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Healthcare in Digital Environments: An Interdisciplinary Perspective

A special issue of Healthcare (ISSN 2227-9032).

Deadline for manuscript submissions: closed (31 March 2024) | Viewed by 17034

Special Issue Editors


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Guest Editor
Department of New Public Health, Institute for Health Research and Education, Osnabrück University, 49076 Osnabrück, Germany
Interests: public health; digital health; health inequities

E-Mail Website
Guest Editor
Health Informatics Research Group, Faculty of Business Management and Social Sciences, Hochschule Osnabrück, 49076 Osnabrück, Germany
Interests: continuity of care; learning health system; clinical decision support

Special Issue Information

Dear Colleagues,

We would like to invite you to participate in the latest Healthcare Special Issue entitled ‘Healthcare in Digital Environments: an Interdisciplinary Perspective’. Healthcare has already been transformed by digital technologies, and in the future, entirely new healthcare approaches will be established, the scope of which is not yet fully foreseeable. Digitalization is accompanied by great expectations; it is assumed that it will improve accessibility to and the quality of healthcare; it is also assumed that it will increase effectiveness. Digitalization leads to far-reaching process and structural changes that affect the foundations of established care services, understanding of the roles and work profiles of health professionals, communication and interaction between patients and providers, and patient role. The aim of the Special Issue is to explore these changes and to examine them consistently from an interdisciplinary perspective. Although there are numerous studies, they often have a monodisciplinary perspective, or they overlook the societal implications.

The intention here is to close this gap by bringing together contributions on the following main areas: The first focus is to addresses the question of how digitalization (telemedicine and eHealth) can contribute to health equity. Here, aspects of social inequality, as well as regional inequalities, e.g., rural areas and low-income countries, are the focus. The second key area addresses the questions regarding process and structural changes, e.g., what are the implications that digitalization has for interprofessional and/or intersectoral collaboration, how are professional roles changing, and in what way does digitalization contribute to new forms of interaction in the patient-provider relationship. The third focus will reveal the effectiveness of digital health applications—examined with rigorous study designs—and thus will shed light on their implementation, use, and added value in practice. Although studies often only address positive outcomes, we encourage the contributors to also report on adverse and unexpected outcomes. These contributions are also expected to reflect system-relevant parameters, on the one hand, and changes among health professionals and patients, on the other. Finally, as a fourth focus, research papers on future scenarios based on existing experiences and emerging technologies, e.g., machine learning and precision medicine and care, fully automated logistics, as well as virtual and augmented reality in rehabilitation, are welcome.

Researchers from different disciplines who are interested in interdisciplinary issues in the field of digitalization in healthcare are also invited. Contributions may use different methodological approaches (qualitative, quantitative, or mixed methods). A reflection on the societal, social, and ethical implications of digital health applications is desired.

Prof. Dr. Birgit Babitsch
Prof. Dr. Ursula Hertha Hübner, FIAHSI
Guest Editors

Manuscript Submission Information

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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. Healthcare is an international peer-reviewed open access semimonthly 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 2700 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

  • learning health systems
  • unbiased data
  • explainable artificial intelligence
  • clinical decision support
  • shared decision making
  • patient–provider relationship
  • interprofessional cooperation
  • workflows and information
  • continuity across settings
  • patient reported outcomes
  • quality of care
  • rural and remote areas
  • underserved populations
  • digital divide
  • socially deprived populations
  • equal and ethical care
  • evaluation

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Published Papers (9 papers)

