SummaryThe majority of UK hospitals now have a Local Lead for Peri-operative Medicine (n = 115). They were asked to take part in an online survey to identify provision and practice of pre-operative assessment and optimisation in the UK. We received 86 completed questionnaires (response rate 75%). Our results demonstrate strengths in provision of shared decision-making clinics. Fifty-seven (65%, 95%CI 55.8-75.4%) had clinics for high-risk surgical patients. However, 80 (93%, 70.2-87.2%) expressed a desire for support and training in shared decision-making. We asked about management of pre-operative anaemia, and identified that 69 (80%, 71.5-88.1%) had a screening process for anaemia, with 72% and 68% having access to oral and intravenous iron therapy, respectively. A need for perioperative support in managing frailty and cognitive impairment was identified, as few (24%, 6.5-34.5%) respondents indicated that they had access to specific interventions. Respondents were asked to rank their 'top five' priority topics in Peri-operative Medicine from a list of 22. These were: shared decision-making; peri-operative team development; frailty screening and its management; postoperative morbidity prediction; and primary care collaboration. We found variation in practice across the UK, and propose to further explore this variation by examining barriers and facilitators to improvement, and highlighting examples of good practice.

Acute postoperative pain is common, distressing and associated with increased morbidity. Targeted interventions can prevent its development. We aimed to develop and internally validate a predictive tool to preemptively identify patients at risk of severe pain following major surgery. We analysed data from the UK Perioperative Quality Improvement Programme to develop and validate a logistic regression model to predict severe pain on the first postoperative day using pre-operative variables. Secondary analyses included the use of peri-operative variables. Data from 17,079 patients undergoing major surgery were included. Severe pain was reported by 3140 (18.4%) patients; this was more prevalent in females, patients with cancer or insulindependent diabetes, current smokers and in those taking baseline opioids. Our final model included 25 preoperative predictors with an optimism-corrected c-statistic of 0.66 and good calibration (mean absolute error 0.005, p = 0.35). Decision-curve analysis suggested an optimal cut-off value of 20-30% predicted risk to identify high-risk individuals. Potentially modifiable risk factors included smoking status and patient-reported measures of psychological well-being. Non-modifiable factors included demographic and surgical factors. Discrimination was improved by the addition of intra-operative variables (likelihood ratio v 2 496.5, p < 0.001) but not by the addition of baseline opioid data. On internal validation, our pre-operative prediction model was well calibrated but discrimination was moderate. Performance was improved with the inclusion of peri-operative covariates suggesting pre-operative variables alone are not sufficient to adequately predict postoperative pain.

Over 1.5 million major surgical procedures take place in the UK NHS each year and approximately 25% of patients develop at least one complication. The most widely used risk-adjustment model for postoperative morbidity in the UK is the physiological and operative severity score for the enumeration of mortality and morbidity. However, this model was derived more than 30 years ago and now overestimates the risk of morbidity. In addition, contemporary definitions of some model predictors are markedly different compared with when the tool was developed. A second model used in clinical practice is the American College of Surgeons National Surgical Quality Improvement Programme risk model; this provides a risk estimate for a range of postoperative complications. This model, widely used in North America, is not open source and therefore cannot be applied to patient populations in other settings. Data from a prospective multicentre clinical dataset of 118 NHS hospitals (the peri-operative quality improvement programme) were used to develop a bespoke risk-adjustment model for postoperative morbidity. Patients aged ≥ 18 years who underwent colorectal surgery were eligible for inclusion. Postoperative morbidity was defined using the postoperative morbidity survey at postoperative day 7. Thirty-one candidate variables were considered for inclusion in the model. Death or morbidity occurred by postoperative day 7 in 3098 out of 11,646 patients (26.6%). Twelve variables were incorporated into the final model, including (among others): Rockwood clinical frailty scale; body mass index; and index of multiple deprivation quintile. The C-statistic was 0.672 (95%CI 0.660-0.684), with a bootstrap optimism corrected C-statistic of 0.666 at internal validation. The model demonstrated good calibration across the range of morbidity estimates with a mean slope gradient of predicted risk of 0.959 (95%CI 0.894-1.024) with an index-corrected intercept of À0.038

Background This paper describes a rapid response project from the Chartered Institute of Ergonomics & Human Factors (CIEHF) to support the design, development, usability testing and operation of new ventilators as part of the UK response during the COVID-19 pandemic. Method A five-step approach was taken to (1) assess the COVID-19 situation and decide to formulate a response; (2) mobilise and coordinate Human Factors/Ergonomics (HFE) specialists; (3) ideate, with HFE specialists collaborating to identify, analyse the issues and opportunities, and develop strategies, plans and processes; (4) generate outputs and solutions; and (5) respond to the COVID-19 situation via targeted support and guidance. Results The response for the rapidly manufactured ventilator systems (RMVS) has been used to influence both strategy and practice to address concerns about changing safety standards and the detailed design procedure with RMVS manufacturers. Conclusion The documents are part of a wider collection of HFE advice which is available on the CIEHF COVID-19 website (https://covid19.ergonomics.org.uk/).

In 2016, NHS England set up 10 integrated care systems (ICSs) which aim to devolve some responsibility for delivery of health and social care services to local healthcare providers in partnership with local government, social care, primary care networks, and voluntary and charitable organisations. These are new ways of working and provide an opportunity to better integrate perioperative care across the entire pathway from the moment of contemplation of surgery through to recovery at home. This review describes the ways in which the aims of many ICS plans can be met with good perioperative care, and how clinicians can use this opportunity to make significant progress in improving outcomes for patients. We describe examples of initiatives in cancer pathways which are already proving successful and have caught the imagination of the local community at all levels, as well as examples of integrated perioperative care across the country which can be applied to other systems. We hope to demonstrate ways in which perioperative care can add value to a local health population given the right support and chance to deliver it.

Introduction Major surgery accounts for a substantial proportion of health service activity, due not only to the primary procedure, but the longer-term health implications of poor short-term outcome. Data from small studies or from outside the UK indicate that rates of complications and failure to rescue vary between hospitals, as does compliance with best practice processes. Within the UK, there is currently no system for monitoring postoperative complications (other than short-term mortality) in major non-cardiac surgery. Further, there is variation between national audit programmes, in the emphasis placed on quality assurance versus quality improvement, and therefore the principles of measurement and reporting which are used to design such programmes. Methods and analysis The PQIP patient study is a multi-centre prospective cohort study which recruits patients undergoing major surgery. Patient provide informed consent and contribute baseline and outcome data from their perspective using a suite of patient-reported outcome tools. Research and clinical staff complete data on patient risk factors and outcomes in-hospital, including two measures of complications. Longer-term outcome data are collected through patient feedback and linkage to national administrative datasets (mortality and readmissions). As well as providing a uniquely granular dataset for research, PQIP provides feedback to participating sites on their compliance with evidence-based processes and their patients’ outcomes, with the aim of supporting local quality improvement. Ethics and dissemination Ethical approval has been granted by the Health Research Authority in the UK. Dissemination of interim findings (non-inferential) will form a part of the improvement methodology and will be provided to participating centres at regular intervals, including near-real time feedback of key process measures. Inferential analyses will be published in the peer-reviewed literature, supported by a comprehensive multi-modal communications strategy including to patients, policy makers and academic audiences as well as clinicians.

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