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The Centre for Evidence-Based Medicine (CEBM) at Oxford University develops, promotes and disseminates better evidence for health care.
Impact and outcomes of the Emerging Leaders Programme: a mixed-methods evaluation of a leadership development programme for healthcare professionals.
BACKGROUND: The significance of effective medical leadership in enhancing healthcare outcomes has been widely acknowledged. This study evaluates the Emerging Leaders Programme, a multidisciplinary leadership development initiative for healthcare professionals at a UK Hospital Trust. METHODS: The evaluation spanned three cohorts (2017-2019) and a total of 54 participants, employing mixed methods to assess participant reactions, learning, behaviour changes and organisational impact. Quantitative pre-/post-measures included the Primary Colours Questionnaire (PCQ), Medical Leadership Competency Framework Questionnaire (MLCFQ) and Brief Resilience Scale (BRS), while qualitative data were gathered via free-text comments and long-term follow-up interviews. RESULTS: The programme had high satisfaction ratings, with particularly positive feedback relating to the multidisciplinary cohort and experiential learning via Quality Improvement projects. Findings indicated improvements in participants' leadership skills, knowledge, confidence and job satisfaction. Organisational outcomes included increased organisational interest in quality improvement and individual career progression. CONCLUSION: The results highlight the value of a structured leadership programme in developing healthcare leaders and driving organisational improvements, with long-term effects. Recommendations for future programmes include multidisciplinary involvement, experiential learning, inspiring speakers and embedded mixed-methods evaluation.
Patient buy-in to social prescribing through link workers as part of person-centred care: a realist evaluation.
BACKGROUND: Social prescribing link workers have become part of primary health care in recent years. They help patients to recognise non-medical factors affecting their health and identify sources of support, often in the voluntary, community and social enterprise sector. They form part of wider work to strengthen person-centred care, which actively seeks to engage individuals in decision-making about their health, taking into account their medical, social, psychological, financial and spiritual circumstances. OBJECTIVE: To understand how buy-in to social prescribing and the link worker role is established for a patient, and how this relates to person-centred care. DESIGN: A realist evaluation. SETTING: Patients engaging with link workers in seven different parts of England were involved. METHODS: As part of data collection, we observed link workers interacting with 35 patients. We also interviewed 61 patients and re-interviewed 41 of them 9-12 months later. Data were coded and developed into context-mechanism-outcome configurations, which were used to produce a programme theory. RESULTS: Data highlighted how patients might be uncertain about the link worker role but agree to a referral as they sought assistance with their non-medical issues. Patients talked about experiencing a sense of hope through the trust they developed in a link worker. This trust was established through the communication skills and knowledge demonstrated by a link worker, and by their ability to act as an anchor point when required - a reliable, consistent source of support to whom patients could offload. The link worker role also involved connecting patients to external support, which called for sensitivity around how ready someone was to move forward; this was shaped by a patient's motivation but also their capacity to make changes given other demands in their life. Connecting patients to external support could be affected by structural factors outside the link workers' control (e.g. housing options or employment opportunities). LIMITATIONS: We did not interview patients who had rejected the offer of social prescribing, and most had a positive view of meeting with a link worker. CONCLUSIONS: Person-centred care is engendered by link workers through their skills, knowledge and ability to respond to the individual readiness of patients to engage with external support. It can be curtailed by structural factors outside link workers' sphere of control, such as access to housing or caring responsibilities of patients. This can hinder patients' ability to 'connect to', leaving link workers to continue 'connecting with' patients as they act as an anchor point. FUTURE WORK: Exploration is required of factors affecting patients who interact with a link worker but do not access external support. Longitudinal work with a cohort of patients, speaking to them on a regular basis, may provide further understanding in this respect. FUNDING: This article presents independent research funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme as award number NIHR130247.
Clinical Prediction Models Incorporating Blood Test Trend for Cancer Detection: Systematic Review, Meta-Analysis, and Critical Appraisal.
