Abstract
During a crisis, hospitals need help to meet the needs of patients with burns. Very few clinicians (1%) of medical doctors and registered nurses and few hospitals (2%) have burn care expertise. Due to these capacity limitations, patients with burns as extensive as 40% TBSA remain outside of burn centers for days to weeks before reaching definitive care. Telemedicine technology (TT) effectively connects a caregiver in any location to an expert burn clinician. However, it remains underused for unknown reasons. Implementation science seeks to uncover the factors affecting the use of innovations like telemedicine to increase uptake. We administered a questionnaire to assess burn center and emergency department clinician perceptions of the feasibility, acceptability, and intention to use TT across a network of 24 hospitals representing 4 of the 6 current American Burn Association disaster response regions. We also collected monthly current TT referral usage rates (# acute burn referrals using TT / # total acute burn referrals). Clinician ratings were generally in the neutral to agreeable (3.04 to 4.01) range for acceptability, feasibility, and intention to use; however, there was no significant relationship between these constructs and the actual use of teleconsultation across the sample. Strong correlations between feasibility and intention to use were observed. However, weaker correlations between ease of use and perceived usefulness suggest that interventions targeting these perceptions are needed to fully realize the potential of teleconsultation in improving the quality of initial and ongoing burn care during a crisis and usual care.
Keywords: telemedicine, burns, crisis, disaster, implementation science, telehealth, mass casualty, emergency
INTRODUCTION
Burn bed and clinician capacity is a well-known mass casualty or crisis care response plan limitation.1–3 The latest estimates of the US burn bed and clinician capacity are staggering. Of the 6000 US registered hospitals, only 134 hospitals (2%) have burn care expertise.2,4,5 Of those, only 56% (75/132) demonstrated competence in all aspects of burn care using the verification criteria set by the American College of Surgeons and the American Burn Association.2,4 For clinicians, of the almost 1 million US physicians, there are less than 1000 burn surgeons.2 There are over 3 million US registered nurses, but a tiny fraction, approximately 3270 (1%) of those nurses have burn expertise.1 The numbers are direr when it comes to children, as less than half of the verified burn centers, and consequently, less than half of their clinicians, have the expertise to care for burned children.1 The physical burn bed capacity is estimated at 2000 beds. Still, as the recent COVID-19 pandemic has demonstrated, clinicians with the requisite expertise, not physical beds, are the rate-limiting step when a large influx of patients with a complex or specialty diagnosis occurs.6
The National Academies published Crisis Standards of Care7 for significant events adapted for use in the care of patients with burns.8 In crisis care, the response plan relies on volunteers, support staff, and mutual aid personnel. It assumes that significant facets of clinical care will be provided in nontraditional locations, like tents, using items from the US Government’s Strategic National Stockpile.2,8 Any surge of 500+ patients with burns in the United States would be deemed a crisis2; the latest standards for burn care during a crisis call for patients to remain in non-burn care facilities for as long as 120 h.2
The evidence for telemedicine’s effectiveness in improving initial burn care is compelling. Patients whose caregivers use telemedicine during the first assessment period experience less over-resuscitation,9 receive a more accurate burn size estimation,9,10 have better communication among their providers,11 and are less often transferred unnecessarily to burn centers.3,9,12,13 Telemedicine can potentially extend the reach of burn care providers by connecting them to non-burn caregivers and is strongly recommended for burn mass casualty events, prolonged field care, and crises.2,14
While acute burn teleconsultation is already readily available, it is underused, with about 34% of burn centers reporting using it for acute consults.15 The exact factors that affect a clinician’s use and intention to use acute burn teleconsultation in a crisis or under usual circumstances are mainly unknown. However, recent research suggests broad factors such as the environment, time pressures, medical hierarchy, and the wide range of clinician expertise are potential barriers to use.16 It is also likely that those who have experience using it will use it more often.
