The Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009 that was signed into law as part of the “stimulus package” represents the largest US initiative to date that is designed to encourage widespread use of electronic health records (EHRs). In light of the changes anticipated from this policy initiative, the purpose of this paper is to review and summarize the literature on the benefits and drawbacks of EHR systems. Much of the literature has focused on key EHR functionalities, including clinical decision support systems, computerized order entry systems, and health information exchange. Our paper describes the potential benefits of EHRs that include clinical outcomes (eg, improved quality, reduced medical errors), organizational outcomes (eg, financial and operational benefits), and societal outcomes (eg, improved ability to conduct research, improved population health, reduced costs). Despite these benefits, studies in the literature highlight drawbacks associated with EHRs, which include the high upfront acquisition costs, ongoing maintenance costs, and disruptions to workflows that contribute to temporary losses in productivity that are the result of learning a new system. Moreover, EHRs are associated with potential perceived privacy concerns among patients, which are further addressed legislatively in the HITECH Act. Overall, experts and policymakers believe that significant benefits to patients and society can be realized when EHRs are widely adopted and used in a “meaningful” way.
BACKGROUND Many beliefs about obesity persist in the absence of supporting scientific evidence (presumptions); some persist despite contradicting evidence (myths). The promulgation of unsupported beliefs may yield poorly informed policy decisions, inaccurate clinical and public health recommendations, and an unproductive allocation of research resources and may divert attention away from useful, evidence-based information. METHODS Using Internet searches of popular media and scientific literature, we identified, reviewed, and classified obesity-related myths and presumptions. We also examined facts that are well supported by evidence, with an emphasis on those that have practical implications for public health, policy, or clinical recommendations. RESULTS We identified seven obesity-related myths concerning the effects of small sustained increases in energy intake or expenditure, establishment of realistic goals for weight loss, rapid weight loss, weight-loss readiness, physical-education classes, breast-feeding, and energy expended during sexual activity. We also identified six presumptions about the purported effects of regularly eating breakfast, early childhood experiences, eating fruits and vegetables, weight cycling, snacking, and the built (i.e., human-made) environment. Finally, we identified nine evidence-supported facts that are relevant for the formulation of sound public health, policy, or clinical recommendations. CONCLUSIONS False and scientifically unsupported beliefs about obesity are pervasive in both scientific literature and the popular press. (Funded by the National Institutes of Health.)
On July 21, 2020, this report was posted as an MMWR Early Release on the MMWR website (https://www.cdc.gov/mmwr).Population prevalence of persons infected with SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), varies by subpopulation and locality. U.S. studies of SARS-CoV-2 infection have examined infections in nonrandom samples (1) or seroprevalence in specific populations* (2), which are limited in their generalizability and cannot be used to accurately calculate infection-fatality rates. During April 25-29, 2020, Indiana conducted statewide random sample testing of persons aged ≥12 years to assess prevalence of active infection and presence of antibodies to SARS-CoV-2; additional nonrandom sampling was conducted in racial and ethnic minority communities to better understand the impact of the virus in certain racial and ethnic minority populations. Estimates were adjusted for nonresponse to reflect state demographics using an iterative proportional fitting method. Among 3,658 noninstitutionalized participants in the random sample survey, the estimated statewide point prevalence of active SARS-CoV-2 infection confirmed by reverse transcriptionpolymerase chain reaction (RT-PCR) testing was 1.74% (95% confidence interval [CI] = 1.10-2.54); 44.2% of these persons reported no symptoms during the 2 weeks before testing. The prevalence of immunoglobulin G (IgG) seropositivity, indicating past infection, was 1.09% (95% CI = 0.76-1.45). The overall prevalence of current and previous infections of SARS-CoV-2 in Indiana was 2.79% (95% CI = 2.02-3.70). In the random sample, higher overall prevalences were observed among Hispanics and those who reported having a household contact who had previously been told by a health care provider that they had COVID-19. By late April, an estimated 187,802 Indiana residents were currently or previously infected with SARS-CoV-2 (9.6 times higher than the number of confirmed cases [17,792]) (3), and 1,099 residents died (infection-fatality ratio = 0.58%). The number of reported cases represents only a fraction of the estimated total number of infections. Given the large number of persons who remain susceptible in Indiana, adherence to evidence-based public health mitigation and containment measures (e.g., social distancing, consistent and correct use of face coverings, and hand hygiene) is needed to * https://www.medrxiv
Expanding eligibility for Medicaid was a central goal of the Affordable Care Act (ACA), which continues to be debated and discussed at the state and federal levels as further reforms are considered. In an effort to provide a synthesis of the available research, we systematically reviewed the peer-reviewed scientific literature on the effects of Medicaid expansion on the original goals of the ACA. After analyzing seventy-seven published studies, we found that expansion was associated with increases in coverage, service use, quality of care, and Medicaid spending. Furthermore, very few studies reported that Medicaid expansion was associated with negative consequences, such as increased wait times for appointments-and those studies tended to use study designs not suited for determining cause and effect. Thus, there is evidence to document improvements in several areas of health care delivery following the ACA Medicaid expansion. We outline areas for future research that can further reduce current knowledge gaps.
Policymakers at federal and local levels should encourage more rigorous scientific research to determine whether altered built environments will result in increased PA and decreased obesity rates.
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