Lost in translation? : negotiating technological innovation in healthcare

Technological innovation in healthcare is growing at a rapid pace. Developments in genetics, stem cell research, bioinformatics, imaging and screening techniques have broadened out the arena of health technology. These developments in sophisticated technology, it is suggested, have the potential to revolutionize the practices of medicine and healthcare by providing more proactive and powerful tools for the diagnosis, treatment, and prevention of illness and disease (Liddell et al, 2008; Webster, 2002). In support of such claims, available research findings suggest that the adoption of new innovative health technologies (IHTs) can result in reducing healthcare costs, increasing productivity, healthcare effectiveness, and improving the patient’s experience of care by better management of chronic diseases (Liddell et al, 2008; Healthcare Industries Task Force, 2004). At the same time, new innovative health technologies present many challenges. Evidence indicates that patient safety and proven clinical effectiveness are insufficient to ensure the adoption and implementation of new clinical technologies. The prevailing organizational and policy context is crucially important as this may present barriers which slow or even prevent uptake (Lehoux 2006). In recent years there has been a continuing debate around issues of clinical resistance, organizational/clinical restructuring, procurement and commissioning, public trust, and, more widely, around the ethical and social implications of techno-scientific innovations in medicine and health (Williams and Dickinson, 2008; Webster, 2006; Ferlie et al., 2005). Moreover, cost-effectiveness evidence is now required to inform decisions about the funding and procurement of new healthcare services and technologies (Fitzgerald et al., 2002). Overall, the value of the innovation has to be clearly evident to a number of different stakeholders if technologies are to be embedded into actual work practices. These potential barriers have given rise to questions related to the diffusion and adoption of emerging medical and healthcare innovations. This paper examines the dynamics and complexity of innovation adoption processes in the context of a rapidly changing healthcare policy landscape. Drawing upon the inherently socially negotiated character of meaning, this paper illustrates the ambivalent nature of technological innovation by examining the complex ongoing interplay of heterogeneous discourses in shaping the adoption of innovative health technologies (Law, 1987, 1994). Drawing upon Rye and Kimberly (2007) adoption is here understood as a distinct organizational process related to an organization’s potential interest in implementing a technological innovation. In so doing, this paper draws on the findings of a three year research project which examines the adoption of innovative clinical technologies in the UK NHS. In particular, we explore the nature, role and dynamics of heterogeneous discourses (technological, managerial/professional, clinical), in shaping the adoption of a retinal imaging technology in a UK hospital Trust. In this regard, we contribute to the development of alternative ways of describing, analysing, and theorizing the process of technological innovation in healthcare

Adding value to laboratory medicine: a professional responsibility

Laboratory medicine is a medical specialty at the centre of healthcare. When used optimally laboratory medicine generates knowledge that can facilitate patient safety, improve patient outcomes, shorten patient journeys and lead to more cost-effective healthcare. Optimal use of laboratory medicine relies on dynamic and authoritative leadership outside as well as inside the laboratory. The first responsibility of the head of a clinical laboratory is to ensure the provision of a high quality service across a wide range of parameters culminating in laboratory accreditation against an international standard, such as ISO 15189. From that essential baseline the leadership of laboratory medicine at local, national and international level needs to ‘add value’ to ensure the optimal delivery, use, development and evaluation of the services provided for individuals and for groups of patients. A convenient tool to illustrate added value is use of the mnemonic ‘SCIENCE’. This tool allows added value to be considered in seven domains: standardisation and harmonisation; clinical effectiveness; innovation; evidence-based practice; novel applications; cost-effectiveness; and education of others. The assessment of added value in laboratory medicine may be considered against a framework that comprises three dimensions: operational efficiency; patient management; and patient behaviours. The profession and the patient will benefit from sharing examples of adding value to laboratory medicine

