Publications
131 results found
Milne-Ives M, Lam C, Rehman N, et al., 2021, Distributed ledger infrastructure to verify adverse event reporting (DeLIVER): proposal for a proof-of-concept study, JMIR Research Protocols, Vol: 10, ISSN: 1929-0748
Background: Adverse drug event reporting is critical for ensuring patient safety; however, numbers of reports have been declining. There is a need for a more user-friendly reporting system and for a means of verifying reports that have been filed. Objectives: This project has two main objectives: 1) to identify the perceived benefits and barriers in the current reporting of adverse events by patients and healthcare providers and 2) to develop a distributed ledger infrastructure and user interface to collect and collate adverse event reports to create a comprehensive and interoperable database.Methods: A review of the literature will be conducted to identify the strengths and limitations of the current UK adverse event reporting system (the Yellow Card System). If insufficient information is found in this review, a survey will be created to collect data from system users. The results of these investigations will be incorporated into the development of a mobile and web app for adverse event reporting. A digital infrastructure will be built using distributed ledger technology to provide a means of linking reports with existing pharmaceutical tracking systems. Results: The key outputs of this project will be the development of a digital infrastructure including the backend distributed ledger system and the app-based user interface.Conclusions: This infrastructure is expected to improve the accuracy and efficiency of adverse event reporting systems by enabling the monitoring of specific medicines or medical devices over their life course while protecting patients’ personal health data.
Lam C, Meinert E, Yang A, et al., 2021, Comparison between centralized and decentralized supply chains of autologous chimeric antigen receptor T-cell therapies: a UK case study based on discrete event simulation, CYTOTHERAPY, Vol: 23, Pages: 433-451, ISSN: 1465-3249
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- Citations: 12
Milne-Ives M, Selby E, Inkster B, et al., 2021, Artificially intelligent mobile apps for mental health: A scoping review of randomised controlled trials and cohort studies (Preprint)
<sec> <title>BACKGROUND</title> <p>Mental health conditions can have significant negative impacts on wellbeing and healthcare systems. Despite their high prevalence worldwide, there is still insufficient recognition and accessible treatments. Many mobile apps are available to the general population that aim to support mental health needs; however, there is limited evidence of their effectiveness. Mobile apps for mental health are beginning to incorporate artificial intelligence and there is a need for an overview of the state of the literature on these apps.</p> </sec> <sec> <title>OBJECTIVE</title> <p>The purpose of this scoping review is to provide an overview of the current research landscape and knowledge gaps regarding the use of artificial intelligence in mobile health apps for mental health.</p> </sec> <sec> <title>METHODS</title> <p>The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) and Population, Intervention, Comparator, Outcome, and Study (PICOS) frameworks were used to structure the review and the search. PubMed was systematically searched for randomised controlled trials and cohort studies published in English since 2014 that evaluate artificial intelligence-enabled mobile apps for mental health support. Two reviewers collaboratively screened references, selected studies for inclusion based on the eligibility criteria, and extracted the data, which were synthesised in a descriptive analysis.</p> </sec> <sec> <title>RESULTS</title> <p>1,022 studies were identifi
Surodina S, Lam C, Grbich S, et al., 2021, Authors’ Response to Peer Reviews of “Machine Learning for Risk Group Identification and User Data Collection in a Herpes Simplex Virus Patient Registry: Algorithm Development and Validation Study” (Preprint)
<sec> <title>UNSTRUCTURED</title> <p>This is author responses.</p> </sec>
Meinert E, Eerens J, Banks C, et al., 2021, Exploring the Cost of eLearning in Health Professions Education: Scoping Review, JMIR MEDICAL EDUCATION, Vol: 7, ISSN: 2369-3762
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- Citations: 8
Milne-Ives M, Lam C, Rehman N, et al., 2021, Distributed Ledger Infrastructure to Verify Adverse Event Reporting (DeLIVER): Proposal for a Proof-of-Concept Study (Preprint)
<sec> <title>BACKGROUND</title> <p>Adverse drug event reporting is critical for ensuring patient safety; however, numbers of reports have been declining. There is a need for a more user-friendly reporting system and for a means of verifying reports that have been filed.</p> </sec> <sec> <title>OBJECTIVE</title> <p>This project has 2 main objectives: (1) to identify the perceived benefits and barriers in the current reporting of adverse events by patients and health care providers and (2) to develop a distributed ledger infrastructure and user interface to collect and collate adverse event reports to create a comprehensive and interoperable database.</p> </sec> <sec> <title>METHODS</title> <p>A review of the literature will be conducted to identify the strengths and limitations of the current UK adverse event reporting system (the Yellow Card System). If insufficient information is found in this review, a survey will be created to collect data from system users. The results of these investigations will be incorporated into the development of a mobile and web app for adverse event reporting. A digital infrastructure will be built using distributed ledger technology to provide a means of linking reports with existing pharmaceutical tracking systems.</p> </sec> <sec> <title>RESULTS</title> <p>The key outputs of this project will be the development of a digital infrastructure, including a backend distributed ledger system and an app-based user interface.</p> </sec> <sec>