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10 pages, 234 KiB  
Article
Comparing Conventional Physician-Led Education with VR Education for Pacemaker Implantation: A Randomized Study
by Adela Drozdova, Karin Polokova, Otakar Jiravsky, Bogna Jiravska Godula, Jan Chovancik, Ivan Ranic, Filip Jiravsky, Jan Hecko and Libor Sknouril
Healthcare 2024, 12(10), 976; https://doi.org/10.3390/healthcare12100976 - 9 May 2024
Viewed by 1004
Abstract
Introduction: Education of patients prior to an invasive procedure is pivotal for good cooperation and knowledge retention. Virtual reality (VR) is a fast-developing technology that helps educate both medical professionals and patients. Objective: To prove non-inferiority of VR education compared to conventional education [...] Read more.
Introduction: Education of patients prior to an invasive procedure is pivotal for good cooperation and knowledge retention. Virtual reality (VR) is a fast-developing technology that helps educate both medical professionals and patients. Objective: To prove non-inferiority of VR education compared to conventional education in patients prior to the implantation of a permanent pacemaker (PPM). Methods: 150 participants scheduled for an elective implantation of a PPM were enrolled in this prospective study and randomized into two groups: the VR group (n = 75) watched a 360° video about the procedure using the VR headset Oculus Meta Quest 2, while the conventional group (n = 75) was educated by a physician. Both groups filled out a questionnaire to assess the quality of education pre- and in-hospital, their knowledge of the procedure, and their subjective satisfaction. Results: There was no significant difference in the quality of education. There was a non-significant trend towards higher educational scores in the VR group. The subgroup with worse scores was older than the groups with higher scores (82 vs. 76 years, p = 0.025). Anxiety was reduced in 92% of participants. Conclusion: VR proved to be non-inferior to conventional education. It helped to reduce anxiety and showed no adverse effects. Full article
(This article belongs to the Special Issue Healthcare in Digital Environments: An Interdisciplinary Perspective)
21 pages, 1667 KiB  
Article
Examining the Use of Autonomous Systems for Home Health Support Using a Smart Mirror
by Liz Dowthwaite, Gisela Reyes Cruz, Ana Rita Pena, Cecily Pepper, Nils Jäger, Pepita Barnard, Ann-Marie Hughes, Roshan das Nair, David Crepaz-Keay, Sue Cobb, Alexandra Lang and Steve Benford
Healthcare 2023, 11(19), 2608; https://doi.org/10.3390/healthcare11192608 - 22 Sep 2023
Viewed by 1838
Abstract
The home is becoming a key location for healthcare delivery, including the use of technology driven by autonomous systems (AS) to monitor and support healthcare plans. Using the example of a smart mirror, this paper describes the outcomes of focus groups with people [...] Read more.
The home is becoming a key location for healthcare delivery, including the use of technology driven by autonomous systems (AS) to monitor and support healthcare plans. Using the example of a smart mirror, this paper describes the outcomes of focus groups with people with multiple sclerosis (MS; n = 6) and people who have had a stroke (n = 15) to understand their attitudes towards the use of AS for healthcare in the home. Qualitative data were analysed using a thematic analysis. The results indicate that the use of such technology depends on the level of adaptability and responsiveness to users’ specific circumstances, including their relationships with the healthcare system. A smart mirror would need to support manual entry, responsive goal setting, the effective aggregation of data sources and integration with other technology, have a range of input methods, be supportive rather than prescriptive in messaging, and give the user full control of their data. The barriers to its adoption include a perceived lack of portability and practicality, a lack of accessibility and inclusivity, a sense of redundancy, feeling overwhelmed by multiple technological devices, and a lack of trust in data sharing. These results inform the development and deployment of future health technologies based on the lived experiences of people with health conditions who require ongoing care. Full article
(This article belongs to the Special Issue Healthcare in Digital Environments: An Interdisciplinary Perspective)
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<p>Screenshot from the positive-scenario video.</p>
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<p>Screenshot from the negative-scenario video.</p>
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<p>Summary of the themes and subthemes developed from the focus groups. Subthemes that spread across both groups horizontally refer to those found in both participant groups and subthemes placed under one group only represent group-specific subthemes.</p>
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<p>Design recommendations. A smart-mirror design needs to consider “soft skills”, “data input”, and “data management”, as well as the placement of the smart mirror in “physical space”.</p>
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12 pages, 1159 KiB  
Article
Establishing a Centralized Virtual Visit Support Team: Early Insights
by James McElligott, Ryan Kruis, Elana Wells, Peter Gardella, Bryna Rickett, Joy Ross, Emily Warr and Jillian Harvey
Healthcare 2023, 11(16), 2230; https://doi.org/10.3390/healthcare11162230 - 8 Aug 2023
Cited by 1 | Viewed by 1372
Abstract
Background: With the removal of many barriers to direct-to-consumer telehealth during the COVID-19 pandemic, which resulted in a historic surge in the adoption of telehealth into ongoing practice, health systems must now identify the most efficient and effective way to sustain these visits. [...] Read more.
