Which computable biomedical knowledge objects will be regulated? Results of a UK workshop discussing the regulation of knowledge libraries and software as a medical device.

Introduction: To understand when knowledge objects in a computable biomedical knowledge library are likely to be subject to regulation as a medical device in the United Kingdom.

Methods: A briefing paper was circulated to a multi-disciplinary group of 25 including regulators, lawyers and others with insights into device regulation. A 1-day workshop was convened to discuss questions relating to our aim.

Modelling clinical narrative as computable knowledge: The NICE computable implementation guidance project.

Introduction: Translating narrative clinical guidelines to computable knowledge is a long-standing challenge that has seen a diverse range of approaches. The UK National Institute for Health and Care Excellence (NICE) Content Advisory Board (CAB) aims ultimately to (1) guide clinical decision support and other software developers to increase traceability, fidelity and consistency in supporting clinical use of NICE recommendations, (2) guide local practice audit and intervention to reduce unwarranted variation, (3) provide feedback to NICE on how future recommendations should be developed.

Objectives: The first phase of work was to explore a range of technical approaches to transition NICE toward the production of natively digital content.

Artificial intelligence and clinical decision support: clinicians' perspectives on trust, trustworthiness, and liability.

Artificial intelligence (AI) could revolutionise health care, potentially improving clinician decision making and patient safety, and reducing the impact of workforce shortages. However, policymakers and regulators have concerns over whether AI and clinical decision support systems (CDSSs) are trusted by stakeholders, and indeed whether they are worthy of trust. Yet, what is meant by trust and trustworthiness is often implicit, and it may not be clear who or what is being trusted.

Insights from developing and evaluating the NHS blood choices transfusion app to support junior and middle-grade doctor decision making against guidelines.

Objectives: To: 1. Develop a CE-marked smartphone App to support doctors' concordance with transfusion guidelines in non-bleeding adult patients, emphasising informed consent and anaemia management. 2.

An overview of the National COVID-19 Chest Imaging Database: data quality and cohort analysis.

Background: The National COVID-19 Chest Imaging Database (NCCID) is a centralized database containing mainly chest X-rays and computed tomography scans from patients across the UK. The objective of the initiative is to support a better understanding of the coronavirus SARS-CoV-2 disease (COVID-19) and the development of machine learning technologies that will improve care for patients hospitalized with a severe COVID-19 infection. This article introduces the training dataset, including a snapshot analysis covering the completeness of clinical data, and availability of image data for the various use-cases (diagnosis, prognosis, longitudinal risk).

Correction: Online Guide for Electronic Health Evaluation Approaches: Systematic Scoping Review and Concept Mapping Study.

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Online Guide for Electronic Health Evaluation Approaches: Systematic Scoping Review and Concept Mapping Study.

Background: Despite the increase in use and high expectations of digital health solutions, scientific evidence about the effectiveness of electronic health (eHealth) and other aspects such as usability and accuracy is lagging behind. eHealth solutions are complex interventions, which require a wide array of evaluation approaches that are capable of answering the many different questions that arise during the consecutive study phases of eHealth development and implementation. However, evaluators seem to struggle in choosing suitable evaluation approaches in relation to a specific study phase.

Digital tools for the recruitment and retention of participants in randomised controlled trials: a systematic map.

Background: Recruiting and retaining participants in randomised controlled trials (RCTs) is challenging. Digital tools, such as social media, data mining, email or text-messaging, could improve recruitment or retention, but an overview of this research area is lacking. We aimed to systematically map the characteristics of digital recruitment and retention tools for RCTs, and the features of the comparative studies that have evaluated the effectiveness of these tools during the past 10 years.

What do senior physicians think about AI and clinical decision support systems: Quantitative and qualitative analysis of data from specialty societies.

Aims: The aim was to help physicians engage with NHS and other policymakers about the use, procurement and regulation of artificial intelligence, algorithms and clinical decision support systems (CDSS) in the NHS by identifying the professional benefits of and concerns about these systems.

Methods: We piloted a three-page survey instrument with closed and open-ended questions on SurveyMonkey, then circulated it to specialty societies via email. Both quantitative and qualitative methods were used to analyse responses.

Using digital tools in the recruitment and retention in randomised controlled trials: survey of UK Clinical Trial Units and a qualitative study.

Background: Recruitment and retention of participants in randomised controlled trials (RCTs) is a key determinant of success but is challenging. Trialists and UK Clinical Research Collaboration (UKCRC) Clinical Trials Units (CTUs) are increasingly exploring the use of digital tools to identify, recruit and retain participants. The aim of this UK National Institute for Health Research (NIHR) study was to identify what digital tools are currently used by CTUs and understand the performance characteristics required to be judged useful.

Chemotherapy effectiveness in trial-underrepresented groups with early breast cancer: A retrospective cohort study.

Background: Adjuvant chemotherapy in early stage breast cancer has been shown to reduce mortality in a large meta-analysis of over 100 randomised trials. However, these trials largely excluded patients aged 70 years and over or with higher levels of comorbidity. There is therefore uncertainty about whether the effectiveness of adjuvant chemotherapy generalises to these groups, hindering patient and clinician decision-making.

