Dataset Information

Improving the introduction of telemedicine in pre-hospital emergency medicine: understanding users and how acceptability, usability and effectiveness influence this process.

ABSTRACT:

Introduction

Increasing numbers of ambulance calls, vacant positions and growing workloads in Emergency Medicine (EM) are increasing the pressure to find adequate solutions. With telemedicine providing health-care services by bridging large distances, connecting remote providers and even patients while using modern communication technologies, such a technology seems beneficial. As the process of developing an optimal solution is challenging, a need to quantify involved processes could improve implementation. Existing models are based on qualitative studies although standardised questionnaires for factors such as Usability, Acceptability and Effectiveness exist.

Methods

A survey was provided to participants within a German county. It was based on telemedical surveys, the System Usabilty Scale (SUS) and earlier works describing Usability, Acceptability and Effectiveness. Meanwhile a telemedical system was introduced in the investigated county. A comparison between user-groups aswell as an exploratory factor analysis (EFA) was performed.

Results

Of n = 91 included participants n = 73 (80,2%) were qualified as emergency medical staff (including paramedics n = 36 (39,56%), EMTs n = 28 (30,77%), call handlers n = 9 (9,89%)) and n = 18 (19,8%) as emergency physicians. Most participants approved that telemedicine positively impacts EM and improved treatment options with an overall Usabilty Score of 68,68. EFA provided a 3-factor solution involving Usability, Acceptability and Effectiveness.

Discussion

With our results being comparable to earlier studies but telemedicine only having being sparsely introduced, a positive attitude could still be attested. While our model describes 51,28% of the underlying factors, more research is needed to identify further influences. We showed that Usability is correlated with Acceptability (strong effect), Usability and Effectiveness with a medium effect, likewise Acceptability and Effectiveness. Therefore available systems need to improve. Our approach can be a guide for decision makers and developers, that a focus during implementation must be on improving usability and on a valid data driven implementation process.

SUBMITTER: O'Sullivan S

PROVIDER: S-EPMC11241972 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature

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Publications

Improving the introduction of telemedicine in pre-hospital emergency medicine: understanding users and how acceptability, usability and effectiveness influence this process.

O'Sullivan Seán S Krautwald Jennifer J Schneider Henning H

BMC emergency medicine 20240712 1

<h4>Introduction</h4>Increasing numbers of ambulance calls, vacant positions and growing workloads in Emergency Medicine (EM) are increasing the pressure to find adequate solutions. With telemedicine providing health-care services by bridging large distances, connecting remote providers and even patients while using modern communication technologies, such a technology seems beneficial. As the process of developing an optimal solution is challenging, a need to quantify involved processes could im ...[more]

PMID: 38992613

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Project description:IntroductionPrevious studies have shown that patients in the emergency department (ED) are frequently given incomplete discharge instructions that are written at least four grade levels above the recommended sixth-grade reading level, leading to poor understanding. Our aims in this study were to implement standardized discharge instructions containing six key components written at a more appropriate reading level for common emergency department (ED) diagnoses to improve patient understanding.MethodsWe conducted this study in a 20-bed ED at an urban Veteran's Administration hospital. Data was collected via in-person patient and clinician interviews. Patient interviews were conducted after patients received their discharge instructions. We compared patient responses to clinician responses and marked them as incorrect, partially correct, or correct with a score of 0, 0.5, or 1, respectively. The maximum possible score for each interview was six. Six key components of discharge instructions were asked about: diagnosis; new medications; at-home care; duration of illness; reasons to return; and follow-up. There were 25 patients in the pre-intervention group and 20 in the intervention group with the standardized set of instructions. We performed a Mann-Whitney U test on the total interview scores in the control and intervention groups and conducted a sub-analysis on the individual scores for each of the six key components.ResultsThe patients in the intervention demonstrated a statistically significant increase in patient-clinician correlation when compared to the patients in the pre-intervention group overall (P < 0.05), and two of the six key components of the discharge instructions individually showed statistically significant increase in patient-clinician correlation when standardized discharge instructions were used.ConclusionPatients who received the standardized discharge instructions had improved understanding of their discharge instructions. Future opportunities extending off this pilot study include expanding the number of diagnoses for which standardized instructions are used and investigating patient-centered outcomes related to these instructions.

