The role of simulation in surgical resident training is expanding to supplement traditional in-hospital training. In surgical training, simulation attempts to reproduce the essential learning points of a real-life experience.1–4 With an increase in operating theater demands, decreased working time for surgeons to learn, and concern for patient safety, the use of simulation in surgical training seems to be a desirable solution at face value.5,6 Simulation used to teach open surgical skills usually consists of synthetic, organic, or animal models to recreate the reality of the operating theater.7,8 Occasionally, models of increasing fidelity are used, such as live animals, fresh cadavers, and, less frequently, virtual reality simulators.1,8 The benefits of simulation allow the surgeon to learn a procedure in a risk-free environment with formative feedback from experts in that specialty.9 This type of simulation also allows the learner to grasp instrument handling and to familiarize themselves with new technology in a flexible and cost-effective setting.10–12 Once proficient with deliberate practice, specific scenarios with challenging pathology can enhance decision-making and error avoidance and thus enhance patient safety when back in the hospital setting.13 In competency-based education, mastery learning with its stringent proficiency targets has been shown to lead to increased maintenance of skills.14–16 The constancy of the simulator for open surgery also provides formative and summative feedback and provides further motivation for the surgeon to achieve mastery outcomes.
Key questions are as follows: are simulators effective in allowing the educator to achieve their learning objectives and the appropriate fidelity for the procedure and have they aided proven transferability of the skill to the patient? When a simulation center is deciding to purchase simulators for surgical training, their priorities will be cost, reusability of the simulator, associated consumables, cost of faculty to teach with them, and the demand to learn a certain procedure. The purchaser would be very much reassured if there was research in the literature demonstrating educational effectiveness, high levels of validity such as discriminative and predictive validity, and transferability of the skill.17–21
With the evolution of many formerly open procedures to endoscopic or laparoscopic surgery, much of the literature looks at simulation for minimally invasive surgery (MIS) with an emphasis on virtual reality simulation. There is more evidence in the literature on the study of the effectiveness of simulation used in MIS.22 The challenges faced by residents converting from closed to open surgery have led to an increase in the numbers seeking out fellowships to refine their open surgical skills. There are comprehensive articles on simulation with valuable descriptions of types of simulators used for training and assessment of surgical skills.3,9 A recent systematic and current review of simulation concentrates on training techniques using simulation and inevitably concentrates on those used in MIS.20,23 In developing simulators to teach open surgical procedures, there is an increasing amount of simulators being developed commercially and by educational institutions; however, it is not clear whether the evidence in the literature supports their educational value. Animal or human models used for simulation have the highest fidelity to teach open surgical skills; however, they require an expensive facility and there are ethics issues. We wish to concentrate on synthetic and virtual reality simulators in this review because we have more control over their design to address particular learning outcomes. Educational institutions can feedback to the makers of simulators to increase the fidelity of their devices or request the insertion of patient-specific pathology into them, for example. Although there are two interesting reviews specifically looking at simulation in open surgery, there is no systematic review looking at learning outcomes with the use of the individual simulators themselves.24,25 The purpose of this systematic review and narrative synthesis is to examine the totality of evidence relating to the educational effectiveness of open surgical simulators or task trainers among surgical trainees.
We conducted a systematic review and narrative synthesis of randomized controlled trials (RCTs) that examined the educational impact of surgical simulators and/or task trainers when compared with routine practice among preregistration and postgraduate surgical trainees. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses standardized reporting guidelines were followed to ensure the conduct and reporting of the research.26
A comprehensive search string was developed in consultation with the faculty librarian. Databases including PubMed, Embase, CINAHL, Scopus, and Web of Science were searched using a combination of the following key words and search terms: “undergraduate” OR “postgraduate” OR “resident” OR “surg*” OR “trainee” OR “internship” AND “simulat*” OR “task trainer” OR “part task trainer” OR “bench model” OR “physical model” OR “virtual reality” OR “low fidelity” OR “high fidelity” OR “open simulat*” AND “surgical education*” OR “assessment” OR “proficiency” OR “education*” OR “train*” OR “skill*” OR “competence” OR “technical skill” OR “skill acquisition” OR “educational efficacy” OR “OSATS.”
