Healthcare Simulation Technology Specialist (HSTS) Survey

Authors

Lisa A. Paganotti, PhD, PA-C, CHSOS¹, Gregory E. Gilbert, EdD, MSPH, PStat®², Scott B. Crawford, MD, CHSOS³, Ronald J. Shope, PhD¹

¹ - George Washington University, Translational Health Sciences Program, Washington D.C.

² - ΣigmaΣtats ConsultingTM, LLC, Charleston, SC

³ - Scott B. Crawford, MD, Associate Professor, Texas Tech University Health Sciences Center El Paso, El Paso, TX

Lisa Paganotti, Gregory E. Gilbert, Scott Crawford, and Ronald J. Shope have no conflicts of interests to declare. Gregory E. Gilbert was not compensated for his contributions to this manuscript.

Corresponding Author

Lisa Paganotti, George Washington University, Department of Health, Human Function and Rehabilitation Science (Email: lisaannbuckley@gwu.edu).

Abstract

In general, little is known about the features of the current healthcare simulation technology specialist (HSTS) workforce. This information is essential to best support and develop a robust workforce to support simulation-based education. The intention of this research is to understand demographic information about HSTS professionals and understand their education and experiences. An online survey was developed and distributed to professional societies that support training and education for HSTS. Researchers analyzed 97 completed, and 23 partially completed surveys, representing a 3% response rate. Investigators evaluated data from the survey to generate a job profile for the HSTS role. This study provides baseline data on the characteristics of the HSTS profession in 2021. Despite the low response rate, these data provide a baseline for characteristics of the HSTS workforce and suggest heterogeneity exists among those working in the HSTS role.

Introduction

Healthcare Simulation Technology Specialist (HSTS) Survey

Simulation in healthcare has been growing over the last twenty years (Motola et al., 2013). As the use of simulation technology has grown, so too has the demand for technical and operations support staff for simulation programs. Job titles and responsibilities for HSTS roles are far from unified due to the varied nature of each simulation center and the evolution of the profession (Bailey et al., 2015; Steer et al., 2019). A review of simulation center operations found “technicians” to be the most common role employed (Tranel et al., 2021). The technical side of simulation operations is essential for a highly functioning simulation center and for the growth of healthcare simulation (Bailey et al., 2015). Qayumi et al. found the need for a dedicated simulation technician was a top barrier to the growth of a simulation program in an international survey (Motola et al., 2013). This article will use the term HSTS to encompass all technical and operational simulation roles (Lioce et al., 2020). ²

In 2012, Gantt described the need to define the title and role of the person who operates the simulator (Gann, 2012). To grow and professionalize HSTS, Bailey et al helped define the responsibilities and core duties (Bailey et al., 2015). Supporting the findings of the Bailey study, the Society for Simulation in Healthcare (SSH) and the Gathering of Healthcare Simulation Technology Specialists (SimGHOSTS) each conducted a practice analysis of necessary skills and domains of knowledge for this role. Crawford et al., described the overlap of these respective five and eight domains with example work tasks (Crawford et al., 2019). The five-domain outline was used as the basis for the Certified Healthcare Simulation Technology Specialist (CHSOS) certification from SSH. Steer et al. developed a capability framework to further define and differentiate the progression of skills for the foundational, intermediate, and senior-level HSTS using the eight-domain outline from SimGHOSTS Steer et al., 2019). Collectively, the described work has clarified and codified the role of the HSTS and was used to support the standards and elements for recognition as a CHSOS – Advanced by the SSH.

In many fields, a job profile is available for employees or for those interested in the profession. Job profiles outline job duties, salary, benefits, educational requirements, physical locations, and additional information. To date, despite the efforts of those in the field of simulation operations, this information has not been universally described for the HSTS role. This study addresses this gap though a survey providing data to understand and describe the current HSTS workforce. The purpose of this survey was to determine characteristics of current HSTS professionals and the education and experiences of those in that role. The study addressed the following research questions: “What is the current state of the HSTS professional workforce in terms of job titles, location, education, experience, salary, and benefits?” and “Is there an association between salary and location, education, licensure, or certification?”

Methods

Survey Design and Pilot Study Procedures

Survey questions were based on the job profile questionnaires of other professions and from the experiences of the authors in consultation with other HSTS experts. Initial survey feedback was provided by two authors (Ron Shope and Gregory E. Gilbert) with expertise in survey development. The initial draft was circulated to five individuals for feedback on design, clarity, grammar, typographical errors, survey flow, visual display features, and ease of use. Subsequently, the survey was pilot tested with HSTS experts who provided feedback on content. Feedback was received from five experts, two of which had substantial experience with survey creation and data collection. All five HSTS experts agreed the survey questions have face validity. Finally, the survey was reviewed by the Board of Directors of SimGHOSTS. See Appendix A for survey questions. This study was reviewed and determined to be exempt by the Institutional Review Board of George Washington University. The authors conducted the project in accordance with the tenets espoused in the Declaration of Helskinki (World Medical Association, 2012).

