Healthcare Engineering Research Articles

Transnational learning and teaching activities: Smart Healthcare Engineering.

The new maintenance engineers become self-taught and learn from daily dedication, from solving repetitive problems, from exchanging experiences with a colleague, from reading a recommended book and little else. Their own experience has been the main reference for maintenance professionals who have not given up and have become experts. And within the maintenance activities, sanitary engineering plays a very important role. Through the Smart Healthcare Engineering project we have facilitated a close connection between 3 universities and 3 hospitals from 3 countries (Spain, Turkey and Romania), which benefit from each other's experience, transferring the know-how available in a single country. The study involves 7 students from each university, meaning that 21 students have worked and studied together for 2 weeks in Spain in the field of healthcare engineering. The chosen hospital was Dr. Negrin Hospital from Gran Canaria. Results at the organizational level include the modernization of content and the provision of resources for healthcare engineering training, the introduction of innovative educational concepts in healthcare engineering and the integration of blended learning methodologies in practical teaching and training activities. A tighter connection and transnational collaboration were established between European hospitals and universities in healthcare engineering, together with unrestricted access to routinely updated information. The specific results for each participant indicated their capacity to engage in the intricate processes of repair and maintenance within a practical context, making real-time judgments on-site.

From Code to Care: The Impact of Software Engineering and QA on Healthcare Delivery Systems

The rapid digitalization of healthcare has led to an unprecedented reliance on software systems to improve patient care, streamline operations, and ensure regulatory compliance. This article presents a comprehensive analysis of the critical role that software engineering and quality assurance (QA) play in three key areas of modern healthcare: Electronic Health Records (EHRs), telemedicine platforms, and medical device software. Through an examination of current practices, challenges, and case studies, we demonstrate how robust software engineering methodologies and rigorous QA processes contribute to the development of reliable, secure, and efficient healthcare applications. Our findings highlight the importance of data integrity, interoperability, user experience, and regulatory compliance in healthcare software development. Furthermore, we explore emerging trends such as artificial intelligence, blockchain, and the Internet of Medical Things (IoMT), discussing their implications for future software engineering and QA practices in healthcare. This article provides valuable insights for healthcare organizations, software developers, and policymakers, offering recommendations to enhance the quality and safety of software-driven healthcare solutions.

Accommodating Learners: An Adaptive Approach to Surgical Hand Preparation With Crutches

Accommodations for injured and disabled surgical providers have to balance an individual's needs with measures that ensure sterility requirements, patient and provider safety. The highly specialized nature of the surgical environment poses challenges when implementing changes in the operating room and literature is limited on adaptive surgical hand preparation techniques necessary to maximize a disabled medical student's active participation in their surgical clerkship. This paper presents a detailed account of the development and implementation of an adaptive surgical hand preparation designed to address mobility needs, enabling a student's active participation and education in the surgical curriculum. This offers a framework for adapting traditional surgical hand preparation techniques for crutches consisting of essential requirements in terms of equipment and personnel, step-by-step guide for implementation, discussion of potential risks related to contamination and safety, and a discussion on future directions for further innovation. An adaptive surgical hand preparation technique was necessary to sterilize forearm crutches for a third-year medical student with a physical disability to ensure accessibility in the operating room and equity in surgical clerkship and medical education. Successful use of this protocol, in over 40 surgical cases throughout an 8-week surgical clerkship, created opportunity for a disabled medical student to access the sterile operating table through collaboration and innovation in the operating room. The adaptive hand preparation and sterile crutch cover solution was necessary for the student to assist in open, laparoscopic, and surgical procedures resulting in high clinical performance marks in the surgical clerkship. Beyond the individual benefit, this protocol promotes the importance of equity in medication education and encourages diversity through adaptive measures in the surgical field. Designing an adaptive sterilization protocol for use of crutches in the operating room serves as an example of educational engineering and adaptable accessibility. The entire collaborative effort involving the medical student, university, surgical providers and operating room staff demonstrates the importance of teamwork in creating access in healthcare settings. Through learned experience, the authors provide insights for future directions for innovation, aiming to enhance access and inclusivity in medical education and surgical practice. This paper reflects on the broader implications of educational engineering and inclusive practices in healthcare.

Exploring Emergent Nanotechnology Applications in Mechanical and Health Engineering

Abstract: Nanotechnology is a promising area of research in science and technology with potential benefits in automotive, aircraft, construction, energy, healthcare, agriculture, food processing, although it has its own risks in environmental sustainability. Recent advances in this area have stimulated research and their applications in different fields, with important results in mechanical engineering and health engineering. The aim of this article is to give an overview of some recent advances of nanotechnology, exploring emerging applications of these typical technologies. Examples of some successful practical applications in mechanical and healthcare engineering based on this technology are given, and an analysis of the prospects and main problems of this area is also conducted. Furthermore, mechanical engineers and health professionals would find this review valuable in updating their knowledge on the latest developments in nanotechnology applications.

