Download Digital Infrastructure for the Learning Health System: The by Institute of Medicine, Roundtable on Value and PDF
By Institute of Medicine, Roundtable on Value and Science-Driven Health Care, J. Michael McGinnis, Brian Powers, Claudia Grossmann
Like many different industries, overall healthiness care is more and more turning to electronic details and using digital assets. The Institute of Medicine's Roundtable on price & Science-Driven wellbeing and fitness Care hosted 3 workshops to discover present efforts and possibilities to speed up development in enhancing future health and wellbeing and fitness care with info expertise structures.
Read or Download Digital Infrastructure for the Learning Health System: The Foundation for Continuous Improvement in Health and Health Care: Workshop Series Summary (The Learning Health System Series) PDF
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Additional info for Digital Infrastructure for the Learning Health System: The Foundation for Continuous Improvement in Health and Health Care: Workshop Series Summary (The Learning Health System Series)
Previous work on the ULS concept has identified the following key characteristics of ULS systems: Decentralization: The scale of ULS systems means that they will necessarily be decentralized in a variety of ways—decentralized data, development, evolution, and operational control. Inherently conflicting, unknowable, and diverse requirements: ULS systems will be developed and used by a wide variety of stakeholders with unavoidably different, conflicting, complex, and changing needs. New and different capabilities will be deployed, and unused capabilities will be dropped; the system will be evolving not in phases, but continuously.
Institutions retain flexibility for innovation in their choices, and evolutionary functional change can be shaped by architectural precepts, incentives, and compliance assessment, but not by centralized control. ULS functionality is therefore facilitated by protocols that allow maximum practical flexibility for participants. Incorporating decentralization of data, development, and operational authority and control, this approach fosters local innovation, personalization, and emergent behaviors.
Key elements of the framework include an open and transparent process, specification of purpose, individual participation and control, and accountability and oversight. Closing with a warning that overreliance on consent leads to weak protection—shifting the burden of privacy protection from the institution to the individual—and that existing regulations are insufficient to cover the privacy issues inherent in a learning health system, she underscored the need for a trust fabric based on fair information practices.