Clinician Perspectives on Unmet Needs for Mobile Technology Among Hospitalists:Workflow Analysis Based on Semistructured Interviews

Background: The hospitalist workday is cognitively demanding and dominated by activities away from patients’ bedsides. Although mobile technologies are offered as solutions, clinicians report lower expectations of mobile technology after actual use. Objective: The purpose of this study is to better understand opportunities for integrating mobile technology and apps into hospitalists’ workflows. We aim to identify difficult tasks and contextual factors that introduce inefficiencies and characterize hospitalists’ perspectives on mobile technology and apps. Methods: We conducted a workflow analysis based on semistructured interviews. At a Midwestern US medical center, we recruited physicians and nurse practitioners from hospitalist and inpatient teaching teams and internal medicine residents. Interviews focused on tasks perceived as frequent, redundant, and difficult. Additionally, participants were asked to describe opportunities for mobile technology interventions. We analyzed contributing factors, impacted workflows, and mobile app ideas. Results: Over 3 months, we interviewed 12 hospitalists. Participants collectively identified chart reviews, orders, and documentation as the most frequent, redundant, and difficult tasks. Based on those tasks, the intake, discharge, and rounding workflows were characterized as difficult and inefficient. The difficulty was associated with a lack of access to electronic health records at the bedside. Contributing factors for inefficiencies were poor usability and inconsistent availability of health information technology combined with organizational policies. Participants thought mobile apps designed to improve team communications would be most beneficial. Based on our analysis, mobile apps focused on data entry and presentation supporting specific tasks should also be prioritized. Conclusions: Based on our results, there are prioritized opportunities for mobile technology to decrease difficulty and increase the efficiency of hospitalists’workflows. Mobile technology and task-specific mobile apps with enhanced usability could decrease overreliance on hospitalists’ memory and fragmentation of clinical tasks across locations. This study informs the design and implementation processes of future health information technologies to improve continuity in hospital-based medicine.This work was supported by a pilot grant (PPO 15-401; AS) and a Center of Innovation grant (CIN 13-416, M Weiner), both from the United States Department of Veterans Affairs Health Services Research and Development. AS is supported in part by the following grants: KL2TR002530 (A Carroll, PI), and UL1TR002529 (A Shekhar, PI) from the National Institutes of Health, National Center for Advancing Translational Sciences, Clinical and Translational Sciences Award

PATH-10. Accelerating comprehensive CNS tumor molecular diagnostics with Rapid-CNS2 and MNP-flex: a prospective multi-center validation [Abstract]

BACKGROUND The 2021 WHO classification update highlights the necessity of integrating molecular alterations for precise central nervous system (CNS) tumor diagnoses. However, current molecular reporting methods are hindered by significant initial investment, labor-intensive protocols, and lengthy turnaround times. Methylation-based classification has emerged as a pivotal diagnostic tool but is currently limited to array-based techniques. This necessitates exploration of novel technologies to streamline molecular analysis. METHODS We implemented Rapid-CNS2 - our adaptive sampling-based nanopore sequencing workflow- on 190 adult and pediatric samples at University Hospital Heidelberg and University of Nottingham. Intraoperative potential was assessed through real-time analysis followed by 24-hour sequencing for comprehensive genomic insights. Additionally, we developed MNP-Flex, a platform-agnostic version of the Heidelberg methylation classifier covering 184 CNS tumor classes. We evaluated MNP-flex on a global cohort of over 78,000 samples from methylation arrays, whole genome bisulfite sequencing, nanopore whole genome sequencing, methylation panels and Rapid-CNS2. RESULTS Rapid-CNS2 validation yielded accurate integrated diagnoses in all 190 samples. Within a crucial 30-minute timeframe, we reported accurate methylation families and arm-level copy number profiles followed by next-day reporting of fine-grained methylation classification, SNVs, focal CNVs, MGMT status, fusions and novel structural variants. Moreover, MNP-Flex achieved 92% accuracy over the validation dataset spanning over 78,000 samples from five different technologies. CONCLUSIONS The adoption of Rapid-CNS2 and MNP-Flex enables rapid intraoperative broad methylation classification and copy number alteration reporting within 30 minutes, with additional clinically relevant, fine-grained molecular insights available the following day. It offers clinicians rapid access to comprehensive molecular information critical for treatment decisions. Furthermore, MNP-Flex extends the utility of the Heidelberg methylation classifier to diverse sequencing-based data. By overcoming the limitations of currently available methods, our workflow represents a paradigm shift in the field, promising improved management of CNS tumor patients. Rapid-CNS2 can be executed with a single command, while MNP-Flex is publicly available as a web service, enhancing accessibility and usability for clinical applications

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Code Status Orders: Do the Options Matter?