Exploring the Future of Prompt Engineering in Healthcare: Mission and Vision, Methods, Opportunities, Challenges, Issues and Their Remedies, Contributions, Advantages, Disadvantages, Applications, and Algorithms

Exploring the Future of Prompt Engineering in Healthcare: Mission and Vision, Methods, Opportunities, Challenges, Issues and Their Remedies, Contributions, Advantages, Disadvantages, Applications, and Algorithms

A Road Map of Prompt Engineering for ChatGPT in Healthcare: A Perspective Study.

Generative AI models, such as ChatGPT, have significantly impacted healthcare through the strategic use of prompts to enhance precision, relevance, and ethical standards. This perspective explores the application of prompt engineering to tailor outputs specifically for healthcare stakeholders: patients, providers, policymakers, and researchers. A nine-stage process for prompt engineering in healthcare is proposed, encompassing identifying applications, understanding stakeholder needs, designing tailored prompts, iterative testing and refinement, ethical considerations, collaborative feedback, documentation, training, and continuous updates. A literature review focused on "Generative AI" or "ChatGPT," prompts, and healthcare informed this study, identifying key prompts through qualitative analysis and expert input. This systematic approach ensures that AI-generated prompts align with stakeholder requirements, offering valuable insights into symptoms, treatments, and prevention, thereby supporting informed decision-making among patients.

Prompt Engineering in Healthcare

Prompt Engineering in Healthcare

RAbDesFlow: a novel workflow for computational recombinant antibody design for healthcare engineering.

Recombinant antibodies (rAbs) have emerged as a promising solution to tackle antigen specificity, enhancement of immunogenic potential and versatile functionalization to treat human diseases. The development of single chain variable fragments has helped accelerate treatment in cancers and viral infections, due to their favorable pharmacokinetics and human compatibility. However, designing rAbs is traditionally viewed as a genetic engineering problem, with phage display and cell free systems playing a major role in sequence selection for gene synthesis. The process of antibody engineering involves complex and time-consuming laboratory techniques, which demand substantial resources and expertise. The success rate of obtaining desired antibody candidates through experimental approaches can be modest, necessitating iterative cycles of selection and optimization. With ongoing advancements in technology, in silico design of diverse antibody libraries, screening and identification of potential candidates for in vitro validation can be accelerated. To meet this need, we have developed rAbDesFlow, a unified computational workflow for recombinant antibody engineering with open-source programs and tools for ease of implementation. The workflow encompasses five computational modules to perform antigen selection, antibody library generation, antigen and antibody structure modeling, antigen-antibody interaction modeling, structure analysis, and consensus ranking of potential antibody sequences for synthesis and experimental validation. The proposed workflow has been demonstrated through design of rAbs for the ovarian cancer antigen Mucin-16 (CA-125). This approach can serve as a blueprint for designing similar engineered molecules targeting other biomarkers, allowing for a simplified adaptation to different cancer types or disease-specific antigens.

A Systematic Review of the Integration of Information Science, Artificial Intelligence, and Medical Engineering in Healthcare: Current Trends and Future Directions

A Systematic Review of the Integration of Information Science, Artificial Intelligence, and Medical Engineering in Healthcare: Current Trends and Future Directions

London Institute for Healthcare Engineering Aims to Unlock UK MedTech Potential

London Institute for Healthcare Engineering Aims to Unlock UK MedTech Potential

Development of Flexible Electronic Biosensors for Healthcare Engineering

Development of Flexible Electronic Biosensors for Healthcare Engineering

Advancing digital healthcare engineering for aging ships and offshore structures: an in-depth review and feasibility analysis

AbstractAging ships and offshore structures face harsh environmental and operational conditions in remote areas, leading to age-related damages such as corrosion wastage, fatigue cracking, and mechanical denting. These deteriorations, if left unattended, can escalate into catastrophic failures, causing casualties, property damage, and marine pollution. Hence, ensuring the safety and integrity of aging ships and offshore structures is paramount and achievable through innovative healthcare schemes. One such paradigm, digital healthcare engineering (DHE), initially introduced by the final coauthor, aims at providing lifetime healthcare for engineered structures, infrastructure, and individuals (e.g., seafarers) by harnessing advancements in digitalization and communication technologies. The DHE framework comprises five interconnected modules: on-site health parameter monitoring, data transmission to analytics centers, data analytics, simulation and visualization via digital twins, artificial intelligence-driven diagnosis and remedial planning using machine and deep learning, and predictive health condition analysis for future maintenance. This article surveys recent technological advancements pertinent to each DHE module, with a focus on its application to aging ships and offshore structures. The primary objectives include identifying cost-effective and accurate techniques to establish a DHE system for lifetime healthcare of aging ships and offshore structures—a project currently in progress by the authors.

