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1.  Understanding regional variation in the use of surgery 
Lancet  2013;382(9898):1121-1129.
The use of common surgical procedures varies widely across geographical regions. Differences in illness burden, diagnostic practices, and patient attitudes about medical intervention explain regional variation in surgery rates to only a small degree. Instead, current evidence suggests that surgical variation primarily reflects 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 explain the “surgical signatures” of specific procedures, as well as why some consistently vary more than others. Variation in clinical decision making is in turn influenced by broader environmental factors, including technology diffusion, specialist supply and local training paradigms, financial incentives, and regulatory factors, which vary across countries. Better scientific evidence about the comparative effectiveness of surgical and non-surgical interventions may help mitigate regional variation, but broader dissemination of shared decision making tools will be essential in reducing variation with preference-sensitive conditions.
PMCID: PMC4211114  PMID: 24075052
2.  Oxford NOTECHS II: A Modified Theatre Team Non-Technical Skills Scoring System 
PLoS ONE  2014;9(3):e90320.
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.
PMCID: PMC3942429  PMID: 24594911
3.  Poor adherence of randomised trials in surgery to CONSORT guidelines for non-pharmacological treatments (NPT): a cross-sectional study 
BMJ Open  2013;3(12):e003898.
To systematically assess adherence of randomised trials in surgery to Consolidated Standards of Reporting Trials (CONSORT) guidelines for non-pharmacological treatments (NPT). Surgical trials are considered more difficult to design and execute than pharmacological trials. Furthermore, the original CONSORT statement does not address some aspects that are vital to the transparent reporting of surgical trials. The CONSORT-NPT extension was designed to address these issues but adherence in medical and surgical journals has not been assessed.
Cross-sectional study.
We identified eight general medical and eight surgical journals, indexed in PubMed and published in 2011, with the highest impact factors in their respective categories.
Main outcomes
Adherence to CONSORT statement and CONSORT-NPT extension items.
We identified 54 surgical trials (22 published in medical journals and 32 in surgical journals). There were eight items for which there was less than 30% overall compliance (seven were specific to the CONSORT-NPT extension). These seven items are related to: a full description of the care providers, centres and blinding status in the abstract (n=7/54, 13%), eligibility criteria for centres performing the interventions (n=13/54, 24%), how adherence of care providers with the protocol was assessed or enhanced (n=7/54, 13%), how clustering by care providers or centres was addressed as it relates to sample size (n=3/54, 6%), how care providers were allocated to each group (n=9/54, 17%), how clustering by care providers or centres was addressed as it relates to statistical methods (n=2/54, 4%), a description of care providers (case volume, qualification, expertise, etc) and centres (volume) in each group (n=0/54, 0%).
Adherence of surgical trials to CONSORT-NPT extension items is much poorer than to the standard CONSORT statement. Adherence also appears to be superior in general medical journals compared with surgical journals. Raising awareness and conducting qualitative research to identify areas for specific intervention will be important going forward.
PMCID: PMC3884742  PMID: 24353256
5.  Capturing intraoperative process deviations using a direct observational approach: the glitch method 
BMJ Open  2013;3(11):e003519.
To develop a sensitive, reliable tool for enumerating and evaluating technical process imperfections during surgical operations.
Prospective cohort study with direct observation.
Operating theatres on five sites in three National Health Service Trusts.
Staff taking part in elective and emergency surgical procedures in orthopaedics, trauma, vascular and plastic surgery; including anaesthetists, surgeons, nurses and operating department practitioners.
Outcome measures
Reliability and validity of the glitch count method; frequency, type, temporal pattern and rate of glitches in relation to site and surgical specialty.
The glitch count has construct and face validity, and category agreement between observers is good (κ=0.7). Redundancy between pairs of observers significantly improves the sensitivity over a single observation. In total, 429 operations were observed and 5742 glitches were recorded (mean 14 per operation, range 0–83). Specialty-specific glitch rates varied from 6.9 to 8.3/h of operating (ns). The distribution of glitch categories was strikingly similar across specialties, with distractions the commonest type in all cases. The difference in glitch rate between specialty teams operating at different sites was larger than that between specialties (range 6.3–10.5/h, p<0.001). Forty per cent of glitches occurred in the first quarter of an operation, and only 10% occurred in the final quarter.
