Pediatric TAFRO syndrome: A multi-institution case series illustrating clinical challenges and excellent outcomes.

A rare lymphoproliferative disorder involving thrombocytopenia (T), anasarca (A), fever (F), reticulin fibrosis (R), renal dysfunction (R), and organomegaly (O), called TAFRO syndrome, was first reported in 2010. Considered a variant of idiopathic multicentric Castleman's disease, the recent discovery and rarity of this syndrome pose challenges to diagnosis and management. Herein, we review three pediatric cases, including an infant, that illustrate the heterogeneity of TAFRO syndrome. Despite differences in presentation and treatment responses, all patients experienced excellent outcomes. This multi-institutional case series highlights the need to work toward earlier diagnosis and improved long-term management recommendations for patients with TAFRO syndrome.

Illness Trajectories After Revascularization in Patients With Peripheral Artery Disease: A Unified Approach to Understanding the Risk of Major Amputation and Death.

BACKGROUND: The aim of this study was to investigate the illness trajectories of patients with peripheral artery disease (PAD) after revascularization and estimate the independent risks of major amputation and death (from any cause) and their interaction. METHODS: Data from Hospital Episode Statistics Admitted Patient Care were used to identify patients (≥50 years of age) who underwent lower limb revascularization for PAD in England from April 2013 to March 2020. A Markov illness-death model was developed to describe patterns of survival after the initial lower limb revascularization, if and when patients experienced major amputation, and survival after amputation. The model was also used to investigate the association between patient characteristics and these illness trajectories. We also analyzed the relative contribution of deaths after amputation to overall mortality and how the risk of mortality after amputation was related to the time from the index revascularization to amputation. RESULTS: The study analyzed 94 690 patients undergoing lower limb revascularization for PAD from 2013 to 2020. The majority were men (65.6%), and the median age was 72 years (interquartile range, 64-79). One-third (34.8%) of patients had nonelective revascularization, whereas others had elective procedures. For nonelective patients, the amputation rate was 15.2% (95% CI, 14.4-16.0) and 19.9% (19.0-20.8) at 1 and 5 years after revascularization, respectively. For elective patients, the corresponding amputation rate was 2.7% (95% CI, 2.4-3.1) and 5.3% (4.9-5.8). Overall, the risk of major amputation was higher among patients who were younger, had tissue loss, diabetes, greater frailty, nonelective revascularization, and more distal procedures. The mortality rate at 5 years after revascularization was 64.3% (95% CI, 63.2-65.5) for nonelective patients and 33.0% (32.0-34.1) for elective patients. After major amputation, patients were at an increased risk of mortality if they underwent major amputation within 6 months after the index revascularization. CONCLUSIONS: The illness-death model provides an integrated framework to understand patient outcomes after lower limb revascularization for PAD. Although mortality increased with age, the study highlights patients <60 years of age were at increased risk of major amputation, particularly after nonelective revascularization.

Complex Hospital-Based Electronic Prescribing-Based Intervention to Support Antimicrobial Stewardship: Qualitative Study.

BACKGROUND: Antimicrobial resistance (AMR) represents a growing concern for public health. OBJECTIVE: We sought to explore the challenges associated with development and implementation of a complex intervention designed to improve AMS in hospitals. METHODS: We conducted a qualitative evaluation of a complex AMS intervention with educational, behavioral, and technological components in 5 wards of an English hospital. At 2 weeks and 7 weeks after initiating the intervention, we interviewed 25 users of the intervention, including senior and junior prescribers, a senior nurse, a pharmacist, and a microbiologist. Topics discussed included perceived impacts of different elements of the intervention and facilitators and barriers to effective use. Interviews were supplemented by 2 observations of ward rounds to gain insights into AMS practices. Data were audio-recorded, transcribed, and inductively and deductively analyzed thematically using NVivo12. RESULTS: Tracing the adoption and impact of the various components of the intervention was difficult, as it had been introduced into a setting with competing pressures. These particularly affected behavioral and educational components (eg, training, awareness-building activities), which were often delivered ad hoc. We found that the participatory intervention design had addressed typical use cases but had not catered for edge cases that only became visible when the intervention was delivered in real-world settings (eg, variations in prescribing workflows across different specialties and conditions). CONCLUSIONS: Effective user-focused design of complex interventions to promote AMS can support acceptance and use. However, not all requirements and potential barriers to use can be fully anticipated or tested in advance of full implementation in real-world settings.

