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Digital Health and Point of Care: Contributions to the ‘New Normal’ of Healthcare Provision

A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Digital Health".

Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 17009

Special Issue Editors

School of Nursing, College of Health and Medicine, Newnham Campus, University of Tasmania, Launceston 7250, Australia
Interests: evaluation; digital professionalism; health literacy; higher education; human computer interaction; nursing; mobile learning; mobile technology; nursing informatics; participatory health; primary health; social media
Special Issues, Collections and Topics in MDPI journals
Faculty of Health and Education, Torrens University Australia, Melbourne, VIC 3000, Australia
Interests: advanced practice nursing; higher education; impact evaluation; multidisciplinary; nurse practitioners; nurse led models of care; policy; professionalism; rural and remote nursing; research translation; sustainability
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

As 2020, the WHO-declared Year and of the Nurse and Midwife, concludes, this Special Issue will focus on digital health and the progress of the connection of points of care by all stakeholders within healthcare administration, clinical, education or research environments. Studies that explore the nexus of nursing, other disciplines, health professions, and consumers to promote person-centered care, health and wellbeing are encouraged. Celebration of innovations, solutions, and services that enhance the role and function of healthcare professionals within the multidisciplinary digital team can be showcased. Improvements to models of care and new ways of working or harnessing digital technology to overcome healthcare or service delivery challenges are also welcome. While the Year of the Nurse and Midwife took an unexpected path to meet the demand of the COVID-19 pandemic, there are still lessons learned and achievements to be shared. This Special Issue seeks original articles that inform or can influence how digital health provision at the point of care can be enhanced to deliver high-quality and safe care and lead health professionals into the next decade.

Dr. Carey Mather
Prof. Dr. Kathleen Tori
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Environmental Research and Public Health is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • COVID-19
  • digital health
  • point of care
  • technology
  • administration
  • education
  • clinical research
  • team
  • safety

Published Papers (8 papers)