Milne-Ives M, Leyden J, Maramba I, et al., 2021, The Potential Impacts of a Digital Preoperative Assessment Service on Appointments, Travel-Related Carbon Dioxide Emissions, and User Experience: Case Study (Preprint)
<sec> <title>BACKGROUND</title> <p>The National Health Service (NHS) cannot keep up with the demand for operations and procedures. Preoperative assessments can be conducted on the internet to improve efficiency and reduce wait times for operations. MyPreOp is a cloud-based platform where patients can complete preoperative questionnaires. These are reviewed by a nurse who determines whether they need a subsequent face-to-face appointment.</p> </sec> <sec> <title>OBJECTIVE</title> <p>The primary objective of this study is to describe the potential impact of MyPreOp (Ultramed Ltd) on the number of face-to-face appointments. The secondary objectives are to examine the time spent on preoperative assessments completed using MyPreOp in NHS Trusts and user ratings of usability and acceptability.</p> </sec> <sec> <title>METHODS</title> <p>The study design was a case study service evaluation. Data were collected using the MyPreOp system from 2 NHS Trusts (Guy’s and St Thomas’ and Royal United Hospitals Bath) and the private BMI Bath Clinic during the 4-month period from September to December 2020. Participants were adults of any age and health status at the participating hospitals who used MyPreOp to complete a preoperative assessment before a scheduled surgery. The primary outcome was the number of face-to-face appointments avoided by patients who used MyPreOp. The investigated secondary outcomes included the length of time spent by nurses completing preoperative assessments, associated travel-related carbon dioxide emissions compared with standard care, and quantitative user feedback. User feedback was assessed at all 3 sites; however, the other outcomes
Milne-Ives M, Homer S, Andrade J, et al., 2021, Associations between Behaviour Change Techniques and engagement with mobile health apps: systematic review protocol, JMIR Research Protocols, Vol: 23, ISSN: 1929-0748
Background: The use of digitally-enabled care and the emphasis on self-management of health is growing. Mobile health apps provide a promising means of supporting health behaviour change; however, engagement with them is often poor and evidence of their impact on health outcomes is lacking. As engagement is a key prerequisite to health behaviour change, it is essential to understand how engagement with mobile health apps and their target health behaviours can be better supported. Despite an increasing recognition of the importance of engagement in the literature, there is still a lack of understanding of how different components of engagement are associated with specific techniques that aim to change behaviours. Objective: The purpose of this systematic review protocol is to provide a synthesis of the associations between various Behaviour Change Techniques (BCTs) and the different components of engagement (and their outcome measures) with mobile health apps.Methods: The review protocol was structured using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P) and the Population, Intervention, Comparator, and Outcome (PICO) frameworks. Seven databases will be systematically searched: PubMed, Embase, Cumulative Index to Nursing and Allied Health Literature (CINAHL), APA PsycInfo, ScienceDirect, Cochrane Library and Web of Science. Title and abstract screening, full-text review, and data extraction will be conducted by two independent reviewers. Data will be extracted into a predetermined form, and any disagreements in screening or data extraction will be discussed, with a third reviewer consulted if consensus cannot be reached. Risk of bias will be assessed using the Cochrane Collaboration Risk of Bias 2 and ROBINS-I tools and descriptive and thematic analyses will be used to summarise the relationships between BCTs and the different components of engagement.Results: The systematic review has not been started. It is expected to b
Milne-Ives M, Lam C, Meinert E, 2021, Digital Technologies for Monitoring and Improving Treatment Adherence in Children and Adolescents With Asthma: Scoping Review of Randomized Controlled Trials (Preprint)
