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Trainee doctors' experiences of common problems in the antibiotic prescribing process: an activity theory analysis of narrative data from UK hospitals.

ABSTRACT: INTRODUCTION:Prescribing antibiotics is an error-prone activity and one of the more challenging responsibilities for doctors in training. The nature and extent of challenges experienced by them at different stages of the antibiotic prescribing process are not well described, meaning that interventions may not target the most problematic areas. OBJECTIVES:Our aim was to explore doctors in training experiences of common problems in the antibiotic prescribing process using cultural-historical activity theory (CHAT). Our research questions were as follows: What are the intended stages in the antibiotic prescribing process? What are the challenges and where in the prescribing process do these occur? METHODS:We developed a process model based on how antibiotic prescribing is intended to occur in a 'typical' National Health Service hospital in the UK. The model was first informed by literature and refined through consultation with practising healthcare professionals and medical educators. Then, drawing on CHAT, we analysed 33 doctors in training narratives of their antibiotic prescribing experiences to identify and interpret common problems in the process. RESULTS:Our analysis revealed five main disturbances commonly occurring during the antibiotic prescribing process: consultation challenges, lack of continuity, process variation, challenges in patient handover and partial loss of object. Our process model, with 31 stages and multiple practitioners, captures the complexity, inconsistency and unpredictability of the process. The model also highlights 'hot spots' in the process, which are the stages that doctors in training are most likely to have difficulty navigating. CONCLUSIONS:Our study widens the understanding of doctors in training prescribing experiences and development needs regarding the prescribing process. Our process model, identifying the common disturbances and hot spots in the process, can facilitate the development of antibiotic prescribing activities and the optimal design of interventions to support doctors in training.

SUBMITTER: Kajamaa A

PROVIDER: S-EPMC6576120 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Trainee doctors' experiences of common problems in the antibiotic prescribing process: an activity theory analysis of narrative data from UK hospitals.

Kajamaa Anu A Mattick Karen K Parker Hazel H Hilli Angelique A Rees Charlotte C

BMJ open 20190611 6

<h4>Introduction</h4>Prescribing antibiotics is an error-prone activity and one of the more challenging responsibilities for doctors in training. The nature and extent of challenges experienced by them at different stages of the antibiotic prescribing process are not well described, meaning that interventions may not target the most problematic areas.<h4>Objectives</h4>Our aim was to explore doctors in training experiences of common problems in the antibiotic prescribing process using cultural-h ...[more]

PMID: 31189683

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Project description:ObjectivesStudy objectives were to investigate the prevalence and causes of prescribing errors amongst foundation doctors (i.e. junior doctors in their first (F1) or second (F2) year of post-graduate training), describe their knowledge and experience of prescribing errors, and explore their self-efficacy (i.e. confidence) in prescribing.MethodA three-part mixed-methods design was used, comprising: prospective observational study; semi-structured interviews and cross-sectional survey. All doctors prescribing in eight purposively selected hospitals in Scotland participated. All foundation doctors throughout Scotland participated in the survey. The number of prescribing errors per patient, doctor, ward and hospital, perceived causes of errors and a measure of doctors' self-efficacy were established.Results4710 patient charts and 44,726 prescribed medicines were reviewed. There were 3364 errors, affecting 1700 (36.1%) charts (overall error rate: 7.5%; F1:7.4%; F2:8.6%; consultants:6.3%). Higher error rates were associated with : teaching hospitals (p<0.001), surgical (p = <0.001) or mixed wards (0.008) rather thanmedical ward, higher patient turnover wards (p<0.001), a greater number of prescribed medicines (p<0.001) and the months December and June (p<0.001). One hundred errors were discussed in 40 interviews. Error causation was multi-factorial; work environment and team factors were particularly noted. Of 548 completed questionnaires (national response rate of 35.4%), 508 (92.7% of respondents) reported errors, most of which (328 (64.6%) did not reach the patient. Pressure from other staff, workload and interruptions were cited as the main causes of errors. Foundation year 2 doctors reported greater confidence than year 1 doctors in deciding the most appropriate medication regimen.ConclusionsPrescribing errors are frequent and of complex causation. Foundation doctors made more errors than other doctors, but undertook the majority of prescribing, making them a key target for intervention. Contributing causes included work environment, team, task, individual and patient factors. Further work is needed to develop and assess interventions that address these.

Project description:OBJECTIVES:Many countries are driving forward policies to widen the socioeconomic profile of medical students and to train more medical students for certain specialties. However, little is known about how socioeconomic origin relates to specialty choice. Nor is there a good understanding of the relationship between academic performance and specialty choice. To address these gaps, our aim was to identify the relationship between socioeconomic background, academic performance and accepted offers into specialty training. DESIGN:Longitudinal, cohort study using data from the UK Medical Education Database (https://www.ukmed.ac.uk/). PARTICIPANTS:6065 (60% females) UK doctors who accepted offers to a specialty training (residency) post after completing the 2-year generic foundation programme (UK Foundation Programme) between 2012 and 2014. MAIN OUTCOME MEASURES:Χ2 tests were used to examine the relationships between sociodemographic characteristics, academic ability and the dependent variable, specialty choice. Multiple data imputation was used to address the issue of missing data. Multinomial regression was employed to test the independent variables in predicting the likelihood of choosing a given specialty. RESULTS:Participants pursuing careers in more competitive specialties had significantly higher academic scores than colleagues pursuing less competitive ones. After controlling for the presence of multiple factors, trainees who came from families where no parent was educated to a degree level had statistically significant lower odds of choosing careers in medical specialties relative to general practice (OR=0.78, 95% CI, 0.67 to 0.92). Students who entered medical school as school leavers, compared with mature students, had odds 1.2 times higher (95% CI, 1.04 to 1.56) of choosing surgical specialties than general practice. CONCLUSIONS:The data indicate a direct association between trainees' sociodemographic characteristics, academic ability and career choices. The findings can be used by medical school, training boards and workforce planners to inform recruitment and retention strategies.