BACKGROUND: Blood tests used to identify patients at increased risk of undiagnosed cancer are commonly used in isolation, primarily by monitoring whether results fall outside the normal range. Some prediction models incorporate changes over repeated blood tests (or trends) to improve individualized cancer risk identification, as relevant trends may be confined within the normal range. OBJECTIVE: Our aim was to critically appraise existing diagnostic prediction models incorporating blood test trends for the risk of cancer. METHODS: MEDLINE and EMBASE were searched until April 3, 2025 for diagnostic prediction model studies using blood test trends for cancer risk. Screening was performed by 4 reviewers. Data extraction for each article was performed by 2 reviewers independently. To critically appraise models, we narratively synthesized studies, including model building and validation strategies, model reporting, and the added value of blood test trends. We also reviewed the performance measures of each model, including discrimination and calibration. We performed a random-effects meta-analysis of the c-statistic for a trends-based prediction model if there were at least 3 studies validating the model. The risk of bias was assessed using the PROBAST (prediction model risk of bias assessment tool). RESULTS: We included 16 articles, with a total of 7 models developed and 14 external validation studies. In the 7 models derived, full blood count (FBC) trends were most commonly used (86%, n=7 models). Cancers modeled were colorectal (43%, n=3), gastro-intestinal (29%, n=2), nonsmall cell lung (14%, n=1), and pancreatic (14%, n=1). In total, 2 models used statistical logistic regression, 2 used joint modeling, and 1 each used XGBoost, decision trees, and random forests. The number of blood test trends included in the models ranged from 1 to 26. A total of 2 of 4 models were reported with the full set of coefficients needed to predict risk, with the remaining excluding at least one coefficient from their article or were not publicly accessible. The c-statistic ranged 0.69-0.87 among validation studies. The ColonFlag model using trends in the FBC was commonly externally validated, with a pooled c-statistic=0.81 (95% CI 0.77-0.85; n=4 studies) for 6-month colorectal cancer risk. Models were often inadequately tested, with only one external validation study assessing model calibration. All 16 studies scored a low risk of bias regarding predictor and outcome details. All but one study scored a high risk of bias in the analysis domain, with most studies often removing patients with missing data from analysis or not adjusting the derived model for overfitting. CONCLUSIONS: Our review highlights that blood test trends may inform further investigation for cancer. However, models were not available for most cancer sites, were rarely externally validated, and rarely assessed calibration when they were externally validated.
Variation in prescription duration for long term conditions: a cohort study in English NHS primary care using OpenPrescribing.
BACKGROUND: Many patients receive routine medications for long-term conditions (LTCs). Doctors typically issue repeat prescriptions in one to three month durations, but England currently has no national guidance on the optimal duration. AIM: Describe current prescription durations for common LTCs in England, explore and visualise geographical variation, and identify practice factors associated with shorter prescribing duration to inform policy making. Design and Setting A retrospective cohort study of English GP prescribing data December 2018-November 2019 Methods: We calculated the duration of prescriptions for common LTCs in England including the medications ramipril, atorvastatin, simvastatin, levothyroxine and amlodipine . We assessed the level of variation between regional clinical commissioning groups (CCGs) and determined practice factors associated with different durations. RESULTS: Of the common medications included, 28-day (one-monthly) prescriptions accounted for 48.5% (2.5 billion) tablets/capsules issued, whilst 43.6% were issued for 56 days (two monthly). There was very wide regional variation in the proportion of 28-day prescriptions (7.2% to 95.0%). Practice dispensing status was the most likely predictor of prescription duration. The proportion of patients with LTCs and the electronic health record software used by a practice were also associated with prescription duration. CONCLUSIONS: One month prescription durations are common for patients taking medicines routinely for long term conditions, particularly in dispensing practices. Electronic health record configurations offer an opportunity to implement and evaluate new policies on repeat prescription duration in England.
Social demographics and clinical characteristics of referred adult mental health patients to an Australian secure extended care unit: A 5-year retrospective study.
INTRODUCTION: Secure Extended Care Units (SECU) offer low-secure, long-term inpatient rehabilitation for patients with severe mental illnesses. Limited research is available about the profile of patients referred to such units. OBJECTIVE: This study aimed to explore the sociodemographic and clinical characteristics of patients referred to Austin Health SECU over a 5-year period in Australia. METHODS: A retrospective study design was used to investigate 121 consecutive referrals. The 98 first-time patient referrals were included in the primary analysis. Descriptive statistics were used with non-parametric comparisons (Chi-square and Fisher's exact test where appropriate). RESULTS: Most of the total sample were single males of European ancestry, between 25 and 34 years old, with 10 years or less of education and receiving disability benefits. Schizophrenia was the predominant diagnosis, with 50% having a comorbid personality trait/disorder; substance use was high (82.6%). More than three-fourths had a history of trauma. Physical comorbidity was high (80%), with hepatitis C positivity at 20%. Treatments like Clozapine and Electroconvulsive therapy (ECT) were low. The Median Health of Nations Outcome Scale (HoNOS) was 20 (IQR: 14, 23) and the Life Skills Profile (LSP) was 22.5 (IQR: 16.25, 27). CONCLUSIONS: Referrals showed a high level of psychosocial-physical complexity, with a range of patient needs, service goals, and high psychiatric and interpersonal risk before the referral. The study discusses the need for medium and high-secure beds and a new model of care that integrates Community Care Units (CCU). A trauma-informed approach that creates holistic treatment plans and includes patients and families is indicated. The study makes a case for Universal screening of patients for Bloodborne Hepatitis and treatment for this cohort in an inpatient setting.