<sec> <title>BACKGROUND</title> <p>Inadequate pediatric asthma care has resulted in potentially avoidable unplanned hospital admissions and morbidity. A wide variety of digital technologies have been developed to monitor and support treatment adherence in children and adolescents with asthma. However, existing reviews need to be updated and expanded to provide an overview of the current state of research on these technologies and how they are being integrated into existing health care services and care pathways.</p> </sec> <sec> <title>OBJECTIVE</title> <p>This study aims to provide an overview of the current research landscape and knowledge gaps regarding the use of digital technologies to support the care of children and adolescents with asthma.</p> </sec> <sec> <title>METHODS</title> <p>This study was structured according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) and Population, Intervention, Comparator, Outcome, and Study frameworks. Five databases (PubMed, the Cochrane Central Register of Controlled Trials, Web of Science, Embase, and PsycINFO) were systematically searched for studies published in English from 2014 onward. Two reviewers independently screened the references and selected studies for inclusion based on the eligibility criteria. Data were systematically extracted per research question, which were synthesized in a descriptive analysis.</p> </sec> <sec> <title>RESULTS</title> <p>A wide variety of study characteristics, including the number and ag
Milne-Ives M, Meinert E, 2021, Digital technologies for monitoring and improving treatment adherence in children and adolescents with asthma: A scoping review of randomised controlled trials
<jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>Inadequate paediatric asthma care has resulted in potentially avoidable unplanned hospital admissions and morbidity. A wide variety of digital technologies have been developed to help monitor and support treatment adherence for children and adolescents with asthma. However, existing reviews need to be updated and expanded to provide an overview of the current state of research around these technologies and how they are being integrated into existing healthcare services and care pathways.</jats:p></jats:sec><jats:sec><jats:title>Objective</jats:title><jats:p>The purpose of this scoping review is to provide an overview of the current research landscape and knowledge gaps regarding the use of digital technologies to support the care of children and adolescents with asthma.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>The review was structured according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) and Population, Intervention, Comparator, Outcome, and Study (PICOS) frameworks. Five databases (PubMed, the Cochrane Central Register of Controlled Trials (CENTRAL), Web of Science, EMBASE, and PsycINFO) were systematically searched for studies published in English from 2014 on. One reviewer screened references, selected studies for inclusion based on the eligibility criteria, and extracted the data, which were synthesised in a descriptive analysis.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>A wide variety in study characteristics - including the number and age of participants, study duration, and type of digital intervention - was identified. There was mixed evidence for the effectiveness of the interventions; 6 of the 9 studies
de Pennington N, Mole G, Lim E, et al., 2021, Safety and Acceptability of a Natural Language Artificial Intelligence Assistant to Deliver Clinical Follow-up to Cataract Surgery Patients: Proposal (Preprint)
<sec> <title>BACKGROUND</title> <p>Due to an aging population, the demand for many services is exceeding the capacity of the clinical workforce. As a result, staff are facing a crisis of burnout from being pressured to deliver high-volume workloads, driving increasing costs for providers. Artificial intelligence (AI), in the form of conversational agents, presents a possible opportunity to enable efficiency in the delivery of care.</p> </sec> <sec> <title>OBJECTIVE</title> <p>This study aims to evaluate the effectiveness, usability, and acceptability of Dora agent: Ufonia’s autonomous voice conversational agent, an AI-enabled autonomous telemedicine call for the detection of postoperative cataract surgery patients who require further assessment. The objectives of this study are to establish Dora’s efficacy in comparison with an expert clinician, determine baseline sensitivity and specificity for the detection of true complications, evaluate patient acceptability, collect evidence for cost-effectiveness, and capture data to support further development and evaluation.</p> </sec> <sec> <title>METHODS</title> <p>Using an implementation science construct, the interdisciplinary study will be a mixed methods phase 1 pilot establishing interobserver reliability of the system, usability, and acceptability. This will be done using the following scales and frameworks: the system usability scale; assessment of Health Information Technology Interventions in Evidence-Based Medicine Evaluation Framework; the telehealth usability questionnaire; and the Non-Adoption, Abandonment, and Challenges to the Scale-up, Spread and Suitability framework.</p>
Meinert E, Eerens J, Banks C, et al., 2021, Exploring the cost of eLearning within the field of health professions education: Scoping review, JMIR Medical Education, Vol: 7, ISSN: 2369-3762