Background: With the removal of many barriers to direct-to-consumer telehealth during the COVID-19 pandemic, which resulted in a historic surge in the adoption of telehealth into ongoing practice, health systems must now identify the most efficient and effective way to sustain these visits. The Medical University of South Carolina Center for Telehealth developed a Telehealth Centralized Support team as part of a strategy to mature the support infrastructure for the continued large-scale use of outpatient virtual care. The team was deployed as the Center for Telehealth rolled out a new ambulatory telehealth software platform to monitor clinical activity, support patient registration and virtual rooming, and ensure successful visit completion. Methods: A multi-method, program-evaluation approach was used to describe the development and composition of the Telehealth Centralized Support Team in its first 18 months utilizing the Reach, Effectiveness, Adoption, Implementation, Maintenance framework. Results: In the first 18 months of the Telehealth Centralized Support team, over 75,000 visits were scheduled, with over 1500 providers serving over 46,000 unique patients. The team was successfully deployed over a large part of the clinical enterprise and has been well received across the health system. It has proven to be a scalable model to support enterprise-level virtual health care delivery. Conclusions: While further research is needed to evaluate the long-term program outcomes, the results of its early implementation suggest great promise for improved telehealth patient and provider satisfaction, the more equitable delivery of virtual services, and more cost-effective means for supporting virtual care. Full article
(This article belongs to the Special Issue Healthcare in Digital Environments: An Interdisciplinary Perspective)
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<p>Telehealth claims as a percentage of all claims (data provided by FAIRHealth Regional Telehealth Tracker [<a href="#B2-healthcare-11-02230" class="html-bibr">2</a>]).</p>
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<p>Organizational Reporting Structure of TCS Team Members. Note: Descriptions of team roles are included in <a href="#healthcare-11-02230-t002" class="html-table">Table 2</a>.</p>
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<p>Growth of TCS-supported Visits.</p>
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<p>TCS volumes by hour/day.</p>
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<p>Virtual visit loss rates.</p>
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16 pages, 1315 KiB  
Article
Interviews with HIV Experts for Development of a Mobile Health Application in HIV Care—A Qualitative Study
by Jannik Schaaf, Timm Weber, Michael von Wagner, Christoph Stephan, Jonathan Carney, Susanne Maria Köhler, Alexander Voigt, Richard Noll, Holger Storf and Angelina Müller
Healthcare 2023, 11(15), 2180; https://doi.org/10.3390/healthcare11152180 - 1 Aug 2023
Cited by 2 | Viewed by 1988
Abstract
The Communication and Tracing App HIV (COMTRAC-HIV) project aims to develop a mobile health application for integrated care of HIV patients due to the low availability of those apps in Germany. This study addressed organizational conditions and necessary app functionalities, especially for the [...] Read more.
The Communication and Tracing App HIV (COMTRAC-HIV) project aims to develop a mobile health application for integrated care of HIV patients due to the low availability of those apps in Germany. This study addressed organizational conditions and necessary app functionalities, especially for the care of late diagnosed individuals (late presenters) and those using pre-exposure prophylaxis. We followed a human-centered design approach and interviewed HIV experts in Germany to describe the context of use of the app. The interviews were paraphrased and analyzed with a qualitative content analysis. To define the context of use, user group profiles were defined and tasks derived, which will represent the functionalities of the app. A total of eight experts were included in the study. The results show that the app should include a symptom diary for entering symptoms, side effects, and their intensity. It offers chat/video call functionality for communication with an HIV expert, appointment organization, and sharing findings. The app should also provide medication overview and reminders for medications and appointments. This qualitative study is a first step towards the development of an app for HIV individuals in Germany. Further research includes involving patients in the initial app design and test design usability. Full article
(This article belongs to the Special Issue Healthcare in Digital Environments: An Interdisciplinary Perspective)
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<p>Human-centered design according to the “ISO 9241-210:2019 Ergonomics of human-system interaction–Part 210: Human centered design for interactive systems” [<a href="#B33-healthcare-11-02180" class="html-bibr">33</a>,<a href="#B34-healthcare-11-02180" class="html-bibr">34</a>].</p>
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<p>Steps performed in this study according to Geis and Polekehn [<a href="#B33-healthcare-11-02180" class="html-bibr">33</a>].</p>
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<p>Overview of tasks for the COMTRAC-HIV app.</p>
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47 pages, 17581 KiB  
Article
Impact of a Digital Tool on Pharmacy Students’ Ability to Perform Medication Reviews: A Randomized Controlled Trial
by Armin Dabidian, Emina Obarcanin, Bushra Ali Sherazi, Sabina Schlottau, Holger Schwender and Stephanie Laeer
