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Neonatal mortality remains disproportionately high in sub-Saharan Africa partly due to insufficient numbers of adequately trained and skilled front-line health workers. Opportunities for improving neonatal care may result from upskilling frontline health workers using innovative technological approaches. This practice paper describes the key steps involved in the design, development and implementation of an innovative smartphone-based training application using an agile, human-centred design approach. The Life-saving Instruction for Emergencies (LIFE) app is a three-dimension (3D) scenario-based mobile app for smartphones and is free to download. Two clinical modules are currently included with further scenarios planned. Whilst the focus of the practice paper is on the lessons learned during the design and development process, we also share key learning related to project management and sustainability plans, which we hope will help researchers working on similar projects.

In this paper, we describe techniques for predictive modeling of human-computer interaction (HCI) and discuss how they could be used in the development and evaluation of user interfaces for digital health systems such as electronic health record systems. Predictive HCI modeling has the potential to improve the generalizability of usability evaluations of digital health interventions beyond specific contexts, especially when integrated with models of distributed cognition and higher-level sociotechnical frameworks. Evidence generated from building and testing HCI models of the user interface (UI) components for different types of digital health interventions could be valuable for informing evidence-based UI design guidelines to support the development of safer and more effective UIs for digital health interventions.

Background Although smartphone-based emergency care training is more affordable than traditional avenues of training, it is still in its infancy, remains poorly implemented, and its current implementation modes tend to be invariant to the evolving learning needs of the intended users. In resource-limited settings, the use of such platforms coupled with gamified approaches remains largely unexplored, despite the lack of traditional training opportunities, and high mortality rates in these settings. Objective The primary aim of this randomized experiment is to determine the effectiveness of offering adaptive versus standard feedback, on the learning gains of clinicians, through the use of a smartphone-based game that assessed their management of a simulated medical emergency. A secondary aim is to examine the effects of learner characteristics and learning spacing with repeated use of the game on the secondary outcome of individualized normalized learning gain. Methods The experiment is aimed at clinicians who provide bedside neonatal care in low-income settings. Data were captured through an Android app installed on the study participants’ personal phones. The intervention, which was based on successful attempts at a learning task, included adaptive feedback provided within the app to the experimental arm, whereas the control arm received standardized feedback. The primary end point was completion of the second learning session. Of the 572 participants enrolled between February 2019 and July 2019, 247 (43.2%) reached the primary end point. The primary outcome was standardized relative change in learning gains between the study arms as measured by the Morris G effect size. The secondary outcomes were the participants individualized normalized learning gains. Results The effect of adaptive feedback on care providers’ learning gain was found to be g=0.09 (95% CI −0.31 to 0.46; P=.47). In exploratory analysis, using normalized learning gains, when subject-treatment interaction and differential time effect was controlled for, this effect increased significantly to 0.644 (95% CI 0.35 to 0.94; P Conclusions There is a considerable learning gain between the first two rounds of learning with both forms of feedback and a small added benefit of adaptive feedback after controlling for learner differences. We suggest that linking the adaptive feedback provided to care providers to how they space their repeat learning session(s) may yield higher learning gains. Future work might explore in more depth the feedback content, in particular whether or not explanatory feedback (why answers were wrong) enhances learning more than reflective feedback (information about what the right answers are). Trial Registration Pan African Clinical Trial Registry (PACTR) 201901783811130; https://pactr.samrc.ac.za/TrialDisplay.aspx?TrialID=5836 International Registered Report Identifier (IRRID) RR2-10.2196/13034

Summary Objective: The International Medical Informatics Association (IMIA) Open Source Working Group (OSWG) initiated a group discussion to discuss current privacy and security issues in the open data movement in the healthcare domain from the perspective of the OSWG membership. Methods: Working group members independently reviewed the recent academic and grey literature and sampled a number of current large-scale open data projects to inform the working group discussion. Results: This paper presents an overview of open data repositories and a series of short case reports to highlight relevant issues present in the recent literature concerning the adoption of open approaches to sharing healthcare datasets. Important themes that emerged included data standardisation, the inter-connected nature of the open source and open data movements, and how publishing open data can impact on the ethics, security, and privacy of informatics projects. Conclusions: The open data and open source movements in healthcare share many common philosophies and approaches including developing international collaborations across multiple organisations and domains of expertise. Both movements aim to reduce the costs of advancing scientific research and improving healthcare provision for people around the world by adopting open intellectual property licence agreements and codes of practice. Implications of the increased adoption of open data in healthcare include the need to balance the security and privacy challenges of opening data sources with the potential benefits of open data for improving research and healthcare delivery.

Summary Objectives : Artificial Intelligence (AI) offers significant potential for improving healthcare. This paper discusses how an “open science” approach to AI tool development, data sharing, education, and research can support the clinical adoption of AI systems. Method : In response to the call for participation for the 2019 International Medical Informatics Association (IMIA) Yearbook theme issue on AI in healthcare, the IMIA Open Source Working Group conducted a rapid review of recent literature relating to open science and AI in healthcare and discussed how an open science approach could help overcome concerns about the adoption of new AI technology in healthcare settings. Results : The recent literature reveals that open science approaches to AI system development are well established. The ecosystem of software development, data sharing, education, and research in the AI community has, in general, adopted an open science ethos that has driven much of the recent innovation and adoption of new AI techniques. However, within the healthcare domain, adoption may be inhibited by the use of “black-box” AI systems, where only the inputs and outputs of those systems are understood, and clinical effectiveness and implementation studies are missing. Conclusions : As AI-based data analysis and clinical decision support systems begin to be implemented in healthcare systems around the world, further openness of clinical effectiveness and mechanisms of action may be required by safety-conscious healthcare policy-makers to ensure they are clinically effective in real world use.