Background:Existing research on the costs associated with the design and deployment of eLearning in health professions education is limited. The relative costs of these learning platforms to those of face-to-face learning are also not well understood. The lack of predefined costing models used for eLearning cost data capture has made it difficult to complete cost evaluation.Objective:The key aim of this scoping review was to explore the state of evidence concerning cost capture within eLearning in health professions education. The review explores the available data to define cost calculations related to eLearning.Methods:The scoping review was performed using a search strategy with Medical Subject Heading terms and related keywords centered on eLearning and cost calculation with a population scope of health professionals in all countries. The search was limited to articles published in English. No restriction was placed on literature publication date.Results:In total, 7344 articles were returned from the original search of the literature. Of these, 232 were relevant to associated keywords or abstract references following screening. Full-text review resulted in 168 studies being excluded. Of these, 61 studies were excluded because they were unrelated to eLearning and focused on general education. In addition, 103 studies were excluded because of lack of detailed information regarding costs; these studies referred to cost in ways either indicating cost favorability or unfavorability, but without data to support findings. Finally, 4 studies were excluded because of limited cost data that were insufficient for analysis. In total, 42 studies provided data and analysis of the impact of cost and value in health professions education. The most common data source was total cost of training (n=29). Other sources included cost per learner, referring to the cost for individual students (n=13). The population most frequently cited was medical students (n=15), although 12 article
Milne-Ives M, Swancutt D, Burns L, et al., 2020, The Effectiveness and Usability of Online, Group-Based Interventions for People With Severe Obesity: Protocol for a Systematic Review (Preprint)
<sec> <title>BACKGROUND</title> <p>Globally, obesity is a growing crisis. Despite obesity being preventable, over a quarter of the UK adult population is currently considered clinically obese (typically body mass index ≥35 kg/m<sup>2</sup>). Access to treatment for people with severe obesity is limited by long wait times and local availability. Online and group-based interventions provide means of increasing the accessibility of obesity prevention and treatment services. However, there has been no prior review of the effectiveness of group-based interventions delivered online for people with severe obesity.</p> </sec> <sec> <title>OBJECTIVE</title> <p>The purpose of this systematic review protocol is to provide an evaluation of the effectiveness and usability of different types of online, group-based interventions for people with severe obesity.</p> </sec> <sec> <title>METHODS</title> <p>The Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P) and the Population, Intervention, Comparator, Outcome, and Study (PICOS) frameworks were used to structure this review. The review will systematically search 7 databases: MEDLINE, Embase, the Cumulative Index of Nursing and Allied Health Literature, APA PsycNet, Web of Science, CENTRAL, and the ProQuest Dissertations and Theses databases. Two authors (MM-I and LB) will independently screen the titles and abstracts of identified articles, select studies for inclusion based on the eligibility criteria, and extract data into a standardized form. Any disagreements will be discussed and resolved by a third reviewer (EM) if necessary. Risk of bias will be asse
Maramba ID, Jones R, Austin D, et al., 2020, The Role of Health Kiosks: Scoping Review (Preprint)
<sec> <title>BACKGROUND</title> <p>Health kiosks are publicly accessible computing devices that provide access to services, including health information provision, clinical measurement collection, patient self–check-in, telemonitoring, and teleconsultation. Although the increase in internet access and ownership of smart personal devices could make kiosks redundant, recent reports have predicted that the market will continue to grow.</p> </sec> <sec> <title>OBJECTIVE</title> <p>We seek to clarify the current and future roles of health kiosks by investigating the settings, roles, and clinical domains in which kiosks are used; whether usability evaluations of health kiosks are being reported, and if so, what methods are being used; and what the barriers and facilitators are for the deployment of kiosks.</p> </sec> <sec> <title>METHODS</title> <p>We conducted a scoping review using a bibliographic search of Google Scholar, PubMed, and Web of Science databases for studies and other publications between January 2009 and June 2020. Eligible papers described the implementation as primary studies, systematic reviews, or news and feature articles. Additional reports were obtained by manual searching and querying the key informants. For each article, we abstracted settings, purposes, health domains, whether the kiosk was opportunistic or integrated with a clinical pathway, and whether the kiosk included usability testing. We then summarized the data in frequency tables.</p> </sec> <sec> <title>RESULTS</title> <p>A total of 141 articles were
Lam C, van Velthoven M, Meinert E, 2020, Developing a blockchain-based supply chain system for advanced therapies: study protocol, JMIR Research Protocols, Vol: 9, Pages: 1-6, ISSN: 1929-0748
Advanced therapies, including cell and gene therapies, have shown therapeutic promise in curing life-threatening diseases such as leukaemia and lymphoma. However, they can be complicated and expensive to deliver due to their sensitivity to environment, troublesome tissue, cell, or genetic material sourcing and complicated regulatory requirements.