Healthcare 2023, 11(13), 1968; https://doi.org/10.3390/healthcare11131968 - 7 Jul 2023
Cited by 4 | Viewed by 1642
Abstract
Digital Medication Review Tools (DMRTs) are increasingly important in pharmacy practice. To ensure that young pharmacists are sufficiently competent to perform medication reviews after graduation, the introduction of DMRTs teaching in academic education is necessary. The aim of our study was to demonstrate [...] Read more.
Digital Medication Review Tools (DMRTs) are increasingly important in pharmacy practice. To ensure that young pharmacists are sufficiently competent to perform medication reviews after graduation, the introduction of DMRTs teaching in academic education is necessary. The aim of our study was to demonstrate the effect of DMRTs use on pharmacy students’ performance when conducting a medication review (MR) in a randomized controlled pre-post design. Forty-one pharmacy students were asked to complete a MR within 60 min, followed by a 10-min consultation with (intervention group) and without a DMRT (control group). The MR performance was subdivided into four categories: communication skills, subjective and objective patient data, assessment, and plan. Performance was assessed using objective structured clinical examinations (OSCEs) and analytical checklists. With the use of DMRTs, the overall performance was improved by 17.0% compared to the control group (p < 0.01). Improvement through DMRTs was seen in the subcategories “Assessment” and “Plan”. Furthermore, pharmacy students liked using DMRTs and felt more confident overall. Our study results demonstrate that DMRTs improve the performance of MRs, hence DMRTs should become an integral part of pharmacy curriculum. Consequently, digitally enabled pharmacists using DMRTs will be better prepared for their professional careers in pharmacy practice. Full article
(This article belongs to the Special Issue Healthcare in Digital Environments: An Interdisciplinary Perspective)
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<p>Study procedure and time-schedule. OSCE = objective structured clinical examination.</p>
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<p>Overall performance in the first and second OSCE measured by an analytic checklist. Horizontal line = median; (*) = outlier.</p>
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<p>Performance development for the control and the intervention groups between the first and the second OSCE. Performance development was generated by subtracting participants’ performance on the second OSCE with their performance on the first OSCE. Horizontal line = median.</p>
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<p>Performance of the first and second OSCE in the subcategory “Assessment”. Horizontal line = median; (*) = outlier.</p>
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<p>Performance of the first and second OSCE in the subcategory “Plan”. Horizontal line = median; (*) = outlier.</p>
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<p>Display of the results of the questionnaire in a forest plot. The box represents the arithmetic mean. The horizontal lines to the left and right of the box indicate the 95% confidence interval. Consensus on a statement is reached when the confidence interval does not intersect the vertical line on 3 of the X-axis of the forest plot. While consensus was reached on all statements for the intervention group, no consensus was reached on statements 2, 3, 5, and 6 for the control group.</p>
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<p>Subjective and objective patient data—Patient 1 in the first OSCE.</p>
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<p>Medication schedule—Patient 1 in the first OSCE.</p>
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<p>Subjective and objective patient data—Patient 2 in the first OSCE.</p>
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<p>Medication schedule—Patient 2 in the first OSCE.</p>
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<p>Subjective and objective patient data—Patient 3 in the first OSCE.</p>
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<p>Medication schedule—Patient 3 in the first OSCE.</p>
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<p>Subjective and objective patient data—Patient 4 in the first OSCE.</p>
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<p>Medication schedule—Patient 4 in the first OSCE.</p>
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<p>Subjective and objective patient data—Patient 5 in the second OSCE.</p>
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<p>Medication schedule—Patient 5 in the second OSCE.</p>
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<p>Subjective and objective patient data—Patient 6 in the second OSCE.</p>
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<p>Medication schedule—Patient 6 in the second OSCE.</p>
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<p>Subjective and objective patient data—Patient 7 in the second OSCE.</p>
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<p>Medication schedule—Patient 7 in the second OSCE.</p>
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<p>Subjective and objective patient data—Patient 8 in the second OSCE.</p>
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<p>Medication schedule—Patient 8 in the second OSCE.</p>
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<p>Corresponding OSCE checklist for Patient 1 in the first OSCE.</p>
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<p>Corresponding OSCE checklist for Patient 1 in the first OSCE.</p>
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<p>Corresponding OSCE checklist for Patient 2 in the first OSCE.</p>
