Applied clinical informatics
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Clinician progress notes are an important record for care and communication, but there is a perception that electronic notes take too long to write and may not accurately reflect the patient encounter, threatening quality of care. Automatic speech recognition (ASR) has the potential to improve clinical documentation process; however, ASR inaccuracy and editing time are barriers to wider use. We hypothesized that automatic text processing technologies could decrease editing time and improve note quality. To inform the development of these technologies, we studied how physicians create clinical notes using ASR and analyzed note content that is revised or added during asynchronous editing. ⋯ Process interventions to reduce ASR documentation burden, whether related to technology or the dictation/editing workflow, should apply a portfolio of solutions to address all categories of required edits. Improved processes could reduce an important barrier to broader use of ASR by clinicians and improve note quality.
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We aimed to determine the characteristics of quantitative metrics for nursing narratives documented in electronic nursing records and their association with hospital admission traits and diagnoses in a large data set not limited to specific patient events or hypotheses. ⋯ Diverse hospital admissions can be consistently described with nursing-document-derived metrics for similar hospital admissions and diagnoses. Some areas of hospital admissions may have consistently increasing volumes of nursing documentation across years. Usability of electronic nursing document metrics for evaluating healthcare requires multiple aspects of hospital admissions to be considered.
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Electronic health information overload makes it difficult for providers to quickly find and interpret information to support care decisions. The purpose of this study was to better understand how clinicians use information in critical care to support the design of improved presentation of electronic health information. ⋯ The results from this study can be used to guide the design of future acute care electronic health information display. Additional research and collaboration is needed to refine and implement intelligent graphical user interfaces to improve clinical information organization and prioritization to support care decisions.
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This case study overviews the conversion of provider training of the electronic medical record (EMR) from an instructor-led training (ILT) program to eLearning at an Academic Medical Center (AMC). This conversion provided us with both a useful training tool and the opportunity to maximize efficiency within both our training and optimization team and organization. eLearning Development Principles were created and served as a guide to assist us with designing an eLearning curriculum using a five step process. The result was a new training approach that allowed learners to complete training at their own pace, and even test out of sections based on demonstrated competency. The information we have leads us to believe that a substantial return on our investment can be obtained from the conversion with positive impacts that have served as the foundation for the future of end user EMR training at our AMC.
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In the US, the new subspecialty of Clinical Informatics focuses on systems-level improvements in care delivery through the use of health information technology (HIT), data analytics, clinical decision support, data visualization and related tools. Clinical informatics is one of the first subspecialties in medicine open to physicians trained in any primary specialty. Clinical Informatics benefits patients and payers such as Medicare and Medicaid through its potential to reduce errors, increase safety, reduce costs, and improve care coordination and efficiency. ⋯ To maintain the value of HIT investments by the government and health care organizations, we must train sufficient leaders in Clinical Informatics. In the best interest of patients, payers, and the US society, it is therefore critical to find viable financial models for Clinical Informatics fellowship programs. To support the development of adequate training programs in Clinical Informatics, we request that the Centers for Medicare and Medicaid Services (CMS) issue clarifying guidance that would allow accredited ACGME institutions to bill for clinical services delivered by fellows at the fellowship program site within their primary specialty.