Surodina S, Lam C, Grbich S, et al., 2020, Machine Learning for Risk Group Identification and User Data Collection in a Herpes Simplex Virus Patient Registry: Algorithm Development and Validation Study (Preprint)
<sec> <title>BACKGROUND</title> <p>Researching people with herpes simplex virus (HSV) is challenging because of poor data quality, low user engagement, and concerns around stigma and anonymity.</p> </sec> <sec> <title>OBJECTIVE</title> <p>This project aimed to improve data collection for a real-world HSV registry by identifying predictors of HSV infection and selecting a limited number of relevant questions to ask new registry users to determine their level of HSV infection risk.</p> </sec> <sec> <title>METHODS</title> <p>The US National Health and Nutrition Examination Survey (NHANES, 2015-2016) database includes the confirmed HSV type 1 and type 2 (HSV-1 and HSV-2, respectively) status of American participants (14-49 years) and a wealth of demographic and health-related data. The questionnaires and data sets from this survey were used to form two data sets: one for HSV-1 and one for HSV-2. These data sets were used to train and test a model that used a random forest algorithm (devised using Python) to minimize the number of anonymous lifestyle-based questions needed to identify risk groups for HSV.</p> </sec> <sec> <title>RESULTS</title> <p>The model selected a reduced number of questions from the NHANES questionnaire that predicted HSV infection risk with high accuracy scores of 0.91 and 0.96 and high recall scores of 0.88 and 0.98 for the HSV-1 and HSV-2 data sets, respectively. The number of questions was reduced from 150 to an average of 40, depending on age and gender. The model, therefore, provided high predictability of risk of
Milne-Ives M, de Cock C, Lim E, et al., 2020, The effectiveness of artificial intelligence conversational agents in healthcare: a systematic review, Journal of Medical Internet Research, Vol: 22, ISSN: 1438-8871
Background: High demand on healthcare services and the growing capability of artificial intelligence has led to the development of conversational agents designed to support a variety of health-related activities - including behaviour change, treatment support, health monitoring, training, triage, and screening support. Automation of these tasks could free clinicians to focus on more complex work and increase accessibility to healthcare services for the general public. An overarching assessment of the acceptability, usability, and effectiveness of these agents in healthcare is needed to collate the evidence so that future development can target areas for improvement and potential for sustainable adoption. Objective: This systematic review aimed to assess the effectiveness and usability of conversational agents in healthcare and identify the elements that users like and dislike, to inform future research and development of these agents. Methods: PubMed, Medline (Ovid), EMBASE, CINAHL, Web of Science, and ACM Digital Library were systematically searched for articles published since 2008 that evaluated unconstrained natural language processing conversational agents used in healthcare. Endnote (version X9; Clarivate Analytics) reference management software was used for initial screening, then full-text screening was conducted by one reviewer. Data was extracted and risk of bias was assessed by one reviewer and validated by another. Results: A total of 31 studies were selected and included a variety of conversational agents - 14 chatbots (two of which were voice chatbots), 6 embodied conversational agents, 3 each of interactive voice response calls, virtual patients, and speech recognition screening systems, as well as one contextual question answering agent and one voice recognition triage system. Overall, the evidence reported was mostly positive or mixed. Usability and satisfaction performed well (27/30 and 26/31) and positive or mixed effectiveness was found in three
Milne-Ives M, Lam C, van Velthoven M, et al., 2020, The impact of Brexit on the UK pharmaceutical supply chain: a scoping review protocol, JMIR Research Protocols, Vol: 9, Pages: 1-6, ISSN: 1929-0748
The continuing uncertainty around Brexit has caused concern in the pharmaceutical industry and among healthcare professionals and patients. The exact consequences of Brexit on the UK pharmaceutical supply chain will depend on whether a deal is reached and what it entails, but it is likely to be affected by the withdrawal of the UK from the EU. Regulatory issues and delays in supply have the potential to seriously negatively affect the ability of UK residents to receive an adequate and timely supply of necessary medicines.
Milne-Ives M, Lam C, Van Velthoven M, et al., 2020, Mobile fitness and weight management apps: an evaluation protocol, JMIR Research Protocols, Vol: 9, Pages: 1-5, ISSN: 1929-0748
Obesity is a large contributing factor for many non-communicable diseases and is a growing problem worldwide. Many mobile apps have been developed to help users improve their fitness and weight management behaviours. However, the speed at which apps are created and updated means that it is important to periodically assess their quality.