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<p>Corresponding OSCE checklist for Patient 2 in the first OSCE.</p>
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<p>Corresponding OSCE checklist for Patient 3 in the first OSCE.</p>
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<p>Corresponding OSCE checklist for Patient 3 in the first OSCE.</p>
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<p>Corresponding OSCE checklist for Patient 4 in the first OSCE.</p>
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<p>Corresponding OSCE checklist for Patient 4 in the first OSCE.</p>
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<p>Corresponding OSCE checklist for Patient 5 in the second OSCE.</p>
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<p>Corresponding OSCE checklist for Patient 5 in the second OSCE.</p>
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<p>Corresponding OSCE checklist for Patient 6 in the second OSCE.</p>
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<p>Corresponding OSCE checklist for Patient 6 in the second OSCE.</p>
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<p>Corresponding OSCE checklist for Patient 7 in the second OSCE.</p>
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<p>Corresponding OSCE checklist for Patient 7 in the second OSCE.</p>
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<p>Corresponding OSCE checklist for Patient 8 in the second OSCE.</p>
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<p>Corresponding OSCE checklist for Patient 8 in the second OSCE.</p>
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13 pages, 1779 KiB  
Article
Digital Patient-Reported Outcome Measures Assessing Health-Related Quality of Life in Skull Base Diseases—Analysis of Feasibility and Pitfalls Two Years after Implementation
by Christine Steiert, Johann Lambeck, Tanja Daniela Grauvogel, Juergen Beck and Juergen Grauvogel
Healthcare 2023, 11(4), 472; https://doi.org/10.3390/healthcare11040472 - 6 Feb 2023
Cited by 1 | Viewed by 1338
Abstract
Health-related quality of life (HRQoL) assessment is becoming increasingly important in neurosurgery following the trend toward patient-centered care, especially in the context of skull base diseases. The current study evaluates the systematic assessment of HRQoL using digital patient-reported outcome measures (PROMs) in a [...] Read more.
Health-related quality of life (HRQoL) assessment is becoming increasingly important in neurosurgery following the trend toward patient-centered care, especially in the context of skull base diseases. The current study evaluates the systematic assessment of HRQoL using digital patient-reported outcome measures (PROMs) in a tertiary care center specialized in skull base diseases. The methodology and feasibility to conduct digital PROMs using both generic and disease-specific questionnaires were investigated. Infrastructural and patient-specific factors affecting participation and response rates were analyzed. Since August 2020, 158 digital PROMs were implemented in skull base patients presenting for specialized outpatient consultations. Reduced personnel capacity led to significantly fewer PROMs being conducted during the second versus (vs.) the first year after introduction (mean: 0.77 vs. 2.47 per consultation day, p = 0.0002). The mean age of patients not completing vs. those completing long-term assessments was significantly higher (59.90 vs. 54.11 years, p = 0.0136). Follow-up response rates tended to be increased with recent surgery rather than with the wait-and-scan strategy. Our strategy of conducting digital PROMs appears suitable for assessing HRQoL in skull base diseases. The availability of medical personnel for implementation and supervision was essential. Response rates during follow-up tended to be higher both with younger age and after recent surgery. Full article
(This article belongs to the Special Issue Healthcare in Digital Environments: An Interdisciplinary Perspective)
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<p>Availability of PROMs within 2 years after implementation, participation rate, and reasons for non-participation. Numbers in white/gray = number of patients (each left circle) who participated (orange) or did not participate (dark blue), or number of patients subdivided according to reasons for non-participation (each right circle).</p>
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<p>Analysis of the conduction of PROMs in relation to the COVID-19 pandemic. no. = number, * = statistically significant difference (<span class="html-italic">p</span> &lt; 0.05), (<b>A</b>,<b>B</b>): Comparison of the mean number (with standard deviation) of (<b>A</b>) consultations per “skull base consultation day” (SBCD) or of (<b>B</b>) completed PROMs per SBCD (in relation to the total of 96 SBCDs), illustrated for the 13 months during COVID-19 waves (“all waves” or subdivided into “second wave” (2nd wave), “third wave” (3rd wave), and “fourth wave” (4th wave)) and the 11 months beyond COVID-19 waves (“no wave”), and illustrated for the “first year” (1st year) and “second year “ (2nd year) after implementation of PROMs.</p>
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<p>Evaluation of the response rate to PROMs depending on subgroup and neurosurgical procedure. ALL = total group, AMSB = subgroup “anterior and middle skull base”, CPA = subgroup “cerebellopontine angle”, NVC = subgroup “neurovascular conflict”, no. = number, T1 = initial assessment, T2 = follow-up assessment after 3 months, T3 = follow-up assessment after 12 months, “surgery after T1” = surgical treatment was performed after the initial assessment and before the follow-up assessment after 3 months, “wait-and-scan” = wait-and-scan strategy, “surgery before T1” = surgical treatment had already been performed before the initial assessment. (<b>A</b>): Number of completed assessments T1, T2, and T3 according to the neurosurgical procedure among ALL. (<b>B</b>): Number of completed assessments T1, T2, and T3 according to the neurosurgical procedure among AMSB (<b>B1</b>), CPA (<b>B2</b>), and NVC (<b>B3</b>).</p>
