011; Institute of Medicine [IOM], 2009).
Health data provide significant insights to providers, consumers, and policy makers as data are transformed into usable information for treatment, evaluation of quality, and costs of care (Green et al., 2013; McGinnis et al., 2010; Tripathi, Delano, Lund, & Rudolph, 2009). Health care data offers the opportunity to fast-track evaluation on the six dimensions of quality care: safe, effective, person-centered, timely, efficient, and equitable (Berwick, 2009; Chaudhry et al., 2006; IOM, 2009). Still, additional evaluation metrics are needed, such as attention to information privacy, systems effectiveness, and legal and public policy support. Health information represents some of the most sensitive personal data available (Harper, 2014). The health data being recorded about people, when aggregated, provide a comprehensive picture of one’s health status and the health of populations of interest (Harper, 2014; Pritts, 2001).
Copyrighted by Moon, Lisa A. 2017. Health Data Sharing Preferences of Consumers (Dissertation Research). University of Minnesota.
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