Background: Code status orders in hospitalized patients guide urgent medical decisions. Inconsistent terminology and treatment options contribute to varied interpretations. Objective: To compare two code status order options, traditional (three option) and modified to include additional care options (four option). Design: Prospective, randomized, cross-sectional survey conducted on February-March 2020. Participants were provided with six clinical scenarios and randomly assigned to the three or four option code status order. In three scenarios, participants determined the most appropriate code status. Three scenarios provided clinical details and code status and respondents were asked whether they would provide a particular intervention. This study was conducted at three urban, academic hospitals. Participants: Clinicians who routinely utilize code status orders. Of 4006 participants eligible, 549 (14%) were included. Main measures: The primary objective was consensus (most commonly selected answer) based on provided code status options. Secondary objectives included variables associated with participant responses, participant code status model preference, and participant confidence about whether their selections would match their peers. Key results: In the three scenarios participants selected the appropriate code status, there was no difference in consensus for the control scenario, and higher consensus in the three option group (p-values < 0.05) for the remaining two scenarios. In the scenarios to determine if a clinical intervention was appropriate, two of the scenarios had higher consensus in the three option group (p-values 0.018 and < 0.05) and one had higher consensus in the four option group (p-value 0.001). Participants in the three option model were more confident that their peers selected the same code status (p-value 0.0014); however, most participants (72%) preferred the four option model. Conclusions: Neither code status model led to consistent results. The three option model provided consistency more often; however, the majority of participants preferred the four option model

Test for Non-Synergistic Interactions in Phytomedicine, Just as You Do for Isolated Compounds

Phytomedicine has often been used as “alternative therapy,” which in our opinion is unfortunate as it prevents its main actions being systematically studied, side effects explored, and toxicity tested, like all single-compound-based medicine. Our group is interested in finding which traditional or modern phytomedicines actually work and which are simply “working” through placebo, standardizing phytomedicine preparations, studying their toxicity, and finding active molecules in plants for modification and chemical synthesis as single compounds. Although fluctuation in efficacy due to seasonal and geographical variations in phytomedicine remains a concern, if well regulated, even plant extracts without isolated compounds can serve medicinal needs where single-compound options are currently not great. A potential concern with such phytomedicine is frequent mixing of ingredients in commercial formulations without test of synergism. Our study on the use of 2 traditional plants for Parkinson disease shows a clear lack of synergism, and to study nonsynergism better, we developed a new visualization approach. In this commentary, using our study on Parkinson disease as an example, we make a case for better evaluation of phytomedicines, especially testing for synergistic interactions. We also critique our own exploration of oxidative stress and few behavioral parameters alone to lay grounds for what we and hopefully others can do in future to extract more information from their phytomedicine studies. We hope this commentary acts as a good warning for anyone mixing 2 phytomedicines without testing

Patient-Derived Tumor Organoids for Guidance of Personalized Drug Therapies in Recurrent Glioblastoma

An obstacle to effective uniform treatment of glioblastoma, especially at recurrence, is genetic and cellular intertumoral heterogeneity. Hence, personalized strategies are necessary, as are means to stratify potential targeted therapies in a clinically relevant timeframe. Functional profiling of drug candidates against patient-derived glioblastoma organoids (PD-GBO) holds promise as an empirical method to preclinically discover potentially effective treatments of individual tumors. Here, we describe our establishment of a PD-GBO-based functional profiling platform and the results of its application to four patient tumors. We show that our PD-GBO model system preserves key features of individual patient glioblastomas in vivo. As proof of concept, we tested a panel of 41 FDA-approved drugs and were able to identify potential treatment options for three out of four patients; the turnaround from tumor resection to discovery of treatment option was 13, 14, and 15 days, respectively. These results demonstrate that this approach is a complement and, potentially, an alternative to current molecular profiling efforts in the pursuit of effective personalized treatment discovery in a clinically relevant time period. Furthermore, these results warrant the use of PD-GBO platforms for preclinical identification of new drugs against defined morphological glioblastoma features