Publications
239 results found
Poovendran D, Wadge H, Roy R, et al., 2017, A qualitative evaluation of the CIE Programme implementation in North West London
Neves AL, Roy R, Wadge H, et al., 2017, A framework for evaluating the economic impact of EHR-based interventions
Khanbhai M, Flott K, Darzi A, et al., 2017, Evaluating digital maturity and patient acceptability of real-time patient experience feedback systems: systematic review, Publisher: JMIR Publications Inc.
Background:One of the essential elements of a strategic approach to improving patients’ experience is to measure and report on patients’ experiences in real time. Real-time feedback (RTF) is increasingly being collected using digital technology; however, there are several factors that may influence the success of the digital system.Objective:The aim of this review was to evaluate the digital maturity and patient acceptability of real-time patient experience feedback systems.Methods:We systematically searched the following databases to identify papers that used digital systems to collect RTF: The Cochrane Library, Global Health, Health Management Information Consortium, Medical Literature Analysis and Retrieval System Online, EMBASE, PsycINFO, Web of Science, and CINAHL. In addition, Google Scholar and gray literature were utilized. Studies were assessed on their digital maturity using a Digital Maturity Framework on the basis of the following 4 domains: capacity/resource, usage, interoperability, and impact. A total score of 4 indicated the highest level of digital maturity.Results:RTF was collected primarily using touchscreens, tablets, and Web-based platforms. Implementation of digital systems showed acceptable response rates and generally positive views from patients and staff. Patient demographics according to RTF responses varied. An overrepresentation existed in females with a white predominance and in patients aged ≥65 years. Of 13 eligible studies, none had digital systems that were deemed to be of the highest level of maturity. Three studies received a score of 3, 2, and 1, respectively. Four studies scored 0 points. While 7 studies demonstrated capacity/resource, 8 demonstrated impact. None of the studies demonstrated interoperability in their digital systems.Conclusions:Patients and staff alike are willing to engage in RTF delivered using digital technology, thereby disrupting previous paper-based f
Camacho N, Van Loo P, Edwards S, et al., 2017, Appraising the relevance of DNA copy number loss and gain in prostate cancer using whole genome DNA sequence data, PLoS Genetics, Vol: 13, ISSN: 1553-7390
A variety of models have been proposed to explain regions of recurrent somatic copy number alteration (SCNA) in human cancer. Our study employs Whole Genome DNA Sequence (WGS) data from tumor samples (n = 103) to comprehensively assess the role of the Knudson two hit genetic model in SCNA generation in prostate cancer. 64 recurrent regions of loss and gain were detected, of which 28 were novel, including regions of loss with more than 15% frequency at Chr4p15.2-p15.1 (15.53%), Chr6q27 (16.50%) and Chr18q12.3 (17.48%). Comprehensive mutation screens of genes, lincRNA encoding sequences, control regions and conserved domains within SCNAs demonstrated that a two-hit genetic model was supported in only a minor proportion of recurrent SCNA losses examined (15/40). We found that recurrent breakpoints and regions of inversion often occur within Knudson model SCNAs, leading to the identification of ZNF292 as a target gene for the deletion at 6q14.3-q15 and NKX3.1 as a two-hit target at 8p21.3-p21.2. The importance of alterations of lincRNA sequences was illustrated by the identification of a novel mutational hotspot at the KCCAT42, FENDRR, CAT1886 and STCAT2 loci at the 16q23.1-q24.3 loss. Our data confirm that the burden of SCNAs is predictive of biochemical recurrence, define nine individual regions that are associated with relapse, and highlight the possible importance of ion channel and G-protein coupled-receptor (GPCR) pathways in cancer development. We concluded that a two-hit genetic model accounts for about one third of SCNA indicating that mechanisms, such haploinsufficiency and epigenetic inactivation, account for the remaining SCNA losses.
Camara M, Pratt P, Darzi A, et al., 2017, Simulation of Patient-Specific Deformable Ultrasound Imaging in Real Time, Lecture Notes in Computer Science, Vol: 10549, Pages: 11-18, ISSN: 0302-9743
Intraoperative ultrasound is an imaging modality frequently used to provide delineation of tissue boundaries. This paper proposes a simulation platform that enables rehearsal of patient-specific deformable ultrasound scanning in real-time, using preoperative CT as the data source. The simulation platform was implemented within the GPU-accelerated NVIDIA FleX position-based dynamics framework. The high-resolution particle model is used to deform both surface and volume meshes. The latter is used to compute the barycentric coordinates of each simulated ultrasound image pixel in the surrounding volume, which is then mapped back to the original undeformed CT volume. To validate the computation of simulated ultrasound images, a kidney phantom with an embedded tumour was CT-scanned in the rest position and at five different levels of probe-induced deformation. Measures of normalised cross-correlation and similarity between features were adopted to compare pairs of simulated and ground truth images. The accurate results demonstrate the potential of this approach for clinical translation.