Foreword

Welcome to the inaugural edition of the Annals of Innovation in Medicine! It is with great pleasure and enthusiasm that I introduce this landmark publication, which marks the beginning of a remarkable journey towards advancing healthcare through research and discovery. The creation of this journal has been driven by a shared vision among a diverse group of esteemed professionals who recognize the paramount importance of fostering innovation and collaboration in the field of medicine. Our mission is clear: to provide a platform for groundbreaking research, to encourage interdisciplinary dialogue, and to inspire transformative change that benefits patients and healthcare systems worldwide. In today\u27s rapidly evolving healthcare landscape, innovation is not just a buzzword; it is an imperative. We are witnessing extraordinary advancements in technology, diagnostic techniques, therapeutic interventions, and healthcare delivery models. The potential for improving patient outcomes and transforming the way we practice medicine has never been greater. It is our duty as researchers, clinicians, and healthcare professionals to embrace this era of innovation and push the boundaries of medical knowledge. The Annals of Innovation in Medicine is dedicated to showcasing the cutting-edge work that is shaping the future of healthcare. We welcome submissions from all corners of the medical community, be it original research articles, systematic reviews, case reports, or thought-provoking perspectives. By providing a platform for the dissemination of knowledge and ideas, we aim to catalyze collaboration, inspire creativity, and foster meaningful change. As the Editor of this esteemed journal, I am committed to maintaining the highest standards of scientific integrity, editorial excellence, and transparency. Each article published in the Annals of Innovation in Medicine will undergo a rigorous peer-review process to ensure that only the most impactful and reliable research finds its way into our pages. We strive to provide our readers with thoughtfully curated content that informs, challenges, and inspires. I would like to express my sincere gratitude to the dedicated reviewers, esteemed editorial board members, and the entire team who have worked tirelessly to bring this vision to life. Without their expertise, passion, and commitment, this journal would not have been possible. I also extend my appreciation to the authors who have entrusted us with their innovative research. Your contributions are invaluable, and we are honored to have the opportunity to showcase your work. I invite all readers, authors, and reviewers to join us on this exciting journey as we explore the frontiers of medical innovation. Together, let us push the boundaries of knowledge, revolutionize patient care, and shape the future of medicine.   Warm regards, Dr. Preet Pal Singh Bhinder Editor, Annals of Innovation in Medicin

From Admission to Discharge, How Artificial Intelligence Could Optimize Patient Care

The applications of artificial intelligence (AI) in healthcare have been steadily growing over the past few years. This is largely due to the availability of large amounts of healthcare data, coupled with a dramatic increase in computational power. Today AI-based algorithms have been developed for numerous applications, from predicting patient outcomes to optimizing the clinical workflow. Given the current pace of innovation, AI is bound to play a significant role in healthcare in the years to come.Vinit Joseph Gilvaz, MD (1), George M. Abraham, MD (2), Shree Radhakrishnan (3), Zeba Hasmath, MD (1); 1. Department of Internal Medicine, Saint Vincent Hospital. 2. Department of Internal Medicine, Saint Vincent Hospital, and Professor of Medicine, University of Massachusetts Medical School. 3. Technical product manager, Innovation Incubator Inc.Includes bibliographical reference

Innovation management in healthcare: A multi-level perspective in three essays

Innovation in healthcare is a central way of coping with the changes affecting the healthcare system through the megatrends of demographic change, digitalization as well as the opportunities in the life-sciences sector and the “-omics” subjects. Due to the multiple facets of the topic, research on innovation in healthcare is diverse and draws insights from systems theory, management theory, human resources, innovation and change management. While the literature on innovation in healthcare has grown steadily in the last 20 years and publications on pharmaceutical and medical device innovation, health technology assessment strategies, or digital innovations have increased significantly, other areas such as sectoral health innovation systems, the creation and implementation of innovation in hospitals still remain fairly uncharted. Applying established concepts such as systems of innovation theory, mass customization theory or management of employee involvement in innovation activities to the healthcare sector provides new insights into a field that is often considered a “blackbox”. This thesis adds to the topic in three essays, each focusing on a different aspect and depth level ranging from a macro perspective on healthcare innovation on a global scale to a meso level perspective on the implementation of personalized medicine in one country and putting a micro lens on innovation activities of hospital staff. The aim of this thesis is to provide an overview for researchers, policy makers and healthcare stakeholders about current developments, propose tools for measuring innovation and allow for benchmarking the current status quo in healthcare in order to foster new and innovative developments