Sampling Plan

The target population was HSTS currently working in the field. Over 4,000 individuals with membership to either SimGHOSTS or SSH CHSOS and Simulation Operations and Technology Section Listserv groups received an invitation to complete the survey. The survey link remained open for one month and reminders were sent weekly. ³

Analysis

Data analysis was completed using R statistical software. Researchers calculated absolute frequencies and percentages for the data. Researchers investigated several questions related to salary using null hypothesis statistical tests that used Fisher’s exact test and report Cramer’s V as an effect size. In accordance with the 2019 American Statistical Association statement admonishing investigators draw no conclusions with respect to “statistical significance”, the authors chose not to dichotomize “statistical significance” in favor of interpreting p values in the vicinity of .05 as evidence of statistical difference (Wasserstein et al., 2019).

Results

At the close of the survey link, 97 respondents completed surveys and an additional 23 surveys were partially completed, representing a total of 120 survey respondents (a 3% response rate of the possible 4,000 list serve recipients). The results showed most respondents worked over 51% of their time in a technical role and worked 31 to 40 hours weekly. Roughly half of respondents (Table 1) were not a licensed or registered healthcare professional. The vast majority of HSTSs spend most of their time on manikin-based simulation (79%, n=76) followed by task trainers (15%, n=14), standardized patients (4%, n=4), and lastly virtual reality/augmented reality, or mixed reality simulation (2%, n=2).

In response to experience, respondents were equally distributed between two and fifteen years. Responses showed 25% (n=24) had been employed with their current employer for less than two years, 34% (n=34) two to four years, 14% (n=13) four to six years, 6% (n=6) longer than six to eight years, 6% (n=6) eight to ten years, 8% (n=8) ten to fifteen years, and 5% (n=5) for greater than fifteen years. Employer-paid funding for professional development revealed 18% (n=18) had no funding. The remainder of responses ranged from $1 to more than $2,000 annually.

Table 1 shows the location and demographic characteristics of respondents. Educational background responses varied with the majority having a bachelor’s degree (Table 1). In addition, over 50% of respondents have the CHSOS credential. Twenty-seven percent (n=25) plan to take the CHSOS examination, and 20% (n=18) do not have it and are not planning to take it. Twenty-seven percent (n=26) of respondents use the job title Simulation Operations Specialist or HSTS. Respondents identified various job titles which include simulation manager, coordinator, director of simulation education and research, simulation operations technician, simulation engineer, surgical lab manager, lead simulation operations specialist, and senior trainer.

There was a range of informal education opportunities described as on-the-job training (79%), attending conferences (81%), and being mentored or mentoring (50%). Additional text responses included reading articles, posts in a listserv community, performing committee work, attending simulation courses, college courses, participating in vendor training, or attending simulation webinars. Fifty-five percent of respondents spend between 21 and 40 hours annually in informal training; however, additional written responses ranged from 80 to 200 hours.

Table 2 represents the organizational characteristics of respondents. Most respondents (67%, n=62) have no employees reporting to them; 11% (n=10) one direct report, 4% (n=4) have two direct reports, 3% (n=3) have three direct reports, 2% (n =2) have four direct reports, and 13% (n =12) have five or more employees reporting to them. Almost all respondents (98%, n =91) reported employers paid for vacation, sick and/or personal leave. Respondents described their employer as an academic medical center (37% n =36), nursing school (20%, n=19), a medical school (11%, n=11), a health profession school (9%, n=9), a community hospital (7%, n=7), or a government, consultant, military, or vendor position (4%, n=4) (Table 2). Still, an additional 11% (n=11) listed their employer as “other”.

Respondents reported a wide range of annual salaries. Responses varied from less than $25,000 per year to over $86,000 United States Dollars (USD) per year. The category with the most responses was ≥$86,000 (14%, n=12). The next highest response rate was tied between $36-41,000 and $51-56,000 (both 11% (n=10). Cramer's V was used to evaluate a relationship between salary and role/respondent characteristics. There was a weak (Cramer's V=.32) association between the number of direct reports and salary. There was statistical evidence of an association (p=.060), however weak.