The specific barriers to burn teleconsultation technology—what prevents clinicians and organizations from using it––are not well understood, which limits the ability to increase its use through individual and organizational behavior change. One effective way to identify barriers to interventions and affect behavior change in organizations and individuals is to use implementation science. Implementation science seeks to narrow the evidence-to-practice gap in real-world settings by using established theoretical frameworks and the scientific method to identify what best supports the implementation of evidence (or intervention) in the healthcare setting.17
In the case of burn teleconsultation, a crucial first step in increasing the use of telemedicine technology is uncovering clinician’s perceptions of it and their intentions regarding its use under usual care and crisis care circumstances. To understand the relationship between experience and use, we hypothesize that clinicians working in hospitals that use teleconsultation for burn care more often will view its use more favorably in general and may have a higher intention to use it during a crisis. In this study, we leverage current, validated implementation science survey instruments to describe current perceptions and practices for burn teleconsultation uses across 4 diverse American Burn Association Disaster Response Regions of the United States and examine the relationships between clinician perceptions of feasibility, acceptability, intention to use, and the actual use of acute burn teleconsultation.
METHODS
To capture the broadest spectrum of teleconsultation technologies, we defined teleconsultation as any synchronous or asynchronous use of images and written or verbal communication about patient care.18 It can be from clinician to clinician, patient to clinician, or patient to patient. Examples include video calling, sharing pictures electronically, sharing video clips electronically, or any other combination of a photo or video and text or verbal communication. Because all burn team members could provide teleconsultation if needed, we have included all clinicians in our study, including nurses, physicians, advanced practice providers, therapists, and others. We also defined usual care as the care a patient could typically receive as a part of everyday practice and crisis care as care that provides sufficiency in times of disaster or mass casualty events. Still, the spaces, staff, and supplies are inconsistent with the standard of care during usual circumstances.2 Finally, we defined “initial care” as care occurring within the first 48 h post-injury and ongoing care as care occurring on days 2-7 post-injury.
We approached a diverse group of burn centers in 4 geographically separate disaster response regions in the United States. Burn centers were recruited based on teleconsultation capability and diversity of telemedicine practices. We leveraged existing regional telemedicine-capable burn care referral networks to recruit hospitals and clinicians from 4 regional ABA-verified burn hospitals and 5 non-burn hospital emergency departments (EDs) in each burn center’s existing telemedicine-capable regional referral network. All enrolled sites (n = 4 burn centers and n = 20 non-burn hospitals, n = 24 total) informed their staff about the study using a recruitment email from our study team. We sought voluntary participation and obtained informed consent from each clinician and hospital. We administered an electronic survey to measure clinician perceptions of the acceptability and feasibility of burn teleconsultation and their intention to use it under usual care and during a hypothetical crisis. The online survey took approximately 15 min, and each participant received a $15 gift card as a token of appreciation. The study was granted exempt status from the local Institutional Review Board.
From the 4 regional burn centers, we simultaneously collected de-identified, aggregated real-time referral data for each of their study network ED’s teleconsultation practices over 12 months. We determined teleconsultation rates by dividing the number of acute care consultations using telemedicine technology (ie, live or recorded video, synchronous or asynchronous sharing of pictures) of each study hospital by that hospital’s total number of acute burn care referrals during the data collection period.
Feasibility is whether an intervention or treatment can be used successfully in the clinical setting.19 Acceptability is the perception among implementation stakeholders that a therapy, service, practice, or innovation is agreeable or satisfactory.19 The Acceptability of Implementation Measure (AIM) and Feasibility of Implementation Measure (FIM) are existing, validated survey instruments used in our electronic surveys to assess clinician perceptions of acceptability and feasibility.20 A higher score indicates a more positive perception of acceptability or feasibility. These measures have been extensively used in implementation research and demonstrate good internal reliability (Cronbach’s alpha 0.85-0.91)20 and construct validity.20
We also used a previously validated Simulated Technology Acceptance Tool (STAT) tool to measure intention to use teleconsultation technology.21 The STAT tool survey included 36 questions scaled on a Likert scale. A higher score indicates greater acceptance of telemedicine technology. The STAT instrument has been previously used to study the intention to use burn telemedicine in an emergency and has demonstrated good internal reliability with a Cronbach’s alpha of 0.951.21 In addition to these measures, the study was guided by the Consolidated Framework for Implementation Research (CFIR). The CFIR is an implementation science determinants framework used to examine barriers and facilitators to implementation and plan organizational change interventions in diverse settings.22
The sample size required for the study was determined a priori. Assuming an initial baseline literature-reported acute burn teleconsultation rate of 0.3415 and a conservative difference in the proportion of acute burn consultations using telemedicine technology of 0.12, we determined a sample size of 720 was needed to obtain 80% power with a type I error rate of 5%.
