Background As management of chronic pain continues to be suboptimal, there is a need for tools that support frequent, longitudinal pain self-reporting to improve our understanding of pain. This study aimed to assess the feasibility and acceptability of daily pain self-reporting using a smartphone-based pain manikin. Methods For this prospective feasibility study, we recruited adults with lived experience of painful musculoskeletal condition. They were asked to complete daily pain self-reports via an app for 30 days. We assessed feasibility by calculating pain report completion levels, and investigated differences in completion levels between subgroups. We assessed acceptability via an end-of-study questionnaire, which we analysed descriptively. Results Of the 104 participants, the majority were female ( n = 87; 84%), aged 45-64 ( n = 59; 57%), and of white ethnic background ( n = 89; 86%). The mean completion levels was 21 (± 7.7) pain self-reports. People who were not working (odds ratio (OR) = 1.84; 95% confidence interval (CI), 1.52-2.23) were more likely, and people living in less deprived areas (OR = 0.77; 95% CI, 0.62-0.97) and of non-white ethnicity (OR = 0.45; 95% CI, 0.36-0.57) were less likely to complete pain self-reports than their employed, more deprived and white counterparts, respectively. Of the 96 participants completing the end-of-study questionnaire, almost all participants agreed that it was easy to complete a pain drawing ( n = 89; 93%). Conclusion It is feasible and acceptable to self–report pain using a smartphone–based manikin over a month. For its wider adoption for pain self–reporting, the feasibility and acceptability should be further explored among people with diverse socio–economic and ethnic backgrounds.

Introduction Globally, allergic responses to medications is a growing concern (1), can result in adverse outcomes of differing levels of severity for patients and if undetected at point of prescription, increase patient risk and potentially increase hospital workload (2). With clinical decision support systems becoming more common as hospitals modernise data management structures to improve overall efficiency and safety, there is an increased ability to carry out drug-allergy interaction monitoring. The alert warnings generated by such clinical decision support systems are based on standard protocols which may not be applicable to all patients. Aim To quantify the types of allergy and intolerance alerts contained in an EHR system at an academic, tertiary care hospital. The objectives were to undertake an analysis of alert appropriateness and the factors associated with warning overrides at point of prescribing. Methods Retrospective analysis of allergy data alerts extracted from an EHR system over an 11-month period between June 2019 and March 2021, comprising data on prescriber actions, prescription description and frequency of allergic response and patient intolerance (i.e., adverse reactions/drug intolerances) to various prescriptions. Variables included provider type, provider speciality, description, context, drug-allergy reactions, drug-allergy contraindication group, importance level, severity, along-with the patients’ sex and age. Descriptive analysis was conducted, as well as unadjusted and adjusted logistic regression analysis with results presented as odds ratios (OR), 95% confidence intervals and p-values. Results In the total dataset (n=53,057), females represented 68.53% (n=36,361) and males represented 31.4% (n=16,696). Overrides made up 61.3% (n=32,520) and heeded/actioned made up 20% (n=10,599) of the total alerts. Prescriber overrides were significantly associated with provider type, provider speciality, description, context, drug-allergy reactions, drug-allergy contraindication group, importance level, severity, along-with the patients’ sex and age. Allergies (adjusted-OR 0.88 [0.82-0.94], p<0.001) were 12% less likely to be overridden than ‘adverse reactions/drug intolerances’, while ‘drug class match’ (adjusted-OR 0.50 [0.35-0.72], p<0.001) and ‘ingredient match’ (adjusted-OR 0.26 [0.18-0.37], p<0.001) were less likely to be associated with an override as compared to cross-sensitive matches. The most frequently recorded reason for overrides was ‘benefit outweighs risk’ (n=12,331; 23.2%), followed by ‘does not apply to patient’ (16.6%) and ‘inaccurate warning’ (4.6%). The key strength of the study is the volume of alerts that allowed an analysis of the factors that were associated with warning overrides. Limitations include the lack of information about actual prescribing decision, patient outcome following the alert action and potential influence of the pandemic. The study adds further evidence to the burden of alerts in EHR systems and identifies factors that may be utilised to improve the design and sensitivity of warnings. Conclusion A high level of alert overrides was seen, with allergies relating to antibiotics least likely to be overridden. Override reasons indicated that prescribers considered the warning to be either inappropriate or inaccurate in one in five cases. References 1. Légat, L., Van Laere, S., Nyssen, M., Steurbaut, S., Dupont, A.G., Cornu, P., 2018. Clinical Decision Support Systems for Drug Allergy Checking: Systematic Review. J Med Internet Res 20. https://doi.org/10.2196/jmir.8206 2. K Goss, F.R., Zhou, L., Plasek, J.M., Broverman, C., Robinson, G., Middleton, B., Rocha, R.A., 2013. Evaluating standard terminologies for encoding allergy information. J Am Med Inform Assoc 20, 969–979. https://doi.org/10.1136/amiajnl-2012-000816