Although the vast majority of U.S. physicians still handwrite prescriptions, adoption of electronic prescribing is slowly growing. Major barriers to adoption remain, including the inability to electronically submit prescriptions for controlled substances and confusion about standards for data exchange. Federal and state governments and private insurers are using payment and policy incentives to boost e-prescribing because they still believe in its promise for improving the quality and efficiency of health care. However, additional efforts and further investments are needed to reap the benefits of e-prescribing on a national scale.
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http://dx.doi.org/10.1377/hlthaff.28.2.393 | DOI Listing |
Surg Obes Relat Dis
December 2024
Department of Surgery, The Ohio State University Wexner Medical Center, Columbus, Ohio.
Background: Prescription opioids are responsible for a significant proportion of opioid-related deaths in the United States. Approximately 6% of opioid-naïve patients who receive opioid prescriptions after surgery become chronic opioid users. However, chronic opioid use after bariatric surgery may be twice as common.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Pharmacy, Shanghai Gonghui Hospital, Shanghai, People's Republic of China.
Elderly patients with multiple concomitant chronic diseases are the particularly vulnerable during the Coronavirus disease 2019 (COVID-19) epidemic, which accounts for a large number of COVID-19-related deaths. The purpose of the study was to investigate the impact of polypharmacy and potentially inappropriate medications (PIMs) on in-hospital mortality in a secondary hospital in China. A cross-sectional, retrospective study was conducted using electronic medical data collected from Shanghai Gonghui Hospital from April 2022 to June 2022.
View Article and Find Full Text PDFClin Ther
December 2024
Department of Preventive Medicine and Public Health, University of Santiago de Compostela, Santiago de Compostela, Spain; Consortium for Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública/CIBERESP), Madrid, Spain; Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Galicia, Spain.
Purpose: One of the main goals of an in-hospital drug formulary (in-HDF) is to modulate hospitalized patients' drug utilization. Theoretically, however, in-HDFs could also have an impact on out-of-hospital prescriptions in several ways, including discharged patients taking chronic medications that were initiated during hospitalization, hospital physicians prescribing to outpatients as if in-HDFs were equally applicable to the latter ("spillover effect"), and primary care physicians subsequently not changing such prescriptions ("induced prescription"). The aim of this study was thus to conduct a systematic review of papers that studied the impact of changes to in-HDF on out-of-hospital prescriptions.
View Article and Find Full Text PDFOcul Surf
December 2024
Centre for Ocular Research and Education (CORE), School of Optometry and Vision Science, University of Waterloo, Canada; Optometry and Vision Science Research Group, College of Health and Life Sciences, Aston University, Birmingham, United Kingdom; Department of Ophthalmology, Aotearoa New Zealand National Eye Centre, The University of Auckland, New Zealand.
Aims: To understand current clinical management of dry eye disease (DED), based on its perceived severity and subtype by practitioners across the world.
Methods: The content of the anonymous survey was chosen to reflect the DED management strategies reported by the Tear Film and Ocular Surface Society (TFOS) 2 Dry Eye Workshop (DEWS II). Questions were designed to ascertain practitioner treatment choice, depending on the subtype and severity of DED.
J Infect
December 2024
Big Data Institute, Nuffield Department of Population Health, University of Oxford, Oxford, UK; NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, University of Oxford, Oxford, UK; NIHR Oxford Biomedical Research Centre, Oxford, UK; Oxford University Hospitals NHS Foundation Trust, Oxford, UK. Electronic address:
Background: Patients with Gram-negative bloodstream infections are at risk of serious adverse outcomes without active treatment, but identifying who has antimicrobial resistance (AMR) to target empirical treatment is challenging.
Methods: We used XGBoost machine learning models to predict antimicrobial resistance to seven antibiotics in patients with Enterobacterales bloodstream infection. Models were trained using hospital and community data from Oxfordshire, UK, for patients with positive blood cultures between 01-January-2017 and 31-December-2021.
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