In addition to hypothesis testing, we conducted a comprehensive descriptive statistical analysis. We calculated the mean and standard deviation for the Acceptability (AIM) and Feasibility (FIM) questionnaire and STAT instruments. Using the Spearman rank correlation method, we evaluated the correlations between the results of the AIM, FIM, and STAT instruments. AIM and FIM results were stratified as Initial and Ongoing Crisis Care and Acute Care by the type of burn care provided. The STAT measure consisted of 4 cognitive domains: attitude towards use, perception of its usefulness, ease of use and the clinician’s understanding of the process, and an intention to use affective score. Each domain can be measured independently to understand factors affecting technology acceptance.21
To evaluate the relationship between actual teleconsultation use and clinician perceptions of teleconsultation, we used a linear regression model with average AIM, FIM questionnaire by burn type, and STAT instrument subscale scores as independent predictors and each hospital’s average teleconsultation use as the outcome variable. A P-value < .05 was considered statistically significant. All analysis was conducted using SAS 9.4.
RESULTS
Burn center clinicians’ overall electronic survey response rate was 61% (target was 60%), and emergency clinicians was 12% (target was 60%). We successfully obtained the total referrals count and the number of telemedicine referrals for each month from October 2022 to 2023 for each hospital within each region. The referral rates are presented in Figure 1, and Figures S6-S9 present the aggregate referral rates for each region individually.
Figure 1.
Referral Rates for All Sites by ABA-Region. Rate Refers to the Number of Acute Burn Referrals Using Any Type of Teleconsultation Technology Divided by the Total Number of Acute Burn Referrals From Each Site, Monthly.
The demographics of the survey participants are presented in Table 1. We received responses to AIM, FIM questionnaire, and STAT instrument from 389 survey participants, with 101 respondents from the Western region burn center and its ED referral hospitals, 83 from the Northeastern region burn center and its ED referral hospitals, 67 from the Great Lakes region burn center and its ED referral hospitals, and 138 from the Midwest region burn center and its ED referral hospitals. 269 (69.2%) respondents self-identified as female, 117 (30.1%) self-identified as male, and 3 (0.8%) preferred not to disclose their gender identity. A large majority, 340 (87.4%), had personally provided burn care to patients of any age within the past 12 months. 211 respondents (54.2%) most often cared for patients with burns in the ED, 147 (37.8%) in an inpatient care area, and 31 (8.0%) in other areas. 102 (26.2%) respondents considered themselves in a formal leadership role in their organization.
Table 1.
Participant Demographics
| Variable | Total (n = 389) | Western region (n = 101) | Northeastern region (n = 83) | Great Lakes region (n = 67) | Midwest region (n = 138) | |
|---|---|---|---|---|---|---|
| Have you personally provided care to a patient of any age with a burn injury in the last 12 months? | No | 49 (12.6%) | 9 (8.9%) | 13 (15.7%) | 7 (10.4%) | 20 (14.5%) |
| Yes | 340 (87.4%) | 92 (91.1%) | 70 (84.3%) | 60 (89.6%) | 118 (85.5%) | |
| Please choose the profession that most closely corresponds to your clinical role | Physician | 91 (23.4%) | 36 (35.6%) | 29 (34.9%) | 12 (17.9%) | 14 (10.1%) |
| Registered nurse | 198 (50.9%) | 33 (32.7%) | 34 (41.0%) | 38 (56.7%) | 93 (67.4%) | |
| Advanced practice professional (APP) | 27 (6.9%) | 8 (7.9%) | 4 (4.8%) | 8 (11.9%) | 7 (5.1%) | |
| Social worker and psychosocial | 3 (0.8%) | 1 (1.0%) | 2 (1.4%) | |||
| Respiratory therapist | 1 (0.3%) | 1 (0.7%) | ||||
| Occupational and physical therapy | 12 (3.1%) | 8 (7.9%) | 3 (4.5%) | 1 (0.7%) | ||
