Healthcare Engineering Defined: A White Paper

Cross-disciplinary training of nursing informatics and nursing engineering at the postgraduate level: A feasibility analysis based on the qualitative method

BACKGROUND

The trend of interdisciplinary education is becoming increasingly prominent. Nursing informatics and nursing engineering have received much attention and development at different levels of nursing education in many Western countries. Meanwhile, in China, the cultivation of interdisciplinary nursing talents has either not been initiated or has only entered an initial stage.

OBJECTIVES

This study aims to explore experts' opinions from nursing, informatics and engineering on the feasibility of interdisciplinary education at graduate master's level in nursing through interview.

DESIGN

This was a descriptive qualitative study.

SETTING

Interviews were conducted online or face to face.

PARTICIPANTS

Experts in the fields of nursing, informatics, and engineering who met the study qualifications were enrolled.

METHODS

This study used a purposive sampling method and collected data via semi-structured interviews. A total of 14 experts were involved based on data saturation, which eight were interviewed face-to-face and six were interviewed online. A content analysis method was used to summarize and analyze the attitudes, opinions, and suggestions of experts.

RESULTS

A total of 579 min of interviews with 66,387 words were transcribed and analyzed after 30-50 min time range of each interview, and 4 themes were established. A consensus was obtained on the necessity and importance of interdisciplinary education. Policy guidance, financial support, and mutual recognition were the prerequisites for the cultivation. Moreover, feasibility of interdisciplinary education depends on multi-cooperation, including society, university, and hospital. Finally, a linkage mechanism among relevant stakeholders was required.

CONCLUSION

The necessity and feasibility of such integrated training was concluded. Learning from the experience of relevant countries, China should launch an interdisciplinary training model suitable for its national condition.

Study to assess the utility of discrete event simulation software in projection & optimization of resources in the out‐patient department at an apex cancer institute in India

Background and Aims

Methods

Results

Conclusion

A Practical Guide for Building Collaborations Between Clinical Researchers and Engineers: Lessons Learned From a Multidisciplinary Patient Safety Project

OBJECTIVES

Engineering and operations research have much to contribute to improve patient safety, especially within complex, highly regulated, and constantly evolving hospital environments. Despite new technologies, clinical checklists, and alarm systems, basic challenges persist that impact patient safety, such as how to improve communication between healthcare providers to prevent hospital-acquired complications. Because these collaborations are often new territory for both clinical researchers and engineers, the aim of the study was to prepare research teams that are embarking on similar collaborations regarding common challenges and training needs to anticipate while developing multidisciplinary teams.

METHODS

Using a specific patient safety project as a case study, we share lessons learned and research training tools developed in our experience from recent multidisciplinary collaborations between clinical and engineering teams, which included many nonclinical undergraduate and graduate students.

RESULTS

We developed a practical guide to describe anticipated challenges and solutions to consider for developing successful partnerships between engineering and clinical researchers. To address the extensive clinical, regulatory, data collection, and laboratory education needed for orienting multidisciplinary team members to join research projects, we also developed and shared a checklist for project managers as well as the training materials as adaptable resources to facilitate other teams' initiation into these types of collaborations. These resources are appropriate and tailorable for orienting both clinical and nonclinical team members, including faculty and staff as well as undergraduate and graduate students.

CONCLUSIONS

We shared a practical guide to prepare teams for new multidisciplinary collaborations between clinicians and engineers.

Interdisciplinary collaboration between nursing and engineering in health care: A scoping review

BACKGROUND

Due to the rapid advancements in precision medicine and artificial intelligence, interdisciplinary collaborations between nursing and engineering have emerged. Although engineering is vital in solving complex nursing problems and advancing healthcare, the collaboration between the two fields has not been fully elucidated.

OBJECTIVES

To identify the study areas of interdisciplinary collaboration between nursing and engineering in health care, particularly focusing on the role of nurses in the collaboration.

METHODS

In this study, a scoping review using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Extension for Scoping Reviews was performed. A comprehensive search for published literature was conducted using the PubMed, Cumulative Index to Nursing and Allied Health Literature, Scopus, Embase, Web of Science, ScienceDirect, Institute of Electrical and Electronics Engineers Digital Library, and Association for Computing Machinery Digital Library from inception to November 22, 2020. Data screening and extraction were performed independently by two reviewers. Any discrepancies in results were resolved through discussions or in consultation with a third reviewer. Data were analyzed by descriptive statistics and content analysis. Results were visualized in an interdisciplinary collaboration model.

RESULTS

We identified 6,752 studies through the literature search, and 60 studies met the inclusion criteria. The study areas of interdisciplinary collaboration concentrated on patient safety (n = 18), symptom monitoring and health management (n = 18), information system and nursing human resource management (n = 16), health education (n = 5), and nurse-patient communication (n = 3). The roles of nurses in the interdisciplinary collaboration were divided into four themes: requirement analyst (n = 21), designer (n = 22), tester(n = 37) and evaluator (n = 49). Based on these results, an interdisciplinary collaboration model was constructed.

CONCLUSIONS

Interdisciplinary collaborations between nursing and engineering promote nursing innovation and practice. However, these collaborations are still emerging and in the early stages. In the future, nurses should be more involved in the early stages of solving healthcare problems, particularly in the requirement analysis and designing phases. Furthermore, there is an urgent need to develop interprofessional education, strengthen nursing connections with the healthcare engineering industry, and provide more platforms and resources to bring nursing and engineering disciplines together.