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<p>Evaluation of the response rate to PROMs depending on age. (group) ALL = total group, (subgroup) AMSB = subgroup “anterior and middle skull base”, (subgroup) CPA = subgroup “cerebellopontine angle”, (subgroup) NVC = subgroup “neurovascular conflict”, T1 completed/T1 pos = completed initial assessments T1, T2/T3 pos = completed follow-up assessments T2/T3, T2/T3 neg = not-completed follow-up assessments T2/T3, * = statistically significant difference (<span class="html-italic">p</span> &lt; 0.05). (<b>A</b>): Comparison of the mean age of the total group and the subgroups AMSB, CPA, and NVC at initial participation (T1), presented as median values (black horizontal lines) with 25–75% percentiles (colored box) and minimum/maximum (black vertical lines). (<b>B</b>,<b>C</b>): Comparison of the mean age of participants who completed T1 (T1 pos), T2 (T2 pos), and T3 (T3 pos) and those who did not complete T2 (T2 neg) or T3 (T3 neg) (values presented the same as in “(<b>A</b>)”) according to the total group (<b>B</b>) or the subgroups AMSB (<b>C1</b>), CPA (<b>C2</b>), or NVC (<b>C3</b>).</p>
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<p>Evaluation of the response rate to PROMs depending on gender. ALL = total group, AMSB = subgroup “anterior and middle skull base”, CPA = subgroup “cerebellopontine angle”, NVC = subgroup “neurovascular conflict”, no. = number, T1 = initial assessment, T2 = follow-up assessment after 3 months, T3 = follow-up assessment after 12 months. (<b>A</b>,<b>B</b>): Number of completed assessments T1, T2, and T3 in relation to gender among ALL (<b>A</b>) and the subgroups AMSB (<b>B1</b>), CPA (<b>B2</b>), or NVC (<b>B3</b>) (the proportion of completed T2/T3 assessments in relation to the corresponding number of T1 assessments, sorted by gender, is presented as a percentage).</p>
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11 pages, 2372 KiB  
Article
Implementation and Evaluation of Two Nudges in a Hospital’s Electronic Prescribing System to Optimise Cost-Effective Prescribing
by Saval Khanal, Kelly Ann Schmidtke, Usman Talat, Asif Sarwar and Ivo Vlaev
Healthcare 2022, 10(7), 1233; https://doi.org/10.3390/healthcare10071233 - 1 Jul 2022
Cited by 2 | Viewed by 2273
Abstract
Providing healthcare workers with cost information about the medications they prescribe can influence their decisions. The current study aimed to analyse the impact of two nudges that presented cost information to prescribers through a hospital’s electronic prescribing system. The nudges were co-created by [...] Read more.
Providing healthcare workers with cost information about the medications they prescribe can influence their decisions. The current study aimed to analyse the impact of two nudges that presented cost information to prescribers through a hospital’s electronic prescribing system. The nudges were co-created by the research team: four behavioural scientists and the lead hospital pharmacist. The nudges were rolled out sequentially. The first nudge provided simple cost information (percentage cost-difference between two brands of mesalazine: Asacol® and Octasa®). The second nudge provided information about the potential annual cost savings if the cheaper medication were selected across the National Health Service. Neither nudge influenced prescribing. Prescribing of Asacol® and Octasa® at baseline and during the implementation of the first nudge did not differ (at p ≥ 0.05), nor was there a difference between the first nudge and second (at p ≥ 0.05). Although these nudges were not effective, notable administrative barriers were overcome, which may inform future research. For example, although for legal reasons the cost of medicine cannot be displayed, we were able to present aggregated cost information to the prescribers. Future research could reveal more behavioural factors that facilitate medication optimisation. Full article
(This article belongs to the Special Issue Healthcare in Digital Environments: An Interdisciplinary Perspective)
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<p>The cost information used as the nudges to promote cost-effective prescribing.</p>
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<p>Nudge presented in the PICS prescribing system.</p>
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<p>The trend of prescription of Asacol<sup>®</sup> prior to and during the implementation of intervention 1. Note: The first panel shows the data and a counterfactual prediction for the post-treatment period. The second panel shows the difference between observed data and counterfactual predictions. This is the pointwise causal effect, as estimated by the model. The third panel adds up the pointwise contributions from the second panel, resulting in a plot of the cumulative effect of the intervention.</p>
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<p>Trend of prescription of Asacol<sup>®</sup> post intervention 1 and post intervention 2. Note: The first panel shows the data and a counterfactual prediction for the post-treatment period. The second panel shows the difference between observed data and counterfactual predictions. This is the pointwise causal effect, as estimated by the model. The third panel adds up the pointwise contributions from the second panel, resulting in a plot of the cumulative effect of the intervention.</p>
