Gerard McKay

Learning curves, taking instructions, and patient safety: using a theoretical domains framework in an interview study to investigate prescribing errors among trainee doctors

BackgroundPrescribing 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.MethodSemistructured 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.ResultsSeven 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.ConclusionsIn 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.

Perceived causes of prescribing errors by junior doctors in hospital inpatients: a study from the PROTECT programme

Introduction Prescribing errors are a major cause of patient safety incidents. Understanding the underlying factors is essential in developing interventions to address this problem. This study aimed to investigate the perceived causes of prescribing errors among foundation (junior) doctors in Scotland. Methods In eight Scottish hospitals, data on prescribing errors were collected by ward pharmacists over a 14-month period. Foundation doctors responsible for making a prescribing error were interviewed about the perceived causes. Interview transcripts were analysed using content analysis and categorised into themes previously identified under Reasons Model of Accident Causation and Human Error. Results 40 prescribers were interviewed about 100 specific errors. Multiple perceived causes for all types of error were identified and were categorised into five categories of error-producing conditions, (environment, team, individual, task and patient factors). Work environment was identified as an important aspect by all doctors, especially workload and time pressures. Team factors included multiple individuals and teams involved with a patient, poor communication, poor medicines reconciliation and documentation and following incorrect instructions from other members of the team. A further team factor was the assumption that another member of the team would identify any errors made. The most frequently noted individual factors were lack of personal knowledge and experience. The main task factor identified was poor availability of drug information at admission and the most frequently stated patient factor was complexity. Conclusions This study has emphasised the complex nature of prescribing errors, and the wide range of error-producing conditions within hospitals including the work environment, team, task, individual and patient. Further work is now needed to develop and assess interventions that address these possible causes in order to reduce prescribing error rates.

Metformin action on AMP‐activated protein kinase: a translational research approach to understanding a potential new therapeutic target

Diabet. Med. 27, 1097–1106 (2010)

A simple tool to predict admission at the time of triage

Aim To create and validate a simple clinical score to estimate the probability of admission at the time of triage. Methods This was a multicentre, retrospective, cross-sectional study of triage records for all unscheduled adult attendances in North Glasgow over 2 years. Clinical variables that had significant associations with admission on logistic regression were entered into a mixed-effects multiple logistic model. This provided weightings for the score, which was then simplified and tested on a separate validation group by receiving operator characteristic (ROC) analysis and goodness-of-fit tests. Results 215 231 presentations were used for model derivation and 107 615 for validation. Variables in the final model showing clinically and statistically significant associations with admission were: triage category, age, National Early Warning Score (NEWS), arrival by ambulance, referral source and admission within the last year. The resulting 6-variable score showed excellent admission/discharge discrimination (area under ROC curve 0.8774, 95% CI 0.8752 to 0.8796). Higher scores also predicted early returns for those who were discharged: the odds of subsequent admission within 28 days doubled for every 7-point increase (log odds=+0.0933 per point, p<0.0001). Conclusions This simple, 6-variable score accurately estimates the probability of admission purely from triage information. Most patients could accurately be assigned to ‘admission likely’, ‘admission unlikely’, ‘admission very unlikely’ etc., by setting appropriate cut-offs. This could have uses in patient streaming, bed management and decision support. It also has the potential to control for demographics when comparing performance over time or between departments.

Diabetes control in older people

Treat the patient not the HbA1c

Diabetes, colorectal cancer and cyclooxygenase 2 inhibition

Diabetes is a risk factor for cancer and specifically colorectal cancer. It is also associated with increased cancer mortality. Aspirin, non‐steroidal anti‐inflammatory drugs (NSAIDs) and cyclooxygenase 2 (Cox‐2) inhibitors have been shown to decrease the incidence of colorectal cancer. This effect may be mediated by inhibiting prostaglandin synthesis. Long‐term use of high‐dose aspirin and NSAIDs is associated with significant gastrointestinal side effects. Unfortunately, the use of Cox‐2 inhibitors is associated with an increased incidence of acute myocardial infarction and death from cardiovascular disease. The increased risk of cardiovascular disease in patients with diabetes results in the loss of the potential to use Cox‐2 inhibitors for cancer chemoprophylaxis. Until a safer type of Cox‐2 inhibitor is available, or low‐dose aspirin is evaluated for chemoprophylaxis, a more intense screening programme for colorectal cancer may be appropriate for patients with diabetes, especially men. Healthcare professionals managing patients with diabetes should be aware of the increased risk of this type of cancer.

Predicting admission at triage: are nurses better than a simple objective score?