Mutation Screening of Dictyostelium Restriction Enzyme-Mediated Integration (REMI) Libraries.

Identifying the mechanisms of action of existing and novel drugs is essential for the development of new compounds for therapeutic and commercial use. Here we provide a technique to identify these mechanisms through isolating mutant cell lines that show resistance to drug-induced phenotypes using Dictyostelium discoideum REMI libraries. This approach provides a robust and rapid chemical-genetic screening technique that enables an unbiased approach to identify proteins and molecular pathways that control drug sensitivity. Mutations that result in drug resistance often occur in target proteins thus identifying the specific protein targets for drugs and bioactive natural products. Following the identification of a list of putative molecular targets user selected compound targets can be analyzed to confirm and validate direct inhibitory effects.

Developing a Tanshinone IIA Memetic by Targeting MIOS to Regulate mTORC1 and Autophagy in Glioblastoma.

Tanshinone IIA (T2A) is a bioactive compound that provides promise in the treatment of glioblastoma multiforme (GBM), with a range of molecular mechanisms including the inhibition of the mechanistic target of rapamycin complex 1 (mTORC1) and the induction of autophagy. Recently, T2A has been demonstrated to function through sestrin 2 (SESN) to inhibit mTORC1 activity, but its possible impact on autophagy through this pathway has not been investigated. Here, the model system Dictyostelium discoideum and GBM cell lines were employed to investigate the cellular role of T2A in regulating SESN to inhibit mTORC1 and activate autophagy through a GATOR2 component MIOS. In D. discoideum, T2A treatment induced autophagy and inhibited mTORC1 activity, with both effects lost upon the ablation of SESN (sesn-) or MIOS (mios-). We further investigated the targeting of MIOS to reproduce this effect of T2A, where computational analysis identified 25 novel compounds predicted to strongly bind the human MIOS protein, with one compound (MIOS inhibitor 3; Mi3) reducing cell proliferation in two GBM cells. Furthermore, Mi3 specificity was demonstrated through the loss of potency in the D. discoideum mios- cells regarding cell proliferation and the induction of autophagy. In GBM cells, Mi3 treatment also reduced mTORC1 activity and induced autophagy. Thus, a potential T2A mimetic showing the inhibition of mTORC1 and induction of autophagy in GBM cells was identified.

Evaluation of venous thromboembolism risk assessment models for hospital inpatients: the VTEAM evidence synthesis.

Background: Pharmacological prophylaxis during hospital admission can reduce the risk of acquired blood clots (venous thromboembolism) but may cause complications, such as bleeding. Using a risk assessment model to predict the risk of blood clots could facilitate selection of patients for prophylaxis and optimise the balance of benefits, risks and costs. Objectives: We aimed to identify validated risk assessment models and estimate their prognostic accuracy, evaluate the cost-effectiveness of different strategies for selecting hospitalised patients for prophylaxis, assess the feasibility of using efficient research methods and estimate key parameters for future research. Design: We undertook a systematic review, decision-analytic modelling and observational cohort study conducted in accordance with Enhancing the QUAlity and Transparency Of health Research (EQUATOR) guidelines. Setting: NHS hospitals, with primary data collection at four sites. Participants: Medical and surgical hospital inpatients, excluding paediatric, critical care and pregnancy-related admissions. Interventions: Prophylaxis for all patients, none and according to selected risk assessment models. Main outcome measures: Model accuracy for predicting blood clots, lifetime costs and quality-adjusted life-years associated with alternative strategies, accuracy of efficient methods for identifying key outcomes and proportion of inpatients recommended prophylaxis using different models. Results: We identified 24 validated risk assessment models, but low-quality heterogeneous data suggested weak accuracy for prediction of blood clots and generally high risk of bias in all studies. Decision-analytic modelling showed that pharmacological prophylaxis for all eligible is generally more cost-effective than model-based strategies for both medical and surgical inpatients, when valuing a quality-adjusted life-year at £20,000. The findings were more sensitive to uncertainties in the surgical population; strategies using risk assessment models were more cost-effective if the model was assumed to have a very high sensitivity, or the long-term risks of post-thrombotic complications were lower. Efficient methods using routine data did not accurately identify blood clots or bleeding events and several pre-specified feasibility criteria were not met. Theoretical prophylaxis rates across an inpatient cohort based on existing risk assessment models ranged from 13% to 91%. Limitations: Existing studies may underestimate the accuracy of risk assessment models, leading to underestimation of their cost-effectiveness. The cost-effectiveness findings do not apply to patients with an increased risk of bleeding. Mechanical thromboprophylaxis options were excluded from the modelling. Primary data collection was predominately retrospective, risking case ascertainment bias. Conclusions: Thromboprophylaxis for all patients appears to be generally more cost-effective than using a risk assessment model, in hospitalised patients at low risk of bleeding. To be cost-effective, any risk assessment model would need to be highly sensitive. Current evidence on risk assessment models is at high risk of bias and our findings should be interpreted in this context. We were unable to demonstrate the feasibility of using efficient methods to accurately detect relevant outcomes for future research. Future work: Further research should evaluate routine prophylaxis strategies for all eligible hospitalised patients. Models that could accurately identify individuals at very low risk of blood clots (who could discontinue prophylaxis) warrant further evaluation. Study registration: This study is registered as PROSPERO CRD42020165778 and Researchregistry5216. Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme (NIHR award ref: NIHR127454) and will be published in full in Health Technology Assessment; Vol. 28, No. 20. See the NIHR Funding and Awards website for further award information.

