Perioperative shared decision making - How do we train clinicians?

Objective: Decision making about high-risk surgery can be complex, particularly when outcomes may be uncertain. Clinicians have a legal and ethical responsibility to support decision making which fits with patients' values and preferences. In the UK, preoperative assessment and optimisation is led by Anaesthetists in clinic several weeks prior to planned surgery. Training in supporting shared decision making (SDM) has been identified as an area of need among UK anaesthetists with leadership roles in perioperative care. Methods: We describe adaptation of a generic SDM workshop to perioperative care, in particular to decisions on high-risk surgery, and its delivery to UK healthcare professionals over a two-year period. Feedback from workshops were thematically analysed. We explored further improvements to the workshop and ideas for development and dissemination. Results: The workshops were well received, with high satisfaction for techniques used, including video demonstrations, role-play and discussions. Thematic analysis identified a desire for multidisciplinary training and training in using patient aids. Conclusion: Qualitative findings suggest workshops were considered useful with perceived improvement in SDM awareness, skills and reflective practice. Innovation: This pilot introduces a new modality of training in the perioperative setting providing physicians, particularly Anaesthetists, with previously unavailable training needed to facilitate complex discussions.

Implementing shared decision making according to the choosing wisely programme: Perioperative medicine for older people undergoing surgery.

BACKGROUND: Shared decision making (SDM) is the process whereby patients and healthcare professionals work together to achieve a consensus management decision, based on best clinical evidence and patient's preferences. No formal approach to documentation of SDM conversations exists in setting of peri-operative medicine. OBJECTIVE: To assess and improve the quality and consistency of documentation regarding SDM conversations in an elective surgical outpatient population and appraise the satisfaction of patients and professionals in SDM. METHODS: The study was conducted in a geriatrician led perioperative medicine for older people undergoing surgery service, at an inner-city teaching hospital serving a tertiary surgical referral population. The quality improvement programme intervention comprised a Choosing Wisely, UK SDM tool, consisting of Benefits, Risks, Alternatives and Doing Nothing (BRAN mnemonic), clinic posters, patient leaflets, and an introductory SDM workshop and education sessions, and observation and standardised feedback of SDM. Clinic letters were reviewed to identify SDM documentation compliance. Participants included clinicians of all grades and disciplines, and consecutive patients attending the clinic. RESULTS: Clinician interviews revealed inconsistent documentation of SDM. We reviewed 203 clinic letters following the initial implementation of SDM documentation tool, only 59% (n = 120) had fully completement BRAN tool. Additional interventions improved clinic SDM documentation compliance to 98%. A prospective observation study conducted revealed patients and clinician satisfaction at 93% and 79%, respectively. CONCLUSION: The BRAN tool is adaptable to many health decision settings, including discussions related to treatment, investigations, and procedures, which expands its potential to improve patient safety.

Predicting Hospital Resource Use During COVID-19 Surges: A Simple but Flexible Discretely Integrated Condition Event Simulation of Individual Patient-Hospital Trajectories.

OBJECTIVES: To assist with planning hospital resources, including critical care (CC) beds, for managing patients with COVID-19. METHODS: An individual simulation was implemented in Microsoft Excel using a discretely integrated condition event simulation. Expected daily cases presented to the emergency department were modeled in terms of transitions to and from ward and CC and to discharge or death. The duration of stay in each location was selected from trajectory-specific distributions. Daily ward and CC bed occupancy and the number of discharges according to care needs were forecast for the period of interest. Face validity was ascertained by local experts and, for the case study, by comparing forecasts with actual data. RESULTS: To illustrate the use of the model, a case study was developed for Guy's and St Thomas' Trust. They provided inputs for January 2020 to early April 2020, and local observed case numbers were fit to provide estimates of emergency department arrivals. A peak demand of 467 ward and 135 CC beds was forecast, with diminishing numbers through July. The model tended to predict higher occupancy in Level 1 than what was eventually observed, but the timing of peaks was quite close, especially for CC, where the model predicted at least 120 beds would be occupied from April 9, 2020, to April 17, 2020, compared with April 7, 2020, to April 19, 2020, in reality. The care needs on discharge varied greatly from day to day. CONCLUSIONS: The DICE simulation of hospital trajectories of patients with COVID-19 provides forecasts of resources needed with only a few local inputs. This should help planners understand their expected resource needs.

Teaching clinicians shared decision making and risk communication online: an evaluation study.

