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Background: The clinical and cost-effectiveness of left ventricular assist device (LVAD) therapy for patients with advanced heart failure (HF) who are ineligible for heart transplantation is debated in the UK. This study develops an indirect comparison between the fully magnetically levitated HeartMate 3 (HM 3) LVAD and medical therapy (MT) to evaluate expected clinical and cost-effectiveness in the UK National Health Service (NHS) context. Methods: We performed an economic analysis comparing the HM3 pump against the HeartMate II LVAD (MOMENTUM 3), and then another analysis comparing MT with the first- and second-generation HeartMate XVE pump LVAD and HeartMate II LVAD for the same patient population (REMATCH and ROADMAP, respectively). By bridging those 2 analyses, an indirect comparison between HM3 and MT in the form of a network meta-analysis was developed. A literature search was performed to select the most appropriate pair of studies for this purpose. Outcomes were adjusted to produce Kaplan-Meier curves for the cost-effectiveness evaluation by using a decision-analytic model. Data were extrapolated linearly over a 5-year time horizon. Uncertainty and additional scenarios were addressed by one-way and probabilistic sensitivity analysis. Local costs and health utility were used from England, thereby representing the UK context. Results: The incremental cost-effectiveness ratio (ICER) for LVAD vs MT in transplant ineligible patients with advanced HF was estimated to be £47,361 per quality-adjusted life year gained, with a 97.1% probability of being cost-effective at £50,000. In a subgroup of patients who are inotropic therapy dependent (INTERMACS 1-3 severity profile), the ICER was £45,616, while for a population with less-ill ambulatory HF (INTERMACS profile 4-7) the ICER changed to £64,051. Conclusions: This study provides evidence that HM3 LVAD therapy in advanced HF patients ineligible for heart transplantation may be cost-effective compared to MT in the NHS

OBJECTIVE: To evaluate the impact of sharing electronic health records (EHRs) with patients and map it across six domains of quality of care (ie, patient-centredness, effectiveness, efficiency, timeliness, equity and safety). DESIGN: Systematic review and meta-analysis. DATA SOURCES: CINAHL, Cochrane, Embase, HMIC, Medline/PubMed and PsycINFO, from 1997 to 2017. ELIGIBILITY CRITERIA: Randomised trials focusing on adult subjects, testing an intervention consisting of sharing EHRs with patients, and with an outcome in one of the six domains of quality of care. DATA ANALYSIS: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed. Title and abstract screening were performed by two pairs of investigators and assessed using the Cochrane Risk of Bias Tool. For each domain, a narrative synthesis of the results was performed, and significant differences in results between low risk and high/unclear risk of bias studies were tested (t-test, p<0.05). Continuous outcomes evaluated in four studies or more (glycated haemoglobin (HbA1c), systolic blood pressure (SBP) and diastolic blood pressure (DBP)) were pooled as weighted mean difference (WMD) using random effects meta-analysis. Sensitivity analyses were performed for low risk of bias studies, and long-term interventions only (lasting more than 12 months). RESULTS: Twenty studies were included (17 387 participants). The domain most frequently assessed was effectiveness (n=14), and the least were timeliness and equity (n=0). Inconsistent results were found for patient-centredness outcomes (ie, satisfaction, activation, self-efficacy, empowerment or health literacy), with 54.5% of the studies (n=6) demonstrating a beneficial effect. Meta-analyses showed a beneficial effect in effectiveness by reducing absolute values of HbA1c (unit: %; WMD=-0.316; 95% CI -0.540 to -0.093, p=0.005, I 2=0%), which remained significant in the sensitivity analyses for low risk of bias studies (WMD= -0.405; 95

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. The res

Despite the large number of new medicines entering the market every year, the vast majority offer few clinical advantages for patients over existing alternatives. Governments and pharmaceutical companies share the responsibility for this innovation deficit in the sector.

Introduction: Automation of routine clinical data shows promise in relieving health systems of the burden associated with manual data collection. Identifying consistent points of documentation in the electronic health record (EHR) provides salient targets to improve data entry quality. Using our pituitary surgery service as an exemplar, we aimed to demonstrate how process mapping can be used to identify reliable areas of documentation in the patient pathway to target structured data entry interventions. Materials and methods: This mixed methods study was conducted in the largest pituitary centre in the UK. Purposive snowball sampling identified frontline stakeholders for process mapping to produce a patient pathway. The final patient pathway was subsequently validated against a real-world dataset of 50 patients who underwent surgery for pituitary adenoma. Events were categorized by frequency and mapped to the patient pathway to determine critical data points. Results: Eighteen stakeholders encompassing all members of the multidisciplinary team (MDT) were consulted for process mapping. The commonest events recorded were neurosurgical ward round entries (N = 212, 14.7%), pituitary clinical nurse specialist (CNS) ward round entries (N = 88, 6.12%) and pituitary MDT treatment decisions (N = 88, 6.12%) representing critical data points. Operation notes and neurosurgical ward round entries were present for every patient. 43/44 (97.7%) had a pre-operative pituitary MDT entry, pre-operative clinic letter, a post-operative clinic letter, an admission clerking entry, a discharge summary, and a post-operative histopathology pituitary multidisciplinary (MDT) team entries. Conclusion: This is the first study to produce a validated patient pathway of patients undergoing pituitary surgery, serving as a comparison to optimise this patient pathway. We have identified salient targets for structured data entry interventions, including mandatory datapoints seen in every admission and h