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<p>The trend of prescription of Octasa<sup>®</sup> prior to and during the implementation of intervention 1. Note: The first panel shows the data and a counterfactual prediction for the post-treatment period. The second panel shows the difference between observed data and counterfactual predictions. This is the pointwise causal effect, as estimated by the model. The third panel adds up the pointwise contributions from the second panel, resulting in a plot of the cumulative effect of the intervention.</p>
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<p>The trend of prescription of Octasa<sup>®</sup> post intervention 1 and post intervention 2. Note: The first panel shows the data and a counterfactual prediction for the post-treatment period. The second panel shows the difference between observed data and counterfactual predictions. This is the pointwise causal effect, as estimated by the model. The third panel adds up the pointwise contributions from the second panel, resulting in a plot of the cumulative effect of the intervention.</p>
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7 pages, 210 KiB  
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Digital Biobanking and Big Data as a New Research Tool: A Position Paper
by Pamela Tozzo, Arianna Delicati, Beatrice Marcante and Luciana Caenazzo
Healthcare 2023, 11(13), 1825; https://doi.org/10.3390/healthcare11131825 - 22 Jun 2023
Cited by 8 | Viewed by 1728
Abstract
Big data analytics in medicine is driving significant change, as it offers vital information for improving functions, developing cutting-edge solutions and overcoming inefficiencies. With the right archiving and analysis tools, all players in the healthcare system, from hospitals to patients and from medical [...] Read more.
Big data analytics in medicine is driving significant change, as it offers vital information for improving functions, developing cutting-edge solutions and overcoming inefficiencies. With the right archiving and analysis tools, all players in the healthcare system, from hospitals to patients and from medical personnel to the pharmaceutical industry, can yield numerous benefits. Therefore, to analyze and interpret these analytics effectively, so that they can be useful for the advancement of scientific knowledge, we require information sharing, specific skills, training, integration between all system players, unique infrastructures and security. All these characteristics will make it possible to establish and harmonize real big data biobanks, for which it will be appropriate to consider new forms of governance compared to those traditionally conceived for large-sample biobanks. Full article
(This article belongs to the Special Issue Healthcare in Digital Environments: An Interdisciplinary Perspective)
11 pages, 1256 KiB  
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Proposing a Scientific and Technological Approach to the Summaries of Clinical Issues of Inpatient Elderly with Delirium: A Viewpoint
by Vincenza Frisardi, Matteo Nicolini, Nicola Cautero, Remo Ghirardelli, Federica Davolio, Mohamad Haouili and Mauro Barani
Healthcare 2022, 10(8), 1534; https://doi.org/10.3390/healthcare10081534 - 13 Aug 2022
Cited by 2 | Viewed by 2224
Abstract
Background/rationale: Despite mounting evidence about delirium, this complex geriatric syndrome is still not well managed in clinical contexts. The aging population creates a very demanding area for innovation and technology in healthcare. For instance, an outline of an aging-friendly healthcare environment and clear [...] Read more.
Background/rationale: Despite mounting evidence about delirium, this complex geriatric syndrome is still not well managed in clinical contexts. The aging population creates a very demanding area for innovation and technology in healthcare. For instance, an outline of an aging-friendly healthcare environment and clear guidance for technology-supported improvements for people at delirium risk are lacking. Objective: We aimed to foster debate about the importance of technical support in optimizing healthcare professional practice and improving the outcomes for inpatients’ at delirium risk. We focused on critical clinical points in the field of delirium worthy of being addressed by a multidisciplinary approach. Methods: Starting from a consensus workshop sponsored by the Management Perfectioning Course based at the Marco Biagi Foundation (Modena, Italy) about clinical issues related to delirium management still not addressed in our healthcare organizations, we developed a requirements’ analysis among the representatives of different disciplines and tried to formulate how technology could support the summaries of the clinical issues. We analyzed the national and international panorama by a PubMed consultation of articles with the following keywords in advanced research: “delirium”, “delirium management”, “technology in healthcare”, and “elderly population”. Results: Despite international recommendations, delirium remains underdiagnosed, underdetected, underreported, and mismanaged in the acute hospital, increasing healthcare costs, healthcare professionals’ job distress, and poor clinical outcomes. Discussion: Although all healthcare professionals recognize delirium as a severe and potentially preventable source of morbidity and mortality for hospitalized older people, it receives insufficient attention in resource allocation and multidisciplinary research. We synthesized how tech-based tools could offer potential solutions to the critical clinical points in delirium management. Full article
(This article belongs to the Special Issue Healthcare in Digital Environments: An Interdisciplinary Perspective)
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Graphical abstract