Future Location Prediction for Emergency Vehicles Using Big Data: A Case Study of Healthcare Engineering

The number of devices equipped with GPS sensors has increased enormously, which generates a massive amount of data. To analyse this huge data for various applications is still challenging. One such application is to predict the future location of an ambulance in the healthcare system based on its previous locations. For example, many smart city applications rely on user movement and location prediction like SnapTrends and Geofeedia. There are many models and algorithms which help predict the future location with high probabilities. However, in terms of efficiency and accuracy, the existing algorithms are still improving. In this study, a novel algorithm, NextSTMove, is proposed according to the available dataset which results in lower latency and higher probability. Apache Spark, a big data platform, was used for reducing the processing time and efficiently managing computing resources. The algorithm achieved 75% to 85% accuracy and in some cases 100% accuracy, where the users do not change their daily routine frequently. After comparing the prediction results of our algorithm, it was experimentally found that it predicts processes up to 300% faster than traditional algorithms. NextSTMove is therefore compared with and without Apache Spark and can help in finding useful knowledge for healthcare medical information systems and other data analytics related solutions especially healthcare engineering.

Scheduling of Preventive Maintenance in Healthcare Buildings Using Markov Chain

The optimization of maintenance in healthcare buildings reduces operating costs and contributes towards increasing the sustainability of the healthcare system. This paper proposes a tool to schedule preventive maintenance for healthcare centers using Markov chains. To this end, the authors analyzed 25 healthcare centers belonging to the three Healthcare Districts of Spain and built between 1985 and 2005. Markov chains proved useful in choosing the most suitable maintenance policies for each healthcare building without exceeding a specific degradation boundary, which enabled achieving an ideal maintenance frequency and reduced the use of resources. Markov chains have also proven useful in optimizing the periodicity of routine maintenance tasks, ensuring a suitable level of maintenance according to the frequency of the failures and reducing the cost and carbon footprint. The healthcare centers observed during the study managed to save more than 700 km of journeys, reduce emissions in its operations as a whole by 174.3 kg of CO2 per month and increase the overall efficiency of maintenance operations by 15%. This approach, therefore, renders it advisable to plan the maintenance of healthcare buildings.

Analysis of the Installed Productive Capacity in a Medical Angiography Room through Discrete Event Simulation

The installed productive capacity of a healthcare center’s equipment limits the efficient use of its resources. This paper, therefore, analyzes the installed productive capacity of a hospital angiography room and how to optimize patient demand. For this purpose, a Discrete Event Simulation (DES) model based on historical variables from the current system was created using computer software. The authors analyzed 2044 procedures performed between 2014 and 2015 in a hospital in San José, Costa Rica. The model was statistically validated to determine that it does not significantly differ from the current system, considering the DMAIC stages for continuous process improvement. In the current scenario, resource utilization is 0.99, and the waiting list increases every month. The results showed that the current capacity of the service could be doubled, and that resource utilization could be reduced to 0.64 and waiting times by 94%. An increase in service efficiency could be achieved by shortening maximum waiting times from 6.75 days to 3.70 h. DES simulation, therefore, allows optimizing of the use of healthcare systems’ resources and hospital management.

Analytical Determination of Medical Gases Consumption and Their Impact on Hospital Sustainability

Medical gases are known to show a great environmental impact and also to consume relevant resources in terms of hospital management. The present work reports on a study performed between 2008 and 2016 in a target set of 12 Spanish hospitals with floor area and number of beds ranging 2314–23,300 m2 and 20–194, respectively, for which the average annual consumption rates of oxygen, nitrogen, medicinal air, carbon dioxide and nitrogen protoxide were analysed. The annual consumption of medical gases in a hospital was proved to be correlated with the number of hospital discharges, the number of surgeries, the number of emergency interventions, the number of hospitalisations, the number of hospital beds, the useful floor area of the building and the number of workers. In particular, the annual consumption per hospital bed was computed as 350 m3 for oxygen, 325 m3 for medicinal air, 9 m3 for nitrogen protoxide and 3 m3 for carbon dioxide. It is shown that healthcare activity appears as an adequate variable to quantify and to monitor medical gases consumption in hospitals, to assess the size of their facilities as well as to optimise maintenance management.

Kids' Perceptions toward Children's Ward Healing Environments: A Case Study of Taiwan University Children's Hospital

This paper summarizes the opinions of experts who participated in designing the environment of a children's hospital and reports the results of a questionnaire survey conducted among hospital users. The grounded theory method was adopted to analyze 292 concepts, 79 open codes, 25 axial codes, and 4 selective codes; in addition, confirmatory factor analysis and reliability analysis were performed to identify elements for designing a healing environment in a children's hospital, and 21 elements from 4 dimensions, namely, emotions, space design, interpersonal interaction, and pleasant surroundings, were determined. Subsequently, this study examined the perceptions of 401 children at National Taiwan University Children's Hospital. The results revealed that, regarding the children's responses to the four dimensions and their overall perception, younger children accepted the healing environment to a significantly higher degree than did older children. The sex effect was significant for the space design dimension, and it was not significant for the other dimensions.