The glitch method allows collection of a rich dataset suitable for analysing the changes following interventions to improve process safety, and appears reliable and sensitive. Glitches occur more frequently in the early stages of an operation. Hospital environment, culture and work systems may influence the operative process more strongly than the specialty.
PMCID: PMC3845041  PMID: 24282244
SURGERY; patient safety; quality improvement; process of care
6.  Consensus-based recommendations for investigating clinical heterogeneity in systematic reviews 
Critics of systematic reviews have argued that these studies often fail to inform clinical decision making because their results are far too general, that the data are sparse, such that findings cannot be applied to individual patients or for other decision making. While there is some consensus on methods for investigating statistical and methodological heterogeneity, little attention has been paid to clinical aspects of heterogeneity. Clinical heterogeneity, true effect heterogeneity, can be defined as variability among studies in the participants, the types or timing of outcome measurements, and the intervention characteristics. The objective of this project was to develop recommendations for investigating clinical heterogeneity in systematic reviews.
We used a modified Delphi technique with three phases: (1) pre-meeting item generation; (2) face-to-face consensus meeting in the form of a modified Delphi process; and (3) post-meeting feedback. We identified and invited potential participants with expertise in systematic review methodology, systematic review reporting, or statistical aspects of meta-analyses, or those who published papers on clinical heterogeneity.
Between April and June of 2011, we conducted phone calls with participants. In June 2011 we held the face-to-face focus group meeting in Ann Arbor, Michigan. First, we agreed upon a definition of clinical heterogeneity: Variations in the treatment effect that are due to differences in clinically related characteristics. Next, we discussed and generated recommendations in the following 12 categories related to investigating clinical heterogeneity: the systematic review team, planning investigations, rationale for choice of variables, types of clinical variables, the role of statistical heterogeneity, the use of plotting and visual aids, dealing with outlier studies, the number of investigations or variables, the role of the best evidence synthesis, types of statistical methods, the interpretation of findings, and reporting.
Clinical heterogeneity is common in systematic reviews. Our recommendations can help guide systematic reviewers in conducting valid and reliable investigations of clinical heterogeneity. Findings of these investigations may allow for increased applicability of findings of systematic reviews to the management of individual patients.
PMCID: PMC3847163  PMID: 24004523
7.  A qualitative study comparing experiences of the surgical safety checklist in hospitals in high-income and low-income countries 
BMJ Open  2013;3(8):e003039.
Bold claims have been made for the ability of the WHO surgical checklist to reduce surgical morbidity and mortality and improve patient safety regardless of the setting. Little is known about how far the challenges faced by low-income countries are the same as those in high-income countries or different. We aimed to identify and compare the influences on checklist implementation and compliance in the UK and Africa.
Ethnographic study involving observations, interviews and collection of documents. Thematic analysis of the data.
Operating theatres in one African university hospital and two UK university hospitals.
112 h of observations were undertaken. Interviews with 39 theatre and administrative staff were conducted.
Many staff saw value in the checklist in the UK and African hospitals. Some resentment was present in all settings, linked to conflicts between the philosophy behind the checklist and the realities of local cultural, social and economic contexts. Compliance—involving use, completeness and fidelity—was considerably higher, though not perfect, in the UK settings. In these hospitals, compliance was supported by established structures and systems, and was not significantly undermined by major resource constraints; the same was not true of the low-income context. Hierarchical relationships were a major barrier to implementation in all settings, but were more marked in the low-income setting. Introducing a checklist in a professional environment characterised by a lack of accountability and transparency could make the staff feel jeopardised legally, professionally, and personally, and it encouraged them to make misleading records of what had actually been done.
Surgical checklist implementation is likely to be optimised, regardless of the setting, when used as a tool in multifaceted cultural and organisational programmes to strengthen patient safety. It cannot be assumed that the introduction of a checklist will automatically lead to improved communication and clinical processes.
PMCID: PMC3752057  PMID: 23950205
8.  Developing appropriate methodology for the study of surgical techniques 
PMCID: PMC2642873  PMID: 19208868
9.  A three-dimensional model of error and safety in surgical health care microsystems. Rationale, development and initial testing 
BMC Surgery  2011;11:23.