Flott K, Darzi A, Gancarczyk S, et al., 2017, Improving the usefulness and use of patient survey programs: National Health Service Interview Study, Publisher: JMIR Preprints
Background: A growing body of evidence suggests a concerning lag between collection of patient experience data and its application in service improvement. This study aims to identify what health care staff perceive to be the barriers and facilitators to using patient-reported feedback and showcase successful examples of doing so.Objective: This study aimed to apply a systems perspective to suggest policy improvements that could support efforts to use data on the frontlines.Methods: Qualitative interviews were conducted in eight National Health Service provider locations in the United Kingdom, which were selected based on National Inpatient Survey scores. Eighteen patient-experience leads were interviewed about using patient-reported feedback with relevant staff. Interviews were transcribed and underwent thematic analysis. Staff-identified barriers and facilitators to using patient experience feedback were obtained.Results: The most frequently cited barriers to using patient reported feedback pertained to interpreting results, understanding survey methodology, presentation of data in both national Care Quality Commission and contractor reports, inability to link data to other sources, and organizational structure. In terms of a wish list for improved practice, staff desired more intuitive survey methodologies, the ability to link patient experience data to other sources, and more examples of best practice in patient experience improvement. Three organizations also provided examples of how they successfully used feedback to improve care.Conclusions: Staff feedback provides a roadmap for policy makers to reconsider how data is collected and whether or not the national regulations on surveys and patient experience data are meeting the quality improvement needs of local organizations.
Vuik SI, Fontana G, Mayer E, et al., 2017, Do hospitalisations for Ambulatory Care Sensitive Conditions reflect low access to primary care? An observational cohort study of primary care utilisation prior to hospitalisation, BMJ Open, Vol: 7, ISSN: 2044-6055
Objectives To explore whether hospitalisations for ambulatory care sensitive conditions (ACSCs) are associated with low access to primary care.Design Observational cohort study over 2008 to 2012 using the Clinical Practice Research Datalink (CPRD) and Hospital Episode Statistics (HES) databases.Setting English primary and secondary care.Participants A random sample of 300 000 patients.Main outcome measures Emergency hospitalisation for an ACSC.Results Over the long term, patients with ACSC hospitalisations had on average 2.33 (2.17 to 2.49) more general practice contacts per 6 months than patients with similar conditions who did not require hospitalisation. When accounting for the number of diagnosed ACSCs, age, gender and GP practice through a nested case–control method, the difference was smaller (0.64 contacts), but still significant (p<0.001).In the short-term analysis, measured over the 6 months prior to hospitalisation, patients used more GP services than on average over the 5 years. Cases had significantly (p<0.001) more primary care contacts in the 6 months before ACSC hospitalisations (7.12, 95% CI 6.95 to 7.30) than their controls during the same 6 months (5.57, 95% CI 5.43 to 5.72). The use of GP services increased closer to the time of hospitalisation, with a peak of 1.79 (1.74 to 1.83) contacts in the last 30 days before hospitalisation.Conclusions This study found no evidence to support the hypothesis that low access to primary care is the main driver of ACSC hospitalisations. Other causes should also be explored to understand how to use ACSC admission rates as quality metrics, and to develop the appropriate interventions.