Im C, Meinert E, 2020, What are the implications of standards to ensure safe use of dermatological health apps? (Preprint)
<sec> <title>BACKGROUND</title> <p>Dermatological health applications can address a range of pathologies from melanoma to eczema and have the potential to significantly impact the health of the user. This paper details a systematic review of standards addressing dermatological health apps and their implication on the safe use of such apps.</p> </sec> <sec> <title>OBJECTIVE</title> <p>To survey the literature to ascertain the state of evidence to address this review’s primary research question: “What are the implications of standards to ensure safe use of dermatological health apps?”</p> </sec> <sec> <title>METHODS</title> <p>Six databases were systematically searched for records relevant to the questions using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The Reporting Items for Practice Guidelines in Healthcare (RIGHT) checklist was used to analyse records when applicable, and when not a standardised checklist was used. Database searches identified 2193 records, of which 67 records were ultimately included for analysis.</p> </sec> <sec> <title>RESULTS</title> <p>A total of 67 records were identified, and these could be organised into 6 themes. These 6 themes included studies investigating the accuracy of apps, general standards, articles, reviews of current dermatological apps, recommendations and reviews of mobile medical apps and standards.</p> </sec> <sec> <title>CONCLUSIONS</title>
Meinert E, Rahman E, Potter A, et al., 2020, Usability of the mobile digital health ‘NoObesity’ app for families and healthcare professionals: a feasibility study, JMIR Research Protocols, Vol: 9, Pages: 1-10, ISSN: 1929-0748
Background: Almost a quarter or more than a fifth of children in the United Kingdom (UK) are overweight or obese by the time they start school. The UK Department of Health and Social Care has updated national policy for combating childhood obesity in 2018, with critical outcomes centred on sugar and caloric consumption reduction. Health Education England has developed two digital apps for families with children up to 15 and for their associated health care professionals (HCPs) to provide a digital learning resource and tool aimed at encouraging healthy lifestyles to prevent obesity.Objective: This feasibility study assesses Health Education England’s NoObesity app usability and acceptability to undertake activities to improve families’ diet and physical activity. The purpose of the study is to evaluate the app’s influence on self-efficacy and goal setting and to determine what can be learned to improve its design for future studies, should there be evidence of adoption and sustainability. Methods: The study population will include 20-40 families and their linked health care professionals. Recognising issues related to digital access associated with socioeconomic status (SES) and impact on information technology (IT) use, study recruitment will be regionally focused on a low SES area. The study will last nine-months; three months intervention period and six months follow up. The evaluation of feasibility, acceptability, and usability will be conducted using the following scales and theoretical frameworks: 1. The system usability scale; 2. The Reach Effectiveness Adoption Implementation Maintenance (RE-AIM) framework; 3. Bandura’s model of health promotion; and 4. The Nonadoption, Abandonment, and Challenges to the Scale-up, Spread, and Suitability (NASSS) framework. App use will be captured and quantitatively analysed for net use patterns (e.g. number of screens viewed, number of logins, cumulative minutes using the app, number of plans made
Surodina S, Lam C, Grbich S, et al., 2020, Requirements Engineering of a Herpes Simplex Virus Patient Registry: Alpha Phase
<jats:title>Abstract</jats:title> <jats:p><jats:bold>Background</jats:bold> Collecting data from people with herpes simplex virus is challenging because of poor data quality, low user engagement, and concerns around stigma and anonymity. This project aimed to improve data collection for a real-world HSV registry by identifying predictors of HSV infection and selecting a limited number of relevant questions to ask new registry users in order to determine the HSV infection risk group. <jats:bold>Methods</jats:bold>. The US National Health and Nutrition Examination Survey (NHANES, 2015-16) database has confirmed HSV1 and HSV2 status of American participants (14-49 years) as well as a wealth of demographic and health-related data. Two datasets – for HSV1 and HSV2 – were formed using this database, and an anonymous lifestyle-data based questionnaire with a Random Forest algorithm was devised using Python. The algorithm was optimised to reduce the number of questions and to identify risk groups for HSV. Data was split into subsets to train and test the model. <jats:bold>Results </jats:bold>The model selected a reduced number of questions from the NHANES questionnaire that predicted HSV infection risk with high accuracy scores of 0.91 and 0.96 and high recall scores of 0.88 and 0.98 for HSV1 and HSV2 datasets, respectively. The number of questions was reduced from 150 to an average of 40, depending on age and gender, that together provides high predictability of the infection <jats:bold>Conclusions</jats:bold> This machine-learning algorithm for risk identification of people infected with HSV can be used in a real-world evidence registry to collect relevant lifestyle data. A current limitation is the absence of real user data and integration with electronic medical records that would enable model learning and improvement. Future work will explore model adjustments, anonymisation options, e
de Cock C, van Velthoven M, Milne-Ives M, et al., 2020, Use of apps to promote childhood vaccination: a systematic review, JMIR mHealth and uHealth, Vol: 8, ISSN: 2291-5222
Vaccination is a critical step to reducing child mortality; however, vaccination rates have declined in many countries in recent years. This decrease has been associated with an increase in outbreaks of vaccine-preventable diseases. The potential for leveraging mobile platforms to promote vaccination coverage has been investigated in the development of numerous mobile apps. Whilst many are available for public use, there is little robust evaluation of these applications.