| Dietician | 1 (0.3%) | 1 (0.7%) | ||||
| Hospital administration | 3 (0.8%) | 2 (2.0%) | 1 (0.7%) | |||
| EMT/paramedic | 13 (3.3%) | 3 (3.6%) | 1 (1.5%) | 9 (6.5%) | ||
| Medical resident/fellow/trainee | 15 (3.9%) | 1 (1.0%) | 12 (14.5%) | 2 (3.0%) | ||
| Other | 25 (6.4%) | 12 (11.9%) | 1 (1.2%) | 3 (4.5%) | 9 (6.5%) | |
| Which of these burn centers is closest to you? | Western region burn center | 79 (20.3%) | 79 (95.2%) | |||
| Northeastern region burn center | 67 (17.2%) | 67 (100.0%) | ||||
| Great Lakes region burn center | 96 (24.7%) | 96 (95.0%) | ||||
| Midwest region burn center | 138 (35.5%) | 138 (100.0%) | ||||
| Other/not sure | 9 (2.3%) | 5 (5.0%) | 4 (4.8%) | |||
| Do you primarily work in a burn center? | No | 232 (59.6%) | 59 (58.4%) | 58 (69.9%) | 29 (43.3%) | 86 (62.3%) |
| Yes | 157 (40.4%) | 42 (41.6%) | 25 (30.1%) | 38 (56.7%) | 52 (37.7%) | |
| Please select the option that corresponds to the place you most often care for patients with burns | Emergency department | 211 (54.2%) | 53 (52.5%) | 56 (67.5%) | 28 (41.8%) | 74 (53.6%) |
| Inpatient care area | 147 (37.8%) | 40 (39.6%) | 23 (27.7%) | 38 (56.7%) | 46 (33.3%) | |
| Other | 31 (8.0%) | 8 (7.9%) | 4 (4.8%) | 1 (1.5%) | 18 (13.0%) | |
| Do you consider yourself to be in a formal leadership role in your organization? | No | 287 (73.8%) | 74 (73.3%) | 63 (75.9%) | 52 (77.6%) | 98 (71.0%) |
| Yes | 102 (26.2%) | 27 (26.7%) | 20 (24.1%) | 15 (22.4%) | 40 (29.0%) | |
| Please choose the option that most closely represents your gender identity | Female | 269 (69.2%) | 58 (57.4%) | 58 (69.9%) | 48 (71.6%) | 105 (76.1%) |
| Male | 117 (30.1%) | 41 (40.6%) | 25 (30.1%) | 19 (28.4%) | 32 (23.2%) | |
| Prefer not to answer | 3 (0.8%) | 2 (2.0%) | 1 (0.7%) | |||
| How many years of clinical experience do you have? | N | 389 | 101 | 83 | 67 | 138 |
| Mean | 12.3 | 14.6 | 10.1 | 10.9 | 12.6 | |
| STD | 9.70 | 10.12 | 9.66 | 8.28 | 9.74 | |
| Min | 0 | 0 | 1 | 0 | 0 | |
| Max | 46 | 42 | 46 | 40 | 44 |
For each of the 3 validated measures in the survey (AIM, FIM, STAT), the items were scored on a Likert scale from 1 to 5 (1 = completely agree, 2 = disagree, 3 = neither agree nor disagree, 4 = agree, and 5 = completely agree). The mean and standard deviation for the AIM, FIM, and STAT instruments across the entire sample are presented in Table 2. Overall, clinicians in the sample rated acceptability and feasibility for initial and ongoing crisis burn care as “neither agree nor disagree” to “agree” (3-4 out of 5 on the Likert scale). The highest ratings on average were for the feasibility of using teleconsultation for initial burn care (4.01/5 (agree) on average). The lowest on average were clinicians’ intentions to use teleconsultation in a crisis related to their understanding of the process (3.05/5 (neither agree nor disagree) on average) and their perceived ease of use (3.04/5 (neither agree nor disagree) on average).
Table 2.
Descriptive Values for Survey Items
| Variable | N | Mean (Std)a |
|---|---|---|
| Usual Care: Acceptability for Initial Burn Care | 389 | 3.87 (0.9) |
| Usual Care: Feasibility for Initial Burn Care | 389 | 4.01 (0.8) |
| Usual Care: Acceptability for Ongoing Burn Care: | 389 | 3.77 (0.9) |
| Usual Care: Feasibility of Ongoing Burn Care | 389 | 3.88 (0.8) |
| Crisis Care: Acceptability | 389 | 3.81 (1.0) |
| Crisis Care: Feasibility | 389 | 3.8 (0.9) |
| STAT—Intention To Use eCM (IUe) | 389 | 3.49 (0.6) |
| STAT—Attitude Toward Use of eCM (ATUe) | 389 | 3.93 (0.6) |
| STAT—Perceived Usefulness of eCM (PUe) | 389 | 3.47 (0.7) |
| STAT—Perceived Ease of Use of eCM (PEUe) | 389 | 3.04 (0.3) |
| STAT—Understanding of Process (UPe) | 389 | 3.05 (0.5) |
aNumbers represent the numeric mean of a 5-point Likert scale where 1 = completely disagree, 2 = disagree, 3 = neither agree nor disagree, 4 = agree, and 5 = completely agree.