Only RCTs (including quasi-RCTs or cluster RCTs) were included where the population of interest included either or both undergraduate and postgraduate surgical trainees. In RCTs, the unit of randomization is the individual participant, whereas in cluster RCTs, the unit of randomization is the participating center (eg, medical school, emergency department, etc). In RCTs, randomization to groups (intervention or control) is usually completed using computer-generated random numbers. Some studies use other methods to randomize such as day of the week or birthdate. These are termed quasi-RCTs because true randomization has not occurred. We included both of these types of experimental studies because randomization is the only method to prevent systematic differences between baseline characteristics of participants in the intervention and control groups in terms of both known and unknown confounding effects. Empirical evidence suggests that on average, nonrandomized studies produce effect estimates that indicate more extreme benefits of the effects of interventions than RCTs.27 All postgraduate surgical specialties were included in the review. The types of intervention included any task trainer or bench top model that is used as simulation for open surgical training. Simulators include physical models made from synthetic or biological material or a mixture of both, including commercially available models or a model developed by the authors. For the purposes of this systematic review, we focused on models that provided haptic feedback while performing the skill. We also included any simulator of both low and high fidelity. We were interested in outcomes that captured a change in proficiency or skill or confidence of the trainee after the intervention. Studies investigating the training of closed or endoscopic skills were excluded. Examples of closed skills included laparoscopic, endoscopic, and arthroscopic skills. In this study, we looked at studies, which referred to learning open surgical procedures. We also excluded all computer-based simulators including virtual reality that did not have a simulated instrument attached, software imaging controlled by touch screen, or hybrid augmented reality trainers. Medical skills training that did not involve an invasive surgical element were excluded, such as the physical examination of a patient or taking a blood pressure. Studies examining skills where a needle or a tube was inserted into a body cavity or a blood vessel were also excluded.
Data Extraction and Synthesis
A data extraction form was developed by the review team and data extraction was independently undertaken for each study by two reviewers (L.H., R.G.). Information was extracted on authors, year of publication, country of origin, study design, population studied, intervention examined, comparison group and outcome measures assessed, as well as the duration of follow-up. The methodological quality of the included studies was assessed using the Cochrane risk of bias tool for RCTs.27 Domains include selection bias, performance bias, detection bias, attrition bias, selective reporting of outcomes bias, and other biases associated with the study. Selection bias arises because of inadequate generation of a randomized sequence or inadequate concealment of allocations before assignment. Performance bias occurs where there is knowledge of the allocated interventions by participants and personnel during the study. Detection bias refers to knowledge of the allocated interventions by outcome assessors. Attrition bias occurs where the amount, nature, or handling of outcome data is incomplete. Reporting bias arises because of selective reporting of study outcomes. As per the Cochrane guidance notes, each domain was rated by two independent reviewers (L.H., R.G.) as low, unclear, or high risk of bias.27 A “low risk” of bias was awarded if each criterion was met; a “high risk” of bias was documented if each criterion was not met and an “unclear risk” of bias was determined if there was insufficient information presented in the article to permit judgment of low risk or high risk. A consensus meeting was held to resolve discrepancies between reviewers. Seven discrepancies were identified from a total of 42 assessments by each reviewer. In four cases, the discrepancies across reviewers related to selection bias [randomization and allocation concealment (AC)] and three cases related to detection bias in the studies. All discrepancies were resolved without the need for a third independent reviewer.
Study Identification and Selection
Figure 1 describes the flow of studies in the review. After the removal of duplicate studies, 9934 studies were screened by title/abstract. The full-text articles of 11 studies were retrieved for review, five studies28–32 were subsequently excluded and the remaining six RCTs were included in the review.33–38 There were no trials looking at the effectiveness of a virtual reality simulator in open surgery.
Descriptive Characteristics of the Studies
The sum of the participants over all RCTs was 197. Two studies evaluated the effectiveness with undergraduate students evaluating suturing skills of theses novice participants. The remaining studies evaluated tasks that are more complex for postgraduate trainees. Only two of the studies reported the cost of the simulators being studied, for example, the anterior cruciate ligament (ACL) model cost US $20 to make and the temporary vascular shunt placement simulator cost US $40 to make.33,34 Table 1 details the descriptive characteristics of the included RCTs. One study investigated an orthopedic simulator, two investigated a minor suturing procedure, and three investigated a vascular surgery model.33–38 Two of the studies tested two simulators against each other (high-fidelity model vs. low-fidelity model) when compared with the control group.35,37 In four of the six studies, the control group were taught by a video, lecture, and textbook.33,35–37 All studies used a form of global rating to document how the participant in the studies performed. Some of the global rating tools were validated, and some were bespoke or modified. Four of the studies used specific check lists for assessing steps in the procedure in addition to the global score rate. The maximum score for each study was different. Some studies had additional test parameters included such as self-reported confidence levels of the participants, time to complete the test, and final product scoring.34,35,37,38
Methodological Quality of the Included Studies
Table 2 details the methodological quality of the included studies. Four studies had a low risk of selection bias34–37 because participants were randomly selected or block randomization was performed. In two studies,33,38 random sequence generation was not described. Two studies showed low risk of AC bias because they used a computer-generated allocation.35,36 The other four studies did not describe how they allocated their groups. Performance bias was considered to be high risk across all interventions because it was not possible to blind participants and personnel to group allocation. In one study,38 it is not clear whether the examiners were blinded or if they were involved in the training on the simulator, so this study has a high risk of detection bias. All other studies had a low risk as they blinded their examiners by using video recordings of the examinations and the examiners were independent to the study.
