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.
Among patients undergoing emergency laparotomy, 30-day postoperative mortality is around 10–15%. The risk of death among these patients, however, varies greatly because of their clinical ...characteristics. We developed a risk prediction model for 30-day postoperative mortality to enable better comparison of outcomes between hospitals.
We analysed data from the National Emergency Laparotomy Audit (NELA) on patients having an emergency laparotomy between December 2013 and November 2015. A prediction model was developed using multivariable logistic regression, with potential risk factors identified from existing prediction models, national guidelines, and clinical experts. Continuous risk factors were transformed if necessary to reflect their non-linear relationship with 30-day mortality. The performance of the model was assessed in terms of its calibration and discrimination. Interval validation was conducted using bootstrap resampling.
There were 4458 (11.5%) deaths within 30-days among the 38 830 patients undergoing emergency laparotomy. Variables associated with death included (among others): age, blood pressure, heart rate, physiological variables, malignancy, and ASA physical status classification. The predicted risk of death among patients ranged from 1% to 50%. The model demonstrated excellent calibration and discrimination, with a C-statistic of 0.863 (95% confidence interval, 0.858–0.867). The model retained its high discrimination during internal validation, with a bootstrap derived C-statistic of 0.861.
The NELA risk prediction model for emergency laparotomies discriminates well between low- and high-risk patients and is suitable for producing risk-adjusted provider mortality statistics.
We present the main findings of the 5th National Audit Project (NAP5) on accidental awareness during general anaesthesia (AAGA). Incidences were estimated using reports of accidental awareness as the ...numerator, and a parallel national anaesthetic activity survey to provide denominator data. The incidence of certain/probable and possible accidental awareness cases was ∼1:19 600 anaesthetics (95% confidence interval 1:16 700–23 450). However, there was considerable variation across subtypes of techniques or subspecialities. The incidence with neuromuscular block (NMB) was ∼1:8200 (1:7030–9700), and without, it was ∼1:135 900 (1:78 600–299 000). The cases of AAGA reported to NAP5 were overwhelmingly cases of unintended awareness during NMB. The incidence of accidental awareness during Caesarean section was ∼1:670 (1:380–1300). Two-thirds (82, 66%) of cases of accidental awareness experiences arose in the dynamic phases of anaesthesia, namely induction of and emergence from anaesthesia. During induction of anaesthesia, contributory factors included: use of thiopental, rapid sequence induction, obesity, difficult airway management, NMB, and interruptions of anaesthetic delivery during movement from anaesthetic room to theatre. During emergence from anaesthesia, residual paralysis was perceived by patients as accidental awareness, and commonly related to a failure to ensure full return of motor capacity. One-third (43, 33%) of accidental awareness events arose during the maintenance phase of anaesthesia, mostly due to problems at induction or towards the end of anaesthesia. Factors increasing the risk of accidental awareness included: female sex, age (younger adults, but not children), obesity, anaesthetist seniority (junior trainees), previous awareness, out-of-hours operating, emergencies, type of surgery (obstetric, cardiac, thoracic), and use of NMB. The following factors were not risk factors for accidental awareness: ASA physical status, race, and use or omission of nitrous oxide. We recommend that an anaesthetic checklist, to be an integral part of the World Health Organization Safer Surgery checklist, is introduced as an aid to preventing accidental awareness. This paper is a shortened version describing the main findings from NAP5—the full report can be found at http://www.nationalauditprojects.org.uk/NAP5_home.