Project description:BackgroundEmergency medicine (EM) residency interviews are an important, yet costly process for programs and applicants. The total economic burden of the EM interviewing process is previously unstudied. Graduate medical education funding and student finances are both fragile shifting sources, which appear to fund most of these economic expenditures.ObjectivesThe total economic impact of the EM interview season is unknown. This study sought to calculate total dollars spent by EM residency programs and senior medical students (M4) during interview season. Potential solutions for reducing this burden will be outlined.MethodsInstitutional review board-approved, piloted e-mail surveys were sent to accredited (Accreditation Council for Graduate Medical Education [ACGME] and American Osteopathic Association [AOA]) EM program directors (PDs) and M4 student members of EMRA. PDs were queried after the 2014-2015 interview season. PDs questions included demographics, estimated faculty, and resident and administrative time used, along with dollars spent during the 2014-2015 interview season. M4 questions included demographics and dollars spent during the 2015-2016 season. Results were reported using descriptive statistics. Financial data for EM programs were calculated with academic EM faculty, resident, and administrative assistant salaries along with reported hours used during the interview season.ResultsA total of 82 of 223 EM PDs completed the survey, reporting an mean annual cost of $210,649.04 per program to review, screen, and interview applicants based on time spent by faculty, resident, and administrative assistants. A total of 84.6% of EM program costs were due to faculty hours. A total of 180 of 1,425 EM-bound M4 students completed the survey, reporting a mean annual estimate of US$5,065.44 per student to apply and interview. Seventy-two percent of estimated costs were due to airfare and lodging. Loans and credit cards were the top two methods of payments of these interview costs by students. Extrapolating the cost of EM personnel with hours spent, the economic burden of an interview season for EM programs is approximately US$46,974,735.92. M4 students spent US$19,724,823.40 for application fees and interview-related expenses.ConclusionsEmergency medicine residency programs and applicants appear to spend over US$66 million per cycle on the interview process. EM residency programs may save resources by reducing faculty hours associated with the interview process and leveraging administrative and resident resources. Creation of regional or national fixed interview locations may also be appropriate. Applicants may reduce travel costs by participating in video interviews, reducing program applications, and attending regionalized interview days. A full conversation among all specialties and organized medicine needs to take place to reform the systems in place to reduce the economic burden on students and residency programs.

Project description:BackgroundPrehospital telemedicine triage systems combined with machine learning (ML) methods have the potential to improve triage accuracy and safely redirect low-acuity patients from attending the emergency department. However, research in prehospital settings is limited but needed; emergency department overcrowding and adverse patient outcomes are increasingly common.ObjectiveIn this scoping review, we sought to characterize the existing methods for ML-enhanced telemedicine emergency triage. In order to support future research, we aimed to delineate what data sources, predictors, labels, ML models, and performance metrics were used, and in which telemedicine triage systems these methods were applied.MethodsA scoping review was conducted, querying multiple databases (MEDLINE, PubMed, Scopus, and IEEE Xplore) through February 24, 2023, to identify potential ML-enhanced methods, and for those eligible, relevant study characteristics were extracted, including prehospital triage setting, types of predictors, ground truth labeling method, ML models used, and performance metrics. Inclusion criteria were restricted to the triage of emergency telemedicine services using ML methods on an undifferentiated (disease nonspecific) population. Only primary research studies in English were considered. Furthermore, only those studies using data collected remotely (as opposed to derived from physical assessments) were included. In order to limit bias, we exclusively included articles identified through our predefined search criteria and had 3 researchers (DR, JS, and KS) independently screen the resulting studies. We conducted a narrative synthesis of findings to establish a knowledge base in this domain and identify potential gaps to be addressed in forthcoming ML-enhanced methods.ResultsA total of 165 unique records were screened for eligibility and 15 were included in the review. Most studies applied ML methods during emergency medical dispatch (7/15, 47%) or used chatbot applications (5/15, 33%). Patient demographics and health status variables were the most common predictors, with a notable absence of social variables. Frequently used ML models included support vector machines and tree-based methods. ML-enhanced models typically outperformed conventional triage algorithms, and we found a wide range of methods used to establish ground truth labels.ConclusionsThis scoping review observed heterogeneity in dataset size, predictors, clinical setting (triage process), and reported performance metrics. Standard structured predictors, including age, sex, and comorbidities, across articles suggest the importance of these inputs; however, there was a notable absence of other potentially useful data, including medications, social variables, and health system exposure. Ground truth labeling practices should be reported in a standard fashion as the true model performance hinges on these labels. This review calls for future work to form a standardized framework, thereby supporting consistent reporting and performance comparisons across ML-enhanced prehospital triage systems.

