Engineering and Technology for Healthcare

Muhammad Ali Imran, Rami Ghannam, Qammer H. Abbasi

• Publisher: Wiley-IEEE Press
• Year: 2020
• ISBN:
  9781119644286
• Edition: 1
• Topic: Biological Sciences
• Subtopic: Biotechnology
• Index: Biological Sciences

Innovation in healthcare is currently a "hot" topic. Innovation allows us to think differently, to take risks and to develop ideas that are far better than existing solutions. Currently, there is no single book that covers all topics related to microelectronics, sensors, data, system integration and healthcare technology assessment in one reference. This book aims to critically evaluate current state-of-the-art technologies and provide readers with insights into developing new solutions. With contributions from a fully international team of experts across electrical engineering and biomedical fields, the book discusses how advances in sensing technology, computer science, communications systems and proteomics/genomics are influencing healthcare technology today.

Chapter 1
Maximizing the Value of Engineering and Technology Research in Healthcare: Development‐Focused Health Technology Assessment

Janet Boutell, Neil Hawkins and Eleanor Grieve

Institute of Health & Wellbeing, University of Glasgow, Glasgow, UK

This chapter focuses on three main topics. The first aims to provide an explanation of the principles of health technology assessment (HTA) and its familiar role in determining coverage of healthcare provision. Second, we discuss the growing contribution of HTA in the development and translation of medical devices introducing what we term “development‐focused HTA”(DF‐HTA). We set out the role of DF‐HTA in identifying needs, assessing the potential of technologies in development, aiding design, and tailoring evidence generation activities. Finally, we outline the challenges of development and assessment presented by medical devices distinguishing large capital items, point of care devices, diagnostics, implantables, and digital devices. Each category of device has its own set of challenges for developers and HTA analysts alike. Challenges include a complex licensing and regulation environment, short lifespan and incremental improvement, difficulties in generating clinical evidence, the importance of contextual factors (e.g., how the device will be used and by whom), patient and clinician acceptance, and the indirect health benefit from diagnostic devices.

1.1 Introduction

Advancements in engineering and technology have the potential to revolutionise patient care and medical research. However, resources available for research and development and for healthcare provision are limited, so it is essential that any funds invested are spent on those projects that are both likely to succeed and likely to make a difference to patients' health. Health Technology Assessment (HTA) is a multi‐disciplinary approach that studies the medical, social, ethical, and economic implications of development, diffusion, and use of health technology (INAHTA.ORG 2019). HTA has been most widely used by public payers or reimbursement agencies when a technology (such as a pharmaceutical or a medical device) is ready for market. However, there is increasing recognition that HTA undertaken at an earlier stage in the development of a health technology can aid investors and developers to focus their resources on technologies that are likely to succeed as well as identifying those that are likely to fail (IJzerman et al. 2017). We term this earlier form of HTA, “development‐focused HTA” (DF‐HTA) and the more familiar form of HTA “use‐focused HTA.”

Health technology is a broad term that encompasses drugs, medical procedures, tests, and service configuration. Medical devices form a sub‐set of health technology. The diverse sub‐set includes large, expensive, capital equipment such as the Da Vinci robotic surgery platform (INTUITIVE.COM 2019) and small consumable items such as sticking plasters. There are some common challenges for developers of all categories of medical device. In particular, the licensing and regulatory environment is highly complex and differs according to the jurisdiction where the device will be used. Evidence generation is also particularly challenging for many kinds of medical devices as different decision‐makers require different levels of evidence. For devices with short lifespans, when it is common for different versions to be developed sequentially with incremental improvements, it is difficult to know which version of the device the evidence relates to. Items like the robotic surgery platform are subject to the “learning curve” effect, as surgeons need an initial training period to improve their competence before the clinical effectiveness of the new equipment can reasonably be compared with prior standards of care. Diagnostic tests form an important sub‐category of medical devices. Evidence generation for diagnostics is challenging because any health outcome resulting from the use of the diagnostic is indirect rather than direct. In order for there to be an improvement in health, the diagnostic test needs to change the diagnostic or treatment pathway so that the patient is treated sooner or more effectively. Not only is any health gain indirect, it also depends upon the behavior of the clinician and the patient. A test may indicate that treatment B is more appropriate for the patient, but if the patient and/or the clinician prefer treatment A, the test cost has been wasted and the patient's health is not improved. The value proposition for many devices is also contextually dependent. By this we mean that the device may add value in some places but not others, depending on factors such as what the current treatment and diagnostic pathways are; staffing levels; capacity and workflow; and, what other capital equipment is in place.