Cramer’s V was used and there was no statistical evidence in this sample of an association between salary (<$55,000, $56,000-$85,999, and ≥$86,000) and region of the world (Asia-Pacific, North America, and Europe) (p=.110). Cramer’s V is .21, meaning the maximum amount of variation in salary explained by region is 21%. However, there was statistical evidence of an association between education (Associate’s or less, Bachelor’s, and Master’s+) and salary (<$55,000, $56,000-$85,999, and ≥$86,000) (p=.021with 26% of the variance in salary being explained by education. Similarly, association in the sample between licensure (licensed, not licensed, and previously licensed) and salary (<$55,000, $56,000-$85,999, and ≥$86,000) also showed statistical evidence of an association (p=.026) with 26% of the variance in salary being explained by licensure category. There was no statistical evidence of an association between certification (CHSOS and no CHSOS) and salary (<$55,000, $56,000-$85,999, and ≥$86,000) (p=1.000). Virtually no variation in salary was explained by certification (2%). Lastly, salary (<$55,000, $56,000-$85,999, and ≥$86,000) and institution were examined (corporate/government, healthcare school, and hospital) salary and institution showed no statistical evidence of association (p=.174). The maximum amount of variation in salary explained by institution was 20%.

Discussion

Prior studies identified the lack of persons in the HSTS profession to be a barrier to simulation education development (Qayumi et al., 2014). A study reported at the SSH conference in 2017 surveyed 108 simulation center directors, and only two respondents found well-qualified HSTS individuals available to hire and 81% of respondents (n=87) found few applicants for the positions (Forinash et al., 2017). The same survey found a similar dichotomy in salary reported with 42% (n=52) of directors surveyed in 2016 reporting a salary for HSTS between $30,000-50,000 and 38% (n=47) in the $50,000-70,000 range (Forinash et al., 2017). Promoting the HSTS role as a healthcare career with science, technology, engineering, and math (STEM) opportunities may be a way to increase the availability of persons in this role and increase the diversity of the workforce.

A comparison was made between this study and the Bailey et al. article. Bailey et al. had slightly more male (64%) respondents than female (36%) compared to this study (55% male and 43% female) (Tranel et al., 2021). One explanation is an increase in HSTS women between 2015 and 2021. Alternatively, it is possible more women were motivated to respond to this survey. Age ranges and degrees were similar in both studies.

An article by Tranel et al. in 2021 surveyed simulation centers about their operations (Tranel et al., 2021). The only data collected by both studies was the distribution of employers associated with a school. Trenel and Qayumi, 57% and 79%, respectively, were associated with a school and in this study, 40% (n=39) were employed by a nursing, medical, or health professions school (Tranel et al., 2021; Qayumi et al., 2014). This contrasts with those employed by a hospital, government, or other employer, which represented 45% of responses in this study. This may represent an expansion in location of simulation centers from academic institutions to academic and community hospitals.

Interestingly, Qayumi et al. noted the most used modality was online simulation modules, followed by task trainers and lastly human patient simulation (Qayumi et al., 2014). This contrasts with this study where respondents reported spending most of their time on manikin-based training, then task training, followed by standardized patients, and lastly virtual/augmented or mixed reality simulations. It could represent a shift in simulation use over time and will be interesting to follow this trend into the future.

This study had a high number of respondents (53%, n=49) who earned their CHSOS. This is likely biased by using the CHSOS distribution list to recruit study participants, and therefore, the percentage of overall HSTS professionals with the credential of CHSOS may be lower than represented by this survey.

The lack of racial and ethnic diversity in responses provides an opportunity for outreach to encourage the inclusion of diverse backgrounds in the HSTS profession. Since 50% of 7 respondents reported being mentored or mentoring another individual, mentorship could increase diversity.

This study demonstrates heterogeneity across the HSTS profession in the characteristics surveyed and provides a baseline on characteristics for HSTS professionals. This heterogeneity may present a barrier to the growth of the profession, the development of training programs, and the recruitment of new HSTS into the field. A similar survey targeting other simulation center staff, to identify areas of role overlap could help identify this possibility. The results are not only interesting for those in the field of healthcare simulation but also for individuals interested in an HSTS career.

Limitations

The main limitation was the small sample size (n=120). The low response rate may be due to inactive or out-of-date email accounts, individuals deleting the survey without opening it, or ignoring the content due to email/survey fatigue. Another explanation is individuals did not participate if they did not primarily identify as an HSTS and thought it did not apply to them. This may have occurred because a common feature described by simulation staff is the concept of a hybrid role, where an educator or administrator may also be asked to perform the duties outlined in HSTS domains.

Conclusions

Prior to this research, summary data has been collected for marketing and tracking purposes by professional societies but, the authors are not aware of any studies that have sought to identify characteristics of the HSTS professionals and jobs. Therefore, these results provide baseline data for the profession in 2021. Due to the low response rate, the authors are hesitant to generalize the data to the HSTS profession. Despite the response rate, it is suggested that much heterogeneity exists among the HSTS workforce. The authors plan to repeat the survey with the hope to increase the response rate and to compare and track changes in the HSTS profession over time. Efforts to increase the response rate will include in-person advertising and promotion of the survey at the annual conferences for SSH’s SimOps, International Meeting for Simulation in Healthcare, and SimGHOSTS.