People who are admitted to hospital are at risk of blood clots that can cause serious illness or death. Patients are often given low doses of blood-thinning drugs to reduce this risk. However, these drugs can cause side effects, such as bleeding. Hospitals currently use complex risk assessment models (risk scores, which usually include patient, disease, mobility and intervention factors) to determine the individual risk of blood clots and identify people most likely to benefit from blood-thinning drugs. There are a lot of different risk scores and we do not know which one is best. We also do not know how these scores compare to each other or whether using scores to decide who should get blood-thinning drugs provides good value for money to the NHS. We reviewed all previous studies of risk scores. We found that they did not predict blood clots very well and we could not recommend one score over another. We then created a mathematical model to simulate the use of blood-thinning drugs in people admitted to hospital. The model suggested that giving blood-thinning drugs to everyone who could have them would probably provide the best value for money, in medical patients. Our findings were the same, but less certain, for surgical patients. We also collected information from four NHS hospitals to explore possibilities for future research. Our work showed that routinely collected electronic data on blood clots and bleeding events is not very accurate and that using different scores could result in variable use of blood-thinning medications. Our findings suggest that it may be better value to the NHS and better for patients if we were to offer blood-thinning medications to everyone on admission to hospital, without using any risk score. However, this approach needs further research to ensure it is safe and effective. Such research would not be able to rely on routine electronic data to identify blood clots or bleeding events, in isolation.

A phase 1/2 study of pepinemab in children, adolescents, or young adults with recurrent or refractory solid tumors: A children's oncology group consortium report (ADVL1614).

PURPOSE: Pepinemab, a humanized IgG4 monoclonal antibody, targets the SEMA4D (CD100) antigen to inhibit binding to its high-affinity receptors (plexin B1/PLXNB1, plexin B2/PLXNB2) and low-affinity receptor (CD72). SEMA4D blockade leads to increased cytotoxic T-cell infiltration, delayed tumor growth, and durable tumor rejection in murine tumor models. Pepinemab was well tolerated and improved T cell infiltration in clinical studies in adults with refractory tumors. SEMA4D was identified as a strong candidate proto-oncogene in a model of osteosarcoma. Based on these preclinical and clinical data, we conducted a phase 1/2 study to determine the recommended phase 2 dose (RP2D), pharmacokinetics, pharmacodynamics, and immunogenicity, of pepinemab in pediatric patients with recurrent/refractory solid tumors, and activity in osteosarcoma. EXPERIMENTAL DESIGN: Pepinemab was administered intravenously on Days 1 and 15 of a 28-day cycle at 20 mg/kg, the adult RP2D. Part A (phase 1) used a Rolling 6 design; Part B (phase 2) used a Simon 2-stage design in patients with osteosarcoma. Pharmacokinetics and target saturation were evaluated in peripheral blood. RESULTS: Pepinemab (20 mg/kg) was well tolerated and no dose-limiting toxicities were observed during Part A. There were no objective responses. Two patients with osteosarcoma achieved disease control and prolonged stable disease. Pepinemab pharmacokinetics were similar to adults. CONCLUSIONS: Pepinemab (20 mg/kg) is safe, well tolerated and resulted in adequate and sustained target saturation in pediatric patients. Encouraging disease control in two patients with osteosarcoma warrants further investigation with novel combination strategies to modulate the tumor microenvironment and antitumor immune response. CLINICAL TRIAL REGISTRY: This trial is registered as NCT03320330 at Clinicaltrials.gov. DISCLAIMER: The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Functional mechanism study of the allelochemical myrigalone A identifies a group of ultrapotent inhibitors of ethylene biosynthesis in plants.