In terms of selective reporting of outcomes, one study33 reported participant's skills performance scores but failed to give a numerical value for their confidence and knowledge scores and could be considered high risk. All articles were considered to have a low risk of attrition bias.
The variability across the studies in terms of populations studied, simulators examined, comparisons tested, and outcomes explored limited our ability to statistically pool the data. For example, two of the six studies did not perform a pretest of baseline knowledge or skills at the beginning of the RCT,34,38 thus limiting our ability to interpret the educational value of the intervention. There was significant heterogeneity across the studies with respect to outcomes reported. Four of the six articles used a check list to explore the impact of the simulator33,34,37,38 with scores across the variety of check lists ranging from 1033 to 30 points.37 Table 3 displays the differences in outcome across the control and intervention groups on the checklist scores. Three of the studies demonstrated a significant educational impact of the simulator postintervention when compared with the comparison group.
There were some checklist components incorporated into the global rating score in one study.35 With regard to the global rating score, only one article used the OSATS (Objective Structured Assessment of Technical Skill)39 in its original format34 with a maxim score of 35. All other studies the authors adapted the global assessment tool, including extra items particular to the procedure, and in some cases, they added a final product score. Therefore, the max score ranged from 35 to 40 and the adaptation made the scores less comparable across the studies. However, all studies that used a pretest showed a significant increase in scores by the participants using the simulators when compared with participants in the controlled groups. Table 4 displays these findings.
The final product analysis, where the appearance of the finished skill is studied, is often excluded from studies on open skills. The quality of the final product analysis was incorporated into the adapted global rating tools used in three studies.35,36,38 The study investigating the effectiveness of a silicon tube and live vas deferens and a control go a step further in their posttests to examine effectiveness of the simulators.37 They examine the final product just after the initial assessment and then 30 days later to determine whether the structure is still patent, with significant differences still evident across the groups at 30 days.
Although subjective, two of the articles included an additional self-reported confidence or knowledge of skills in the pretest and posttest, which adds to the complexity of the outcomes.33,35 In both cases, the use of the ACL simulator and the four models to teach the excision of a lesion significantly increased the confidence of the exposed group when compared with the control group.
This systematic review explored the totality of evidence regarding the educational effectiveness of simulators used in open surgical training. We identified six studies that met our inclusion criteria.33–38 All simulators examined were noncommercial and made by the authors of the studies. There was significant heterogeneity across the studies in terms of the populations, interventions, comparison groups, and outcomes examined. This limited our ability to pool the data using statistical methods. However, our narrative synthesis demonstrates that overall, the results favor the use of simulators over conventional methods used to teach open surgical skills among undergraduate and postgraduate trainees. We have to acknowledge in the study of task trainers for an open surgical simulator that the input of the facilitator is important in bringing out the most value of the simulator as a learning tool. One study that developed an in-house aortic aneurysm repair model showed a superior effect when the model was facilitated with a vascular surgeon as compared with a technician.40 Most of the included studies addressed this performance bias by ensuring that the control group got similar training.