Clinician ratings of acceptability and feasibility by type of care and practice location are illustrated in Figure 2. On average, clinician ratings of the acceptability of using TT for routine burn care were higher in the ED clinicians than those working in Burn Centers (4.07 (agree), SD = 0.87 vs 3.45, SD = 1), and this trend was consistent for initial care and ongoing care during a crisis (4.17 (agree); SD = 0.77 vs 3.48; SD = 0.96 and 3.83; SD = 0.89 vs 3.71; SD = 0.8, respectively). We observed similar trends by practice location in feasibility and intention to use during a crisis across the sample. There were consistently generally neutral to positive (3 to 4 on the Likert scale) ratings in the STAT tool domains of intention, attitude, and perceived usefulness across all clinicians regardless of practice location; however, ease of use and understanding of the process were consistently rated lower (3 = neither agree nor disagree).
Figure 2.
Clinician Ratings of Acceptability and Feasibility by Type of Care and Practice Location. Initial Crisis Care = First 24 Hours After Event, Ongoing = 25–72 Hours After Event, and Acute Is Routine Burn Care Without Any Crisis.
The highest overall mean (SD) score = 4.01 (0.84) was obtained for the initial burn care feasibility measure (FIM) subscore. Similarly, the lowest mean (SD) = 3.04 (0.32) was obtained for the intention to use measure (STAT) around ease of use. We present the breakdown of scores by site, type of burn care, whether a respondent personally provided burn care or not within the past 12 months, the place care was provided, whether a respondent held a formal leadership position, and their gender graphically in Figures S1-S5.
To evaluate our primary hypothesis that clinicians with more favorable ratings of acceptability (AIM) and feasibility (FIM) and those with a high intention to use (STAT) score will work in hospitals that currently use telemedicine more often for acute burn care consultation, we fit a linear regression model with average teleconsultation referral rate as an outcome and average AIM, FIM, and intention to use (STAT) score as a predictor. The findings are presented in Table 3. Our analysis did not reveal any statistically significant association between the average teleconsultation referral rate and these predictors. Of note, all hospitals in the study have burn teleconsultation capability, and in one region (Western) it was used zero times during the data collection period despite consistent patient transfers occurring between the hospitals in the burn center’s region.
Table 3.
Results From the Regression Model With Teleconsultation Rate as Outcome
| Variable | Regression estimate | R 2 | P-value |
|---|---|---|---|
| Usual Care: Acceptability for Initial Burn Care | 15.2 | 0.04 | .366 |
| Usual Care: Feasibility for Initial Burn Care | 12.9 | 0.02 | .490 |
| Usual Care: Acceptability for Ongoing Burn Care: | −4.3 | 0.00 | .838 |
| Usual Care: Feasibility of Ongoing Burn Care | −3.6 | 0.00 | .867 |
| Crisis Care: Acceptability | 22.0 | 0.07 | .245 |
| Crisis Care: Feasibility | 19.4 | 0.05 | .324 |
| STAT—Intention To Use eCM (IUe) | −18.9 | 0.01 | .655 |
| STAT—Attitude Toward Use of eCM (ATUe) | 40.4 | 0.08 | .209 |
| STAT—Perceived Usefulness of eCM (PUe) | 13.5 | 0.01 | .619 |
| STAT—Perceived Ease of Use of eCM (PEUe) | 30.1 | 0.01 | .685 |
| STAT—Understanding of Process (UPe) | 78.1 | 0.14 | .085 |
We tested whether clinician perceptions of acceptability and feasibility relate to their intention to use teleconsultation under usual care and during a crisis. We did observe statistically significant correlations between most of the clinicians’ ratings of acceptability and feasibility (AIM and FIM) and the components of the STAT intention to use tool. These results are presented in Table 4. Of the statistically significant correlations, most were strong in magnitude. Those with the weakest significant correlations were between crisis care acceptability and perceived usefulness (Spearman rank correlation = 0.50, P < .001), perceived ease of use (Spearman rank correlation = 0.10, P < .001), and understanding the process (Spearman rank correlation = 0.22, P < .001). Regarding feasibility, weak correlations between crisis care feasibility and perceived usefulness (Spearman rank correlation = 0.55, P < .001), perceived ease of use (Spearman rank correlation = 0.18, P < .001), and understanding of the process (Spearman rank correlation = 0.31, P < .001) were also observed.
