Connections, Communication and Collaboration in Healthcare’s Complex Adaptive Systems Comment on “Using Complexity and Network Concepts to Inform Healthcare Knowledge Translation”

Abstract A more sophisticated understanding of the unpredictable, disorderly and unstable aspects of healthcare organisations is developing in the knowledge translation (KT) literature. In an article published in this journal, Kitson et al introduced a new model for KT in healthcare based on complexity theory. The Knowledge Translation Complexity Network Model (KTCNM) provides a fresh perspective by making the complexity inherent in complex systems overt. The model encourages a whole system view and focuses on the interdependent relationships between actions, interactions and actors. Taking a systems approach assists our understanding of the connections, communication and collaboration necessary to promote knowledge mobilisation and facilitate the adoption of change. With further development, this could enable the targeting of more effective strategies across the various stakeholders and levels of service, fostering redesign and innovation

Equity in vaccine trials for higher weight people? A rapid review of weight-related inclusion and exclusion criteria for COVID-19 clinical trials

Higher weight status, defined as body mass index (BMI) ≥ 30 kg/m2, is frequently described as a risk factor for severity and susceptibility to severe acute respiratory syndrome coron-avirus 2 (SARS-CoV-2) disease (known as COVID-19). Therefore, study groups in COVID-19 vaccine trials should be representative of the weight spectrum across the global population. Appropriate subgroup analysis should be conducted to ensure equitable vaccine outcomes for higher weight people. In this study, inclusion and exclusion criteria of registered clinical trial protocols were reviewed to determine the proportion of trials including higher weight people, and the proportion of trials conducting subgroup analyses of efficacy by BMI. Eligibility criteria of 249 trial protocols (phase I, II, III and IV) were analysed; 51 protocols (20.5%) specified inclusion of BMI > 30, 73 (29.3%) specified exclusion of BMI > 30, and 125 (50.2%) did not specify whether BMI was an inclusion or exclusion criterion, or if BMI was included in any ‘health’ screenings or physical examinations during recruitment. Of the 58 protocols for trials in phase III and IV, only 2 (3.4%) indicated an intention to report subgroup analysis of vaccine efficacy by weight status. Higher weight people appear to be significantly under-represented in the majority of vaccine trials. This may result in reduced efficacy and acceptance of COVID-19 vaccines for higher weight people and exacerbation of health inequities within this population group. Explicit inclusion of higher weight people in COVID-19 vaccine trials is required to reduce health inequities

Development and external validation of the eFalls tool: a multivariable prediction model for the risk of ED attendance or hospitalisation with a fall or fracture in older adults.

Falls are common in older adults and can devastate personal independence through injury such as fracture and fear of future falls. Methods to identify people for falls prevention interventions are currently limited, with high risks of bias in published prediction models. We have developed and externally validated the eFalls prediction model using routinely collected primary care electronic health records (EHR) to predict risk of emergency department attendance/hospitalisation with fall or fracture within 1 year. Data comprised two independent, retrospective cohorts of adults aged ≥65 years: the population of Wales, from the Secure Anonymised Information Linkage Databank (model development); the population of Bradford and Airedale, England, from Connected Bradford (external validation). Predictors included electronic frailty index components, supplemented with variables informed by literature reviews and clinical expertise. Fall/fracture risk was modelled using multivariable logistic regression with a Least Absolute Shrinkage and Selection Operator penalty. Predictive performance was assessed through calibration, discrimination and clinical utility. Apparent, internal-external cross-validation and external validation performance were assessed across general practices and in clinically relevant subgroups. The model's discrimination performance (c-statistic) was 0.72 (95% confidence interval, CI: 0.68 to 0.76) on internal-external cross-validation and 0.82 (95% CI: 0.80 to 0.83) on external validation. Calibration was variable across practices, with some over-prediction in the validation population (calibration-in-the-large, -0.87; 95% CI: -0.96 to -0.78). Clinical utility on external validation was improved after recalibration. The eFalls prediction model shows good performance and could support proactive stratification for falls prevention services if appropriately embedded into primary care EHR systems. [Abstract copyright: © The Author(s) 2024. Published by Oxford University Press on behalf of the British Geriatrics Society.

