A qualitative study of the barriers and facilitators impacting the implementation of a quality improvement program for emergency departments: SurgeCon.

BACKGROUND: The implementation of intervention programs in Emergency Departments (EDs) is often fraught with complications due to the inherent complexity of the environment. Hence, the exploration and identification of barriers and facilitators prior to an implementation is imperative to formulate context-specific strategies to ensure the tenability of the intervention. OBJECTIVES: In assessing the context of four EDs prior to the implementation of SurgeCon, a quality improvement program for ED efficiency and patient satisfaction, this study identifies and explores the barriers and facilitators to successful implementation from the perspective of the healthcare providers, patients, researchers, and decision-makers involved in the implementation. SETTINGS: Two rural and two urban Canadian EDs with 24/7 on-site physician support. METHODS: Data were collected prior to the implementation of SurgeCon, by means of qualitative and quantitative methods consisting of semi-structured interviews with 31 clinicians (e.g., physicians, nurses, and managers), telephone surveys with 341 patients, and structured observations from four EDs. The interpretive description approach was utilized to analyze the data gathered from interviews, open-ended questions of the survey, and structured observations. RESULTS: A set of five facilitator-barrier pairs were extracted. These key facilitator-barrier pairs were: (1) management and leadership, (2) available resources, (3) communications and networks across the organization, (4) previous intervention experiences, and (5) need for change. CONCLUSION: Improving our understanding of the barriers and facilitators that may impact the implementation of a healthcare quality improvement intervention is of paramount importance. This study underscores the significance of identifing the barriers and facilitators of implementating an ED quality improvement program and developing strategies to overcome the barriers and enhance the facilitators for a successful implementations. We propose a set of strategies for hospitals when implementing such interventions, these include: staff training, champion selection, communicating the value of the intervention, promoting active engagement of ED staff, assigning data recording responsibilities, and requiring capacity analysis. TRIAL REGISTRATION: ClinicalTrials.gov. NCT04789902. 10/03/2021.

Investigating a Work System Approach to Implement an Emergency Department Surge Management System: Case Study.

BACKGROUND: Emergency department (ED) crowding is a global health care issue. eHealth systems have the potential to reduce crowding; however, the true benefits are seldom realized because the systems are not integrated into clinicians' work. We sought a deep understanding of how an eHealth system implementation can be structured to truly integrate the system into the workflow. OBJECTIVE: The specific objectives of this study were to examine whether work system theory (WST) is a good approach to structure the implementation of an eHealth system by incorporating the entire work system, and not just the eHealth system, in the implementation framework; identify the role that specific elements of WST's static framework and dynamic work system life cycle model play in the implementation; and demonstrate how WST can be applied in the health care setting to guide the implementation of an eHealth system. METHODS: Through a case study of an ED in a rural hospital, we used a mixed methods approach to examine the implementation of a surge management system through the lens of WST. We conducted 14 hours of observation in the ED; 20 interviews with clinicians, management, and members of the implementation team; and a survey of 23 clinicians; reviewed related documentation; and analyzed ED data to measure wait times. We used template analysis based on WST to structure our analysis of qualitative data and descriptive statistics for quantitative data. RESULTS: The surge management system helped to reduce crowding in the ED, staff was satisfied with the implementation, and wait time improvements have been maintained for several years. Although study participants indicated changes to their workflow, 72% (13/18) of survey participants were satisfied with their use of the system, and 82% (14/17) indicated that it was integrated with their workflow. Examining the implementation through the lens of WST enabled us to identify the aspects of the implementation that made it so successful. By applying the WST static framework, we saw how the implementation team incorporated the elements of the ED work system, assessed their alignment, and designed interventions to address areas of misalignment. The dynamic work system life cycle model captured how planned and unplanned changes were managed throughout the iterative implementation cycle-83% (15/18) of participants indicated that there was sufficient management support for the changes and 80% (16/20) indicated the change served an important purpose. CONCLUSIONS: The broad scope and holistic approach of WST is well suited to guide eHealth system implementations as it focuses efforts on the entire work system and not just the IT artifact. We broaden the focus of WST by applying it to the implementation of an ED surge management system. These findings will guide further studies and implementations of eHealth systems using WST.

Evaluation of a Mobile Telesimulation Unit to Train Rural and Remote Practitioners on High-Acuity Low-Occurrence Procedures: Pilot Randomized Controlled Trial.