Milne-Ives M, de Cock C, Lim E, et al., 2020, The Effectiveness of Artificial Intelligence Conversational Agents in Health Care: Systematic Review (Preprint)
<sec> <title>BACKGROUND</title> <p>The high demand for health care services and the growing capability of artificial intelligence have led to the development of conversational agents designed to support a variety of health-related activities, including behavior change, treatment support, health monitoring, training, triage, and screening support. Automation of these tasks could free clinicians to focus on more complex work and increase the accessibility to health care services for the public. An overarching assessment of the acceptability, usability, and effectiveness of these agents in health care is needed to collate the evidence so that future development can target areas for improvement and potential for sustainable adoption.</p> </sec> <sec> <title>OBJECTIVE</title> <p>This systematic review aims to assess the effectiveness and usability of conversational agents in health care and identify the elements that users like and dislike to inform future research and development of these agents.</p> </sec> <sec> <title>METHODS</title> <p>PubMed, Medline (Ovid), EMBASE (Excerpta Medica dataBASE), CINAHL (Cumulative Index to Nursing and Allied Health Literature), Web of Science, and the Association for Computing Machinery Digital Library were systematically searched for articles published since 2008 that evaluated unconstrained natural language processing conversational agents used in health care. EndNote (version X9, Clarivate Analytics) reference management software was used for initial screening, and full-text screening was conducted by 1 reviewer. Data were extracted, and the risk of bias was assessed by one reviewer and validated by another.</p>
Meinert E, Milne-Ives M, Surodina S, et al., 2020, Agile requirements engineering and software planning for a digital health platform to engage the effects of isolation caused by social distancing: A Case study and feasibility study protocol, JMIR Public Health and Surveillance, Vol: 6, ISSN: 2369-2960
BackgroundSocial distancing measures have been put in place to reduce social interaction to slow transmission of coronavirus (COVID-19). For older people, self-isolation presents particular challenges for mental health and social relationships. As time progresses, continued social distancing could have a compounding impact on these concerns.ObjectiveThis project aims to provide a tool for older people, their families, and peers to improve their wellbeing and health during and after regulated social distancing. Firstly, we will evaluate the tool’s feasibility, acceptability, and usability to encourage positive nutrition, enhance physical activity, and enable virtual interaction during social-distancing. Secondly, we will be implementing the app to provide an online community to assist families and peer groups in maintaining contact with older people using goal setting. Anonymised data from the app will be aggregated with other real-world data sources to develop a machine-learning algorithm to improve COVID-19 patient identification and track for real-time use by health systems.MethodsDevelopment of this project is occurring at the time of publication, and therefore a case study design was selected to provide a systematic means of capturing software engineering in progress. To mitigate potential issues of non-adoption of the proposed intervention, the system was designed using the non-adoption, abandonment, scale-up, spread and sustainability (NASSS) framework. The application development framework utilised is based on Agile methods. The evaluation of the solution’s acceptability and usability shall be conducted as a feasibility study to analyse factors impacting the solution’s use, adoption and uptake.Results Making use of a pre-existing software framework for health behaviour change, a proof of concept was developed, and multi-stage application development and deployment for the solution created. Grant submissions to fund the project and study exec
Milne-Ives M, van Velthoven M, Meinert E, 2020, Mobile apps for real-world evidence in health care, Journal of the American Medical Informatics Association, Vol: 27, Pages: 976-980, ISSN: 1067-5027
The use of real-world evidence for health care research and evaluation is growing. Mobile health apps have often-overlooked potential to contribute valuable real-world data that are not captured by other sources and could provide data that are more cost-effective and generalizable than can randomized controlled trials. However, there are several challenges that must be overcome to realize the potential value of patient-used mobile health app real-world data, including data quality, motivation for long-term use, privacy and security, methods of analysis, and standardization and integration. Addressing these challenges will increase the value of data from mobile health apps to inform real-world evidence and improve patient empowerment, clinical management, disease research, and treatment development.