Project description:Telemedicine as a technology can support processes in the field of emergency medicine (EM) including therapies and diagnostics, but technically is often based on hardware solutions for local EM structures, especially when involving the field of pre-hospital EM. By developing an open-source, data protection compliant solution (EU GDPR and HIPAA) as well as using standardized web and open-source based technology the Emergency Talk Application (ETA) can be used as a technology that can connect emergency medical providers and include already available regional structures. By actively involving patients and connecting these with emergency or urgent care physicians ETA can be used not only as a teleconsultation system for paramedics and physicians, but in a wider network. Randomised simulation trial, comparing EM scenarios from the field of internal medicine, trauma and neurology. Participants were qualified as certified paramedics or emergency physicians (EP). Paramedics performed as ambulances crews and involved an EP if needed via ETA as Tele-Emergency Physicians (TEP). EP participated from a device of their choice, while being able to stay within their clinical workspace. From 141 scenarios 129 used ETA. Significant differences were found for the length of scenarios, duration of time the TEP was on scene, TEP arrival after scenario start, duration until TEP was called and the duration until a diagnosis was made. Also a strong positive and significant correlation between duration of the scenario and the time a TEP was bound could be described. Telemedicine is a technology that is increasingly used in the field of EM. Improving the use of telemedicine by using up-to date technology while allowing an integration of available technical and human resources is a challenge in the field of emergency medicine especially with its regional but also broad medical variety. When using one technical solution, understanding that different cases need a different medical and also telemedical approach can help in the understanding and improving therapies, diagnostics but also the involved processes and solutions. Such results are not only relevant for healthcare providers but especially by law and decision makers as to which type of solution could be introduced in each regional setting.

Project description:IntroductionPatients who stay in the emergency department (ED) for prolonged periods of time require verification of home medications, a process known as medication reconciliation. The complex nature of medication reconciliation can lead to adverse events and staff dissatisfaction. A multidisciplinary team was formed to improve accuracy, timing, and staff satisfaction with the medication reconciliation process.MethodsBetween November 2021-January 2022, stakeholders were surveyed to identify gaps in the medication reconciliation process. This project implemented education on role-specific tasks, as well as a "Let's chat!" huddle, bringing together the entire care team to perform medication reconciliation. We used real-time evaluations by frontline staff to evaluate effectiveness during plan- do-study-act cycles and obtain feedback. Following the implementation period, stakeholders completed the post-intervention survey between June-July 2022, using a 4-point Likert scale (0 = very dissatisfied to 3 = very satisfied). We calculated the change in staff satisfaction from pre-intervention to post-intervention. Differences in proportions and 95% confidence intervals are reported. This study adhered to the Standards for Quality Improvement Reporting Excellence (SQUIRE 2.0) and followed the Lean Six Sigma rapid cycle process improvement (define-measure-analyze-improve-control).ResultsA total of 111 front-line ED staff (physicians, nurse practitioners, physician assistants, pharmacists, nurses) completed the pre-intervention survey (of 350 ED staff, corresponding to a 31.7% response rate), and 89 stakeholders completed the post-intervention survey (a 25.4% response rate). Subjective feedback from staff identifying causes of low satisfaction with the initial process included the following: complexity of process; unclear delineation of staff roles; time burden to completion; high patient volume; and lack of standardized communication of task completion. Overall satisfaction improved after the intervention. The greatest improvement was seen in the correct medication (difference 20.7%, confidence interval [CI] 6.3-33.9%, P < 0.01), correct dose (25.6%, CI 11.4-38.6%, P < 0.001) and time last taken (24.5%, CI 11.4-37.0%, P < 0.001).ConclusionThere is a steep learning curve to educate multidisciplinary staff on a new process and implement the associated changes. With goals to impact the safety of our patients and reduce negative outcomes, engagement and awareness of the team involved in the medication reconciliation process is critical to improve staff satisfaction.

Dataset Information

Improving the introduction of telemedicine in pre-hospital emergency medicine: understanding users and how acceptability, usability and effectiveness influence this process.

Introduction

Methods

Results

Discussion

Publications

Improving the introduction of telemedicine in pre-hospital emergency medicine: understanding users and how acceptability, usability and effectiveness influence this process.

Similar Datasets

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