Allelochemicals represent a class of natural products released by plants as root, leaf, and fruit exudates that interfere with the growth and survival of neighboring plants. Understanding how allelochemicals function to regulate plant responses may provide valuable new approaches to better control plant function. One such allelochemical, Myrigalone A (MyA) produced by Myrica gale, inhibits seed germination and seedling growth through an unknown mechanism. Here, we investigate MyA using the tractable model Dictyostelium discoideum and reveal that its activity depends on the conserved homolog of the plant ethylene synthesis protein 1-aminocyclopropane-1-carboxylic acid oxidase (ACO). Furthermore, in silico modeling predicts the direct binding of MyA to ACO within the catalytic pocket. In D. discoideum, ablation of ACO mimics the MyA-dependent developmental delay, which is partially restored by exogenous ethylene, and MyA reduces ethylene production. In Arabidopsis thaliana, MyA treatment delays seed germination, and this effect is rescued by exogenous ethylene. It also mimics the effect of established ACO inhibitors on root and hypocotyl extension, blocks ethylene-dependent root hair production, and reduces ethylene production. Finally, in silico binding analyses identify a range of highly potent ethylene inhibitors that block ethylene-dependent response and reduce ethylene production in Arabidopsis. Thus, we demonstrate a molecular mechanism by which the allelochemical MyA reduces ethylene biosynthesis and identify a range of ultrapotent inhibitors of ethylene-regulated responses.

Concerted adoption as an emerging strategy for digital transformation of healthcare-lessons from Australia, Canada, and England.

OBJECTIVES: With an increasing focus on the digitalization of health and care settings, there is significant scope to learn from international approaches to promote concerted adoption of electronic health records. MATERIALS AND METHODS: We review three large-scale initiatives from Australia, Canada, and England, and extract common lessons for future health and social care transformation strategy. RESULTS: We discuss how, despite differences in contexts, concerted adoption enables sharing of experience and learning to streamline the digital transformation of health and care. DISCUSSION AND CONCLUSION: Concerted adoption can be accelerated through building communities of expertise and partnerships promoting knowledge transfer and circulation of expertise; commonalities in geographical and cultural contexts; and commonalities in technological systems.

Fair and equitable AI in biomedical research and healthcare: Social science perspectives.

Artificial intelligence (AI) offers opportunities but also challenges for biomedical research and healthcare. This position paper shares the results of the international conference "Fair medicine and AI" (online 3-5 March 2021). Scholars from science and technology studies (STS), gender studies, and ethics of science and technology formulated opportunities, challenges, and research and development desiderata for AI in healthcare. AI systems and solutions, which are being rapidly developed and applied, may have undesirable and unintended consequences including the risk of perpetuating health inequalities for marginalized groups. Socially robust development and implications of AI in healthcare require urgent investigation. There is a particular dearth of studies in human-AI interaction and how this may best be configured to dependably deliver safe, effective and equitable healthcare. To address these challenges, we need to establish diverse and interdisciplinary teams equipped to develop and apply medical AI in a fair, accountable and transparent manner. We formulate the importance of including social science perspectives in the development of intersectionally beneficent and equitable AI for biomedical research and healthcare, in part by strengthening AI health evaluation.

Early Experiences of Integrating an Artificial Intelligence-Based Diagnostic Decision Support System into Radiology Settings: A Qualitative Study.