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Research

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20 pages, 539 KiB  
Article
Robust Operating Room Scheduling Model with Violation Probability Consideration under Uncertain Surgery Duration
by Yanbo Ma, Kaiyue Liu, Zheng Li and Xiang Chen
Int. J. Environ. Res. Public Health 2022, 19(20), 13685; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph192013685 - 21 Oct 2022
Viewed by 1305
Abstract
This paper proposes an operating room (OR) scheduling model to assign a group of next-day patients to ORs while adhering to OR availability, priorities, and OR overtime constraints. Existing studies usually consider OR scheduling problems by ignoring the influence of uncertainties in surgery [...] Read more.
This paper proposes an operating room (OR) scheduling model to assign a group of next-day patients to ORs while adhering to OR availability, priorities, and OR overtime constraints. Existing studies usually consider OR scheduling problems by ignoring the influence of uncertainties in surgery durations on the OR assignment. In this paper, we address this issue by formulating accurate patient waiting times as the cumulative sum of uncertain surgery durations from the robust discrete approach point of view. Specifically, by considering the patients’ uncertain surgery duration, we formulate the robust OR scheduling model to minimize the sum of the fixed OR opening cost, the patient waiting penalty cost, and the OR overtime cost. Then, we adopt the box uncertainty set to specify the uncertain surgery duration, and a robustness coefficient is introduced to control the robustness of the model. This resulting robust model is essentially intractable in its original form because there are uncertain variables in both the objective function and constraint. To make this model solvable, we then transform it into a Mixed Integer Linear Programming (MILP) model by employing the robust discrete optimization theory and the strong dual theory. Moreover, to evaluate the reliability of the robust OR scheduling model under different robustness coefficients, we theoretically analyze the constraint violation probability associated with overtime constraints. Finally, an in-depth numerical analysis is conducted to verify the proposed model’s effectiveness and to evaluate the robustness coefficient’s impact on the model performance. Our analytical results indicate the following: (1) With the robustness coefficient, we obtain the tradeoff relationship between the total management cost and the constraint violation probability, i.e., a smaller robustness coefficient yields remarkably lower total management cost at the expense of a noticeably higher constraint violation probability and vice versa. (2) The obtained total management cost is sensitive to small robustness coefficient values, but it hardly changes as the robustness coefficient increases to a specific value. (3) The obtained total management cost becomes increasingly sensitive to the perturbation factor with the decrease in constraint violation probability. Full article
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30 pages, 1019 KiB  
Article
The Role of Personality and Top Management Support in Continuance Intention to Use Electronic Health Record Systems among Nurses
by Adi Alsyouf, Awanis Ku Ishak, Abdalwali Lutfi, Fahad Nasser Alhazmi and Manaf Al-Okaily
Int. J. Environ. Res. Public Health 2022, 19(17), 11125; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph191711125 - 05 Sep 2022
Cited by 14 | Viewed by 3199
Abstract
This study examines nurses’ Continuance Intention (CI) to use electronic health records (EHRs) through a combination of three conceptual frameworks: the Unified Theory of Acceptance and Use of Technology (UTAUT), the theory of expectation-confirmation (ECT), and the Five-Factor Model (FFM). A model is [...] Read more.
This study examines nurses’ Continuance Intention (CI) to use electronic health records (EHRs) through a combination of three conceptual frameworks: the Unified Theory of Acceptance and Use of Technology (UTAUT), the theory of expectation-confirmation (ECT), and the Five-Factor Model (FFM). A model is developed to examine and predict the determinants of nurses’ CI to use EHRs, including top management support (TMS) and the FFM’s five personality domains. Data were collected from a survey of 497 nurses, which were analyzed using partial least squares. No significant relationship was found between TMS and CI. The study revealed that performance expectancy significantly mediated the influences of two different hypotheses of two predictors: agreeableness and openness to testing CI. A significant moderating impact of conscientiousness was found on the relationship between performance expectancy and CI and the relationship between social influence and CI. The findings of this study indicated that rigorous attention to the personality of individual nurses and substantial TMS could improve nurses’ CI to use EHRs. A literature gap was filled concerning the mediating effects of performance expectancy on the FFM-CI relationship, and the moderation effects of Conscientiousness on UTAUT constructs and CI are another addition to the literature. The results are expected to assist government agencies, health policymakers, and health institutions all over the globe in their attempts to understand the post-adoption use of EHRs. Full article
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15 pages, 548 KiB  
Article
Detection of COVID-19 Patients Using Machine Learning Techniques: A Nationwide Chilean Study
by Pablo Ormeño, Gastón Márquez, Camilo Guerrero-Nancuante and Carla Taramasco
Int. J. Environ. Res. Public Health 2022, 19(13), 8058; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph19138058 - 30 Jun 2022
Cited by 2 | Viewed by 1338
Abstract
Epivigila is a Chilean integrated epidemiological surveillance system with more than 17,000,000 Chilean patient records, making it an essential and unique source of information for the quantitative and qualitative analysis of the COVID-19 pandemic in Chile. Nevertheless, given the extensive volume of data [...] Read more.
Epivigila is a Chilean integrated epidemiological surveillance system with more than 17,000,000 Chilean patient records, making it an essential and unique source of information for the quantitative and qualitative analysis of the COVID-19 pandemic in Chile. Nevertheless, given the extensive volume of data controlled by Epivigila, it is difficult for health professionals to classify vast volumes of data to determine which symptoms and comorbidities are related to infected patients. This paper aims to compare machine learning techniques (such as support-vector machine, decision tree and random forest techniques) to determine whether a patient has COVID-19 or not based on the symptoms and comorbidities reported by Epivigila. From the group of patients with COVID-19, we selected a sample of 10% confirmed patients to execute and evaluate the techniques. We used precision, recall, accuracy, F1-score, and AUC to compare the techniques. The results suggest that the support-vector machine performs better than decision tree and random forest regarding the recall, accuracy, F1-score, and AUC. Machine learning techniques help process and classify large volumes of data more efficiently and effectively, speeding up healthcare decision making. Full article