Preserving the Open Access Benefits Pioneered by the Journal of Medical Internet Research and Discouraging Fraudulent Journals.

The Journal of Medical Internet Research (JMIR) was an early pioneer of open access online publishing, and two decades later, some readers and authors may have forgotten the challenges of previous scientific publishing models. This commentary summarizes the many advantages of open access publishing for each of the main stakeholders in scientific publishing and reminds us that, like every innovation, there are disadvantages that we need to guard against, such as the problem of fraudulent journals. This paper then reviews the potential impact of some current initiatives, such as Plan S and JMIRx, concluding with some suggestions to help new open-access publishers ensure that the advantages of open access publishing outweigh the challenges.

Health Behaviour Theory in Health Informatics: Support for Positive Change.

The rising use of the Internet and information technology has made computerized interventions an attractive channel for providing advice and support for behaviour change. Health behaviour and behaviour change theories are a family of theories which aim to explain the mechanisms by which human behaviours change and use that knowledge to promote change. Among the best-known of these theories are the Social Learning and Social Cognitive theories, the Health Belief Model, the Theory of Reasoned Action and its successors the Theory of Planned Behaviour and the Reasoned Action Approach, and the Transtheoretical model.

Correction to: How can clinicians, specialty societies and others evaluate and improve the quality of apps for patient use?

Since the publication of this article [1] it has come to my attention that it contains an error in which the y-axis in Fig. 1 was inverted, thus incorrectly displaying a weak negative correlation rather than a weak positive one. This error was introduced as the order of the data on which Fig.

DIGITAL TECHNOLOGY: Opportunities and barriers for usage of personal health records in hospital - report from a -workshop of the Health Informatics Unit at the Royal -College of Physicians.

Personal health records (PHRs) are thought to offer benefits and are promoted by health policy makers and some healthcare systems. Evidence for usage by patients in hospital is limited.  This article reports a one-day workshop hosted by the Royal College of Physicians that considered the evidence of the value to patients and others, the challenges to adoption and use of PHRs and sought to identify the practical and research questions that need to be answered.

A review of measurement practice in studies of clinical decision support systems 1998-2017.

Objective: To assess measurement practice in clinical decision support evaluation studies.

Materials And Methods: We identified empirical studies evaluating clinical decision support systems published from 1998 to 2017. We reviewed titles, abstracts, and full paper contents for evidence of attention to measurement validity, reliability, or reuse.

Real-world evidence was feasible for estimating effectiveness of chemotherapy in breast cancer: a cohort study.

Objective: Evidence-based guidelines recommend adjuvant chemotherapy in early stage breast cancer whenever treatment benefit is considered sufficient to outweigh the associated risks. However, many groups of patients were either excluded from or underrepresented in the clinical trials that form the evidence base for this recommendation. This study aims to determine whether using administrative health care data-real world data-and econometric methods for causal analysis to provide "real world evidence" (RWE) are feasible methods for addressing this gap.

Evaluation of stakeholder views on peer review of NIHR applications for funding: a qualitative study.

Objectives: Innovations resulting from research have both national and global impact, so selecting the most promising research studies to fund is crucial. Peer review of research funding applications is part of the selection process, and requires considerable resources. This study aimed to elicit stakeholder opinions about which factors contribute to and influence effective peer review of funding applications to the UK National Institute for Health Research (NIHR), and to identify possible minor improvements to current processes and any major changes or potential innovations to achieve a more efficient peer review process.

Influence of external peer reviewer scores for funding applications on funding board decisions: a retrospective analysis of 1561 reviews.

Objectives: To evaluate the influence of external peer reviewer scores on the National Institute for Health Research (NIHR) research funding board decisions by the number of reviewers and type of reviewer expertise.

Design: Retrospective analysis of external peer review scores for shortlisted full applications for funding (280 funding applications, 1236 individual reviewers, 1561 review scores).

Setting: Four applied health research funding programmes of NIHR, UK.

How can clinicians, specialty societies and others evaluate and improve the quality of apps for patient use?

Background: Health-related apps have great potential to enhance health and prevent disease globally, but their quality currently varies too much for clinicians to feel confident about recommending them to patients. The major quality concerns are dubious app content, loss of privacy associated with widespread sharing of the patient data they capture, inaccurate advice or risk estimates and the paucity of impact studies. This may explain why current evidence about app use by people with health-related conditions is scanty and inconsistent.

Independent validation of the PREDICT breast cancer prognosis prediction tool in 45,789 patients using Scottish Cancer Registry data.

Background: PREDICT is a widely used online prognostication and treatment benefit tool for patients with early stage breast cancer. The aim of this study was to conduct an independent validation exercise of the most up-to-date version of the PREDICT algorithm (version 2) using real-world outcomes from the Scottish population of women with breast cancer.

Methods: Patient data were obtained for all Scottish Cancer Registry (SCR) records with a diagnosis of primary invasive breast cancer diagnosed in the period between January 2001 and December 2015.