
Private- and public-sector initiatives, using electronic health record (EHR) databases from millions of people, could rapidly advance the U.S. evidence base for clinical care. Rapid learning could fill major knowledge gaps about health care costs, the benefits and risks of drugs and procedures, geographic variations, environmental health influences, the health of special populations, and personalized medicine. Policymakers could use rapid learning to revitalize value-based competition, redesign Medicare's payments, advance Medicaid into national health care leadership, foster national collaborative research initiatives, and design a national technology assessment system.
Male, Public Health Informatics, Evidence-Based Medicine, Public Sector, Medical Records Systems, Computerized, Medicaid, Regional Medical Programs, Medicare, United States, Systems Integration, Humans, Learning, Female, Private Sector, National Health Insurance, United States, Delivery of Health Care, Information Systems, Total Quality Management
Male, Public Health Informatics, Evidence-Based Medicine, Public Sector, Medical Records Systems, Computerized, Medicaid, Regional Medical Programs, Medicare, United States, Systems Integration, Humans, Learning, Female, Private Sector, National Health Insurance, United States, Delivery of Health Care, Information Systems, Total Quality Management
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 279 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 0.1% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
