AI Article Synopsis
- - This study investigates the factors influencing the adoption of a virtual reality tool for pain management in a Swiss university hospital's emergency department, emphasizing the need to balance effective treatment with the practicalities of clinical application.
- - Key facilitators for adoption identified include supportive organizational environment, ease of use and clarity of benefits, and engagement from healthcare employees, while barriers consist of increased workloads, disruptions to current clinical practices, and reimbursement issues.
- - The findings suggest that despite a strong desire for improved pain management solutions, successful integration of VR tools hinges on fostering a conducive organizational culture and addressing reimbursement challenges.
Article Abstract
Background: Pain and its adequate treatment are an issue in hospitals and emergency departments (EDs). A virtual reality (VR) tool to manage pain could act as a valuable complement to common pharmaceutical analgesics. While efficacy could be shown in previous studies, this does not assure clinical adoption in EDs.
Objective: The main aim of this study was to investigate which factors affect the adoption and potential reimbursement of a VR tool for pain management in the ED of a Swiss university hospital.
Methods: Key informant interviews were conducted using in-depth semistructured interviews with 11 participants reflecting the perspectives of all the relevant stakeholder groups, including physicians, nurses, patients, health technology providers, and health insurance and reimbursement experts. The interviews were recorded and transcribed, and the extracted data were systematically analyzed using a thematic analysis and narrative synthesis of emergent themes. A consolidated framework for eHealth adoption was used to enable a systematic investigation of the topic and help determine which adoption factors are considered as facilitators or barriers or as not particularly relevant for the tool subject of this study.
Results: According to the participants, the three key facilitators are (1) organizational environment; (2) tension for change, ease of use, and demonstrability; and (3) employee engagement. Further, the three key barriers to adoption are (1) workload, (2) changes in clinical workflow and habit, and (3) reimbursement.
Conclusions: This study concludes that the adoption of a VR tool for pain management in the ED of the hospital subject of this study, although benefiting from a high tension for change in pain and workload management, is highly dependent on the respective organizational environment, engagement of the clinical staff, and reimbursement considerations. While tailored incentive structures and ambassador roles could benefit initial adoption, a change in the reimbursement landscape and further investigation of the positive effects on workflow effectiveness are required to drive long-term adoption.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11634046 | PMC |
| http://dx.doi.org/10.2196/59073 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Dissemination of Decision Aids about Hip and Knee Osteoarthritis to Spanish-Speaking Adults through Social Media.
MDM Policy Pract
January 2025
Department of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA.
Background: Older adults and Hispanic individuals are increasingly turning to social media platforms to access health-related information. The purpose of this project was to evaluate a social media campaign to disseminate information from decision aids (DAs) on hip and knee osteoarthritis to Spanish-speaking adults.
Methods: A social media marketing team helped create an 8-mo campaign posted across 3 social media platforms to promote visits to a Web site offering free multilingual DAs for treatment of hip or knee osteoarthritis.
The shoulder joint complex is prone to musculoskeletal issues, such as rotator cuff-related pain, which affect two-thirds of adults and often result in suboptimal treatment outcomes. Current musculoskeletal models used to understand shoulder biomechanics are limited by challenges in personalization, inaccuracies in predicting joint and muscle loads, and an inability to simulate anatomically accurate motions. To address these deficiencies, we developed a novel, personalized modeling framework capable of calibrating subject-specific joint centers and functional axes for the shoulder complex.
View Article and Find Full Text PDFBackground: Contamination of sterilized surgical instruments is not a typically suspected source of increased infection rate, especially if no abnormalities in the sterilization process are detected.
Purpose/hypothesis: The purpose of this study was to report increased infection rates after knee ligament reconstructions due to undetectable sterilization process errors leading to residual moisture, not limited to a specific surgical tool. It was hypothesized that (1) residual moisture on surgical tools due to autoclave overloading would not be detected by autoclave self-diagnostics, chemical and biological tests, or organoleptic assessment and (2) this kind of contamination may elevate infection rates, especially in knee intra-articular reconstruction procedures.
The development of a decision support tool in the prehospital setting for acute chest pain - a study protocol for an observational study (BRIAN2).
Scand J Trauma Resusc Emerg Med
January 2025
PreHospen-Centre for Prehospital Research, Faculty of Caring Science, Work Life and Social Welfare, University of Borås, Borås, Sweden.
Introduction: Chest pain is one of the most common reasons for contacting the emergency medical services (EMS). It is difficult for EMS personnel to distinguish between patients suffering from a high-risk condition in need of prompt hospital care and patients suitable for non-conveyance. A vast majority of patients with chest pain are therefore transported to the emergency department (ED) for further investigation even if hospital care is not necessary.
View Article and Find Full Text PDFTesting Machine Learning-Based Pain Assessment for Postoperative Geriatric Patients.
Comput Inform Nurs
January 2025
Author Affiliations: Zonguldak Atatürk State Hospital (Dr Alkan); and Faculty of Health Sciences, Department of Nursing, Zonguldak Bülent Ecevit University (Dr Taşdemir), Zonguldak, Turkey.
The global population is aging, and there is a concomitant increase in surgery for the elderly. In geriatric patients, where postoperative pain assessment is difficult, technological tools that perform automatic pain assessment are needed to alleviate the workload of nurses and to accurately assess patients' pain. This study offers a more reliable and rapid assessment tool for assessing the pain of elderly patients undergoing surgery.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!