We used robust and transparent methods to identify, select, appraise, and synthesize the findings from the review. Our comprehensive search string across multiple databases yielded a significant number of studies for consideration. A large number of studies addressed simulation in MIS particularly with the use of virtual reality trainers. The search also yielded studies, which concentrated on different teaching methods, validation studies, and nontechnical skills simulation studies. Some RCTs did not address educational effectiveness directly but looked at issues such as using a carotid artery bench model to assess competency before doing in-hospital surgery or examined the effectiveness of an extended skills course where the simulator only featured in a small part of the entire course.41 An RCT included in the two previously published open simulation reviews included the transfer of skills for the Berlin Operation Trainer, which teaches the trainee to stand in the correct position for a bowel anastomosis and creates human anatomical visuals of the inner abdomen. We did not use this study because the trainer necessitates the insertion of animal bowel for the anastomosis.42 The non-RCTs relating to open surgical simulators included technical descriptions of materials such as urinary catheters being used in tendon repair or a synthetic bowel being used as the prepuce for a circumcision model.43,44 The use of 3D printing was also featured with patient data being used to create a skull for cranial base surgery and a soft kidney phantom with realistic anatomical structures.45,46 There are a few virtual reality simulators for teaching open surgical skills, such as Sim-Ortho for open spinal surgery, the virtual reality education surgical tool to teach open hernia surgical repair and the Boston Dynamics INC surgical simulator for teaching suturing.47–49 We did not include virtual reality simulators, which do not have physical instrument with haptic feedback but aid the learning of the anatomy, procedural steps, and decision-making. Examples of these include the open inguinal hernia repair simulation model and touch surgery.31 We noticed that when using the key word “high fidelity” in our search, it yielded a significant number of studies describing virtual reality simulators as opposed to likeness to real-life models.
It is surprising that so few randomized controlled trials were finally selected. It may be possible that trials studying the educational merit of commercial simulators may have taken place in-house and thus the findings are not published. It may be also difficult to design theses studies in the student setting but an element of using cross-over study designs should discourage any ethical issues. Although the literature demonstrating a positive educational contribution of simulators in open surgery is increasing, the evidence for validity and transferability to the patient has not been widely explored. This is predominantly due to the design of the studies where the surgical simulator is often used as a component of a larger training course with lots of other contributing factors to the end of course assessment. Furthermore, it is difficult to prove transferability of specific simulators because there are so many other factors such as in-hospital training that may influence the student experience.
The variability across the studies limits the internal and external validity of the findings of the review. Further methodologically robust longitudinal studies are warranted using standardized methods to conduct and report the findings. There are emerging articles exploring the development of guidelines for specific validation simulators used in surgical practice.50 There are some efforts at creating consensus guidelines for the validation of virtual reality simulators used in endoscopic surgical education.51 It would appear from our review, with the lack of high evidence studies on both commercial and noncommercial simulators, that such guidelines should include educational effectiveness demonstration and evidence of transferability to the hospital setting.19,52 In addition, this higher level of evidence would help educators decide on the most effective simulators to add to their curriculum and simulation centers. This type of research is bound to encourage the development of more sophisticated simulators that satisfy the teaching of learning outcomes important for that open procedure. Demonstration of a reduction in medical error and enhanced recognition of patient safety issues would further enhance the rate of simulator use.
A small number of studies were found that assessed the educational benefit of open surgical training tools. It was not possible to meta-analyze these studies because of methodological and clinical differences across the studies. Further studies are needed to secure higher evidence for the educational value, validity, and transferability of the skills to the hospital setting for all simulators in use in surgical training. In the interim, this systematic review adds positive encouragement to their use.
1. Tan SS, Sarker SK. Simulation
in surgery: a review. Scott Med J
2. Issenberg SB, McGaghie WC, Hart IR, Mayer JW, Felner JM, Petrusa ER, et al. Simulation
technology for health care professional skills training and assessment. JAMA