BACKGROUND: Artificial Intelligence (AI) based clinical decision support systems to aid diagnosis are increasingly being developed and implemented but with limited understanding of how such systems integrate with existing clinical work and organizational practices. We explored the early experiences of stakeholders using an AI-based e-learning imaging software tool Veye Lung Nodules (VLN) aiding the detection, classification, and measurement of pulmonary nodules in computed tomography scans of the chest. We performed semi-structured interviews and observations across early adopter deployment sites with clinicians, strategic decision-makers, suppliers, patients with long-term chest conditions, and academics with expertise in the use of diagnostic AI in radiology settings. We coded the data using the Technology, People, Organizations and Macro-environmental factors framework (TPOM). We conducted 39 interviews. Clinicians reported VLN to be easy to use with little disruption to the workflow. There were differences in patterns of use between experts and novice users with experts critically evaluating system recommendations and actively compensating for system limitations to achieve more reliable performance. Patients also viewed the tool positively. There were contextual variations in tool performance and use between different hospital sites and different use cases. Implementation challenges included integration with existing information systems, data protection, and perceived issues surrounding wider and sustained adoption, including procurement costs. Tool performance was variable, affected by integration into workflows and divisions of labor and knowledge, as well as technical configuration and infrastructure. These under-researched factors require attention and further research.

Optimising ePrescribing in hospitals through the interoperability of systems and processes: a qualitative study in the UK, US, Norway and the Netherlands.

BACKGROUND: Investment in the implementation of hospital ePrescribing systems has been a priority in many economically-developed countries in order to modernise the delivery of healthcare. However, maximum gains in the safety, quality and efficiency of care are unlikely to be fully realised unless ePrescribing systems are further optimised in a local context. Typical barriers to optimal use are often encountered in relation to a lack of systemic capacity and preparedness to meet various levels of interoperability requirements, including at the data, systems and services levels. This lack of systemic interoperability may in turn limit the opportunities and benefits potentially arising from implementing novel digital heath systems. METHODS: We undertook n = 54 qualitative interviews with key stakeholders at nine digitally advanced hospital sites across the UK, US, Norway and the Netherlands. We included hospitals featuring 'standalone, best of breed' systems, which were interfaced locally, and multi-component and integrated electronic health record enterprise systems. We analysed the data inductively, looking at strategies and constraints for ePrescribing interoperability within and beyond hospital systems. RESULTS: Our thematic analysis identified 4 main drivers for increasing ePrescribing systems interoperability: (1) improving patient safety (2) improving integration & continuity of care (3) optimising care pathways and providing tailored decision support to meet local and contextualised care priorities and (4) to enable full patient care services interoperability in a variety of settings and contexts. These 4 interoperability dimensions were not always pursued equally at each implementation site, and these were often dependent on the specific national, policy, organisational or technical contexts of the ePrescribing implementations. Safety and efficiency objectives drove optimisation targeted at infrastructure and governance at all levels. Constraints to interoperability came from factors such as legacy systems, but barriers to interoperability of processes came from system capability, hospital policy and staff culture. CONCLUSIONS: Achieving interoperability is key in making ePrescribing systems both safe and useable. Data resources exist at macro, meso and micro levels, as do the governance interventions necessary to achieve system interoperability. Strategic objectives, most notably improved safety, often motivated hospitals to push for evolution across the entire data architecture of which they formed a part. However, hospitals negotiated this terrain with varying degrees of centralised coordination. Hospitals were heavily reliant on staff buy-in to ensure that systems interoperability was built upon to achieve effective data sharing and use. Positive outcomes were founded on a culture of agreement about the usefulness of access by stakeholders, including prescribers, policymakers, vendors and lab technicians, which was reflected in an alignment of governance goals with system design.

Early experiences of integrating an artificial intelligence-based diagnostic decision support system into radiology settings: a qualitative study.

OBJECTIVES: Artificial intelligence (AI)-based clinical decision support systems to aid diagnosis are increasingly being developed and implemented but with limited understanding of how such systems integrate with existing clinical work and organizational practices. We explored the early experiences of stakeholders using an AI-based imaging software tool Veye Lung Nodules (VLN) aiding the detection, classification, and measurement of pulmonary nodules in computed tomography scans of the chest. MATERIALS AND METHODS: We performed semistructured interviews and observations across early adopter deployment sites with clinicians, strategic decision-makers, suppliers, patients with long-term chest conditions, and academics with expertise in the use of diagnostic AI in radiology settings. We coded the data using the Technology, People, Organizations, and Macroenvironmental factors framework. RESULTS: We conducted 39 interviews. Clinicians reported VLN to be easy to use with little disruption to the workflow. There were differences in patterns of use between experts and novice users with experts critically evaluating system recommendations and actively compensating for system limitations to achieve more reliable performance. Patients also viewed the tool positively. There were contextual variations in tool performance and use between different hospital sites and different use cases. Implementation challenges included integration with existing information systems, data protection, and perceived issues surrounding wider and sustained adoption, including procurement costs. DISCUSSION: Tool performance was variable, affected by integration into workflows and divisions of labor and knowledge, as well as technical configuration and infrastructure. CONCLUSION: The socio-organizational factors affecting performance of diagnostic AI are under-researched and require attention and further research.

