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The use of common surgical procedures varies widely across regions. Differences in illness burden, diagnostic practices, and patient attitudes about medical intervention explain only a small degree of regional variation in surgery rates. Evidence suggests that surgical variation results mainly from differences in physician beliefs about the indications for surgery, and the extent to which patient preferences are incorporated into treatment decisions. These two components of clinical decision making help to explain the so-called surgical signatures of specific procedures, and why some consistently vary more than others. Variation in clinical decision making is, in turn, affected by broad environmental factors, including technology diffusion, supply of specialists, local training frameworks, financial incentives, and regulatory factors, which vary across countries. Better scientific evidence about the comparative effectiveness of surgical and non-surgical interventions could help to mitigate regional variation, but broader dissemination of shared decision aids will be essential to reduce variation in preference-sensitive disorders.

High profile device failures have highlighted the inadequacies of current regulation. Art Sedrakyan and colleagues call for a move to a graduated model of approval and suggest a framework to achieve this goal

Digital health tools, platforms, and artificial intelligence– or machine learning–based clinical decision support systems are increasingly part of health delivery approaches, with an ever-greater degree of system interaction. Critical to the successful deployment of these tools is their functional integration into existing clinical routines and workflows. This depends on system interoperability and on intuitive and safe user interface design. The importance of minimizing emergent workflow stress through human factors research and purposeful design for integration cannot be overstated. Usability of tools in practice is as important as algorithm quality. Regulatory and health technology assessment frameworks recognize the importance of these factors to a certain extent, but their focus remains mainly on the individual product rather than on emergent system and workflow effects. The measurement of performance and user experience has so far been performed in ad hoc, nonstandardized ways by individual actors using their own evaluation approaches. We propose that a standard framework for system-level and holistic evaluation could be built into interacting digital systems to enable systematic and standardized system-wide, multiproduct, postmarket surveillance and technology assessment. Such a system could be made available to developers through regulatory or assessment bodies as an application programming interface and could be a requirement for digital tool certification, just as interoperability is. This would enable health systems and tool developers to collect system-level data directly from real device use cases, enabling the controlled and safe delivery of systematic quality assessment or improvement studies suitable for the complexity and interconnectedness of clinical workflows using developing digital health technologies.

Background Substance use among young people is a significant public health concern, particularly in Scotland. Primary prevention activities are essential in delaying young people’s substance use and reducing the harms associated with use. However, such prevention activities are generally lacking. The Icelandic Model (IM) has received increasing attention and has been associated with improvements in substance use in Iceland since the 1990s. There is interest in implementing the IM in Scotland but concerns regarding transferability. This research study aimed to address a gap in the evidence base by providing insight into stakeholders’ views of the IM in Dundee and more widely in Scotland. Methods Qualitative data were collected via semi-structured telephone interviews with 16 stakeholders. Data were analysed using Framework Analysis in NVivo, informed by the Consolidated Framework for Implementation Research. Results Participants were keen for more prevention activities to be delivered in Scotland and were generally supportive of the IM, given the high rates of substance use and related harm. A range of positive factors were identified, including the evidence base, the multi-component nature of the IM, and availability of current services that could be embedded into delivery. Several barriers were noted, relating to funding, the franchise model, support and buy-in and cultural differences. Conclusions Our findings provide insight into the views of a range of stakeholders regarding the potential implementation of the IM in Scotland, and perceived barriers and facilitators. There is a desire for primary prevention activities in Scotland, driven by concerns about high rates of substance use and related harms, and a general lack of effective and evidence based prevention activities across the country. Several key barriers would need to be addressed in order for implementation to be successful, and participants were clear that initial piloting is required. Future research and evaluation is required to examine its potential and the outcomes of the approach in Scotland.

Early prostate cancer, like breast cancer, is an example of a disease where the evidence has shown that persistence of local disease does not necessarily reduce the chances of long-term survival.3 The proposition behind the new procedure proposed by Sood et al is based on this understanding and on the recognition that patient values often encompass more than simply survival. In these circumstances, responsible innovation requires great care in minimizing risk to patients, complete transparency (both in reporting to peers and in explaining the situation to patients during informed consent), and the collection of the data most likely to assist us in reaching conclusions quickly and appropriately. Whatever your view of the merits of the precision prostatectomy, its publication in the IDEAL format is a commendable effort to ensure its evaluation proceeds according to ethical and scientific principles.

Digital Health Technologies (DHTs) are being applied in a widening range of scenarios in medicine. We describe the emerging phenomenon of the grouping of individual DHTs, with a clinical use case and regulatory approval in their own right, into packages to perform specific clinical tasks in defined settings. Example groupings include suites of devices for remote monitoring, or for smart clinics. In this first article of a two-article series, we describe challenges in implementation and limitations in frameworks for the regulation, health technology assessment, and reimbursement of these device suites and linked novel care pathways.