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14 pages, 1445 KiB  
Article
Using COMPASS (Context Optimisation Model for Person-Centred Analysis and Systematic Solutions) Theory to Augment Implementation of Digital Health Solutions
by Carey Mather and Helen Almond
Int. J. Environ. Res. Public Health 2022, 19(12), 7111; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph19127111 - 10 Jun 2022
Cited by 2 | Viewed by 1680
Abstract
Digital health research is an emerging discipline that requires easy-to-understand theoretical frameworks and implementation models for digital health providers in health and social care settings. The COVID-19 pandemic has heightened the demand for digital health discipline-specific instruction on how to manage evidence-based digital [...] Read more.
Digital health research is an emerging discipline that requires easy-to-understand theoretical frameworks and implementation models for digital health providers in health and social care settings. The COVID-19 pandemic has heightened the demand for digital health discipline-specific instruction on how to manage evidence-based digital health transformation. Access to the use of these models guarantees that digital health providers can investigate phenomena using safe and suitable approaches and methods to conduct research and identify answers to challenges and problems that arise in health and social care settings. The COMPASS theory is designed to aid transformation of health and social care environments. A navigational rose of primary quadrants is divided by four main compass points, with person-centred care being central to the philosophy. Two axes produce Cartesian planes that intersect to form a box plot, which can be used to discover human and physical resource weightings to augment digital health research design and implementation. A third continuum highlights stakeholders’ capabilities, which are critical for any multidisciplinary study. The COMPASS mnemonic guides end users through the process of design, development, implementation, evaluation, and communication of digital health transformations. The theory’s foundations are presented and explained in context of the ‘new normal’ of health and social care delivery. Full article
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11 pages, 585 KiB  
Article
Patient Expectations: Searching Websites on How to Apply to Access Medical Records
by Kay Nicol, Kim Lehman, Joan Carlini, Kathleen Tori and Kerryn Butler-Henderson
Int. J. Environ. Res. Public Health 2022, 19(11), 6503; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph19116503 - 26 May 2022
Cited by 1 | Viewed by 1516
Abstract
Patients who want to know how to access their medical records from a health organization’s website have certain expectations about what must be included to assist in this process. The purpose of this article is to detail patient expectations of a health care [...] Read more.
Patients who want to know how to access their medical records from a health organization’s website have certain expectations about what must be included to assist in this process. The purpose of this article is to detail patient expectations of a health care organization website when searching for information on how to apply for access to their medical records. Using expectation confirmation theory, a survey was developed to ask patients, as consumers of health care, about their expectations when accessing websites. The results revealed that patients want websites to be safe and secure and have help available if there are questions about the website or search functionality. In order to improve the patient experience, health care providers need to understand these expectations from the patient perspective about this information-seeking exercise. Full article
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17 pages, 679 KiB  
Article
Implementing Digital Trainings within Medical Rehabilitations: Improvement of Mental Health and Synergetic Outcomes with Healthcare Service
by Franziska Maria Keller, Alina Dahmen, Christina Derksen, Lukas Kötting and Sonia Lippke
Int. J. Environ. Res. Public Health 2021, 18(17), 8936; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph18178936 - 25 Aug 2021
Cited by 3 | Viewed by 2193
Abstract
The need for new technologies in healthcare services has been stressed. However, little is known about the effectiveness of digital interventions integrated in psychosomatic rehabilitation processes. Data from 724 patients from psychosomatic rehabilitation clinics were analyzed with regard to the effectiveness of digital [...] Read more.
The need for new technologies in healthcare services has been stressed. However, little is known about the effectiveness of digital interventions integrated in psychosomatic rehabilitation processes. Data from 724 patients from psychosomatic rehabilitation clinics were analyzed with regard to the effectiveness of digital trainings indicated by a change in symptoms related to depression, anxiety, stress, and loneliness from pre– to post–rehabilitation. Rehabilitation satisfaction was examined in association with reaching rehabilitation goals and satisfaction with communication. A mixed repeated measures analyses of covariance, analyses of covariance, and hierarchical stepwise regression analyses were performed. Results indicated a superior effectiveness for the intervention group receiving all offered digital treatments in addition to the regular face-to-face rehabilitation program with regard to symptoms of depression (F (2674) = 3.93, p < 0.05, ηp2 = 0.01), anxiety (F (2678) = 3.68, p < 0.05, ηp2 = 0.01) post-rehabilitation, with large effect sizes for both depression (d = 1.28) and anxiety (d = 1.08). In addition, rehabilitation satisfaction was positively associated with reaching rehabilitation goals and perceived communication with healthcare workers. Digital interventions appeared effective in supporting mental health of psychosomatic rehabilitation patients’ post-rehabilitation. These findings support the inclusion of multidisciplinary and interdisciplinary digital and face-to-face treatment programs and call for more implementations of new technologies in a context of complexity to improve health and healthcare service. Full article
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Review

