Assuring safe artificial intelligence in critical ambulance service response: study protocol.

Introduction: Early recognition of out-of-hospital cardiac arrest (OHCA) by ambulance service call centre operators is important so that cardiopulmonary resuscitation can be delivered immediately, but around 25% of OHCAs are not picked up by call centre operators. An artificial intelligence (AI) system has been developed to support call centre operators in the detection of OHCA. The study aims to (1) explore ambulance service stakeholder perceptions on the safety of OHCA AI decision support in call centres, and (2) develop a clinical safety case for the OHCA AI decision-support system. Methods and analysis: The study will be undertaken within the Welsh Ambulance Service. The study is part research and part service evaluation. The research utilises a qualitative study design based on thematic analysis of interview data. The service evaluation consists of the development of a clinical safety case based on document analysis, analysis of the AI model and its development process and informal interviews with the technology developer. Conclusions: AI presents many opportunities for ambulance services, but safety assurance requirements need to be understood. The ASSIST project will continue to explore and build the body of knowledge in this area.

Research: User Interface Software Errors in Medical Devices: Study of U.S. Recall Data.

The current work assessed U.S. medical device recalls during 2012-15, with the goal of under-standing the impact and nature of user interface (UI) software errors in medical devices. Based on information from the Food and Drug Administration's public and internal recall databases, 423 (~140/year) medical device recalls were identified as resulting from UI software errors, which accounted for nearly one-half of recalls caused by software errors during the same period. A total of 499 UI software errors were identified as the root causes of medical device recalls, and a detailed classification of those errors (into 20 categories) was established. This error classification can be used by device manufacturers, end users (e.g., healthcare providers), and regulatory authorities to raise awareness of the type and impact of UI software errors. The classification also provides stakeholders with an evidence-based challenge to assess and improve the quality of UI software in medical devices.

Three laws for paperlessness.

We are familiar with paper and rarely think much about it, except that in healthcare there seems to be too much of it, and it is slow, inefficient, and so old. In contrast, paperlessness promises the future and freedom from paper's obvious limitations. We need to think clearly how to ensure paperlessness really improves healthcare, hence three simple laws: 1. Keep in sight the goal of improving healthcare. Paperlessness must be first about improving clinical processes, supporting staff and patients, not about replacing paper with new 'solutions'. 2. Only implement evidence-based change. Pursue paperlessness only where there is scientific evidence it is better for the real task. Successful paperlessness depends on user centred design and on quality implementation. 3. Plan for cultural change and moving goal posts. Culture has to change to take advantage of technology, and technology is changing at pace regardless. Paperless requires planning for monitoring, improvement, revision and, eventually, obsolescence and further innovation. Pay attention to culture, including regulation, and to developing human skills to exploit new technologies.

Interactive numerals.

Although Arabic numerals (like '2016' and '3.14') are ubiquitous, we show that in interactive computer applications they are often misleading and surprisingly unreliable. We introduce interactive numerals as a new concept and show, like Roman numerals and Arabic numerals, interactive numerals introduce another way of using and thinking about numbers. Properly understanding interactive numerals is essential for all computer applications that involve numerical data entered by users, including finance, medicine, aviation and science.

Using and choosing digital health technologies: a communications science perspective.

Purpose The purpose of this paper is to explore a non-technical overview for leaders and researchers about how to use a communications perspective to better assess, design and use digital health technologies (DHTs) to improve healthcare performance and to encourage more research into implementation and use of these technologies. Design/methodology/approach Narrative overview, showing through examples the issues and benefits of introducing DHTs for healthcare performance and the insights that communications science brings to their design and use. Findings Communications research has revealed the many ways in which people communicate in non-verbal ways, and how this can be lost or degraded in digitally mediated forms. These losses are often not recognized, can increase risks to patients and reduce staff satisfaction. Yet digital technologies also contribute to improving healthcare performance and staff morale if skillfully designed and implemented. Research limitations/implications Researchers are provided with an introduction to the limitations of the research and to how communications science can contribute to a multidisciplinary research approach to evaluating and assisting the implementation of these technologies to improve healthcare performance. Practical implications Using this overview, managers are more able to ask questions about how the new DHTs will affect healthcare and take a stronger role in implementing these technologies to improve performance. Originality/value New insights into the use and understanding of DHTs from applying the new multidiscipline of communications science. A situated communications perspective helps to assess how a new technology can complement rather than degrade professional relationships and how safer implementation and use of these technologies can be devised.

Trust me, I'm a computer?

Computers, IT, digitisation, apps - whatever we call it - is everywhere in healthcare, and it is also racing ahead of healthcare and creating dreams and exciting opportunities for quality improvement and transformation. We want a paperless NHS. Yet we have to be careful what we wish for. We are most familiar with consumer IT, our own personal phones and tablets, but our enthusiasm for this must not be confused with what might be best for healthcare.

Open-source hardware for medical devices.

Open-source hardware is hardware whose design is made publicly available so anyone can study, modify, distribute, make and sell the design or the hardware based on that design. Some open-source hardware projects can potentially be used as active medical devices. The open-source approach offers a unique combination of advantages, including reducing costs and faster innovation. This article compares 10 of open-source healthcare projects in terms of how easy it is to obtain the required components and build the device.

What makes a good clinical app? Introducing the RCP Health Informatics Unit checklist.