Carter AW, Mandavia R, Mayer E, et al., 2017, Systematic review of economic analyses in patient safety: a protocol designed to measure development in the scope and quality of evidence., BMJ Open, Vol: 7, ISSN: 2044-6055
INTRODUCTION: Recent avoidable failures in patient care highlight the ongoing need for evidence to support improvements in patient safety. According to the most recent reviews, there is a dearth of economic evidence related to patient safety. These reviews characterise an evidence gap in terms of the scope and quality of evidence available to support resource allocation decisions. This protocol is designed to update and improve on the reviews previously conducted to determine the extent of methodological progress in economic analyses in patient safety. METHODS AND ANALYSIS: A broad search strategy with two core themes for original research (excluding opinion pieces and systematic reviews) in 'patient safety' and 'economic analyses' has been developed. Medline, Econlit and National Health Service Economic Evaluation Database bibliographic databases will be searched from January 2007 using a combination of medical subject headings terms and research-derived search terms (see table 1). The method is informed by previous reviews on this topic, published in 2012. Screening, risk of bias assessment (using the Cochrane collaboration tool) and economic evaluation quality assessment (using the Drummond checklist) will be conducted by two independent reviewers, with arbitration by a third reviewer as needed. Studies with a low risk of bias will be assessed using the Drummond checklist. High-quality economic evaluations are those that score >20/35. A qualitative synthesis of evidence will be performed using a data collection tool to capture the study design(s) employed, population(s), setting(s), disease area(s), intervention(s) and outcome(s) studied. Methodological quality scores will be compared with previous reviews where possible. Effect size(s) and estimate uncertainty will be captured and used in a quantitative synthesis of high-quality evidence, where possible. ETHICS AND DISSEMINATION: Formal ethical approval is not required as primary data will not be collected. T
Scott A, Mason S, Langdon A, et al., 2017, Risk-factors for the development of post-operative urinary retention after day-case general surgery - a prospective study, International Congress of the Association-of-Surgeons-of-Great-Britain-and-Ireland, Publisher: WILEY, Pages: 53-54, ISSN: 0007-1323
Omar I, Dilley J, Pucher P, et al., 2017, The robotix simulator: face and content validation using the fundamentals of robotic surgery (FRS) curriculum, Annual Meeting of the American-Urological-Association (AUA), Publisher: Elsevier, Pages: E700-E701, ISSN: 0022-5347
Jay A, Aldiwani M, Wijayarathna S, et al., 2017, THE FEATURES AND MANAGEMENT OF LATE RELAPSE OF NON-SEMINOMATOUS GERM CELL TUMOURS, Annual Meeting of the American-Urological-Association (AUA), Publisher: ELSEVIER SCIENCE INC, Pages: E1041-E1041, ISSN: 0022-5347
Kockelbergh R, Hounsome L, Mayer E, 2017, The Epidemiology of urological cancer 2001-2013, JOURNAL OF CLINICAL UROLOGY, Vol: 10, Pages: 3-8, ISSN: 2051-4158
Schams S, Nabavi E, Singh M, et al., 2017, Development And Evaluation Of LED Light Source For Contrast Enhancement In Minimally‐invasive Procedures, CLEO Pacific Rim
Jallad S, Hounsome L, Verne J, et al., 2017, Where are we with improving outcome guidance? An update on pelvic urological services in the NHS, JOURNAL OF CLINICAL UROLOGY, Vol: 10, Pages: 29-33, ISSN: 2051-4158
Mensah EE, Hounsome L, Verne J, et al., 2017, Cardiovascular outcomes in kidney cancer patients, Journal of Clinical Urology, Vol: 10, Pages: 24-28, ISSN: 2051-4158
© 2017, © British Association of Urological Surgeons 2017. Introduction: In the surgical management of small renal tumours, current guidelines recommend that partial nephrectomy should be the preferred option wherever possible. This is based on evidence suggesting improved quality of life outcomes, morbidity and mortality and equivalent oncological outcomes when compared with radical nephrectomy. Chronic kidney disease is a significant risk factor for cardiovascular disease and subsequent mortality. This study explored differences in cardiac-related events and co-morbidity, using linked registry data for patients undergoing radical or partial nephrectomy for T1 renal tumours. Methods: Data from the National Cancer Registration Service was searched to identify T1 renal cancer diagnoses between 1999 and 2012. This data was matched against hospital episode statistics to identify those patients who had undergone radical or partial nephrectomy between 1999 and 2013 using OPCS codes. Data was collected on cardiac-related admissions and deaths in nephrectomy patients. Equivalent data was also collected for the general population to allow age-standardized comparison. Charlson score was used as a proxy for pre-operative co-morbidity. Results: Radical/partial nephrectomy patients had a greater risk of cardiac-related admissions compared with the general population (relative risk (RR) 3.32, 95% confidence interval (CI) 3.24–3.40), but with no increase in cardiac-related deaths (RR 0.84, 95% CI 0.70–1.01). There was no difference in the admission risk, or death, comparing radical or partial nephrectomy for T1 renal tumours (RR 1.02, 95% CI 0.88–1.17) using ‘time to event’ analysis. There was no difference in the comorbidity index between radical nephrectomy and partial nephrectomy patients. Conclusion: The higher incidence of cardiac-related admissions seen for radical/partial nephrectomy patients may be explained by a higher proportion o
Flott K, Hounsome L, Vuik S, et al., 2017, A patient-centric approach to improving experience in urological cancer care, Journal of Clinical Urology, Vol: 10, Pages: 39-46, ISSN: 2051-4166