Correspondence to Peter McCulloch, Nuffield Department of Surgery, Oxford University, Oxford OX3 9DU, UK; peter.mcculloch@nds.ox.ac.uk Reducing harm in hospital care using Human Factors and Quality Improvement approaches has proved harder than expected: better evaluation of our efforts, a more realistic understanding of the challenges we face and an intense focus on engaging staff are the key elements needed for progress. [...]the Human Factors approaches we tried to adopt from other industries had developed organically over time to fit particular contexts, and over-literal translation to healthcare environments was often a poor fit.5 Third, our evaluation of our own efforts has been consistently weak, making it hard to learn the right lessons. [...]importantly, the modern healthcare industry, by its very nature, poses underlying wicked problems of interaction between structure and culture, which make change very hard. The pivotal study on the WHO surgical checklist was a short term, open label, non-randomised before–after comparison with evaluation performed by the team carrying out the study.7 12 13A subsequent observational whole-system study in Canada showed no benefit, and a later, better designed study showed no significant mortality reduction.13 14 The largest ever study of teamwork training compared trained and untrained units halfway through a multihospital programme, but selected units for training priority on the basis of ‘readiness’, thus introducing major bias.15 Randomised studies have been dismissed as impossible by leading figures in this field, but several have been done—and like randomised studies in other fields have tended to disappoint their authors.

Surgery and other invasive therapies are complex interventions, the assessment of which is challenged by factors that depend on operator, team, and setting, such as learning curves, quality variations, and perception of equipoise. We propose recommendations for the assessment of surgery based on a five-stage description of the surgical development process. We also encourage the widespread use of prospective databases and registries. Reports of new techniques should be registered as a professional duty, anonymously if necessary when outcomes are adverse. Case series studies should be replaced by prospective development studies for early technical modifications and by prospective research databases for later pre-trial evaluation. Protocols for these studies should be registered publicly. Statistical process control techniques can be useful in both early and late assessment. Randomised trials should be used whenever possible to investigate efficacy, but adequate pre-trial data are essential to allow power calculations, clarify the definition and indications of the intervention, and develop quality measures. Difficulties in doing randomised clinical trials should be addressed by measures to evaluate learning curves and alleviate equipoise problems. Alternative prospective designs, such as interrupted time series studies, should be used when randomised trials are not feasible. Established procedures should be monitored with prospective databases to analyse outcome variations and to identify late and rare events. Achievement of improved design, conduct, and reporting of surgical research will need concerted action by editors, funders of health care and research, regulatory bodies, and professional societies.

We previously developed and validated the Oxford NOTECHS rating system for evaluating the non-technical skills of an entire operating theatre team. Experience with the scale identified the need for greater discrimination between levels of performance within the normal range. We report here the development of a modified scale (Oxford NOTECHS II) to facilitate this. The new measure uses an eight-point instead of a four point scale to measure each dimension of non-technical skills, and begins with a default rating of 6 for each element. We evaluated this new scale in 297 operations at five NHS sites in four surgical specialities. Measures of theatre process reliability (glitch count) and compliance with the WHO surgical safety checklist were scored contemporaneously, and relationships with NOTECHS II scores explored. Mean team Oxford NOTECHS II scores was 73.39 (range 37-92). The means for surgical, anaesthetic and nursing sub-teams were 24.61 (IQR 23, 27); 24.22 (IQR 23, 26) and 24.55 (IQR 23, 26). Oxford NOTECHS II showed good inter-rater reliability between human factors and clinical observers in each of the four domains. Teams with high WHO compliance had higher mean Oxford NOTECHS II scores (74.5) than those with low compliance (71.1) (p = 0.010). We observed only a weak correlation between Oxford NOTECHS II scores and glitch count; r = -0.26 (95% CI -0.36 to -0.15). Oxford NOTECHS II scores did not vary significantly between 5 different hospital sites, but a significant difference was seen between specialities (p = 0.001). Oxford NOTECHS II provides good discrimination between teams while retaining reliability and correlation with other measures of teamwork performance, and is not confounded by technical performance. It is therefore suitable for combined use with a technical performance scale to provide a global description of operating theatre team performance.

Individual digital health devices are increasingly being bundled together as interacting, multicomponent suites, to deliver clinical services (e.g., teleconsultation and ‘hospital-at-home services’). In the first article of this two-article series we described the challenges in implementation and the current limitations in frameworks for the regulation, health technology assessment, and reimbursement of these device suites and linked novel care pathways. A flexible and fit-for-purpose evaluation framework that can analyze the strengths and weaknesses of digital technology suites is needed. In this second article we describe adaptations that could enable this new technological paradigm while maintaining patient safety and fair value.