Introduction

For efficient wound management, healthcare providers are required to conduct a comprehensive wound assessment, which encompasses precise wound measurements, detailed documentation, and ongoing monitoring [1]. However, this can often be challenging [1,2] as the traditional, manual methods of completing wound assessments, in many cases, are unreliable, timeconsuming, and can lead to poor care quality [3-7]. Further, with the scarcity of systematic wound care approach-many guidelines are consensus-based and lack strong evidence [2,8] there is a high degree of variability in wound care assessments and documentation [9,10], which negatively influences the quality of wound care diagnosis and management [2,8]. Ousey and colleagues reported in their survey study that clinicians were cognisant of existing frameworks for wound bed assessment; however, only 60% used them and did so in variable ways [11]. Another study surveyed 120 nurses working in an acute care facility in a large metropolitan hospital, where 71 nurses reported limited knowledge of the wound management national guidelines [12]. Therefore, with the increase in complex chronic wound prevalence [8], inadequate staffing levels, limited education, and limited wound care experts, standardized, efficient wound management is subject to even more significant challenges [13].

These contextual impediments contribute to high levels of clinical variability in wound care that impact operational care delivery, access to wound care, and healing outcomes. These challenges are exacerbated by the global shortage of nurses in clinical practices [14]. Evidence shows that this crisis is based on poor working conditions for nurses including poor planning and allocation of resources, unsatisfactory recruitment and retention policies, and ineffective utilization of qualifications and skills. This crisis has a dire impact on healthcare delivery and outcomes [14]. Therefore, at the organizational level, decisionmakers are focused on maximizing clinical efficiencies, practice capacity, and increasing nurse retention to facilitate equitable care [15]. Evidence shows that organizational interventions to improve clinical efficiency and work conditions for clinicians should encompass efforts to improve job resources - such as documentation tools, clinical decision supports, and automated alerts - while minimizing job demands [16]. Thus, organizations appreciate that to provide accessible, equitable, and quality care, they must ensure their clinical staff is satisfied and retained with technologies and tools that support efficiency, documentation, and decision support, which significantly improve clinicians’ working conditions.

Therefore, in recent years, considerable efforts have been spent on procuring and implementing digital technologies across the healthcare system to enhance staff productivity, clinical efficiency, and quality of care [17]. For example, a US-based hospital outpatient clinic study reported about a 30% reduction in chargeable expenditures per patient visit following the integration of a point-of-care digital wound management solution within its system [18].

Therefore, to address the challenges with wound assessment and management in healthcare and to support organizational efforts to maximize productivity and minimize costs, Swift Medical’s technology has been adopted various healthcare facilities in the US and Canada. The solution is embraced as a supportive tool to improve the quality and efficiency of wound care by empowering healthcare professionals to easily capture, share and analyze accurate wound data at the point–of–care, enhancing treatment decision-making and clinical outcomes.

Swift Medical’s solution utilizes Artificial Intelligence (AI) to enable the capture of high-quality images and automatically calculate high precision wound measurements in a fraction of the time it takes through traditional, manual methods [4,19]. The application integrates with the Electronic Medical Record (EMR) system, providing clinicians with comprehensive views of wound healing and patient risk. Moreover, this technology supports virtual collaboration between bedside clinicians and remote specialists to enable enhanced treatment decisions.

Investigating user satisfaction and perceived attitudes toward emerging digital technologies has been the focus of many researchers for decades, and the evolution of the applied models and theories is tangible [20,21]. Many theories have been presented to apprehend the attitude and intention toward adopting and using the technology. The widely used theories in health informatics are the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of Technology (UTAUT), and the Unified Theory of Acceptance and Use of Technology (UTAUT2) [17,22]. In general, acceptance of technology can be predicted by the perceived usefulness and perceived ease of use [23,24,25], while adopting the technology depends on effort and performance expectancy, social influences, and availability of supportive infrastructure [17,23] with age, gender, experience, and ability to use the tool voluntarily as moderators [24].

To our knowledge, there are limited publications about clinician satisfaction with electronic wound assessment technology and the intention to adopt it. With the high rates of clinician burnout and attrition across healthcare, creating an even more strained healthcare system, understanding satisfaction with new technology and tools designed to improve their work conditions is more critical now than ever. As the technology, adoption level is vastly dependent on the users’ satisfaction level with the technology and its usefulness [23], there is a need to get insight into contingent factors that facilitate the satisfaction and adoption of wound care assessment technology.