Medium-Chain Fatty Acids Rescue Motor Function and Neuromuscular Junction Degeneration in a Drosophila Model of Amyotrophic Lateral Sclerosis.

Amyotrophic lateral sclerosis (ALS) is an adult-onset neurodegenerative disease characterised by progressive degeneration of the motor neurones. An expanded GGGGCC (G4C2) hexanucleotide repeat in C9orf72 is the most common genetic cause of ALS and frontotemporal dementia (FTD); therefore, the resulting disease is known as C9ALS/FTD. Here, we employ a Drosophila melanogaster model of C9ALS/FTD (C9 model) to investigate a role for specific medium-chain fatty acids (MCFAs) in reversing pathogenic outcomes. Drosophila larvae overexpressing the ALS-associated dipeptide repeats (DPRs) in the nervous system exhibit reduced motor function and neuromuscular junction (NMJ) defects. We show that two MCFAs, nonanoic acid (NA) and 4-methyloctanoic acid (4-MOA), can ameliorate impaired motor function in C9 larvae and improve NMJ degeneration, although their mechanisms of action are not identical. NA modified postsynaptic glutamate receptor density, whereas 4-MOA restored defects in the presynaptic vesicular release. We also demonstrate the effects of NA and 4-MOA on metabolism in C9 larvae and implicate various metabolic pathways as dysregulated in our ALS model. Our findings pave the way to identifying novel therapeutic targets and potential treatments for ALS.

From ACEs to early relational health: Implications for clinical practice.

Children grow and develop in an environment of relationships. Safe, stable, nurturing relationships help build resilience and buffer the negative impact of adverse experiences. Promoting relational health in clinical practice shifts the focus from adverse childhood experiences (ACEs) to positive childhood experiences (PCEs). This approach evaluates a family's strengths and assets, and can be incorporated into both well-child and subspecialty care. While the optimal window for such interventions is in the prenatal period or as early as possible within the first 3 years of life, it is never too late to start. This statement describes how clinicians can bring a relational health approach to any medical encounter by understanding: what toxic stress is and how it can affect the developing brain, family relationships, and child development; how positive relationships, experiences, and behaviours can help buffer such effects and build resilience; observable signs of relational health and risk in parent-child interactions; the attributes of trustful, therapeutic relationships with families; and how to optimize these benefits through conversation and clinical practice.

Des expériences négatives de l'enfance à la santé relationnelle précoce : les conséquences pour la pratique clinique.

Les enfants grandissent et se développent dans un environnement de relations. Des relations sécuritaires, stables et bienveillantes contribuent à consolider la résilience et à atténuer les répercussions des expériences négatives. La promotion de la santé relationnelle en pratique clinique recentre l'attention accordée aux expériences négatives de l'enfance sur les expériences positives de l'enfance. Cette approche, qui évalue les forces et les atouts d'une famille, peut être intégrée à la fois aux rendez-vous réguliers de l'enfant en santé et aux soins surspécialisés. Il est optimal de réaliser de telles interventions pendant la période prénatale ou le plus rapidement possible avant l'âge de trois ans, mais il n'est jamais trop tard pour les entreprendre. Le présent document de principes décrit comment les cliniciens peuvent adopter une approche de santé relationnelle lors de chacune de leurs rencontres médicales s'ils comprennent ce qu'est le stress toxique et ses effets sur le cerveau en développement, les relations familiales et le développement de l'enfant; à quel point les relations, expériences et comportements positifs peuvent en atténuer les effets et renforcer la résilience; quels sont les signes observables de la santé relationnelle et des risques relationnels dans les interactions entre les parents et l'enfant; quelles sont les caractéristiques de relations thérapeutiques de confiance avec les familles et comment en optimiser les avantages par les échanges et la pratique clinique.

Evaluation of Digitalisation in Healthcare and the Quantification of the "Unmeasurable".

