Electronic health records, clinical decision support, and blood pressure control.
ABSTRACT Adding clinical decision support (CDS) to electronic health records (EHRs) is required under meaningful use legislation, but there has been little national data on effectiveness in improving clinical outcomes. We sought to determine whether EHRs with CDS improved blood pressure control in US primary care visits. Study Design: We used a cross-sectional, nationally representative survey.
We examined adult visits to primary care physicians using the 2007 and 2008 National Ambulatory Medical Care Survey (NAMCS).
We found that patients had a mean age of 52 years, 34% were male, 15% had diabetes, and 70% were white. Rates of blood pressure control were significantly higher in visits where both an EHR and CDS (79%) were used, compared with visits where physicians used neither tool (74%; P = .004). Blood pressure control rates remained higher after adjusting for potential confounders. In unadjusted analyses, mean systolic blood pressure was 2 mm Hg lower in visits with the use of both an EHR and CDS, compared with visits where physicians used neither tool (P = .03), and this difference remained significant after adjustment.
The NAMCS shows that physician use of an EHR with CDS is associated with improved blood pressure control. These findings are important because small improvements in blood pressure control are associated with reductions in cardiovascular morbidity and mortality.
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ABSTRACT: Health information technology represents a promising avenue to improve health care delivery. How can we use lessons learnt from existing health information technologies in primary care to inform the optimal design of newer developments such as personal health records? The results of systematic literature reviews about the impact of different information systems on health outcomes in primary care are critically discussed in a narrative synthesis, with a focus on their implications for the development of personal health records. Given the proliferation of systematic reviews and randomized controlled trials, high quality evidence for health information technology in primary care is accumulating with mixed results. The heterogeneity of systems being compared and the quality of research can no longer account for these findings. One potential explanation may be that systems originally designed for acute care settings are being implemented in primary care. Early studies evaluating personal health records suggest that targeting patient outcomes directly and adapting systems to patients' needs may be part of the solution. In order to develop personal health records for primary care, studies are needed that involve the users, namely patients and primary care health professionals, in the design and evaluation of these systems from their inception. Participatory research is a recommended methodological approach.International Journal of Medical Informatics 08/2012; 81(10):654-61. DOI:10.1016/j.ijmedinf.2012.07.008 · 2.72 Impact Factor
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ABSTRACT: Primary-care physicians feel pressure to be knowledgeable, efficient, comprehensive, and compassionate while delivering evidence-based medical care. Incorporating evidence-based medicine into practice requires training in the skills of finding and applying good evidence to patients, and, increasingly, infrastructure that supports the incorporation of evidence into electronic health records. Physicians cite many barriers to the use of evidence-based medicine in practice. In this review, we examine evidence of the value of evidence-based medicine in clinical practice, discuss the interface of evidence and shared decision-making, suggest tools and approaches for incorporating evidence-based medicine into practice, and discuss the impact of recent health insurance reform on expectations and incentives for physicians with respect to evidence-based practice. Mt Sinai J Med 79:545-554, 2012. © 2012 Mount Sinai School of Medicine.Mount Sinai Journal of Medicine A Journal of Translational and Personalized Medicine 09/2012; 79(5):545-54. DOI:10.1002/msj.21337 · 1.56 Impact Factor
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