Exploratory Research for the Identification of a Decision-Making Model for the Adoption and Implementation of Emerging Technology in Healthcare Operations

OBJECTIVES The most promising medical innovations appear to take a long time to be used in healthcare practice. This research has two main objectives: to understand the factors that limit or promote the adoption of Emerging Technologies (ET) in healthcare and to provide a model for understanding, codifying and improving the current situation. METHODOLOGY A case study is used to shed light on the process of adopting ET in healthcare between a teaching hospital (adopter) and a manufacturer of innovation (producer). The primary data, investigated through thematic analysis and literary evidence, consists of nine semi-structured interviews from ET experts on the side of the adopter and the producer. The Attitude, Decision, and Implementation (ADI) decision-making model is used as the theoretical lens for this study. This framework is a modification of the process described in the theory of Diffusion of Innovation (DoI) (Rogers, 2003) adapted to the peculiarities of the healthcare environment. RESULTS From the analysis of the interviews, it is clear that innovation in medicine has several limitations (financial resources, free time of healthcare professionals, correct identification and know-how of the professionals involved, communication, healthcare resistance) against few facilitators (Innovation Champions, appropriate marketing, medical conferences). This study also highlights the absence of a shared and codified model for the adoption of innovation in medicine. DISCUSSION The impediments and the facilitating factors that emerged in the analysis of the primary data have been confirmed in literature. Furthermore, the primary data analysis with literary evidence supports the ADI model as a possible decision-making process for the adoption of ET in healthcare. Its three cyclical phases: the creation of an attitude (A) towards the ET, the decision to continue the collaboration between the parties (D), and the implementation of innovation (I) are sustained by primary data and literary evidence. CONCLUSIONS The ADI model could improve the efficiency and pace of adoption of ET in healthcare by limiting barriers, exploiting facilitating factors and building a beneficial relationship between users and producers of ET

Healthcare Innovation Absenteeism: The Rise of Physician Entrepreneurs & Medical Startups

For years, warning signs have illuminated imminent days of reckoning for stalled healthcare innovation across the dynamic American healthcare landscape. An evolving epic battle for healthcare innovation delivery has silently raged and set arena stages throughout the healthcare industry. Urgent innovative healthcare delivery is needed to ameliorate longstanding points of failures in providing healthcare delivery to society. Historically, the science of medicine has fostered cultural practices of innovation absenteeism and resistance to change. Mired by archaic processes, legacy systems, and fractionally useful equipment, our current healthcare ecosystems are unsustainable. Recently, some unhindered frontline physicians opted to take on a portion of critical healthcare challenges and followed their ideas to leverage clinical expertise and drive the agenda for changing healthcare innovation delivery. Our qualitative multi-case study design centered around empirical evidence that answered the research question: How do physician entrepreneurs navigate decision-making strategies for medical startups from ideation, innovation, to commercialization of new medical products and services? We examined 21 cases of physician founded medical startups to understand particularizations around physician entrepreneurship. Findings suggest three contributions towards knowledge accumulation about physician entrepreneurs and medical startups: exclusive decision-making processes, industry-specific insights, and illuminations of physician voices that might not otherwise be heard

Handling Disruptive Innovation in Clinical and Research Settings

The process of disruptive innovation is a driving force in making healthcare more afforda­ble and effective. Building resilience through diversification of financial resources, networking, and focusing time/effort can help an academic entrepreneur tolerate setbacks and minimize risks. The sleep medicine case study highlights how fast a disruptive innovation can impact organizations on a micro and macro level