Therefore, this study sought to explore clinicians’ level of satisfaction and perception of the technology’s clinical benefits. In addition, the study sought to explore the relationship between users’ practice patterns and perceived benefits and satisfaction of the solution. Finally, the study assessed the predictive factors associated with clinicians’ satisfaction with the digital solution.

Materials and Methods

Study design and population

This is a quality improvement descriptive cross-sectional survey of clinicians currently evaluating wounds using the Swift Medical application.

The study population consisted of active certified wound care clinicians in the US who have been using the application to evaluate wounds. Using the readily available data in the Swift application, of the thousands of wound care clinicians using Swift in the US, about 2,000 clinicians practicing in multiple care settings (i.e., home health care, outpatient clinics, and hospitals) across the US expressed an interest in participating in surveys or benefits evaluation studies upon initial adoption or renewal of the application.

On June 21^st, 2022, 2000 email invites with survey links were sent, either directly or through the administration at the participating organization. This represents over 100 Home Health Agencies (HHA), hospitals, and clinics across the US. Clinicians were encouraged to share the survey link with their networks who were eligible to participate in the study. The survey link directed the users to the Survey Monkey platform - an online survey tool to collect anonymous responses.

The survey link remained active for 13 days from June 21^st till midnight on July 3^rd, 2022. A reminder email was sent on June 28^th, 2022, to the available list of clinicians’ email addresses who adopted the technology; one week after the initial invite. A second and final reminder was sent on June 30^th, 2022, before the survey closing date.

Sample size calculation indicated that with a population size of 2000 and the study’s alpha level set at 0.05 for an 80.0% power, responses from 323 clinicians are required to detect significant differences in data if one exists.

The survey was designed for self-completion by clinicians currently using the wound management solution within their practice. The eligibility criteria allowed active certified clinicians of any age, gender, and years of practice who provide direct wound care and evaluation to patients using Swift to complete the survey. Therefore, a screening question was added to the survey to allow only eligible participants who downloaded and used the application to provide a response. When potential participants answered no to using the solution, they were directed to the end of the survey.

Upon clicking on the survey link, an information note is displayed to participants outlining the reason for collecting the feedback. No identifiable information was collected, making the responses anonymous. The survey took about 10-15 minutes to complete. Participation was voluntary.

Survey Instrument

TAM and UTAUT were used as a theoretical lens to quantify users’ perceived attitudes toward the digital technology, level of acceptance, and perceived efficiency to assess the likelihood of satisfaction and adoption of the new technology [17,22].

A systematic search of satisfaction surveys, digital technology, wound care, and digital wound assessment limited to English was conducted searching for surveys and instruments used by clinicians to assess satisfaction levels with adopting new technology in practice [26-30]. Relevant questions were used as a guide for the authors to develop this study questionnaire and develop a data-gathering tool. Survey questions were cognitively pilot tested for reliability by a diverse group of five community Registered Nurses (RNs) and wound-certified clinicians and two experienced researchers to assess the instrument wording, readability, and simplicity, applicability to participants’ experience, length, and structure. Survey questions were consistently refined and adjusted based on the received feedback. The tool’s face and content validity were determined through multiple discussions among the authors and iterative reviews.

The final simplified version of the survey consisted of 9 questions that included items designed to assess the convenience of the tool, performance expectancy, social influence, and perceived benefits. One question- with subcategories- addressed the perceived efficiency of using the application and the perceived performance expectancy. Of the remaining questions, four captured the practice pattern, including the role of the clinicians, the duration and frequency of use, and the number of wounds evaluated since the use of the application, while one question investigated the level of satisfaction with the wound application, and one assessed the likelihood to recommend it to other clinicians. Questions assessing practice patterns were in a multiple-choice format, while the others were categorical, with 5-point Likert scale response choices ranging from strongly agree/strongly satisfied to strongly disagree/ strongly dissatisfied, or very likely to very unlikely.

Participants were provided with the option to provide further input in a comment box on the perceived benefits they experienced from adopting the solution.

Responses were anonymous, and participants had the choice to skip over questions should they prefer not to respond to them. This quality improvement study has been granted an exemption of ethics review from Pearl IRB.

Statistical Analysis

All data analyses were performed in the Statistical Package for Social Sciences (SPSS) (SPSS, IBM Corp, Armonk, NY. Version 28; 2022). A summary of descriptive statistics generated from numeric and categorical variables of survey responses and summary data was displayed as frequencies (%) or mean.