Brine disposal is a major challenge facing the desalination industry. Discharged brines pollute the oceans and aquifers. Here is it proposed to reduce the volume of brines by means of evaporative coolers in seawater greenhouses, thus enabling the cultivation of high-value crops and production of sea salt. Unlike in typical greenhouses, only natural wind is used for ventilation, without electric fans. We present a model to predict the water evaporation, salt production, internal temperature and humidity according to ambient conditions. Predictions are presented for three case studies: (a) the Horn of Africa (Berbera) where a seawater desalination plant will be coupled to salt production; (b) Iran (Ahwaz) for management of hypersaline water from the Gotvand dam; (c) Gujarat (Ahmedabad) where natural seawater is fed to the cooling process, enhancing salt production in solar salt works. Water evaporation per face area of evaporator pad is predicted in the range 33 to 83 m3/m2·yr, and salt production up to 5.8 tonnes/m2·yr. Temperature is lowest close to the evaporator pad, increasing downwind, such that the cooling effect mostly dissipates within 15 m of the cooling pad. Depending on location, peak temperatures reduce by 8–16 °C at the hottest time of year.

Objectives: The main objectives of the study were to establish the clinical effectiveness and cost-effectiveness of augmentation of clozapine medication with a second antipsychotic, amisulpride, for the management of treatment-resistant schizophrenia.Design: The study was a multicentre, double-blind, individually randomised, placebo-controlled trial with follow-up at 12 weeks.Settings: The study was set in NHS multidisciplinary teams in adult psychiatry.Participants: Eligible participants were people aged 18–65 years with treatment-resistant schizophrenia unresponsive, at a criterion level of persistent symptom severity and impaired social function, to an adequate trial of clozapine monotherapy.Interventions: Interventions comprised clozapine augmentation over 12 weeks with amisulpride or placebo. Participants received 400 mg of amisulpride or two matching placebo capsules for the first 4 weeks, after which there was a clinical option to titrate the dosage of amisulpride up to 800 mg or four matching placebo capsules for the remaining 8 weeks.Main outcome measures: The primary outcome measure was the proportion of ‘responders’, using a criterion response threshold of a 20% reduction in total score on the Positive and Negative Syndrome Scale.Results: A total of 68 participants were randomised. Compared with the participants assigned to placebo, those receiving amisulpride had a greater chance of being a responder by the 12-week follow-up (odds ratio 1.17, 95% confidence interval 0.40 to 3.42) and a greater improvement in negative symptoms, although neither finding had been present at 6-week follow-up and neither was statistically significant. Amisulpride was associated with a greater side effect burden, including cardiac side effects. Economic analyses indicated that amisulpride augmentation has the potential to be cost-effective in the short term [net saving of between £329 and £2011; no difference in quality-adjusted life-years (QALYs)] and possibly in the longer term.Limitations: The trial under-recruited and, therefore, the power of statistical analysis to detect significant differences between the active and placebo groups was limited. The economic analyses indicated high uncertainty because of the short duration and relatively small number of participants.Conclusions: The risk–benefit of amisulpride augmentation of clozapine for schizophrenia that has shown an insufficient response to a trial of clozapine monotherapy is worthy of further investigation in larger studies. The size and extent of the side effect burden identified for the amisulpride–clozapine combination may partly reflect the comprehensive assessment of side effects in this study. The design of future trials of such a treatment strategy should take into account that a clinical response may be not be evident within the 4- to 6-week follow-up period usually considered adequate in studies of antipsychotic treatment of acute psychotic episodes. Economic evaluation indicated the need for larger, longer-term studies to address uncertainty about the extent of savings because of amisulpride and impact on QALYs. The extent and nature of the side effect burden identified for the amisulpride–clozapine combination has implications for the nature and frequency of safety and tolerability monitoring of clozapine augmentation with a second antipsychotic in both clinical and research settings.

Bipolar disorder is a complex, recurrent, and severe mental illness that has an onset typically between 13 and 30 years of age and a lifetime prevalence of 1.4%.1 It is characterised by episodes of mania or hypomania with elation, overactivity, and disinhibited behaviour, as well as episodes of depression with profound loss of interest and motivation, often with milder depressed mood in between episodes. Bipolar disorder is associated with an increased risk of suicide and physical illness, such as ischaemic heart disease, diabetes, chronic obstructive airways disease, pneumonia, and unintentional injury.2 Around two thirds of people with bipolar disorder also experience another mental disorder, usually anxiety disorders, substance misuse disorders, or impulse control disorders.1 The risk of recurrence in the year after a mood episode is especially high (50% in one year and >70% at four years) compared with other psychiatric disorders,3 and this has important implications for the long term management of the disorder. This article summarises the most recent recommendations from the National Institute for Health and Care Excellence (NICE) on assessing and managing bipolar disorder in adults, children, and young people.4 NICE recommendations are based on systematic reviews of the best available evidence and explicit consideration of cost effectiveness. When minimal evidence is available, recommendations are based on the Guideline Development Group’s experience and opinion of what constitutes good practice. Evidence levels for the recommendations are given in italic in square brackets. ### Care for adults, children, and young people across all phases of bipolar disorder