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Objectives To develop and validate a tool to predict the risk of an older adult experiencing medication- related harm (MRH) requiring healthcare use following hospital discharge. Design, setting, participants Multicentre, prospective cohort study recruiting older adults (≥65 years) discharged from five UK teaching hospitals between 2013 and 2015. Primary outcome measure Participants were followed up for 8 weeks in the community by senior pharmacists to identify MRH (adverse drug reactions, harm from non- adherence, harm from medication error). Three data sources provided MRH and healthcare use information: hospital readmissions, primary care use, participant telephone interview. Candidate variables for prognostic modelling were selected using two systematic reviews, the views of patients with MRH and an expert panel of clinicians. Multivariable logistic regression with backward elimination, based on the Akaike Information Criterion, was used to develop the PRIME tool. The tool was internally validated. Results 1116 out of 1280 recruited participants completed follow- up (87%). Uncertain MRH cases ('possible' and 'probable') were excluded, leaving a tool derivation cohort of 818. 119 (15%) participants experienced 'definite' MRH requiring healthcare use and 699 participants did not. Modelling resulted in a prediction tool with eight variables measured at hospital discharge: age, gender, antiplatelet drug, sodium level, antidiabetic drug, past adverse drug reaction, number of medicines, living alone. The tool's discrimination C- statistic was 0.69 (0.66 after validation) and showed good calibration. Decision curve analysis demonstrated the potential value of the tool to guide clinical decision making compared with alternative approaches. Conclusions The PRIME tool could be used to identify older patients at high risk of MRH requiring healthcare use following hospital discharge. Prior to clinical use we recommend the tool's evaluation in other settings. [ABSTRACT FROM AUTHOR]

Objective An international panel of pain specialists (anesthesiology, neurology, neurosurgery, and psychology) and research methodologists developed a screening tool to identify patients who may be suitable for spinal cord stimulation ( SCS)-the Refractory Chronic Pain Screening Tool ( RCPST) prototype. We describe a feasibility study to explore practicality and validity of this prototype. Design Consecutive outpatients were screened in two centers ( United Kingdom and United States). Sixty chronic pain adults without satisfactory pain relief despite treatment were assessed using RCPST (by pain specialist without expertise in neurostimulation) and then evaluated by two pain specialists experienced in SCS implantation and management to determine whether the patient should be referred for SCS. To maintain blinding, the participating physicians did not inform each other or the patient of assessment outcome. Sensitivity and specificity of the RCPST prototype were calculated using implanters' judgment as 'gold standard.' Results The average age of patients was 47.7 years; 53% were female. Fifty-seven patients completed the study (one withdrew consent, two lost to follow-up). The pain specialists agreed the prototype was easy to use and took <10 minutes to complete. Implanter agreement was moderate ( Kappa: 0.63, 95% confidence interval: 0.35-0.91). The prototype had low sensitivity (40%, 19-61%) and moderate specificity (78%, 65-92%). Using the same questionnaire with a modified decision algorithm, new prototypes were generated with range of high sensitivity (80-100%) and specificity (89-97%) values. Conclusions The RCPST aims to identify patients that should be referred for consideration for neurostimulation. The final implant decision requires appropriate neurological diagnostic workup, psychological assessment, and trial stimulation. RCPST was considered practical for routine clinical practice and contained appropriate questions. Sensitivity needs to be improved. A future study should select and validate the ideal RCPST prototype. [ABSTRACT FROM AUTHOR]

Background Evidence suggests that in decision contexts characterized by uncertainty and time constraints (e.g. health-care decisions), fast and frugal decision-making strategies (heuristics) may perform better than complex rules of reasoning. Objective To examine whether it is possible to design deliberation components in decision support interventions using simple models (fast and frugal heuristics). Design The 'Take The Best' heuristic (i.e. selection of a 'most important reason') and 'The Tallying' integration algorithm (i.e. unitary weighing of pros and cons) were used to develop two deliberation components embedded in a Web-based decision support intervention for women facing amniocentesis testing. Ten researchers (recruited from 15), nine health-care providers (recruited from 28) and ten pregnant women (recruited from 14) who had recently been offered amniocentesis testing appraised evolving versions of 'your most important reason' (Take The Best) and 'weighing it up' (Tallying). Results Most researchers found the tools useful in facilitating decision making although emphasized the need for simple instructions and clear layouts. Health-care providers however expressed concerns regarding the usability and clarity of the tools. By contrast, 7 out of 10 pregnant women found the tools useful in weighing up the pros and cons of each option, helpful in structuring and clarifying their thoughts and visualizing their decision efforts. Several pregnant women felt that 'weighing it up' and 'your most important reason' were not appropriate when facing such a difficult and emotional decision. Conclusion Theoretical approaches based on fast and frugal heuristics can be used to develop deliberation tools that provide helpful support to patients facing real-world decisions about amniocentesis. [ABSTRACT FROM AUTHOR]