Aim We compared two methods of predicting hospital admission from ED triage: probabilities estimated by triage nurses and probabilities calculated by the Glasgow Admission Prediction Score (GAPS). Methods In this single-centre prospective study, triage nurses estimated the probability of admission using a 100 mm visual analogue scale (VAS), and GAPS was generated automatically from triage data. We compared calibration using rank sum tests, discrimination using area under receiver operating characteristic curves (AUC) and accuracy with McNemars test. Results Of 1829 attendances, 745 (40.7%) were admitted, not significantly different from GAPS’ prediction of 750 (41.0%, p=0.678). In contrast, the nurses’ mean VAS predicted 865 admissions (47.3%), overestimating by 6.6% (p<0.0001). GAPS discriminated between admission and discharge as well as nurses, its AUC 0.876 compared with 0.875 for VAS (p=0.93). As a binary predictor, its accuracy was 80.6%, again comparable with VAS (79.0%), p=0.18. In the minority of attendances, when nurses felt at least 95% certain of the outcome, VAS’ accuracy was excellent, at 92.4%. However, in the remaining majority, GAPS significantly outperformed VAS on calibration (+1.2% vs +9.2%, p<0.0001), discrimination (AUC 0.810 vs 0.759, p=0.001) and accuracy (75.1% vs 68.9%, p=0.0009). When we used GAPS, but ‘over-ruled’ it when clinical certainty was ≥95%, this significantly outperformed either method, with AUC 0.891 (0.877–0.907) and accuracy 82.5% (80.7%–84.2%). Conclusions GAPS, a simple clinical score, is a better predictor of admission than triage nurses, unless the nurse is sure about the outcome, in which case their clinical judgement should be respected.

Do we need another SGLT2 inhibitor

patients with type 2 diabetes and life expectancy is reduced by an average of seven years.1 The high incidence of cardiovascular events associated with diabetes, including strokes and amputations, is a major cause of illness and an economic burden. There are multiple modifiable risk factors for cardiovascular disease in patients with type 2 diabetes, including hyperglycaemia, hypertension, dyslipidaemia, smoking and obesity, which combined contribute to increased morbidity and mortality.1 There is good evidence in the real-world setting that a multifaceted approach to management improves patients’ cardiovascular outcomes.2 Management of glycaemia as part of this approach remains challenging despite numerous newer therapeutic options, and many patients still do not achieve optimal control (HbA1c <7.0% [53mmol/mol]). Many of the current treatments lose their effectiveness over time, partially due to progressive beta-cell dysfunction, meaning that patients often require multiple glucose-lowering medications and many eventually require insulin therapy, which is associated with weight gain and hypoglycaemia. Several new classes of drugs have been introduced into routine clinical care in the last decade. When the first drug in class is launched there is interest in the mechanism of action. For subsequent members of the class the focus is more on comparative efficacy, safety and side effect profile. For example, rosiglitazone was launched as an insulin sensitiser and data for pioglitazone showed different effects on lipids and a better long-term cardiovascular safety profile. Sitagliptin was the first DPP-4 inhibitor, lowering blood glucose via the incretin effect. Of the subsequent members in the class the only clear difference is with linagliptin, which has a different route of excretion so does not require dose reduction in patients with renal impairment.

Use of metformin in chronic kidney disease should continue to be based on common sense in the absence of an evidence base.

We read with interest the paper by Adam et al. [1] which argues for less restrictive guidelines for using metformin in stable chronic renal failure. While the authors’ assumption that the use of metformin in patients with advanced chronic kidney disease (CKD) may be safe and offer similar cardiovascular disease and mortality benefit is reasonable, their enthusiasm for less restrictive guidance in patients with an estimated GFR of <30 ml/min should be tempered by the lack of good evidence of benefit for this group [2,3].

Differences in level of confidence in diabetes care between different groups of trainees: the TOPDOC diabetes study

BackgroundThere is an increasing prevalence of diabetes. Doctors in training, irrespective of specialty, will have patients with diabetes under their care. The aim of this further evaluation of the TOPDOC Diabetes Study data was to identify if there was any variation in confidence in managing diabetes depending on the geographical location of trainees and career aspirations.MethodsAn online national survey using a pre-validated questionnaire was administered to trainee doctors. A 4-point confidence rating scale was used to rate confidence in managing aspects of diabetes care and a 6-point scale used to quantify how often trainees would contribute to the management of patients with diabetes. Responses were grouped depending on which UK country trainees were based and their intended career choice.ResultsTrainees in Northern Ireland reported being less confident in IGT diagnosis, use of IV insulin and peri-operative management and were less likely to adjust oral treatment, contact specialist, educate lifestyle, and optimise treatment. Trainees in Scotland were less likely to contact a specialist, but more likely to educate on lifestyle, change insulin, and offer follow-up advice. In Northern Ireland, Undergraduate (UG) and Postgraduate (PG) training in diagnosis was felt less adequate, PG training in emergencies less adequate, and reporting of need for further training higher. Trainees in Wales felt UG training to be inadequate. In Scotland more trainees felt UG training in diagnosis and optimising treatment was inadequate. Physicians were more likely to report confidence in managing patients with diabetes and to engage in different aspects of diabetes care. Aspiring physicians were less likely to feel the need for more training in diabetes care; however a clear majority still felt they needed more training in all aspects of care.ConclusionsDoctors in training have poor confidence levels dealing with diabetes related care issues. Although there is variability between different groups of trainees according to geographical location and career aspirations, this is a UK wide issue. There should be a UK wide standardised approach to improving training for junior doctors in diabetes care with local training guided by specific needs.