BACKGROUND: The provision of acute medical care in rural and remote areas presents unique challenges for practitioners. Therefore, a tailored approach to training providers would prove beneficial. Although simulation-based medical education (SBME) has been shown to be effective, access to such training can be difficult and costly in rural and remote areas. OBJECTIVE: The aim of this study was to evaluate the educational efficacy of simulation-based training of an acute care procedure delivered remotely, using a portable, self-contained unit outfitted with off-the-shelf and low-cost telecommunications equipment (mobile telesimulation unit, MTU), versus the traditional face-to-face approach. A conceptual framework based on a combination of Kirkpatrick's Learning Evaluation Model and Miller's Clinical Assessment Framework was used. METHODS: A written procedural skills test was used to assess Miller's learning level- knows-at 3 points in time: preinstruction, immediately postinstruction, and 1 week later. To assess procedural performance (shows how), participants were video recorded performing chest tube insertion before and after hands-on supervised training. A modified Objective Structured Assessment of Technical Skills (OSATS) checklist and a Global Rating Scale (GRS) of operative performance were used by a blinded rater to assess participants' performance. Kirkpatrick's reaction was measured through subject completion of a survey on satisfaction with the learning experiences and an evaluation of training. RESULTS: A total of 69 medical students participated in the study. Students were randomly assigned to 1 of the following 3 groups: comparison (25/69, 36%), intervention (23/69, 33%), or control (21/69, 31%). For knows, as expected, no significant differences were found between the groups on written knowledge (posttest, P=.13). For shows how, no significant differences were found between the comparison and intervention groups on the procedural skills learning outcomes immediately after the training (OSATS checklist and GRS, P=1.00). However, significant differences were found for the control versus comparison groups (OSATS checklist, P<.001; GRS, P=.02) and the control versus intervention groups (OSATS checklist, P<.001; GRS, P=.01) on the pre- and postprocedural performance. For reaction, there were no statistically significant differences between the intervention and comparison groups on the satisfaction with learning items (P=.65 and P=.79) or the evaluation of the training (P=.79, P=.45, and P=.31). CONCLUSIONS: Our results demonstrate that simulation-based training delivered remotely, applying our MTU concept, can be an effective way to teach procedural skills. Participants trained remotely in the MTU had comparable learning outcomes (shows how) to those trained face-to-face. Both groups received statistically significant higher procedural performance scores than those in the control group. Participants in both instruction groups were equally satisfied with their learning and training (reaction). We believe that mobile telesimulation could be an effective way of providing expert mentorship and overcoming a number of barriers to delivering SBME in rural and remote locations.

Implementation of an ED surge management platform: a study protocol.

BACKGROUND: Emergency departments (EDs) around the world are struggling with long wait times and overcrowding. To address these issues, a quality improvement program called SurgeCon was created to improve ED efficiency and patient satisfaction. This paper presents a framework for managing and evaluating the implementation of an ED surge management platform. Our framework builds on the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework to structure our approach and the Consolidated Framework for Implementation Research (CFIR) to guide our choice of outcome variables and scalability. METHODS: Four hospital EDs will receive the SurgeCon quality improvement intervention. Using a stepped wedge cluster design, each ED will be randomized to one of four start dates. Data will be collected before, during, and after the implementation of the intervention. RE-AIM will be used to guide the assessment of SurgeCon, and guided by CFIR, we will measure ED key performance indicators (KPI), patient-reported outcomes, and implementation outcomes related to SurgeCon's scalability, adaptability, sustainability, and overall costs. Participants in this study consist of patients who visit any of the four selected EDs during the study period, providers/staff, and health system managers. A mixed-methods approach will be utilized to evaluate implementation outcomes. DISCUSSION: This study will provide important insight into the implementation and evaluation techniques to enhance uptake and benefits associated with an ED surge-management platform. The proposed framework bridges research and practice by involving researchers, practitioners, and patients in the implementation and evaluation process, to produce an actionable framework that others can follow. We anticipate that the implementation approach would be generalizable to program implementations in other EDs. TRIAL REGISTRATION: • Name of the registry: ClinicalTrials.gov • Trial registration number: NCT04789902 • Date of registration: 03/10/2021.

Patients' intention to use online postings of ED wait times: A modified UTAUT model.

BACKGROUND: As health care becomes more reliant on technology, a better understanding of the factors that contribute to acceptance and use of technology is now critical. The Unified Theory of Acceptance and Use of Technology (UTAUT) has been applied to study a variety of technologies in different settings, and it is one of the most cited theories in Information Systems (IS) research. However, there has been limited application of UTAUT to health IT and, in particular, to patients' IT use. OBJECTIVES: The aim of this study is to adapt UTAUT to the context of patient acceptance and use of an Emergency Department (ED) wait-times website, and to empirically test the modified model and compare the results to those of the original UTAUT model. Specifically, it is proposed that there will be a significant relationship between facilitating conditions and behavioral intention. METHODS: A survey of patients in the ED of a Canadian hospital was conducted, yielding 118 completed surveys, and subsequently analyzed using Partial least squares (PLS). RESULTS: This study found that the modified UTAUT produced a substantial improvement in variance explained in behavioral intention compared to the original UTAUT (66% versus 46%). The modified-UTAUT model showed significant effects in performance expectancy (r = 0.302, p < 0.01) and facilitating conditions (r = 0.539, p < 0.001) on behavioral intention to use the website, while the effort expectancy impact was not significant. CONCLUSIONS: This study provides empirical support for the modified-UTAUT in the context of patients' intention to use an ED wait times website. Some results of this study support prior research, while some differ, such as the non-significant relationship between effort expectancy and behavioral intention and the finding that performance expectancy is not the main driver of intention to use. As proposed, facilitating conditions - having the resources necessary to view the website and having the ability to find the website - were the most important factors influencing behavioral intention. UTAUT is a key theoretical advance in IS research and by modifying it to the context of patient use, we contribute to both IS and health research.