ORCID Profile
0000-0002-3210-8273
Current Organisation
University of Oxford
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
Publisher: Springer Science and Business Media LLC
Date: 12-08-2022
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 09-2018
DOI: 10.1016/J.IJSU.2018.08.003
Abstract: Methods to improve clinical systems safety suffer from significant difficulties in implementation and scaling up. We used an upscaling implementation strategy entitled Supported Ch ions in a quality and safety improvement programme for emergency surgery at regional level, focusing on patients with right iliac fossa pain. A before-after study was conducted across four acute NHS Trusts: A 6 month intervention phase was preceded and followed by 3 months of data collection. An established Human Factors intervention was led at each Trust by a small group of staff selected as Ch ions. Ch ions received training in teamwork and systems improvement and were supported by Human Factors experts. The primary improvement aim was to expedite surgery for patients with sepsis, using Royal College of Surgeons emergency surgery guidelines as the measure. Additional outcomes studied included length of inpatient stay and 30-day readmission rates. Breaches of RCS urgency guidelines decreased markedly from 13.7% of operated patients pre-intervention to 3.5% post-intervention (p = 0.000). Mean time from booking to incision decreased in three of the four sites, whilst median length of stay increased in 3 of 4. Overall 30-day readmission rate remained stable (7.84% pre-intervention versus 7.31% post-intervention, p = 0.959). The Supported Ch ions model allowed all surgical teams to reduce delay for septic patients by more than 50%, using distinct Quality Improvement strategies to address local issues. Improvement was implemented in 4 erse settings with a quarter of the level of expert input previously used in a single hospital.
Publisher: Georg Thieme Verlag KG
Date: 29-01-2016
Abstract: Nur wenn Interventionsbeschreibungen vollständig veröffentlicht sind, können Kliniker und Patienten Interventionen, die sich als nützlich erwiesen haben, verlässlich umsetzen und andere Forscher die Studienergebnisse replizieren oder darauf aufbauen. Die Qualität von Interventionsbeschreibungen in wissenschaftlichen Publikationen ist bemerkenswert gering. Um die Vollständigkeit der Berichterstattung und damit die Replizierbarkeit von Interventionen zu verbessern, entwickelte eine internationale Gruppe von Experten und Interessensvertretern die Checkliste zur Interventionsbeschreibung und Replikation (TIDieR). Der Prozess beinhaltete eine Literaturrecherche zu relevanten Checklisten und wissenschaftlichen Untersuchungen, eine Delphi-Umfrage mit internationalen Experten zur Steuerung der Item-Auswahl und eine Expertenkonferenz. Die daraus resultierende 12-Item-TIDieR Checkliste (Bezeichnung, Warum, Was (Materialien), Was (Verfahren), Wer intervenierte, Wie, Wo, Wann und Wieviel, Anpassungen, Modifikationen, Wie gut (geplante Durchführungskontrolle), Wie gut (tatsächliche Durchführung)) ist eine Erweiterung des CONSORT 2010 Statements (Item 5) und des SPIRIT 2013 Statements (Item 11). Während der Fokus der Checkliste auf klinischen Studien liegt, kann die erweiterte Anleitung bei allen evaluativen Studiendesigns herangezogen werden. Dieser Artikel präsentiert die TIDieR Checkliste und Anleitung mit Erklärung und Erläuterung jedes einzelnen Items sowie Beispielen guter Berichterstattung. Die TIDieR Checkliste und Anleitung sollen das Berichten von Interventionen verbessern und Autoren eine Hilfe bieten, die Berichterstattung ihrer Interventionen zu strukturieren, Gutachtern und Herausgebern, die Beschreibungen zu beurteilen und Lesern, die Informationen zu nutzen.
Publisher: Oxford University Press (OUP)
Date: 23-10-2017
DOI: 10.1093/PTJ/PZX103
Abstract: The IDEAL framework is an established method for initial and ongoing evaluations of innovation and practice for complex health care interventions. First derived for surgical sciences and embedded at a global level for evaluating surgery/surgical devices, the IDEAL framework is based on the principle that innovation and evaluation in clinical practice can, and should, evolve together in an ordered manner: from conception to development and then to validation by appropriate clinical studies and, finally, longer-term follow-up. This framework is highly suited to other complex, nonpharmacological interventions, such as physical therapist interventions. This perspective outlines the application of IDEAL to physical therapy in the new IDEAL-Physio framework. The IDEAL-Physio framework comprises 5 stages. In stage 1, the idea phase, formal data collection should begin. Stage 2a is the phase for iterative improvement and adjustment with thorough data recording. Stage 2b involves the onset of formal evaluation using systematically collected group or cohort data. Stage 3 is the phase for formal comparative assessment of treatment, usually involving randomized studies. Stage 4 involves long-term follow-up. The IDEAL-Physio framework is recommended as a method for guiding and evaluating both innovation and practice in physical therapy, with the overall goal of providing better evidence-based care.