Advancing digital healthcare engineering for aging ships and offshore structures: an in-depth review and feasibility analysis – ERRATUM

Advancing digital healthcare engineering for aging ships and offshore structures: an in-depth review and feasibility analysis – ERRATUM

ENGINEERING INNOVATIONS IN HEALTHCARE: A REVIEW OF DEVELOPMENTS IN THE USA


 The healthcare landscape in the United States is undergoing a transformative evolution fueled by rapid engineering innovations. This study synthesizes and examines key developments at the intersection of engineering and healthcare, emphasizing advancements that have significantly impacted medical practices, patient outcomes, and the overall healthcare ecosystem. The study outlines notable engineering applications, including medical imaging technologies, biomedical devices, telehealth solutions, and health information systems. It explores the integration of artificial intelligence and machine learning in healthcare engineering, emphasizing their role in diagnostics, personalized medicine, and treatment optimization. Additionally, the abstract discusses the implications of engineering innovations on healthcare accessibility, cost-effectiveness, and the potential to address emerging challenges. Through a comprehensive examination of developments in the USA, this study provides insights into the multifaceted role of engineering in shaping the present and future of healthcare delivery.
 Keywords: Engineering Innovations, Healthcare, USA, Review, Public Health, Development

Exploring the Potential of Convolutional Neural Networks in Healthcare Engineering for Skin Disease Identification

Skin disorders affect millions of individuals worldwide, underscoring the urgency of swift and accurate detection for optimal treatment outcomes. Convolutional Neural Networks (CNNs) have emerged as valuable assets for automating the identification of skin ailments. This paper conducts an exhaustive examination of the latest advancements in CNN-driven skin condition detection. Within dermatological applications, CNNs proficiently analyze intricate visual motifs and extricate distinctive features from skin imaging datasets. By undergoing training on extensive data repositories, CNNs proficiently classify an array of skin maladies such as melanoma, psoriasis, eczema, and acne. The paper spotlights pivotal progressions in CNN-centered skin ailment diagnosis, encompassing diverse CNN architectures, refinement methodologies, and data augmentation tactics. Moreover, the integration of transfer learning and ensemble approaches has further amplified the efficacy of CNN models. Despite their substantial potential, there exist pertinent challenges. The comprehensive portrayal of skin afflictions and the mitigation of biases mandate access to extensive and varied data pools. The quest for comprehending the decision-making processes propelling CNN models remains an ongoing endeavor. Ethical quandaries like algorithmic predisposition and data privacy also warrant significant consideration. By meticulously scrutinizing the evolutions, obstacles, and potential of CNN-oriented skin disorder diagnosis, this critique provides invaluable insights to researchers and medical professionals. It underscores the importance of precise and efficacious diagnostic instruments in ameliorating patient outcomes and curbing healthcare expenditures.

Assessing the Sustainability of Initiatives Aimed to Enhance Patient Safety Culture: A > 10-year Experience with Multifaceted Interventions

Culture is a key factor in maintaining high-quality care. We have instituted a series of mutually-reinforcing initiatives aimed to improve operations, and patient and staff safety. We herein review the impact of these initiatives on our Patient Safety Culture over 14 years. We hypothesize that these initiatives can lead to sustained improvements in Culture. In ≈ 2009, our department, with help of dedicated quality improvement coaches from our internal Division of Healthcare Engineering (with knowledge of Lean-Six Sigma and High Reliability methods and tools), instituted (and largely sustained) initiatives aimed to improve our operations, and to improve patient/staff safety; including: (a) daily multidisciplinary team huddles, (b) daily pre-planning/treatment peer review, (c) a robust Incident Learning System, (d) weekly meetings to review reported incidents, (e) monthly department-wide meetings to review the highlights from the weekly incident review meetings, (f) celebration/recognitions for staff participation and (g) leader Gemba walks. Culture was quantitatively assessed via the AHRQ (Agency for Healthcare Research and Quality) Patient Safety Culture Survey (with 51 questions) which was sent to the department every two years (2021 was skipped due to Covid). Changes in the summary survey results over time were assessed using 2-tailed chi-square. Within 2-4 years of starting of our initiatives, there was an increase in the number of survey respondents, and an increase in the % of favorable responses (vs. pre-initiative data from 2009), for most comparisons (see Table with representative data). The % favorable responses plateaued in ≈ 2013-2015, and there was a non-significant decline in % favorable responses in later years (vs. the high scores in 2015). A series of mutually reinforcing initiatives aimed to improve operations, and to improve patient/staff safety, can lead to improvements in Patient Safety Culture; and these improvements can be largely sustained over time. Some of the modest non-significant decline in later years may reflect staff changes, fatigue, increasing practice complexity, financial pressures, and/or Covid-related issues (in the 2022 survey). This speaks to the importance of maintaining quality/safety initiatives through transitions in leadership, staff and external stressors.