Predicting pain and function outcomes in people consulting with shoulder pain: the PANDA-S clinical cohort and qualitative study protocol

Introduction: People presenting with shoulder pain considered to be of musculoskeletal origin is common in primary care but diagnosing the cause of the pain is contentious, leading to uncertainty in management. To inform optimal primary care for patients with shoulder pain, the study aims to (1) to investigate the short-term and long-term outcomes (overall prognosis) of shoulder pain, (2) estimate costs of care, (3) develop a prognostic model for predicting individuals' level and risk of pain and disability at 6 months and (4) investigate experiences and opinions of patients and healthcare professionals regarding diagnosis, prognosis and management of shoulder pain. Methods and analysis: The Prognostic And Diagnostic Assessment of the Shoulder (PANDA-S) study is a longitudinal clinical cohort with linked qualitative study. At least 400 people presenting to general practice and physiotherapy services in the UK will be recruited. Participants will complete questionnaires at baseline, 3, 6, 12, 24 and 36 months. Short-term data will be collected weekly between baseline and 12 weeks via Short Message Serevice (SMS) text or software application. Participants will be offered clinical (physiotherapist) and ultrasound (sonographer) assessments at baseline. Qualitative interviews with ≈15 dyads of patients and their healthcare professional (general practitioner or physiotherapist).Short-term and long-term trajectories of Shoulder Pain and Disability Index (using SPADI) will be described, using latent class growth analysis. Health economic analysis will estimate direct costs of care and indirect costs related to work absence and productivity losses. Multivariable regression analysis will be used to develop a prognostic model predicting future levels of pain and disability at 6 months using penalisation methods to adjust for overfitting. The added predictive value of prespecified physical examination tests and ultrasound findings will be examined. For the qualitative interviews an inductive, exploratory framework will be adopted using thematic analysis to investigate decision making, perspectives of patients and clinicians on the importance of diagnostic and prognostic information when negotiating treatment and referral options. Ethics and dissemination: The PANDA-S study has ethical approval from Yorkshire and The Humber-Sheffield Research Ethics Committee, UK (18/YH/0346, IRAS Number: 242750). Results will be disseminated through peer-reviewed publications, social and mainstream media, professional conferences, and the patient and public involvement and engagement group supporting this study, and through newsletters, leaflets and posters in participating sites

Introducing voluntary assisted dying: staff perspectives in an acute hospital

Background: Voluntary assisted dying (VAD) was legalised in Victoria, Australia in June 2019. Physicians can now assist patients to end their lives by providing drugs for self-administration at their voluntary and competent request (or for physician administration in limited circumstances). This study investigates the opinions of clinicians on the implementation of the legislation in one Victorian hospital. Methods: This exploratory survey study was conducted at a 600-bed acute hospital in Melbourne, Australia in Jan 2019. 382 clinicians completed one or more qualitative questions. Participants commented on VAD, potential workplace challenges and staff support required. Free-text responses were analysed using inductive content analysis. Results: Six themes: (1) Polarised views; (2) Fear of conflict; (3) Emotional burden; (4) Vulnerable patients; (5) Organisational challenges; (6) Decision-making. There were diverse views including objections to VAD for religious or ethical reasons, and whole-hearted support based on a compassionate response to suffering and the right of patients to self-determination. Participants feared conflict between colleagues, families and patients, and aggression towards staff. Clinicians called for educational and psychological support. There was concern that vulnerable patients may be coerced to opt for VAD to lessen the burden on families or the health system. Clinicians feared workloads would increase with the introduction of VAD. Patient decision-making capacity in this context must be firmly established before proceeding, and thorough assessments for depression, and optimal symptom management must be implemented before VAD is approved. A dedicated VAD team was suggested to support staff and manage VAD patients. Conclusion: Participants expressed polarised opinions about VAD and showed considerable anxiety about its introduction. Additional education and support are required to ensure that clinicians understand details of the legislation and their professional and personal options. Tolerance and respect for alternative viewpoints must be advocated within the organisation and more broadly