Research estimates of inadvertent harm to patients undergoing modern healthcare demonstrate a serious problem. Much attention has been paid to analysis of the causes of error and harm, but researchers have typically focussed either on human interaction and communication or on systems design, without fully considering the other components. Existing models for analysing harm are principally derived from theory and the analysis of individual incidents, and their practical value is often limited by the assumption that identifying causal factors automatically suggests solutions. We suggest that new models based on observation are required to help analyse healthcare safety problems and evaluate proposed solutions. We propose such a model which is directed at "microsystem" level (Ward and operating theatre), and which frames problems and solutions within three dimensions.
We have developed a new, simple, model of safety in healthcare systems, based on analysis of real problems seen in surgical systems, in which influences on risk at the "microsystem" level are described in terms of only 3 dimensions - technology, system and culture. We used definitions of these terms which are similar or identical to those used elsewhere in the safety literature, and utilised a set of formal empirical and deductive processes to derive the model. The "3D" model assumes that new risks arise in an unpredictable stochastic manner, and that the three defined dimensions are interactive, in an unconstrained fashion. We illustrated testing of the model, using analysis of a small number of incidents in a surgical environment for which we had detailed prospective observational data.
The model appeared to provide useful explanation and categorisation of real events. We made predictions based on the model, which are experimentally verifiable, and propose further work to test and refine it.
We suggest that, if calibrated by application to a large incident dataset, the 3D model could form the basis for a quantitative statistical method for estimating risk at microsystem levels in many acute healthcare settings.
PMCID: PMC3178466  PMID: 21892929
Patient safety; surgery; medical error; theory, system; culture
10.  When are randomised trials unnecessary? Picking signal from noise 
BMJ : British Medical Journal  2007;334(7589):349-351.
Although randomised trials are widely accepted as the ideal way of obtaining unbiased estimates of treatment effects, some treatments have dramatic effects that are highly unlikely to reflect inadequately controlled biases. We compiled a list of historical examples of such effects and identified the features of convincing inferences about treatment effects from sources other than randomised trials. A unifying principle is the size of the treatment effect (signal) relative to the expected prognosis (noise) of the condition. A treatment effect is inferred most confidently when the signal to noise ratio is large and its timing is rapid compared with the natural course of the condition. For the examples we considered in detail the rate ratio often exceeds 10 and thus is highly unlikely to reflect bias or factors other than a treatment effect. This model may help to reduce controversy about evidence for treatments whose effects are so dramatic that randomised trials are unnecessary.
The relation between a treatment and its effect is sometimes so dramatic that bias can be ruled out as an explanation. Paul Glasziouand colleagues suggest how to determine when observations speak for themselves
PMCID: PMC1800999  PMID: 17303884
11.  Half full or half empty VATS? 
BMJ : British Medical Journal  2004;329(7473):1012.
PMCID: PMC524552  PMID: 15514346
12.  Mortality and morbidity in gastro-oesophageal cancer surgery: initial results of ASCOT multicentre prospective cohort study 
BMJ : British Medical Journal  2003;327(7425):1192-1197.
Objective To evaluate the effect of comorbidity and other risk factors on postoperative mortality and morbidity in patients undergoing major oesophageal and gastric surgery.
Design Multicentre cohort study with data on postoperative mortality and morbidity in hospital.
Data source and methods The ASCOT prospective database, comprising 2087 patients with newly diagnosed oesophageal and gastric cancer in 24 hospitals in England and Wales between 1 January 1999 and 31 December 2002. Multivariate logistic regression analysis was used to model the risk of death and postoperative complications.
Results 955 patients underwent oesophagectomy or gastrectomy. Of these, 253 (27%) were graded ASA III or IV, and 187 (20%) had a high physiological POSSUM score (≥ 20). Operative mortality was 12% (111/955). Physiological POSSUM score, surgeon's assessment, type of operation, hospital case volume, and tumour stage independently predicted operative mortality. Medical complications were associated with higher physiological POSSUM scores and ASA grade, oesophagectomy or total gastrectomy, thoracotomy, and radical nodal dissection. Stage and additional organ resection predicted surgical (technical) complications.