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16 pages, 773 KiB  
Review
Is Teleaudiology Achieving Person-Centered Care: A Review
by Sophie Brice and Helen Almond
Int. J. Environ. Res. Public Health 2022, 19(12), 7436; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph19127436 - 17 Jun 2022
Cited by 4 | Viewed by 2016
Abstract
Digital health and person-centered care are unquestionably linked in today’s Australian healthcare landscape. Teleaudiology is the application of digital health in the field of audiology, and it has become a popular component of standard audiological care. Behavior modification is essential in audiology intervention. [...] Read more.
Digital health and person-centered care are unquestionably linked in today’s Australian healthcare landscape. Teleaudiology is the application of digital health in the field of audiology, and it has become a popular component of standard audiological care. Behavior modification is essential in audiology intervention. Guidance on achieving behavior change, which is dependent on digitally enabled intervention, is a valuable resource when used in tandem to achieve person-centered care. The aim of this review is to determine whether teleaudiology achieves person-centered care. A qualitative review was conducted, followed by mapping and analysis. Analysis identified evidence of teleaudiology use, and ascertained guiding principles are appropriate to behavior change dependent digital intervention supported or enabled person-centered care. In conclusion, teleaudiology will continue to be a promising technology for promoting relatedness, a positive user experience, confidence and capability, and appropriate levels of autonomy for the user to choose from among the person-centered care options available. Full article
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24 pages, 1427 KiB  
Review
Current Artificial Intelligence (AI) Techniques, Challenges, and Approaches in Controlling and Fighting COVID-19: A Review
by Umar Albalawi and Mohammed Mustafa
Int. J. Environ. Res. Public Health 2022, 19(10), 5901; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph19105901 - 12 May 2022
Cited by 2 | Viewed by 2181
Abstract
SARS-CoV-2 (COVID-19) has been one of the worst global health crises in the 21st century. The currently available rollout vaccines are not 100% effective for COVID-19 due to the evolving nature of the virus. There is a real need for a concerted effort [...] Read more.
SARS-CoV-2 (COVID-19) has been one of the worst global health crises in the 21st century. The currently available rollout vaccines are not 100% effective for COVID-19 due to the evolving nature of the virus. There is a real need for a concerted effort to fight the virus, and research from diverse fields must contribute. Artificial intelligence-based approaches have proven to be significantly effective in every branch of our daily lives, including healthcare and medical domains. During the early days of this pandemic, artificial intelligence (AI) was utilized in the fight against this virus outbreak and it has played a major role in containing the spread of the virus. It provided innovative opportunities to speed up the development of disease interventions. Several methods, models, AI-based devices, robotics, and technologies have been proposed and utilized for diverse tasks such as surveillance, spread prediction, peak time prediction, classification, hospitalization, healthcare management, heath system capacity, etc. This paper attempts to provide a quick, concise, and precise survey of the state-of-the-art AI-based techniques, technologies, and datasets used in fighting COVID-19. Several domains, including forecasting, surveillance, dynamic times series forecasting, spread prediction, genomics, compute vision, peak time prediction, the classification of medical imaging—including CT and X-ray and how they can be processed—and biological data (genome and protein sequences) have been investigated. An overview of the open-access computational resources and platforms is given and their useful tools are pointed out. The paper presents the potential research areas in AI and will thus encourage researchers to contribute to fighting against the virus and aid global health by slowing down the spread of the virus. This will be a significant contribution to help minimize the high death rate across the globe. Full article
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