Graphical abstract
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<p>The wall of clinical issues about delirium. Phenomenologically, delirium shows five features: cognitive deficits, attentional deficits, circadian rhythm dysregulation, emotional dysregulation, and psychomotor dysregulation. Phenotypically, there are at least five types of delirium. Healthcare organizations may exacerbate the trigger point’s load with clinical issues that persist despite the increased academic knowledge on this hot topic.</p>
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<p>Technology advances could be useful to support clinicians in their activity thanks to the application of digital devices for telemedicine or tech-based intervention for monitoring, prevention, education, and clinical management of delirium. The importance of technology application comes from the lack of biomarkers for delirium diagnosis, and this determines the underestimation and undertreatment of this impacting syndrome. Technology sprouting will guarantee overcoming logistic obstacles to an aging-friendly environment realization in the healthcare setting, reducing the stress of healthcare workers when they deal with patients developing delirium.</p>
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<p>In a highly organized healthcare organization that is equipped with a delirium unit, within a well-codified PDTA (pathway for diagnosis, treatment, and assistance), delirium care management is characterized by several CCPs (critical clinical points). In the boxes, we report what the CCPs are and the criticism about what is the actual practice by suggesting possible solutions in the parentheses. At hospital admission, the lack of good documentation about the vulnerability of patients increases the risk to expose the elderly to the potential contributing factors precipitating delirium. Elderly patients with behavioral disorders are at risk of being diagnosed with dementia if personnel are not trained to recognize delirium. Sometimes, delirium occurs also in younger people, and they are managed in not-appropriate settings (delirium is mistaken for psychosis). Discharge is another critical point during the “hospital delirium journey”. In the end, people affected by delirium do have not a robust supporting network and they are lost at the follow-up. Therefore, the risk of cognitive decline is not promptly addressed.</p>
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