Evaluating healthcare digitalisation, where technology implementation and adoption transforms existing socio-organisational processes, presents various challenges for outcome assessments. Populations are diverse, interventions are complex and evolving over time, meaningful comparisons are difficult as outcomes vary between settings, and outcomes take a long time to materialise and stabilise. Digitalisation may also have unanticipated impacts. We here discuss the limitations of evaluating the digitalisation of healthcare, and describe how qualitative and quantitative approaches can complement each other to facilitate investment and implementation decisions. In doing so, we argue how existing approaches have focused on measuring what is easily measurable and elevating poorly chosen values to inform investment decisions. Limited attention has been paid to understanding processes that are not easily measured even though these can have significant implications for contextual transferability, sustainability and scale-up of interventions. We use what is commonly known as the McNamara Fallacy to structure our discussions. We conclude with recommendations on how we envisage the development of mixed methods approaches going forward in order to address shortcomings.

The need to strengthen the evaluation of the impact of Artificial Intelligence-based decision support systems on healthcare provision.

Despite the renewed interest in Artificial Intelligence-based clinical decision support systems (AI-CDS), there is still a lack of empirical evidence supporting their effectiveness. This underscores the need for rigorous and continuous evaluation and monitoring of processes and outcomes associated with the introduction of health information technology. We illustrate how the emergence of AI-CDS has helped to bring to the fore the critical importance of evaluation principles and action regarding all health information technology applications, as these hitherto have received limited attention. Key aspects include assessment of design, implementation and adoption contexts; ensuring systems support and optimise human performance (which in turn requires understanding clinical and system logics); and ensuring that design of systems prioritises ethics, equity, effectiveness, and outcomes. Going forward, information technology strategy, implementation and assessment need to actively incorporate these dimensions. International policy makers, regulators and strategic decision makers in implementing organisations therefore need to be cognisant of these aspects and incorporate them in decision-making and in prioritising investment. In particular, the emphasis needs to be on stronger and more evidence-based evaluation surrounding system limitations and risks as well as optimisation of outcomes, whilst ensuring learning and contextual review. Otherwise, there is a risk that applications will be sub-optimally embodied in health systems with unintended consequences and without yielding intended benefits.

ePrescribing-Based Antimicrobial Stewardship Practices in an English National Health Service Hospital: Qualitative Interview Study Among Medical Prescribers and Pharmacists.

BACKGROUND: Antimicrobial resistance, the ability of microorganisms to survive antimicrobial drugs, is a public health emergency. Although electronic prescribing (ePrescribing)-based interventions designed to reduce unnecessary antimicrobial usage exist, these often do not integrate effectively with existing workflows. As a result, ePrescribing-based interventions may have limited impact in addressing antimicrobial resistance. OBJECTIVE: We sought to understand the existing ePrescribing-based antimicrobial stewardship (AMS) practices in an English hospital preceding the implementation of functionality designed to improve AMS. METHODS: We conducted 18 semistructured interviews with medical prescribers and pharmacists with varying levels of seniority exploring current AMS practices and investigating potential areas for improvement. Participants were recruited with the help of local gatekeepers. Topic guides sought to explore both formal and informal practices surrounding AMS, and challenges and opportunities for ePrescribing-based intervention. We coded audio-recorded and transcribed data with the help of the Technology, People, Organizations, and Macroenvironmental factors framework, allowing emerging themes to be added inductively. We used NVivo 12 (QSR International) to facilitate coding. RESULTS: Antimicrobial prescribing and review processes were characterized by competing priorities and uncertainty of prescribers and reviewers around prescribing decisions. For example, medical prescribers often had to face trade-offs between individual patient benefit and more diffuse population health benefits, and the rationale for prescribing decisions was not always clear. Prescribing involved a complex set of activities carried out by various health care practitioners who each only had a partial and temporary view of the whole process, and whose relationships were characterized by deeply engrained hierarchies that shaped interactions and varied across specialties. For example, newly qualified doctors and pharmacists were hesitant to change a consultant's prescribing decision when reviewing prescriptions. Multidisciplinary communication, collaboration, and coordination promoted good AMS practices by reducing uncertainty. CONCLUSIONS: Design of ePrescribing-based interventions to improve AMS needs to take into account the multitude of actors and organizational complexities involved in the prescribing and review processes. Interventions that help reduce prescriber or reviewer uncertainty and improve multidisciplinary collaboration surrounding initial antimicrobial prescribing and subsequent prescription review are most likely to be effective. Without such attention, interventions are unlikely to fulfill their goal of improving patient outcomes and combatting antimicrobial resistance.