Doctors increasingly rely on medical apps running on smart phones or tablet computers to support their work. However, these apps vary hugely in the quality of their data input screens, internal data processing, the methods used to handle sensitive patient data and how they communicate their output to the user. Inspired by Donabedian's approach to assessing quality and the principles of good user interface design, the Royal College of Physicians' Health Informatics Unit has developed and piloted an 18-item checklist to help clinicians assess the structure, functions and impact of medical apps. Use of this checklist should help clinicians to feel more confident about using medical apps themselves, about recommending them to their staff or prescribing them for patients.

Unreliable numbers: error and harm induced by bad design can be reduced by better design.

Number entry is a ubiquitous activity and is often performed in safety- and mission-critical procedures, such as healthcare, science, finance, aviation and in many other areas. We show that Monte Carlo methods can quickly and easily compare the reliability of different number entry systems. A surprising finding is that many common, widely used systems are defective, and induce unnecessary human error. We show that Monte Carlo methods enable designers to explore the implications of normal and unexpected operator behaviour, and to design systems to be more resilient to use error. We demonstrate novel designs with improved resilience, implying that the common problems identified and the errors they induce are avoidable.

Making healthcare safer by understanding, designing and buying better IT.

When nobody or nothing notices an error, it may turn into patient harm. We show that medical devices ignore many errors, and therefore do not adequately support patient safety. In addition to causing preventable patient harm, errors are often reported ignoring potential flaws in medical device design, and front line staff may therefore be inappropriately blamed. We present some suggestions to improve reporting and the procurement of hospital equipment.

A design to empower patients in long term wellbeing monitoring and chronic disease management in mHealth.

With the growing population with chronic disease in most developed countries, the amount and variety of interactive medical devices adopted in healthcare and wellbeing management is on the rise. Studies show that people with chronic conditions are facing many barriers to effective self-management, which leads to significant economic losses in many countries. The question as to how we can design personal medical devices that are able to facilitate an effective self-management by tackling these barriers presents a challenging research topic. We offer an overview of a controlled-experiment designed to evaluate an innovative tagging feature and a confidence of measurement feature in chronic disease management. This is a work-in-progress, which will finish by the end of June 2013.

SYFSA: a framework for systematic yet flexible systems analysis.

Although technological or organizational systems that enforce systematic procedures and best practices can lead to improvements in quality, these systems must also be designed to allow users to adapt to the inherent uncertainty, complexity, and variations in healthcare. We present a framework, called Systematic Yet Flexible Systems Analysis (SYFSA) that supports the design and analysis of Systematic Yet Flexible (SYF) systems (whether organizational or technical) by formally considering the tradeoffs between systematicity and flexibility. SYFSA is based on analyzing a task using three related problem spaces: the idealized space, the natural space, and the system space. The idealized space represents the best practice-how the task is to be accomplished under ideal conditions. The natural space captures the task actions and constraints on how the task is currently done. The system space specifies how the task is done in a redesigned system, including how it may deviate from the idealized space, and how the system supports or enforces task constraints. The goal of the framework is to support the design of systems that allow graceful degradation from the idealized space to the natural space. We demonstrate the application of SYFSA for the analysis of a simplified central line insertion task. We also describe several information-theoretic measures of flexibility that can be used to compare alternative designs, and to measure how efficiently a system supports a given task, the relative cognitive workload, and learnability.

Technology and the future of healthcare.

Healthcare changes dramatically because of technological developments, from anesthetics and antibiotics to magnetic resonance imaging scanners and radiotherapy. Future technological innovation is going to keep transforming healthcare, yet while technologies (new drugs and treatments, new devices, new social media support for healthcare, etc) will drive innovation, human factors will remain one of the stable limitations of breakthroughs. No predictions can satisfy everybody; instead, this article explores fragments of the future to see how to think more clearly about how to get where we want to go. Significance for public healthTechnology drives healthcare more than any other force, and in the future it will continue to develop in dramatic ways. While we can glimpse and debate the details of future trends in healthcare, we need to be clear about the drivers so we can align with them and actively work to ensure the best outcomes for society as a whole.

Analysis of infusion pump error logs and their significance for health care.

Infusion therapy is one of the largest practised therapies in any healthcare organisation, and infusion pumps are used to deliver millions of infusions every year in the NHS. The aircraft industry downloads information from 'black boxes' to help design better systems and reduce risk; however, the same cannot be said about error logs and data logs from infusion pumps. This study downloaded and analysed approximately 360 000 hours of infusion pump error logs from 131 infusion pumps used for up to 2 years in one large acute hospital. Staff had to manage 260 129 alarms; this accounted for approximately 5% of total infusion time, costing about £1000 per pump per year. This paper describes many such insights, including numerous technical errors, propensity for certain alarms in clinical conditions, logistical issues and how infrastructure problems can lead to an increase in alarm conditions. Routine use of error log analysis, combined with appropriate management of pumps to help identify improved device design, use and application is recommended.

Reducing number entry errors: solving a widespread, serious problem.

Number entry is ubiquitous: it is required in many fields including science, healthcare, education, government, mathematics and finance. People entering numbers are to be expected to make errors, but shockingly few systems make any effort to detect, block or otherwise manage errors. Worse, errors may be ignored but processed in arbitrary ways, with unintended results. A standard class of error (defined in the paper) is an 'out by 10 error', which is easily made by miskeying a decimal point or a zero. In safety-critical domains, such as drug delivery, out by 10 errors generally have adverse consequences. Here, we expose the extent of the problem of numeric errors in a very wide range of systems. An analysis of better error management is presented: under reasonable assumptions, we show that the probability of out by 10 errors can be halved by better user interface design. We provide a demonstration user interface to show that the approach is practical.To kill an error is as good a service as, and sometimes even better than, the establishing of a new truth or fact. (Charles Darwin 1879 [2008], p. 229).