Table 4.
Correlation Between Survey Instrument Items
| Variable 1 | Variable 2 | Spearman rank correlation | P-value |
|---|---|---|---|
| Usual Care: Acceptability for Initial Burn Care | Usual Care: Feasibility for Initial Burn Care | 0.83 | <.001 |
| Usual Care: Acceptability for Ongoing Burn Care: | Usual Care: Feasibility of Ongoing Burn Care | 0.86 | <.001 |
| Crisis Care: Acceptability | Crisis Care: Feasibility | 0.83 | <.001 |
| Crisis Care Intentions: Acceptability | Intention To Use eCM (IUe) | 0.60 | <.001 |
| Crisis Care Intentions: Acceptability | Attitude Toward Use of eCM (ATUe) | 0.69 | <.001 |
| Crisis Care Intentions: Acceptability | Perceived Usefulness of eCM (PUe) | 0.50 | <.001 |
| Crisis Care Intentions: Acceptability | Perceived Ease of Use of eCM (PEUe) | 0.10 | .055 |
| Crisis Care Intentions: Acceptability | Understanding of Process (UPe) | 0.22 | <.001 |
| Crisis Care Intentions: Feasibility | Intention To Use eCM (IUe) | 0.64 | <.001 |
| Crisis Care Intentions: Feasibility | Attitude Toward Use of eCM (ATUe) | 0.72 | <.001 |
| Crisis Care Intentions: Feasibility | Perceived Usefulness of eCM (PUe) | 0.55 | <.001 |
| Crisis Care Intentions: Feasibility | Perceived Ease of Use of eCM (PEUe) | 0.18 | .0004 |
| Crisis Care Intentions: Feasibility | Understanding of Process (UPe) | 0.31 | .0004 |
Finally, given the potential for temporal changes based on volume and external and internal trends, we estimated a mixed-effects model with random intercept and slope for the telemedicine referral rate trajectory over time at the hospital level. Results show that EDs start, on average, with a telemedicine referral rate of 27.91 (P = .0001) and that this decreases by −0.17 per month (P = .8609). The intercept and slope of the trajectory for the ED at each of the 20 hospitals examined in our sample are presented as points on the coordinate plane in Figure S10. EDs with a slope greater than the average of −0.17 show improvement in telemedicine referral rates over time and could be targeted for further improvement.
LIMITATIONS
Clinician subject recruitment from EDs was a challenge, with an average response rate of 12%, and this limited our ability to look at an individual referring hospital-level predictors in the regression model with enough power to detect a relationship. This may reflect a broader challenge in engaging ED partners in burn crisis and disaster planning efforts. Some respondents, although reminded of the broad definition of teleconsultation we used, may still conceptualize telemedicine as a patient-to-provider real-time video interaction rather than the use of pictures or video clips. Because participation was voluntary by clinicians, there may be some systematic bias in who responded to the survey based on topic interest and professional experience. Further, the experience level with telemedicine may differ by professional role, limiting the respondents’ ability to see the benefits of their practice in roles such as physical therapy, psychosocial support, and nursing.
Due to resource constraints, it was not possible to recruit burn centers and EDs from every disaster region. To minimize bias, we chose a mix of urban and rural catchment areas and did not limit participation by any hospital based on structural or other characteristics.
DISCUSSION
Consistent with previous research, data from the 24 hospitals enrolled in the study suggest that current teleconsultation use for usual acute burn care is highly variable15 and represents an ongoing opportunity for improvement to improve quality. There are likely multilevel factors influencing the variation.23 Still, our data suggest that clinicians in EDs and burn centers generally agree that teleconsultation is an acceptable and feasible option for usual care and during a crisis. Importantly, burn center professionals rate the feasibility of teleconsultation lower than those working in EDs. Therefore, targeted implementation interventions focusing on their perceived barriers are likely necessary to improve uptake. Concerns likely relate to staffing numbers as clinicians may think about the myriad of other clinical and other responsibilities they would have in addition to being teleconsulted. Currently, no criteria exist for staffing a burn expert teleconsultation service during a crisis or under usual care circumstances, which may present a barrier to implementation. Likely, those with burn expertise will be stretched to care for the most patients possible, and models like existing tele-ICU staffing models may need to be outlined so burn clinicians can adequately dedicate staff to answering teleconsultation requests. Further, the entire multidisciplinary team’s expertise is not typically leveraged in current burn disaster response staffing plans, so attention to matching the right clinician with the knowledge to assist the person requesting the consultation may extend the reach of the entire team without monopolizing burn surgeon time. Attention to this type of team-based “virtual burn center” teleconsultation staffing model may help ease the perception among burn clinicians that this modality is not feasible during a crisis.