The Chi-square test was used to examine the association between categorical variables in relation to the length of use and number of assessed wounds. A binary variable was created for the length of use; clinicians who had used the solution for <9 months versus those that used the solution for ≥9 months of application.

A binomial logistic regression analysis was conducted to investigate the association of the predictor variables- attitude and perceived efficiency of the solutions’ features and clinicians’ practice patterns- on the likelihood of satisfaction with the solution. The model was statistically significant, X2(7) =109.03, p<0.001. Hosmer and Lemeshow goodness of fit test= 0.721, indicating the model is a good fit. The model explained 36% (Cox &Snell R2)-58% (Nagelkerke R2) of the variance in satisfaction correctly classified 88% of the responses with a sensitivity of 92.8% and specificity of 68.2%.

Overall, a 2-sided P-value less than 0.05 was considered statistically significant.

Results

Clinicians’ role and practice pattern

The survey link was sent to approximately 2,000 clinicians, of which 460 responses were received (approximately 23% response rate). A further 75 respondents indicated that they have not used the solution yet and were automatically excluded from the survey. 385 users started the survey (19%), of whom 342 completed the survey and were included in the analysis. Clinicians’ roles and practice patterns are displayed in Table 1.

Table 1: Clinicians’ practice pattern.

Clinicians’ experience using the technology in relation to practice pattern

When clinicians were asked about their experience using the wound care technology, 81% stated they were satisfied with the solution and thought it captured accurate clinical information. The majority (86%) said they were able to successfully track wound progress with their patients. More than three-quarters (76%) agreed/strongly agreed that using the digital tool saved them time measuring wounds, and 77.5% felt it met their clinical needs and that they preferred the digital solution over the traditional, manual methods of wound measurement (Table 2).

Regarding the differences in responses based on the length of application use and the number of wounds assessed with the technology, we investigated the difference in responses for clinicians who had used the solution for <9 months versus those that used the solution for ≥9 months. Clinicians who used the solution for more than nine months were 9% more likely to be satisfied with the solution than those who used the solution for less than nine months (85.5% vs. 76.5%, P=0.034) (Table 2).

Also, clinicians who used the solution for more than nine months were 9.5% more likely to agree that the solution saves time in wound measurements (81.1% vs. 71.6%, P=0.023), 5.1% more likely to agree it tracks changes in clinical conditions (88.7% vs. 83.6%, P=0.045), 5.7% more likely to believe it supports effective collaboration (76.1% vs. 70.4%, P=0.044), and 5.6% more likely to think it meets clinical needs (80.5% vs. 74.9%, P=0.043) (Table 2). 

Clinicians who assessed more than 100 wounds were significantly more likely to prefer the digital wound management technology over traditional methods of wound measurement than those who assessed less than 100 wounds (82.5% vs 72.3%, P=0.014). Moreover, they were more likely to believe that the solution saves time in wound measurements (81.3% vs 70.5%, P=0.012) (Table 2).

Table 2: Clinicians’ experience using the solution by practice pattern.

Factors associated with clinicians’ satisfaction -Logistic regression model

Of the eight predictors introduced to the model, only four were statistically significant: length of time the solution was used, efficient collaboration with another clinician, preferring the digital technology to traditional methods of wound assessment, and productivity at the workplace (Table 3). Odds Ratios using the “length of use” as the focus variable indicate that clinicians using the solution for more than nine months were 2.3 times more likely to be satisfied than those who used it for a shorter period. Clinicians who experienced efficient collaboration with other providers had 2.29 times higher odds of being satisfied with the solution. Clinicians preferring digital technology to traditional methods of wound assessment had 7.31 times higher odds of satisfaction. Finally, clinicians that perceived improved clinical productivity were 10 times more likely to be satisfied with the technology (Table 3).

Table 3: Factors associated with clinician’s satisfaction with Swift digital solution- Binomial Logistic Regression.

Open Ended Question

To understand any additional reflections on the solution’s benefits, content analysis of the open-response question indicated a variety of benefits that clinicians have experienced with the digital tool post-implementation. Nine thematic characteristics were identified from the analysis as essential keys to the solution’s success, of which 11 further sub-thematic categories emerged (Table 4).

The main themes that emerged from responses to the open-ended questions were a) participatory- patients clinician interaction, b) clinician empowerment, c) collaboration, d) standardized, consistent care, e) image quality, f) privacy, g) documentation comprehensiveness, h) accessibility,

Selected quotations related to each theme and subthemes were annotated under each theme and sub-theme and outlined in Table 4.

Table 4: Summary description of themes and related quotes.