Rationale:Patient experience data are often reported at the provider level rather than the patient level, meaning that providers receive an aggregate score of all patient experience scores across their service. This inflates positivity and makes it difficult for providers to use patient experience scores to tailor improvements for patients within specific sites, wards or pathways. Patients have different priorities for their urological cancer care experience, and improvement programmes should take these differences into account. A more granular understanding of different patterns of patient experience will allow health care providers to focus their improvement strategies differently based on the needs of the patient groups that utilise their services.Objective:This study examines what groups exist within the urological cancer patient population, and what are their respective priorities for patient experience improvement.Methods:Using urological cancers as a case study, this paper uses data from the UK National Cancer Patient Experience Survey to segment the patient population based on their scores for 14 domains of experience. TwoStep cluster analyses were carried out on two groups of survey respondents: those who had an operation and those who did not. These analyses identified previously unknown clusters within the two populations. Profiles were created for each cluster based on a series of demographic variables, and a regression analysis was conducted to assess the significance of each demographic variable in determining cluster membership.Results:The TwoStep analysis yielded three clusters for both the operations and non-operations groups based on how patients experienced care: Positive, Middling and Negative. Gender, age, cancer type and income significantly influenced cluster membership: women, younger and more deprived patients were more prevalent in the Negative experience cluster.Conclusion:This more nuanced understanding of the patient population and the v
Vuik SI, Mayer E, Darzi A, 2016, Understanding population health needs: How data-driven population segmentation can support the planning of integrated care, 16th International Conference on Integrated Care, Publisher: Utrecht University, Maastricht University, Groningen University, ISSN: 1568-4156
Vuik SI, Mayer E, Darzi A, 2016, Enhancing risk stratification for use in integrated care - A cluster analysis of high-risk patients in a retrospective cohort study, BMJ Open, Vol: 6, ISSN: 2044-6055
Objective To show how segmentation can enhance risk stratification tools for integrated care, by providing insight into different care usage patterns within the high-risk population.Design A retrospective cohort study. A risk score was calculated for each person using a logistic regression, which was then used to select the top 5% high-risk individuals. This population was segmented based on the usage of different care settings using a k-means cluster analysis. Data from 2008 to 2011 were used to create the risk score and segments, while 2012 data were used to understand the predictive abilities of the models.Setting and participants Data were collected from administrative data sets covering primary and secondary care for a random sample of 300 000 English patients.Main measures The high-risk population was segmented based on their usage of 4 different care settings: emergency acute care, elective acute care, outpatient care and GP care.Results While the risk strata predicted care usage at a high level, within the high-risk population, usage varied significantly. 4 different groups of high-risk patients could be identified. These 4 segments had distinct usage patterns across care settings, reflecting different levels and types of care needs. The 2008–2011 usage patterns of the 4 segments were consistent with the 2012 patterns.Discussion Cluster analyses revealed that the high-risk population is not homogeneous, as there exist 4 groups of patients with different needs across the care continuum. Since the patterns were predictive of future care use, they can be used to develop integrated care programmes tailored to these different groups.Conclusions Usage-based segmentation augments risk stratification by identifying patient groups with different care needs, around which integrated care programmes can be designed.
Vuik SI, Mayer E, Darzi A, 2016, A quantitative evidence base for population health: applying utilization-based cluster analysis to segment a patient population, Population Health Metrics, Vol: 14, ISSN: 1478-7954
Background: To improve population health it is crucial to understand the different care needs within a population. Traditional population groups are often based on characteristics such as age or morbidities. However, this does not take into account specific care needs across care settings, and tends to focus on high needs patients only. This paper explores the potential of using utilisation-based cluster analysis to segment a general patient population into homogenous groups.Methods: Administrative datasets covering primary and secondary care were used to construct a database of 300,000 patients, which included socio-demographics variables, morbidities, care utilisation, and cost. A k-means cluster analysis grouped the patients into segments with distinct care utilisation, based on six utilisation variables: non-elective inpatient admissions, elective inpatient admissions, outpatient visits, GP practice visits, GP home visits, and prescriptions. These segments were analysed post-hoc to understand their morbidity and demographic profile.Results: Eight population segments were identified, and utilisation of each care setting was significantly different across all segments. Each segment also presented with different morbidity patterns and demographic characteristics, creating eight distinct care user types. Comparing these segments to traditional patient groups shows the heterogeneity of these approaches, especially for lower needs patients.Conclusions: This analysis shows that utilisation-based cluster analysis segments a patient population into distinct groups with unique care priorities, providing a quantitative evidence base to improve population health. Contrary to traditional methods, this approach also segments lower needs populations, which can be used to inform preventative interventions. In addition, the identification of different care user types provides insight into needs across the care continuum.
