Purpose: To review the literature on medication safety in primary care in the electronic health record era.
Methods: Included studies measured rates and outcomes of medication safety in patients whose prescriptions were written in primary care clinics with electronic prescribing. Four investigators independently reviewed titles and analyzed abstracts with dual-reviewer review for eligibility, characteristics, and risk of bias.
Results: Of 1464 articles identified, 56 met the inclusion criteria. Forty-three studies were noninterventional and 13 included an intervention. The majority of the studies (30) used their own definition of error. The most common outcomes were potentially inappropriate prescribing/medications (PIPs), adverse drug events (ADEs), and potential prescribing omissions (PPOs). Most of the studies only included high-risk subpopulations (39), usually older adults taking > 4 medications. The rate of PIPs varied widely (0.19% to 98.2%). The rate of ADEs was lower (0.47% to 14.7%). There was poor correlation of PIP and PPO with documented ADEs leading to physical harm.
Conclusions: This literature is limited by its inconsistent and highly variable outcomes. The majority of medication safety studies in primary care were in high-risk populations and measured potential harms rather than actual harms. Applying algorithms to primary care medication lists significantly overestimates rate of actual harms.
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http://dx.doi.org/10.3122/jabfm.2022.03.210334 | DOI Listing |
Ann Intern Med
January 2025
Durham VA Health Care System, Durham; and Division of General Internal Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina (K.M.G.).
Background: Tissue-based genomic classifiers (GCs) have been developed to improve prostate cancer (PCa) risk assessment and treatment recommendations.
Purpose: To summarize the impact of the Decipher, Oncotype DX Genomic Prostate Score (GPS), and Prolaris GCs on risk stratification and patient-clinician decisions on treatment choice among patients with localized PCa considering first-line treatment.
Data Sources: MEDLINE, EMBASE, and Web of Science published from January 2010 to August 2024.
Ann Intern Med
January 2025
959 Medical Operations Squadron, U.S. Air Force, Department of Neurology, Brooke Army Medical Center, San Antonio, Texas (T.K.).
Description: In July 2024, the U.S. Department of Veterans Affairs (VA) and U.
View Article and Find Full Text PDFJMIR Ment Health
January 2025
Division of Psychology and Mental Health, University of Manchester, Manchester, United Kingdom.
Background: Digital mental health interventions (DMHIs) to monitor and improve the health of people with psychosis or bipolar disorder show promise; however, user engagement is variable, and integrated clinical use is low.
Objective: This prospectively registered systematic review examined barriers and facilitators of clinician and patient engagement with DMHIs, to inform implementation within real-world settings.
Methods: A systematic search of 7 databases identified empirical studies reporting qualitative or quantitative data about factors affecting staff or patient engagement with DMHIs aiming to monitor or improve the mental or physical health of people with psychosis or bipolar disorder.
Gac Med Mex
January 2025
Clínica de Hipertensión y Riesgo Cardiovascular, ISSSTESon, Hermosillo, Sonora. México.
Cardiovascular disease is the main cause of mortality in Mexico as well as the rest of the world, with dyslipidemia being one of the main risk factors. Despite the importance of its epidemiological impact, there is still -among primary care physicians- a lack of knowledge ranging from the basic concepts for diagnosis to the most recent recommendations for treatment. This document consisting of 10 questions is done by experts in this field.
View Article and Find Full Text PDFJ Clin Psychiatry
January 2025
Division of Gastrointestinal and Liver Diseases, Department of Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California.
We compared substance use disorder (SUD) prevalence among adult inflammatory bowel disease (IBD) hospitalizations with non-IBD controls from the 2016-2018 National Inpatient Sample, assessing correlations with demographics, socioeconomic status, geographic regions, depression, and anxiety. The primary aim focused on SUD, defined as substance abuse or dependence (: F10-F19) excluding unspecified use or remission, among hospitalizations documenting IBD (Crohn's disease or ulcerative colitis; : K50-51) as one admitting diagnosis (IBD-D). The prevalence of SUD among hospitalizations with and without IBD was compared.
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