Lam C, Meinert E, Yang A, et al., 2020, Tackling the unique challenges of capacity planning for autologous cell therapies, Publisher: ELSEVIER SCI LTD, Pages: S148-S149, ISSN: 1465-3249
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Alturkistani A, Lam C, Foley K, et al., 2020, Massive Open Online Course (MOOC) evaluation methods: A systematic review, Journal of Medical Internet Research, Vol: 22, Pages: 1-14, ISSN: 1438-8871
Background: Massive open online courses (MOOCs) have the potential for broad education impact due to many learners undertaking these courses. Despite their reach, there is a lack of knowledge about which methods are used for evaluating these courses.Objective: This review aims to identify current MOOC evaluation methods in order to inform future study designs.Methods: We systematically searched the following databases: (1) SCOPUS; (2) Education Resources Information Center (ERIC); (3) IEEE Xplore; (4) Medline/PubMed; (5) Web of Science; (6) British Education Index and (7) Google Scholar search engine for studies from January 2008 until October 2018. Two reviewers independently screened abstracts and titles of the studies. Published studies in English that evaluated MOOCs were included. The study design of the evaluations, the underlying motivation for the evaluation studies, data collection and data analysis methods were quantitatively and qualitatively analyzed. The quality of the included studies was appraised using the Cochrane Collaboration Risk of Bias Tool for RCTs, the NIH - National Heart, Lung and Blood Institute quality assessment tool for cohort observational studies, and for “Before-After (Pre-Post) Studies With No Control Group”.Results: The initial search resulted in 3275 studies, and 33 eligible studies were included in this review. Studies mostly had a cross-sectional design evaluating one version of a MOOC. We found that studies mostly had a learner-focused, teaching-focused or platform-focused motivation to evaluate the MOOC. The most used data collection methods were surveys, learning management system data and quiz grades and the most used data analysis methods were descriptive and inferential statistics. The methods for evaluating the outcomes of these courses were diverse and unstructured. Most studies with cross-sectional design had a low-quality assessment, whereas randomized controlled trials and quasi-experimental studies receiv
Meinert E, Milne-Ives M, Surodina S, et al., 2020, Agile Requirements Engineering and Software Planning for a Digital Health Platform to Engage the Effects of Isolation Caused by Social Distancing: Case Study (Preprint)
<sec> <title>BACKGROUND</title> <p>Social distancing and shielding measures have been put in place to reduce social interaction and slow the transmission of the coronavirus disease (COVID-19). For older people, self-isolation presents particular challenges for mental health and social relationships. As time progresses, continued social distancing could have a compounding impact on these concerns.</p> </sec> <sec> <title>OBJECTIVE</title> <p>This project aims to provide a tool for older people and their families and peers to improve their well-being and health during and after regulated social distancing. First, we will evaluate the tool’s feasibility, acceptability, and usability to encourage positive nutrition, enhance physical activity, and enable virtual interaction while social distancing. Second, we will be implementing the app to provide an online community to assist families and peer groups in maintaining contact with older people using goal setting. Anonymized data from the app will be aggregated with other real-world data sources to develop a machine learning algorithm to improve the identification of patients with COVID-19 and track for real time use by health systems.</p> </sec> <sec> <title>METHODS</title> <p>Development of this project is occurring at the time of publication, and therefore, a case study design was selected to provide a systematic means of capturing software engineering in progress. The app development framework for software design was based on agile methods. The evaluation of the app’s feasibility, acceptability and usability shall be conducted using Public Health England's guidance on evaluating digital health produ
Lam C, van Velthoven M, Meinert E, 2020, Application of “Internet of Things” in cell-based therapy delivery: a systematic review protocol, JMIR Research Protocols, Vol: 9, Pages: 1-6, ISSN: 1929-0748
Internet of Things (IoT) or Industry 4.0, represents a ‘smart’ shift to more interconnected manufacturing processes where individual entities within the supply chain communicate with each other in order to achieve greater flexibility and responsiveness in manufacturing and leaner manufacturing to reduce cost of production. IoT has proven itself instrumental in driving leaner manufacturing and more efficient systems in other industries such as transportation and logistics. While cell-based therapeutic products hold the promise of transforming various diseases, the delivery of these products is complex and challenging. This review aims to understand the applicability of IoT in cell-based product supply chain and delivery.
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