Use of integrated services in antenatal care: A case study of Mabvuku Polyclinic, Zimbabwe.
Background The integration of diagnostic services presents a critical opportunity to improve health outcomes in low- and middle-income countries (LMICs), potentially averting up to 1 million premature deaths annually. Antenatal care provides a critical platform for diagnosing multiple diseases in an integrated manner.Aim This study explored the experiences of healthcare providers and pregnant women using integrated diagnostic services at a primary care facility in Zimbabwe.Setting A qualitative case study was conducted at Mabvuku Polyclinic in Harare, Zimbabwe.Methods Using purposive sampling, 14 healthcare workers and 22 pregnant women participated in interviews. Observations and semi-structured interviews were recorded, transcribed and analysed using NVivo software. Thematic analysis was applied to identify key themes related to access, patient-provider interactions and systemic barriers.Results According to the interviewees' reports, challenges such as limited resources, medical equipment and staff hinder efforts to integrate diagnostic services. The women strongly preferred integrated diagnosis, even if it meant enduring long waiting times, and valued the convenience of receiving all necessary services in a single visit. The study highlighted the hidden socio-economic barriers to 'free' healthcare and underscored the importance of addressing systemic inefficiencies.Conclusion The insights gained from this study are transferable and contribute to the understanding of integrated diagnostic services in maternal healthcare contexts.Contribution: They offer practical recommendations for improving service delivery and health outcomes in similar settings.
The Pandemic EVIDENCE Collaboration (EVidence-Informed DevelopmEnt of Non-PharmaCological IntErventions) Pillar 3: Practice and Policy
Slide presentation Pillar 3: Practice and Policy
The Pandemic EVIDENCE Collaboration (EVidence-Informed DevelopmEnt of Non-PharmaCological IntErventions) Pillar 2: Interventions and Evidence
Slide Presentation Pillar 2: Interventions and Evidence
Developing prediction models for electrolyte abnormalities in patients indicated for antihypertensive therapy: evidence-based treatment and monitoring recommendations
Objectives: Evidence from clinical trials suggests that antihypertensive treatment is associated with an increased risk of common electrolyte abnormalities. We aimed to develop and validate two clinical prediction models to estimate the risk of hyperkalaemia and hyponatraemia, respectively, to facilitate targeted treatment and monitoring strategies for individuals indicated for antihypertensive therapy. Design and methods: Participants aged at least 40 years, registered to an English primary care practice within the Clinical Practice Research Datalink (CPRD), with a systolic blood pressure reading between 130 and 179 mmHg were included the study. The primary outcomes were first hyperkalaemia or hyponatraemia event recorded in primary or secondary care. Model development used a Fine-Gray approach with death from other causes as competing event. Model performance was assessed using C-statistic, D-statistic, and Observed/Expected (O/E) ratio upon external validation. Results: The development cohort included 1 773 224 patients (mean age 59 years, median follow-up 6 years). The hyperkalaemia model contained 23 predictors and the hyponatraemia model contained 29 predictors, with all antihypertensive medications associated with the outcomes. Upon external validation in a cohort of 3 805 366 patients, both models calibrated well (O/E ratio: hyperkalaemia 1.16, 95% CI 1.13-1.19; hyponatraemia 1.00, 95% CI 0.98-1.02) and showed good discrimination at 10 years (C-statistic: 0.69, 95% CI 0.69-0.69; 0.80, 95% CI 0.80-0.80, respectively). Conclusion: Current clinical guidelines recommend monitoring serum electrolytes after initiating antihypertensive treatment. These clinical prediction models predicted individuals' risk of electrolyte abnormalities associated with antihypertensive treatment and could be used to target closer monitoring for individuals at a higher risk, where resources are limited.