Conclusions Many patients undergoing surgery for gastro-oesophageal cancer have major comorbid disease, which strongly influences their risk of postoperative death. Technical complications do not seem to be influenced by preoperative factors but reflect the extent of surgery and perhaps surgical judgment. Detailed prospective multicentre cooperative audit, with appropriate risk adjustment, is fundamental in the evaluation of cancer care and must be properly resourced.
PMCID: PMC274052  PMID: 14630753
13.  Mortality control charts for comparing performance of surgical units: validation study using hospital mortality data 
BMJ : British Medical Journal  2003;326(7393):786.
To design and validate a statistical method for evaluating the performance of surgical units that adjusts for case volume and case mix.
Validation study using routinely collected data on in-hospital mortality.
Data sources
Two UK databases, the ASCOT prospective database and the risk scoring collaborative (RISC) database, covering 1042 patients undergoing surgery in 29 hospitals for gastro-oesophageal cancer between 1995 and 2000.
Statistical analysis
A two level hierarchical logistic regression model was used to adjust each unit's operative mortality for case mix. Crude or adjusted operative mortality was plotted on mortality control charts (a graphical representation of surgical performance) as a function of number of operations. Control limits defined as 90%, 95%, and 99% confidence intervals identified units whose performance diverged significantly from the mean.
The mean in-hospital mortality was 12% (range 0% to 50%). The case volume of the units ranged from one to 55 cases a year. When crude figures were plotted on the mortality control chart, four units lay outside the 90% control limit, including two outside the 95% limit. When operative mortality was adjusted for risk, three units lay outside the 90% limit and one outside the 95% limit. The model fitted the data well and had adequate discrimination (area under the receiver operating characteristics curve 0.78).
The mortality control chart is an accurate, risk adjusted means of identifying units whose surgical performance, in terms of operative mortality, diverges significantly from the population mean. It gives an early warning of divergent performance. It could be adapted to monitor performance across various specialties.
What is already known on this topicLeague tables are an established technique for ranking the performance of organisations such as healthcare providersMortality control charts are another way to compare the performance of healthcare providers, particularly for outcomes of surgeryWhat this study addsMortality control charts can be adjusted for case mix and case volume and are better than league tables for monitoring surgical performanceMortality control charts have a “buffer zone” for indicating divergence from the mean mortality and are particularly useful for specialties with a low volume of surgery
PMCID: PMC153096  PMID: 12689973
18.  IDEAL framework for surgical innovation 3: randomised controlled trials in the assessment stage and evaluations in the long term study stage 
The complexity of surgical procedures often poses challenges for conducting a rigorous and comprehensive evaluation. This paper considers the final two IDEAL stages of surgical innovation. Surgical randomised controlled trials are often challenging to undertake and require careful consideration of the intervention definition, who should deliver it, and the impact of surgeon and patient preferences. In the long term study stage, better monitoring of surgical procedures is needed, along with improved surveillance of devices.
PMCID: PMC3685513  PMID: 23778425
19.  IDEAL framework for surgical innovation 2: observational studies in the exploration and assessment stages 
The IDEAL framework describes the stages of evaluation for surgical innovations. This paper considers the role of observational studies in the exploration and assessment stages. At the exploration stage, the surgical intervention is usually more widely used, and observational studies should collect prospective data from multiple surgeons, deal with factors such as case mix and learning, and prepare for a definitive evaluation at the next stage of assessment. Although a randomised controlled trial is preferable, a high quality observational study would be acceptable if a randomised trial is not feasible or, on rare occasions, deemed unnecessary.
PMCID: PMC3685514  PMID: 23778426
20.  IDEAL framework for surgical innovation 1: the idea and development stages 
IDEAL is a framework for evaluations of surgical innovations, which follow a distinct development pathway differing from the approach developed for pharmacological interventions. Many pathway and evaluation challenges are shared by other interventional therapies, requiring individual therapist skills and customisation of treatment to the individual, partly through medical devices. This paper provides an overview of the IDEAL framework and recommendations, and focuses on the first two stages: idea and development.
PMCID: PMC3685515  PMID: 23778427

Results 1-20 (20)