Flott K, Darzi A, Mayer E, 2016, Evaluation framework for patient safety incident reporting systems, International Journal for Quality in Health Care, Vol: 28, Pages: 8-9, ISSN: 1464-3677
Howell AM, Burns EM, Hull L, et al., 2016, Incident reporting: rare incidents may benefit from national problem solving, BMJ Quality & Safety, Vol: 26, ISSN: 2044-5423
Mayer E, Darzi A, 2016, Innovation and surgical clinical trials, Lancet, Vol: 388, Pages: 1027-1028, ISSN: 1474-547X
Flott KM, Graham C, Darzi A, et al., 2016, Can we use patient-reported feedback to drive change? The challenges of using patient-reported feedback and how they might be addressed, BMJ Quality & Safety, Vol: 26, Pages: 502-507, ISSN: 2044-5423
Vuik SI, Mayer EK, Darzi A, 2016, Patient segmentation analysis offers significant benefits for integrated care and support, Health Affairs, Vol: 35, Pages: 769-775, ISSN: 0278-2715
Integrated care aims to organize care around the patient instead of the provider. It is therefore crucial to understand differences across patients and their needs. Segmentation analysis that uses big data can help divide a patient population into distinct groups, which can then be targeted with care models and intervention programs tailored to their needs. In this article we explore the potential applications of patient segmentation in integrated care. We propose a framework for population strategies in integrated care—whole populations, subpopulations, and high-risk populations—and show how patient segmentation can support these strategies. Through international case examples, we illustrate practical considerations such as choosing a segmentation logic, accessing data, and tailoring care models. Important issues for policy makers to consider are trade-offs between simplicity and precision, trade-offs between customized and off-the-shelf solutions, and the availability of linked data sets. We conclude that segmentation can provide many benefits to integrated care, and we encourage policy makers to support its use.
Flott K, Callahan R, Darzi A, et al., 2016, A patient-centered framework for evaluating digital maturity of health services: a systematic review, Journal of Medical Internet Research, Vol: 18, ISSN: 1439-4456
Background: Digital maturity is the extent to which digital technologies are used as enablers to deliver a high-quality health service. Extensive literature exists about how to assess the components of digital maturity, but it has not been used to design a comprehensive framework for evaluation. Consequently, the measurement systems that do exist are limited to evaluating digital programs within one service or care setting, meaning that digital maturity evaluation is not accounting for the needs of patients across their care pathways.Objective: The objective of our study was to identify the best methods and metrics for evaluating digital maturity and to create a novel, evidence-based tool for evaluating digital maturity across patient care pathways.Methods: We systematically reviewed the literature to find the best methods and metrics for evaluating digital maturity. We searched the PubMed database for all papers relevant to digital maturity evaluation. Papers were selected if they provided insight into how to appraise digital systems within the health service and if they indicated the factors that constitute or facilitate digital maturity. Papers were analyzed to identify methodology for evaluating digital maturity and indicators of digitally mature systems. We then used the resulting information about methodology to design an evaluation framework. Following that, the indicators of digital maturity were extracted and grouped into increasing levels of maturity and operationalized as metrics within the evaluation framework.Results: We identified 28 papers as relevant to evaluating digital maturity, from which we derived 5 themes. The first theme concerned general evaluation methodology for constructing the framework (7 papers). The following 4 themes were the increasing levels of digital maturity: resources and ability (6 papers), usage (7 papers), interoperability (3 papers), and impact (5 papers). The framework includes metrics for each of these levels at each stag
Flott K, Callahan R, Darzi A, et al., 2016, A Patient-Centered Framework for Evaluating Digital Maturity of Health Services: A Systematic Review, Journal of Medical Internet Research, Vol: 18, ISSN: 1439-4456
Background: Digital maturity is the extent to which digital technologies are used as enablers to deliver a high-quality health service. Extensive literature exists about how to assess the components of digital maturity, but it has not been used to design a comprehensive framework for evaluation. Consequently, the measurement systems that do exist are limited to evaluating digital programs within one service or care setting, meaning that digital maturity evaluation is not accounting for the needs of patients across their care pathways.Objective: The objective of our study was to identify the best methods and metrics for evaluating digital maturity and to create a novel, evidence-based tool for evaluating digital maturity across patient care pathways.Methods: We systematically reviewed the literature to find the best methods and metrics for evaluating digital