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

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.

Digitization of Follow-Up Care in Orthopedic and Trauma Surgery With Video Consultations: Health Economic Evaluation Study From a Health Provider's Perspective.

BACKGROUND: Recommendations for health care digitization as issued with the Riyadh Declaration led to an uptake in telemedicine to cope with the COVID-19 pandemic. Evaluations based on clinical data are needed to support stakeholders' decision-making on the long-term implementation of digital health. OBJECTIVE: This health economic evaluation aims to provide the first German analysis of the suitability of video consultations in the follow-up care of patients in orthopedic and trauma surgery, investigate the financial impact on hospital operations and personnel costs, and provide a basis for decisions on digitizing outpatient care. METHODS: We conducted a randomized controlled trial that evaluated video consultations versus face-to-face consultations in the follow-up care of patients in orthopedic and trauma surgery at a German university hospital. We recruited 60 patients who had previously been treated conservatively or surgically for various knee or shoulder injuries. A digital health app and a browser-based software were used to conduct video consultations. The suitability of telemedicine was assessed using the Telemedicine Satisfaction Questionnaire and the EQ-5D-5L questionnaire. Economic analyses included average time spent by physician per consultation, associated personnel costs and capacities for additional treatable patients, and the break-even point for video consultation software fees. RESULTS: After 4 withdrawals in each arm, data from a total of 52 patients (telemedicine group: n=26; control group: n=26) were used for our analyses. In the telemedicine group, 77% (20/26) of all patients agreed that telemedicine provided for their health care needs, and 69% (18/26) found telemedicine an acceptable way to receive health care services. In addition, no significant difference was found in the change of patient utility between groups after 3 months (mean 0.02, SD 0.06 vs mean 0.07, SD 0.17; P=.35). Treatment duration was significantly shorter in the intervention group (mean 8.23, SD 4.45 minutes vs mean 10.92, SD 5.58 minutes; P=.02). The use of telemedicine saved 25% (€2.14 [US $2.35]/€8.67 [US $9.53]) in personnel costs and increased the number of treatable patients by 172 annually, assuming 2 hours of video consultations per week. Sensitivity analysis for scaling up video consultations to 10% of the hospital's outpatient cases resulted in personnel cost savings of €73,056 (US $ 80,275.39) for a senior physician. A total of 23 video consultations per month were required to recoup the software fees of telemedicine through reduced personnel costs (break-even point ranging from 12-38 in the sensitivity analysis). CONCLUSIONS: Our study supports stakeholders' decision-making on the long-term implementation of digital health by demonstrating that video consultations in the follow-up care of patients in orthopedic and trauma surgery result in cost savings and productivity gains for clinics with no negative impact on patient utility. TRIAL REGISTRATION: German Clinical Trials Register DRKS00023445; https://drks.de/search/en/trial/DRKS00023445.

Evaluation of Eligibility Criteria Relevance for the Purpose of IT-Supported Trial Recruitment: Descriptive Quantitative Analysis.

BACKGROUND: Clinical trials (CTs) are crucial for medical research; however, they frequently fall short of the requisite number of participants who meet all eligibility criteria (EC). A clinical trial recruitment support system (CTRSS) is developed to help identify potential participants by performing a search on a specific data pool. The accuracy of the search results is directly related to the quality of the data used for comparison. Data accessibility can present challenges, making it crucial to identify the necessary data for a CTRSS to query. Prior research has examined the data elements frequently used in CT EC but has not evaluated which criteria are actually used to search for participants. Although all EC must be met to enroll a person in a CT, not all criteria have the same importance when searching for potential participants in an existing data pool, such as an electronic health record, because some of the criteria are only relevant at the time of enrollment. OBJECTIVE: In this study, we investigated which groups of data elements are relevant in practice for finding suitable participants and whether there are typical elements that are not relevant and can therefore be omitted. METHODS: We asked trial experts and CTRSS developers to first categorize the EC of their CTs according to data element groups and then to classify them into 1 of 3 categories: necessary, complementary, and irrelevant. In addition, the experts assessed whether a criterion was documented (on paper or digitally) or whether it was information known only to the treating physicians or patients. RESULTS: We reviewed 82 CTs with 1132 unique EC. Of these 1132 EC, 350 (30.9%) were considered necessary, 224 (19.8%) complementary, and 341 (30.1%) total irrelevant. To identify the most relevant data elements, we introduced the data element relevance index (DERI). This describes the percentage of studies in which the corresponding data element occurs and is also classified as necessary or supplementary. We found that the query of "diagnosis" was relevant for finding participants in 79 (96.3%) of the CTs. This group was followed by "date of birth/age" with a DERI of 85.4% (n=70) and "procedure" with a DERI of 35.4% (n=29). CONCLUSIONS: The distribution of data element groups in CTs has been heterogeneously described in previous works. Therefore, we recommend identifying the percentage of CTs in which data element groups can be found as a more reliable way to determine the relevance of EC. Only necessary and complementary criteria should be included in this DERI.

Implementation of inclusion and exclusion criteria in clinical studies in OHDSI ATLAS software.

Clinical trials are essential parts of a medical study process, but studies are often cancelled due to a lack of participants. Clinical Trial Recruitment Support Systems are systems that help to increase the number of participants by seeking more suitable subjects. The software ATLAS (developed by Observational Health Data Sciences and Informatics) can support the launch of a clinical trial by building cohorts of patients who fulfill certain criteria. The correct use of medical classification systems aiming at clearly defined inclusion and exclusion criteria in the studies is an important pillar of this software. The aim of this investigation was to determine whether ATLAS can be used in a Clinical Trial Recruitment Support System to portray the eligibility criteria of clinical studies. Our analysis considered the number of criteria feasible for integration with ATLAS and identified its strengths and weaknesses. Additionally, we investigated whether nonrepresentable criteria were associated with the utilized terminology systems. We analyzed ATLAS using 223 objective eligibility criteria from 30 randomly selected trials conducted in the last 10 years. In the next step, we selected appropriate ICD, OPS, LOINC, or ATC codes to feed the software. We classified each criterion and study based on its implementation capability in the software, ensuring a clear and logical progression of information. Based on our observations, 51% of the analyzed inclusion criteria were fully implemented in ATLAS. Within our selected example set, 10% of the studies were classified as fully portrayable, and 73% were portrayed to some extent. Additionally, we conducted an evaluation of the software regarding its technical limitations and interaction with medical classification systems. To improve and expand the scope of criteria within a cohort definition in a practical setting, it is recommended to work closely with personnel involved in the study to define the criteria precisely and to carefully select terminology systems. The chosen criteria should be combined according to the specific setting. Additional work is needed to specify the significance and amount of the extracted criteria.