OBJECTIVES: To describe the development and initial evaluation of a brief e-learning course as a means of teaching shared decision making and risk communication skills to clinicians of all specialties. DESIGN: Comparison pre-course and post-course of scores in subjective confidence and objective knowledge about shared decision making and risk communication. SETTING: Online and open to all specialties and levels of clinical experience, including students. PARTICIPANTS: The course is freely available online and all who started the course from September 2018 to May 2020 were invited to participate in the evaluation study. INTERVENTION: The self-guided e-learning course is made up of four modules and takes approximately 2 hours to complete. It is hosted on the website of the Winton Centre for Risk Communication and the UK's National Health Service e-learning platform. MAIN OUTCOME MEASURES: Pre-course and post-course confidence in performing shared decision making (as measured by a 10-item scale adapted from the OPTION tool; total score range 10-50), and objective knowledge about basic principles of shared decision making and risk communication, as measured by performance on four knowledge questions and three calculations. At course commencement, a single item from the Berlin Numeracy Test, and the eight-item Subjective Numeracy Test were also asked. RESULTS: Of 366 unique participants who consented and commenced the course, 210 completed all modules and the final post-course test. Participants' mean age was 38.1 years, 69% were in current clinical practice and had a mean of 10.5 years of clinical practice. Numeracy was relatively low, with 50.7% correctly answering the Berlin Numeracy Test item pre-course. Participants who completed the course showed a significant improvement in their confidence by a mean summed score of 3.7 units (95% CI 2.9 to 4.6, p<0.0001) from a mean pre-course of 37.4 (SD 6.1) to post-course of 41.1 (SD 6.9). There was an increase in the proportion of correct answers for most knowledge questions (p<0.0001, p=0.013 for two directly compared), although no improvement in most skill questions that involved numbers (eg, calculating relative risks). Participants with higher numeracy appeared to show higher skill and confidence on most questions. CONCLUSIONS: This online, free e-learning course was successful in increasing participants' confidence in, and some aspects of knowledge about, shared decision making and risk communication. It also highlighted the need for improvements in clinicians' numerical skills as a vital part of training. We suggest that the course is used in combination with practical face-to-face experience and more intensive numerical skills training.

Shared decision making in perioperative medicine.

Shared decision making is a collaborative process between clinicians and patients, which aims to select the most suitable management option based on both best available evidence and patient preferences. This article looks at the role of shared decision making in perioperative medicine.

Primum Non Nocere: is shared decision-making the answer?

Surgical ambition is rising, with the Royal College of Surgeons reporting an increase in the number of procedures by a million over the past decade (Royal College of Surgeons. Surgery and the NHS in Numbers. Available from https://www.rcseng.ac.uk). Underpinning, this is a rapidly growing population, especially those in the over 85 age group, coupled with rising perioperative expertise; options for surgery are now present where conditions were once managed conservatively. Matching the right patient to the right procedure has never been so pertinent (Bader, Am Soc Anesthesiol 78(6), 2014). At the heart of these increasingly complex decisions, which may prove fatal or result in serious morbidity, lies the aspiration of shared decision-making (SDM) (Glance et al., N Engl J Med 370:1379-81, 2014). Shared decision-making is a patient-centred approach taking into account the beliefs, preferences and views of the patient as an expert in what is right for them, supported by clinicians who are the experts in diagnostics and valid therapeutic options (Coulter and Collins, Making shared decision-making a reality: no decision about me, without me, 2011). It has been described as the pinnacle of patient-centred care (Barry et al., N Engl J Med 366:780-1, 2012). In this commentary, we explore further the concept of shared decision-making, supported by a recent article which highlights critical deficits in current perioperative practice (Ankuda et al., Patient Educ Couns 94(3):328-33, 2014). This article was chosen for the purposes of this commentary as it is a large study across several surgical specialties investigating preoperative shared decision-making, and to our knowledge, the only of this kind.

The pressure exerted on the tracheal wall by two endotracheal tube cuffs: A prospective observational bench-top, clinical and radiological study.

BACKGROUND: The Lotrach endotracheal tube has a unique low-volume, low-pressure (LVLP) cuff, which has been designed to prevent pressure injury to the tracheal wall. We aimed to estimate the pressure exerted on the tracheal wall by the LVLP cuff and a conventional cuff in a bench-top, clinical and radiological study. METHOD: In the bench-top study, a model trachea was intubated with the LVLP cuff and the conventional cuff. The cuff pressure was controlled using a constant pressure device. We assessed the pressure exerted on the tracheal wall by measuring the ability of the cuffs to support a column of water using a standard protocol. In the clinical study, we tested the ability of both cuffs to prevent air leak during a staged recruitment manoeuvre. In the radiological study, we recorded the degree of anatomical distortion of the trachea from both cuffs in the antero-posterior (AP) and transverse tracheal diameters. We performed statistical analysis using non-inferiority tests. RESULTS: In the bench-top study, the LVLP cuff achieved a plateau at a mean height of 25.2 cmH2O (SD 0.34). In contrast, the conventional cuff failed to maintain any water above the cuff and a plateau could not be measured. In the clinical study, the mean pressure at which air leak occurred was 30.0 +/- 0.8 cmH2O (SD 3.8) using the LVLP cuff and 32.4 +/- 0.7 cmH2O (SD 3.0) using the conventional cuff. In the radiological study, the mean degree of anatomical distortion of the trachea in AP and transverse tracheal diameter was 2.9 +/- 2.2 mm (SD 2.1) and 1.8 +/- 1.4 mm (SD 1.4) using the LVLP cuff and 4.4 +/- 1.3 mm (SD 1.4) and 2.6 +/- 1.5 mm (SD 1.6) using the conventional cuff. CONCLUSIONS: The bench-top and clinical studies both demonstrated that the LVLP cuff exerted approximately 30 cmH2O of pressure on the tracheal wall. These results are supported by our radiological study. We conclude that the LVLP cuff exerts an acceptable amount of pressure on the tracheal wall when it is operated at the recommended intracuff pressure.