We also found that ease of use, understanding the best process for integrating telemedicine into burn care, and perceived usefulness are potential barriers to implementing such a model. A potential evidence-based approach to overcoming these barriers is to use implementation research methods to develop a toolkit that includes a suite of tailored behavior change techniques for clinicians designed to overcome these specific barriers. This is an important area for future research based on these findings. Importantly, clinician attitudes toward use are consistently high, and this can be leveraged as a powerful facilitator of change in future implementation efforts.
Finally, the data suggest that clinician perceptions of the acceptability, feasibility, and intention to use teleconsultation vary by professional role. Like other implementation research studies using similar methods,24 it may be necessary to tailor the implementation intervention (or toolkit) to match the vantage point of each clinician involved. Nurses and therapists may have different professional experiences with teleconsultation than physicians and, therefore, may need more support to accept and find a feasible model that they can participate in during a crisis or under usual care.
Our results suggest that using teleconsultation for acute burn care daily and during a crisis is generally acceptable to clinicians in EDs and burn centers. While barriers currently exist, those can likely be overcome when targeted tools are provided to clinicians in both settings to assist with implementation. Given the widespread use of telemedicine during and after the coronavirus disease (COVID-19) pandemic, clinician comfort with teleconsultation is likely the highest it has ever been. To capitalize on this power facilitator for change, developing an implementation intervention to fully integrate teleconsultation in all forms into routine and crisis burn care should be a priority.
Supplementary Material
Acknowledgments
The research team would like to extend sincere gratitude to the clinicians in the burn centers and emergency rooms for their invaluable contributions to this project. Your expertise and dedication in the field of burn care have greatly enriched our research and provided critical insights that shaped our findings. Thank you for your participation.
Contributor Information
Amanda P Bettencourt, Department of Family and Community Health, University of Pennsylvania School of Nursing, Philadelphia, PA, United States.
Theresa M Davis, AVP High Reliability Operations Center, Inova Health System, Falls Church, VA, United States.
Subhash Aryal, Johns Hopkins School of Nursing, Baltimore, MD, United States.
Joseph Rhodes, BECCA Lab, University of Pennsylvania School of Nursing, Philadelphia, PA, United States.
Mark J Johnston, Regions Hospital Burn Center, St. Paul, MN, United States.
Cindy Wegryn, Department of Surgery, University of Michigan, Ann Arbor, MI, United States.
Matthew D Supple, Massachusetts General Hospital, Boston, MA, United States.
Victor C Joe, UCI Health Regional Burn Center, Orange, CA, United States.
John Schulz, Division of Burns, Department of Surgery, Massachusetts General Hospital, Boston, MA, United States.
Gary Vercruysse, Department of Surgery, University of Michigan, Ann Arbor, MI, United States.
Deena Kelly Costa, Yale School of Nursing and Yale School of Medicine, New Haven, CT, United States.
Colleen Ryan, Department of Surgery, Massachusetts General Hospital, Harvard Medical School, Shriners Children’s Hospital-Boston, Boston, MA, United States.
Funding
This work was supported by the Office of the Assistant Secretary of Defense for Health Affairs through the Military Burn Research Program under award no. (W81XWH-21-1-0422, PI: A.P.B.). Opinions, interpretations, conclusions, and recommendations are those of the author(s) and are not necessarily endorsed by the Department of Defense.
Conflict of interest statement
Dr. A.P.B. reports other support not related to this project from the Agency for Healthcare Research and Quality and the National Institutes of Health. Dr. D.K.C. reports other support not related to this project from National Heart, Lung, and Blood Institute and Agency for Healthcare Research and Quality. Dr. C.R. reports other support not related to his project from ASPR, Shriners Hospitals for Children, the Department of Defense, Mediwound, NIH, and the Fraser Family Fund of the Massachusetts General Hospital.
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