IntroductionHealth administration is complex and serves many masters. Value, quality, infrastructure and reimbursement are just a sample of the competing interests influencing executive decision-making. This creates a need for decision processes that are rational and holistic.MethodsWe created a multicriteria decision analysis tool to evaluate six fields of healthcare provision: return on investment, capacity, outcomes, safety, training and risk. The tool was designed for prospective use, at the beginning of each funding round for competing projects. Administrators were asked to rank their criteria in order of preference. Each field was assigned a representative weight determined from the rankings. Project data were then entered into the tool for each of the six fields. The score for each field was scaled as a proportion of the highest scoring project, then weighted by preference. We then plotted findings on a cost-effectiveness plane. The project was piloted and developed over successive uses by the hospital’s executive board.ResultsTwelve projects competing for funding at the Royal Brisbane and Women’s Hospital were scored by the tool. It created a priority ranking for each initiative based on the weights assigned to each field by the executive board. Projects were plotted on a cost-effectiveness plane with score as the x-axis and cost of implementation as the y-axis. Projects to the bottom right were considered dominant over projects above and to the left, indicating that they provided greater benefit at a lower cost. Projects below the x-axis were cost-saving and recommended provided they did not harm patients. All remaining projects above the x-axis were then recommended in order of lowest to highest cost-per-point scored.ConclusionThis tool provides a transparent, objective method of decision analysis using accessible software. It would serve health services delivery organisations that seek to achieve value in healthcare.
Background: Social media has changed the way surgeons communicate worldwide, particularly in dissemination of trial results. However, it is unclear if social media could be used in recruitment to surgical trials. This study aimed to investigate the influence of Twitter in promoting surgical recruitment in The Emergency Laparotomy and Frailty (ELF) Study. Methods: The ELF Study was a UK-based, prospective, observational cohort that aimed to assess the influence of frailty on 90-day mortality in older adults undergoing emergency surgery. A power calculation required 500 patients to be recruited to detect a 10% change in mortality associated with frailty. A 12-week recruitment period was selected, calculated from information submitted by participating hospitals and the numbers of emergency surgeries performed in adults aged > 65 years. A Twitter handle was designed (@ELFStudy) with eye-catching logos to encourage enrolment and inform the public and clinicians involved in the study. Twitter Analytics and Twitonomy (Digonomy Pty Ltd) were used to analyse user engagement in relation to patient recruitment. Results: After 90 days of data collection, 49 sites from Scotland, England and Wales recruited 952 consecutive patients undergoing emergency laparotomy, with data logged into a database created on REDCap. Target recruitment (n = 500) was achieved by week 11. A total of 591 tweets were published by @ELFStudy since its conception, making 218,136 impressions at time of writing. The number of impressions (number of times users see a particular tweet) prior to March 20th 2017 (study commencement date) was 23,335 (343.2 per tweet), compared to the recruitment period with 114,314 impressions (256.3 per tweet), ending June 20th 2017. Each additional tweet was associated with an increase in recruitment of 1.66 (95%CI 1.36 to 1.97; p < 0.001). Conclusion: The ELF Study over-recruited by nearly 100%, reaching over 200,000 people across the U.K. Branding enhanced tweet aesthetics and helped increase tweet engagement to stimulate discussion and healthy competition amongst clinicians to aid trial recruitment. Other studies may draw from the social media experiences of the ELF Study to optimise collaboration amongst researchers.
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