The numerous challenges facing developers of medical technologies in general, and medical devices in particular, have led to a recognized problem in translating research from bench to bedside. One response to this has been the growth of translational research bodies charged with supporting developers and bridging the translation gap. Two notable contributors to the DF‐HTA literature are the Center for Translational Molecular Medicine (LYGATURE.ORG 2019), based in the Netherlands and MATCH UK (MATCH.AC.UK 2018), a collaboration between several UK universities. This growing literature demonstrates how the various challenges of medical device development can begin to be addressed at an early stage of development using the methods of DF‐HTA.

The aims of this chapter are to explain what HTA is and how it has been used to determine the coverage of healthcare provision; to explain what DF‐HTA is and how it differs from use‐focused HTA; to set out the challenges in the development and assessment of medical devices; and to illustrate the contributions of DF‐HTA in the development and translation of medical devices through a number of case studies.

1.2 What Is HTA?

Healthcare resources are limited in every setting, and decision‐makers are faced with difficult choices about which technologies should be adopted and used within their service. The definition of HTA given in the introduction (INAHTA.ORG 2019) was

HTA is a multi‐disciplinary approach which studies the medical, social, ethical and economic implications of development, diffusion and use of health technology.

Technology in HTA is widely defined and includes drugs, devices, health services, and systems. As the study of these various aspects of health technologies, HTA is well‐placed to inform decision‐makers as they make resource allocation decisions. Indeed, the role of HTA to inform decision‐makers is included in the World Health Organisation (WHO.INT 2019) definition of HTA:

the systematic evaluation of properties, effects and/or impacts of health technologies and interventions. It covers both the direct, intended consequences of technologies and interventions and their indirect, unintended consequences. The approach is used to inform policy and decision‐making in health care, especially on how best to allocate limited funds to health interventions and technologies.

An ongoing project to reach a consensus definition of HTA proposed a definition that includes the important additional factors of a systematic and transparent process.

a multidisciplinary process that uses explicit and scientifically robust methods to assess the value of using a health technology at different points in its lifecycle. The process is comparative, systematic, transparent and involves multiple stakeholders. The purpose is to inform health policy and decision‐making to promote an efficient, sustainable, equitable and high‐quality health system.

Health Technology Assessment, as a discipline, first developed in the United States when Congress requested Technology Assessment of health technologies in the mid 1970s (Stevens et al. 2003), and the term is now internationally used. The adoption of this term gained popularity in wealthier countries that prioritized the evaluation and improvement of health care. HTA draws on Evidence Based Medicine (EBM). EBM developed from the publication in 1972 of Archie Cochrane's “Effectiveness and Efficiency” (Cochrane 1972) and is now championed by the international organization, the Cochrane Collaboration (Stevens et al. 2003). Evidence synthesis methods such as systematic review and meta‐analysis are core to HTA and draw heavily on guidance developed by the Cochrane Collaboration. These methods often form the basis for the clinical effectiveness estimates in cost‐effectiveness analysis and health economic modelling.

The components of HTA vary according to the particular decision‐maker, but many forms of HTA start with the definition of a decision problem to address. Analysts may find it useful to use a structure to help them define the decision problem. A popular structure is PICO, which stands for Population, Intervention, Comparator, and Outcome. The intervention is the technology to be assessed, and the comparator is the current stan...

Table of contents

• Cover
• Table of Contents
• Engineering and Technology for Healthcare
• Copyright
• Dedication
• List of Contributors
• Introduction
• Chapter 1: Maximizing the Value of Engineering and Technology Research in Healthcare: Development‐Focused Health Technology Assessment
• Chapter 2: Contactless Radar Sensing for Health Monitoring
• Chapter 3: Pervasive Sensing: Macro to Nanoscale
• Chapter 4: Biointegrated Implantable Brain Devices
• Chapter 5: Machine Learning for Decision Making in Healthcare
• Chapter 6: Information Retrieval from Electronic Health Records
• Chapter 7: Energy Harvesting for Wearable and Portable Devices
• Chapter 8: Wireless Control for Life‐Critical Actions
• Chapter 9: Role of D2D Communications in Mobile Health Applications: Security Threats and Requirements
• Chapter 10: Automated Diagnosis of Skin Cancer for Healthcare: Highlights and Procedures
• Conclusions
• Index
• End User License Agreement