Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Identifying how GPs spend their time and the obstacles they face: a mixed-methods study.
29
Zitationen
10
Autoren
2021
Jahr
Abstract
BACKGROUND: Although problems that impair task completion - known as operational failures - are an important focus of concern in primary care, they have remained little studied. AIM: To quantify the time GPs spend on different activities during clinical sessions; to identify the number of operational failures they encounter; and to characterise the nature of operational failures and their impact for GPs. DESIGN AND SETTING: Mixed-method triangulation study with 61 GPs in 28 NHS general practices in England from December 2018 to December 2019. METHOD: Time-motion methods, ethnographic observations, and interviews were used. RESULTS: Time-motion data on 7679 GP tasks during 238 hours of practice in 61 clinical sessions suggested that operational failures were responsible for around 5.0% (95% confidence interval [CI] = 4.5% to 5.4%) of all tasks undertaken by GPs and accounted for 3.9% (95% CI = 3.2% to 4.5%) of clinical time. However, qualitative data showed that time-motion methods, which depend on pre-programmed categories, substantially underestimated operational failures. Qualitative data also enabled further characterisation of operational failures, extending beyond those measured directly in the time-motion data (for example, interruptions, deficits in equipment/supplies, and technology) to include problems linked to GPs' coordination role and weaknesses in work systems and processes. The impacts of operational failures were highly consequential for GPs' experiences of work. CONCLUSION: GPs experience frequent operational failures, disrupting patient care, impairing experiences of work, and imposing burden in an already pressurised system. This better understanding of the nature and impact of operational failures allows for identification of targets for improvement and indicates the need for coordinated action to support GPs.
Ähnliche Arbeiten
Machine Learning in Medicine
2019 · 3.754 Zit.
Systematic Review: Impact of Health Information Technology on Quality, Efficiency, and Costs of Medical Care
2006 · 3.173 Zit.
Effects of Computerized Clinical Decision Support Systems on Practitioner Performance and Patient Outcomes
2005 · 2.967 Zit.
Studies in health technology and informatics
2008 · 2.903 Zit.
An overview of clinical decision support systems: benefits, risks, and strategies for success
2020 · 2.707 Zit.