ObjectiveTo identify research priorities for Anaesthesia and Perioperative Medicine.DesignProspective surveys and consensus meetings guided by an independent adviser.SettingUK.Participants45 ...stakeholder organisations (25 professional, 20 patient/carer) affiliated as James Lind Alliance partners.OutcomesFirst ‘ideas-gathering’ survey: Free text research ideas and suggestions. Second ‘prioritisation’ survey: Shortlist of ‘summary’ research questions (derived from the first survey) ranked by respondents in order of priority. Final ‘top ten’: Agreed by consensus at a final prioritisation workshop.ResultsFirst survey: 1420 suggestions received from 623 respondents (49% patients/public) were refined into a shortlist of 92 ‘summary’ questions. Second survey: 1718 respondents each nominated up to 10 questions as research priorities. Top ten: The 25 highest-ranked questions advanced to the final workshop, where 23 stakeholders (13 professional, 10 patient/carer) agreed the 10 most important questions:▸ What can we do to stop patients developing chronic pain after surgery?▸ How can patient care around the time of emergency surgery be improved?▸ What long-term harm may result from anaesthesia, particularly following repeated anaesthetics?▸ What outcomes should we use to measure the ‘success’ of anaesthesia and perioperative care?▸ How can we improve recovery from surgery for elderly patients?▸ For which patients does regional anaesthesia give better outcomes than general anaesthesia?▸ What are the effects of anaesthesia on the developing brain?▸ Do enhanced recovery programmes improve short and long-term outcomes?▸ How can preoperative exercise or fitness training, including physiotherapy, improve outcomes after surgery?▸ How can we improve communication between the teams looking after patients throughout their surgical journey?ConclusionsAlmost 2000 stakeholders contributed their views regarding anaesthetic and perioperative research priorities. This is the largest example of patient and public involvement in shaping anaesthetic and perioperative research to date.
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 pre-emptively identify patients at risk of severe pain following major surgery. We analysed data from the UK Peri-operative 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 insulin-dependent diabetes, current smokers and in those taking baseline opioids. Our final model included 25 pre-operative 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 χ
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.
Summary
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 −0.038 (95%CI −0.112–0.036) at internal validation. Our model provides parsimonious case‐mix adjustment to quantify risk of morbidity on postoperative day 7 for a UK population of patients undergoing major colorectal surgery. Despite the C‐statistic of < 0.7, our model outperformed existing risk‐models in widespread use. We therefore recommend application in case‐mix adjustment, where incorporation into a continuous monitoring tool such as the variable life adjusted display or exponentially‐weighted moving average‐chart could support high‐level monitoring and quality improvement of risk‐adjusted outcome at the population level.
The 5th National Audit Project (NAP5) of the Royal College of Anaesthetists and the Association of Anaesthetists of Great Britain and Ireland into accidental awareness during general anaesthesia ...(AAGA) yielded data related to psychological aspects from the patient, and the anaesthetist, perspectives; patients' experiences ranged from isolated auditory or tactile sensations to complete awareness. A striking finding was that 75% of experiences were for <5 min, yet 51% of patients 95% confidence interval (CI) 43–60% experienced distress and 41% (95% CI 33–50%) suffered longer term adverse effect. Distress and longer term harm occurred across the full range of experiences but were particularly likely when the patient experienced paralysis (with or without pain). The patient's interpretation of what is happening at the time of the awareness seemed central to later impact; explanation and reassurance during suspected AAGA or at the time of report seemed beneficial. Quality of care before the event was judged good in 26%, poor in 39%, and mixed in 31%. Three-quarters of cases of AAGA (75%) were judged preventable. In 12%, AAGA care was judged good and the episode not preventable. The contributory and human factors in the genesis of the majority of cases of AAGA included medication, patient, and education/training. The findings have implications for national guidance, institutional organization, and individual practice. The incidence of ‘accidental awareness' during sedation (∼1:15 000) was similar to that during general anaesthesia (∼1:19 000). The project raises significant issues about information giving and consent for both sedation and anaesthesia. We propose a novel approach to describing sedation from the patient's perspective which could be used in communication and consent. Eight (6%) of the patients had resorted to legal action (12, 11%, to formal complaint) at the time of reporting. NAP5 methodology provides a standardized template that might usefully inform the investigation of claims or serious incidents related to AAGA.
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