Project description:BackgroundArtificial intelligence (AI) technologies are increasingly used in clinical practice. Although there is robust evidence that AI innovations can improve patient care, reduce clinicians' workload and increase efficiency, their impact on medical training and education remains unclear.MethodsA survey of trainee doctors' perceived impact of AI technologies on clinical training and education was conducted at UK NHS postgraduate centers in London between October and December 2020. Impact assessment mirrored domains in training curricula such as 'clinical judgement', 'practical skills' and 'research and quality improvement skills'. Significance between Likert-type data was analysed using Fisher's exact test. Response variations between clinical specialities were analysed using k-modes clustering. Free-text responses were analysed by thematic analysis.ResultsTwo hundred ten doctors responded to the survey (response rate 72%). The majority (58%) perceived an overall positive impact of AI technologies on their training and education. Respondents agreed that AI would reduce clinical workload (62%) and improve research and audit training (68%). Trainees were skeptical that it would improve clinical judgement (46% agree, p = 0.12) and practical skills training (32% agree, p < 0.01). The majority reported insufficient AI training in their current curricula (92%), and supported having more formal AI training (81%).ConclusionsTrainee doctors have an overall positive perception of AI technologies' impact on clinical training. There is optimism that it will improve 'research and quality improvement' skills and facilitate 'curriculum mapping'. There is skepticism that it may reduce educational opportunities to develop 'clinical judgement' and 'practical skills'. Medical educators should be mindful that these domains are protected as AI develops. We recommend that 'Applied AI' topics are formalized in curricula and digital technologies leveraged to deliver clinical education.

Project description:IntroductionDespite common assumptions that doctors are well placed to lead hospitals and healthcare organisations, the peer-reviewed literature contains little evidence on the performance of doctors in leadership roles in comparison with that of non-medical managers.ObjectivesTo determine whether there is an association between the leader's medical background and management performance in terms of organisational performance or patient outcomes.MethodsWe searched for peer-reviewed, English language studies using Medline, Embase and Emerald Management between 2005 and 2017. We included quantitative, qualitative and mixed method empirical studies on the performance of senior healthcare managers where participants were described as doctors or leaders and where comparative performance data were provided on non-medical leaders. Studies without full text available, or no organisational, leadership behaviour or patient measures, were excluded.ResultsThe search, conducted in Medline (n=3395), Embase (n=1913) and Emerald Management (n=454) databases, yielded 3926 entries. After the application of inclusion and exclusion criteria, 16 studies remained. Twelve studies found that there were positive differences between medical and non-medical leaders, and eight studies correlated those findings with hospital performance or patient outcomes. Six studies examined the composition of boards of directors; otherwise, there were few common areas of investigation. Five inter-related themes emerged from a narrative analysis: the impact of medical leadership on outcomes; doctors on boards; contribution of qualifications and experience; the medical leader as an individual or part of a team and doctors transitioning into the medical leadership role.Discussion and conclusionA modest body of evidence supports the importance of including doctors on organisational governing boards. Despite many published articles on the topic of whether hospitals and healthcare organisations perform better when led by doctors, there were few empirical studies that directly compared the performance of medical and non-medical managers. This is an under-researched area that requires further funding and focus.

Project description:Prescribing errors are a major source of morbidity and mortality and represent a significant patient safety concern. Evidence suggests that trainee doctors are responsible for most prescribing errors. Understanding the factors that influence prescribing behavior may lead to effective interventions to reduce errors. Existing investigations of prescribing errors have been based on Human Error Theory but not on other relevant behavioral theories. The aim of this study was to apply a broad theory-based approach using the Theoretical Domains Framework (TDF) to investigate prescribing in the hospital context among a sample of trainee doctors.Semistructured interviews, based on 12 theoretical domains, were conducted with 22 trainee doctors to explore views, opinions, and experiences of prescribing and prescribing errors. Content analysis was conducted, followed by applying relevance criteria and a novel stage of critical appraisal, to identify which theoretical domains could be targeted in interventions to improve prescribing.Seven theoretical domains met the criteria of relevance: "social professional role and identity," "environmental context and resources," "social influences," "knowledge," "skills," "memory, attention, and decision making," and "behavioral regulation." From critical appraisal of the interview data, "beliefs about consequences" and "beliefs about capabilities" were also identified as potentially important domains. Interrelationships between domains were evident. Additionally, the data supported theoretical elaboration of the domain behavioral regulation.In this investigation of hospital-based prescribing, participants' attributions about causes of errors were used to identify domains that could be targeted in interventions to improve prescribing. In a departure from previous TDF practice, critical appraisal was used to identify additional domains that should also be targeted, despite participants' perceptions that they were not relevant to prescribing errors. These were beliefs about consequences and beliefs about capabilities. Specifically, in the light of the documented high error rate, beliefs that prescribing errors were not likely to have consequences for patients and that trainee doctors are capable of prescribing without error should also be targeted in an intervention. This study is the first to suggest critical appraisal for domain identification and to use interview data to propose theoretical elaborations and interrelationships between domains.

Dataset Information

Trainee doctors' experiences of common problems in the antibiotic prescribing process: an activity theory analysis of narrative data from UK hospitals.

Publications

Trainee doctors' experiences of common problems in the antibiotic prescribing process: an activity theory analysis of narrative data from UK hospitals.

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