maturity. We searched the PubMed database for all papers relevant to digital maturity evaluation. Papers were selected if they provided insight into how to appraise digital systems within the health service and if they indicated the factors that constitute or facilitate digital maturity. Papers were analyzed to identify methodology for evaluating digital maturity and indicators of digitally mature systems. We then used the resulting information about methodology to design an evaluation framework. Following that, the indicators of digital maturity were extracted and grouped into increasing levels of maturity and operationalized as metrics within the evaluation framework.Results: We identified 28 papers as relevant to evaluating digital maturity, from which we derived 5 themes. The first theme concerned general evaluation methodology for constructing the framework (7 papers). The following 4 themes were the increasing levels of digital maturity: resources and ability (6 papers), usage (7 papers), interoperability (3 papers), and impact (5 papers). The framework includes metrics for each of these levels at each stag
Camara M, Mayer E, Darzi A, et al., 2016, Soft tissue deformation for surgical simulation: a position-based dynamics approach, International Journal of Computer Assisted Radiology and Surgery, Vol: 11, Pages: 919-928, ISSN: 1861-6410
Mayer E, Flott K, Callahan RP, et al., 2016, National Reporting and Learning System Research and Development
This report presents the findings of the NRLS Researchand Development Programme conducted by thePatient Safety Translational Research Centre (PSTRC)and the Centre for Health Policy (CHP) at ImperialCollege London.It sets out the current state of affairs regardingpatient safety incident reporting in the NHS, andspecifies where the most pressing areas of concerns are,including thorough descriptions of the various incidentreporting systems used in the NHS today. Furthermore itidentifies areas for improvement in the overall landscapeof incident reporting, and suggests how systems like theNRLS can capitalise on developments in technology.The main body of the report is then devoted toexplaining the findings from the research programme. Theresearch was divided into four domains, and the reportdetails the new findings discovered about each of them:1. Purpose of incident reporting in healthcare2. User experience with reporting systems3. Data quality and analysis4. Effective feedback for learningBuilding on these findings, the report moves on to describehow they can be applied to the next generation ofincident reporting. Specifically, it focuses on a prototypefor a new incident reporting system that incorporates theimprovement ideas generated by the research.Finally, the report concludes with a description ofan evidence-based framework for evaluating incidentreporting systems and an ‘Achievement Toolkit’ often recommendations for improvements to incidentreporting systems.
Howell AR, Burns EM, Hull L, et al., 2016, International recommendations for national patient safety incident reporting systems: An expert Delphi consensus-building process, BMJ Quality and Safety, Vol: 26, Pages: 150-163, ISSN: 2044-5415
Background Patient safety incident reporting systems (PSRS) have been established for over a decade, but uncertainty remains regarding the role that they can and ought to play in quantifying healthcare-related harm and improving care.Objective To establish international, expert consensus on the purpose of PSRS regarding monitoring and learning from incidents and developing recommendations for their future role.Methods After a scoping review of the literature, semi-structured interviews with experts in PSRS were conducted. Based on these findings, a survey-based questionnaire was developed and subsequently completed by a larger expert panel. Using a Delphi approach, consensus was reached regarding the ideal role of PSRSs. Recommendations for best practice were devised.Results Forty recommendations emerged from the Delphi procedure on the role and use of PSRS. Experts agreed reporting system should not be used as an epidemiological tool to monitor the rate of harm over time or to appraise the relative safety of hospitals. They agreed reporting is a valuable mechanism for identifying organisational safety needs. The benefit of a national system was clear with respect to medication error, device failures, hospital-acquired infections and never events as these problems often require solutions at a national level. Experts recommended training for senior healthcare professionals in incident investigation. Consensus recommendation was for hospitals to take responsibility for creating safety solutions locally that could be shared nationally.Conclusions We obtained reasonable consensus among experts on aims and specifications of PSRS. This information can be used to reflect on existing and future PSRS, and their role within the wider patient safety landscape. The role of PSRS as instruments for learning needs to be elaborated and developed further internationally.
Mensah EE, Nicol D, Mayer E, 2016, Primary testicular tumours and management of clinical stage 1 testicular cancer, Journal of Clinical Urology, Vol: 9, Pages: 84-92, ISSN: 2051-4166
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