A Transparent, Tough and Self-Healable Biopolymeric Composites Hydrogel for Open Wound Management.

Modern healthcare engineering requires a wound dressing solution supported by materials with outstanding features such as high biological compatibility, strong mechanical strength, and higher transparency with effective antibacterial properties. Here, we present a unique hydrogel technology consisting of two negatively charged biopolymers and a positively charged synthetic polymer. The interaction between charged polymers through hydrogen bonds has been created, which are revealed in the simulation by density functional theory and Fourier transform infrared spectra of individual polymers and the hydrogel film. The transparent hydrogel film dressings showed excellent stretchability, a higher water swelling ratio (60%), and strong mechanical strength (∼100 MPa) with self-healing abilities (85-90%). The fabricated hydrogel film showed stable blood clots (within 119 ± 15 s) with rapid hemostasis (<2%) properties and effective antibacterial studies against E. coli and S. aureus bacterial strains. In addition, the obtained hydrogel film also showed excellent cell viability on mouse fibroblast cells. With their enormous amenability to modification, these hydrogel films may serve as promising biomaterials for wound dressing applications.

A fuzzy cognitive map-based algorithm for predicting water consumption in Spanish healthcare centres

The management of water consumption in healthcare centres can have positive impacts on both the environmental performance and profitability of health systems. Computational tools assist in the decision-making process of managing the operation and maintenance of healthcare centres. This research aimed to integrate the empirical knowledge of experts in Healthcare Engineering and the historical data from 66 healthcare centres in a Fuzzy Cognitive Map. The outputs of the predictive model included water consumption, water cost, and CO2 emissions in healthcare facilities, along with eleven variables to discover the causes and consequences of water consumption in healthcare centres. A healthcare centre with about 12 350 users, located in a city that experiences an average of 1100 heating degree days, whose facilities be moderately energy-efficient contributing over 50% with renewable energies is expected to consume 8.4 dam3 of water with 32.1 k€ of cost, and contribute realising 30.8 ton CO2eq emissions. The use of Fuzzy Cognitive Maps for prediction can provide a high level of effectiveness in identifying the factors that contribute to water consumption and in designing key performance indicators to manage the environmental performance of healthcare buildings. This tool is extremely effective in enhancing the performance of the management division of health systems.

Knowledge graph analysis of artificial intelligence application research in nursing field based on visualization technology

In order to assess the research status, hot issues of artificial intelligence in nursing to provide reference for scholars. This work conduct a quantitative analysis on related literature in WOS from 2011 to 2022 by mathematical and statistical methods, including publication trend, journals, author, institution, national and regional, keyword, literature co-citation. The hotspots and trends were revealed. The results showed that: (1) scholars' attention to it showed a steady increasing. (2) There were 20 journals published more than 6 papers, published 205 papers, that's 30.83 % of the total, Journal of Healthcare Engineering published the most papers, that's 8.78 %. (2) Kendrick Cato, Lisiane Pruinelli published the most papers, that's 2.95 %, which have strong cooperation. (3) Harvard Medical School, Columbia University and University of Minnesota published 114 papers, that's 8.21 % of the total, were the core unit, Harvard Med Sch, Columbia Univ and Univ Penn had strong cooperation. (4) The United States, China, Japan, Australia and United Kingdom are the top five countries for publishing papers, that's 80.3 % of the total. The cooperation degree of the each are 0.51, 0.36, 0.07, 0.04, and 0.06. (6) “electronic health record”, “risk prediction” and “supervised machine learning” are current research hotspots.

Indoor Airflow Dynamics in Compartmentalized Pneumology Units Equipped with Variable-Thickness MERV-13 Filters

Infection containment in the post-pandemic scenario became a top priority for healthcare engineering control staffers, especially in pneumology sectors, where the treatment of airborne infectious diseases is frequent. In Brazil, where COVID-19 left a long record of casualties, there is a lack of information on the influence of filtration systems on the maintenance of regulated operational conditions for indoor comfort in hospital environments. This paper has the following objectives: to study arrangements of filtering systems in hospital acclimatization ducts; to verify how filtering characteristics could compromise safety regulations for airflow in hospital environments; and to identify airflow stagnation points that might favor suspended viral concentrations and increase contamination risks. We used the computational fluid dynamics STAR-CCM+© software to perform numerical simulations of different cases of indoor airflow in a model corresponding to a sector of the Lauro Wanderley University Hospital (João Pessoa city, Brazil). We concluded that standards for maximum velocity are reachable despite thinner or thicker filters affecting the spread of the air. In this way, acclimatization systems are limited by a tradeoff between regulation and protection. Our findings are relevant to future technological development, interventions, safety strategies amidst contamination scenarios, and new filtration arrangements in hospital environments.