Publisher: Oxford University Press (OUP)
Date: 08-02-2011
DOI: 10.1002/BJS.7434
Abstract: Concern over the frequency of unintended harm to patients has focused attention on the importance of teamwork and communication in avoiding errors. This has led to experiments with teamwork training programmes for clinical staff, mostly based on aviation models. These are widely assumed to be effective in improving patient safety, but the extent to which this assumption is justified by evidence remains unclear. A systematic literature review on the effects of teamwork training for clinical staff was performed. Information was sought on outcomes including staff attitudes, teamwork skills, technical performance, efficiency and clinical outcomes. Of 1036 relevant abstracts identified, 14 articles were analysed in detail: four randomized trials and ten non-randomized studies. Overall study quality was poor, with particular problems over blinding, subjective measures and Hawthorne effects. Few studies reported on every outcome category. Most reported improved staff attitudes, and six of eight reported significantly better teamwork after training. Five of eight studies reported improved technical performance, improved efficiency or reduced errors. Three studies reported evidence of clinical benefit, but this was modest or of borderline significance in each case. Studies with a stronger intervention were more likely to report benefits than those providing less training. None of the randomized trials found evidence of technical or clinical benefit. The evidence for technical or clinical benefit from teamwork training in medicine is weak. There is some evidence of benefit from studies with more intensive training programmes, but better quality research and cost-benefit analysis are needed.
Publisher: BMJ
Date: 07-03-2014
DOI: 10.1136/BMJ.G1687
Abstract: Without a complete published description of interventions, clinicians and patients cannot reliably implement interventions that are shown to be useful, and other researchers cannot replicate or build on research findings. The quality of description of interventions in publications, however, is remarkably poor. To improve the completeness of reporting, and ultimately the replicability, of interventions, an international group of experts and stakeholders developed the Template for Intervention Description and Replication (TIDieR) checklist and guide. The process involved a literature review for relevant checklists and research, a Delphi survey of an international panel of experts to guide item selection, and a face to face panel meeting. The resultant 12 item TIDieR checklist (brief name, why, what (materials), what (procedure), who provided, how, where, when and how much, tailoring, modifications, how well (planned), how well (actual)) is an extension of the CONSORT 2010 statement (item 5) and the SPIRIT 2013 statement (item 11). While the emphasis of the checklist is on trials, the guidance is intended to apply across all evaluative study designs. This paper presents the TIDieR checklist and guide, with an explanation and elaboration for each item, and ex les of good reporting. The TIDieR checklist and guide should improve the reporting of interventions and make it easier for authors to structure accounts of their interventions, reviewers and editors to assess the descriptions, and readers to use the information.
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 02-2019
Publisher: Elsevier BV
Date: 09-2009
Publisher: American College of Physicians
Date: 20-06-2017
DOI: 10.7326/M17-0046
Publisher: Informa UK Limited
Date: 11-03-2015
DOI: 10.3109/02688697.2014.997670
Abstract: Deep brain stimulation (DBS) can provide dramatic essential tremor (ET) relief, however no Class I evidence exists. Analysis methods: I) traditional cohort analysis II) N-of-1 single patient randomised control trial and III) signal-to-noise (S/N) analysis. 20 DBS electrodes in ET patients were switched on and off for 3-min periods. Six pairs of on and off periods in each case, with the pair order determined randomly. Tremor severity was quantified with tremor evaluator and patient was blinded to stimulation. Patients also stated whether they perceived the stimulation to be on after each trial. I) Mean end-of-trial tremor severity 0.84 out of 10 on, 6.62 Off, t = - 13.218, p 80% tremor reduction occurred in 99/114 'On' trials (87%), and 3/114 'Off' trials (3%). S/N ratio for 80% improvement with DBS versus spontaneous improvement was 487,757-to-1. DBS treatment effect on ET is too large for bias to be a plausible explanation. Formal N-of-1 trial design, and S/N ratio method for presenting results, allows this to be demonstrated convincingly where conventional randomised controlled trials are not possible. This study is the first to provide Class I evidence for the efficacy of DBS for ET.
Publisher: Springer Science and Business Media LLC
Date: 05-2022
DOI: 10.1038/S41591-022-01772-9
Abstract: A growing number of artificial intelligence (AI)-based clinical decision support systems are showing promising performance in preclinical, in silico evaluation, but few have yet demonstrated real benefit to patient care. Early-stage clinical evaluation is important to assess an AI system's actual clinical performance at small scale, ensure its safety, evaluate the human factors surrounding its use and pave the way to further large-scale trials. However, the reporting of these early studies remains inadequate. The present statement provides a multi-stakeholder, consensus-based reporting guideline for the Developmental and Exploratory Clinical Investigations of DEcision support systems driven by Artificial Intelligence (DECIDE-AI). We conducted a two-round, modified Delphi process to collect and analyze expert opinion on the reporting of early clinical evaluation of AI systems. Experts were recruited from 20 pre-defined stakeholder categories. The final composition and wording of the guideline was determined at a virtual consensus meeting. The checklist and the Explanation & Elaboration (E&E) sections were refined based on feedback from a qualitative evaluation process. In total, 123 experts participated in the first round of Delphi, 138 in the second round, 16 in the consensus meeting and 16 in the qualitative evaluation. The DECIDE-AI reporting guideline comprises 17 AI-specific reporting items (made of 28 subitems) and ten generic reporting items, with an E&E paragraph provided for each. Through consultation and consensus with a range of stakeholders, we developed a guideline comprising key items that should be reported in early-stage clinical studies of AI-based decision support systems in healthcare. By providing an actionable checklist of minimal reporting items, the DECIDE-AI guideline will facilitate the appraisal of these studies and replicability of their findings.
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Peter McCulloch.