3. Sarker SK, Patel B. Simulation
and surgical training. Int J Clin Pract
4. Scott DJ, Cendan JC, Pugh CM, Minter RM, Dunnington GL, Kozar RA. The changing face of surgical education
as the new paradigm. J Surg Res
5. De Montbrun SL, Macrae H. Simulation
in surgical education
. Clin Colon Rectal Surg
6. Kneebone R. Simulation
in surgical training: educational issues and practical implications. Med Educ
7. Hamdorf JM, Hall JC. Acquiring surgical skills. Br J Surg
8. Cosman P, Hemli JM, Ellis AM, Hugh TJ. Learning the surgical craft: a review of skills training options. ANZ J Surg
9. Hammoud MM, Nuthalapaty FS, Goepfert AR, Casey PM, Emmons S, Espey EL, et al. To the point: medical education review of the role of simulators in surgical training. Am J Obstet Gynecol
10. Aucar JA, Groch NR, Troxel SA, Eubanks SW. A review of surgical simulation
with attention to validation methodology. Surg Laparosc Endosc Percutan Tech
11. Schout BM, Hendrikx AJ, Scheele F, Bemelmans BL, Scherpbier AJ. Validation and implementation of surgical simulators: a critical review of present, past, and future. Surg Endosc
12. Maran NJ, Glavin RJ. Low- to high-fidelity simulation
- a continuum of medical education? Med Educ
13. Norman G, Dore K, Grierson L. The minimal relationship between simulation
fidelity and transfer of learning. Med Educ
14. Wayne DB, Barsuk JH, O'Leary KJ, Fudala MJ, McGaghie WC. Mastery learning of thoracentesis skills by internal medicine residents using simulation
technology and deliberate practice. J Hosp Med
15. Siddaiah-Subramanya M, Smith S, Lonie J. Mastery learning: how is it helpful? An analytical review. Adv Med Educ Pract
16. McGaghie WC, Issenberg SB, Cohen ER, Barsuk JH, Wayne DB. Medical education featuring mastery learning with deliberate practice can lead to better health for individuals and populations. Acad Med
17. Kneebone R, ApSimon D. Surgical skills training: simulation
and multimedia combined. Med Educ
18. Reznick RK, MacRae H. Teaching surgical skills-changes in the wind. N Engl J Med
19. Sturm LP, Windsor JA, Cosman PH, Cregan P, Hewett PJ, Maddern GJ. A systematic review of skills transfer after surgical simulation
training. Ann Surg
20. Sutherland LM, Middleton PF, Anthony A, Hamdorf J, Cregan P, Scott D, et al. Surgical simulation
: a systematic review. Ann Surg
21. Anastakis DJ, Regehr G, Reznick RK, Cusimano M, Murnaghan J, Brown M, et al. Assessment of technical skills transfer from the bench training model to the human model. Am J Surg
22. Zendejas B, Brydges R, Hamstra SJ, Cook DA. State of the evidence on simulation
-based training for laparoscopic surgery: a systematic review. Ann Surg
23. Dunkin B, Adrales GL, Apelgren K, Mellinger JD. Surgical simulation
: a current review. Surg Endosc
24. Davies J, Khatib M, Bello F. Open surgical simulation
—a review. J Surg Educ
25. Fonseca AL, Evans LV, Gusberg RJ. Open surgical simulation
in residency training: a review of its status and a case for its incorporation. J Surg Educ
26. Shamseer L, Moher D, Clarke M, Ghersi D, Liberati A, Petticrew M, et al. PRISMA-P Group. BMJ
27. Higgins JP, Green S, editors. Cochrane Handbook for Systematic Reviews of Interventions Version 5.1.0 (updated March 2011). The Cochrane Collaboration, 2011. Available at: handbook.cochrane.org
. Accessed November 5, 2018.
28. Dancz CE, Sun V, Moon HB, Chen JH, Özel B. Comparison of 2 simulation
models for teaching obstetric anal sphincter repair. Simul Healthc
29. Geoffrion R, Suen MW, Koenig NA, Yong P, Brennand E, Mehra N, et al. Teaching vaginal surgery to junior residents: initial validation of 3 novel procedure-specific low-fidelity models. J Surg Educ
30. Grierson L, Melnyk M, Jowlett N, Backstein D, Dubrowski A. Bench model
surgical skill training improves novice ability to multitask: a randomized controlled study. Stud Health Technol Inform
31. Khatib M, Hald N, Brenton H, Barakat MF, Sarker SK, Standfield N, et al. Validation of open inguinal hernia repair simulation
model: a randomized controlled educational trial. Am J Surg
32. Palter VN, Grantcharov T, Harvey A, Macrae HM. Ex vivo technical skills training transfers to the operating room and enhances cognitive learning: a randomized controlled trial. Ann Surg
33. Brusalis CM, Lawrence JTR, Ranade SC, Kerr JC, Pulos N, Wells L, et al. Can a novel, low-cost simulation
model be used to teach anterior cruciate ligament graft preparation? J Pediatr Orthop
34. Carden AJ, Salcedo ES, Leshikar DE, Utter GH, Wilson MD, Galante JM. Randomized controlled trial comparing dynamic simulation
with static simulation
in trauma. J Trauma Acute Care Surg
2016;80(5):748–753; discussion 753–4.
35. Denadai R, Oshiiwa M, Saad-Hossne R. Teaching elliptical excision skills to novice medical students: a randomized controlled study comparing low- and high-fidelity bench models. Indian J Dermatol
36. Denadai R, Saad-Hossne R, Oshiiwa M, Bastos EM. Training on synthetic ethylene-vinyl acetate bench model
allows novice medical students to acquire suture skills. Acta Cir Bras
37. Grober ED, Hamstra SJ, Wanzel KR, Reznick RK, Matsumoto ED, Sidhu RS, et al. The educational impact of bench model
fidelity on the acquisition of technical skill
: the use of clinically relevant outcome measures. Ann Surg
38. Sidhu RS, Park J, Brydges R, MacRae HM, Dubrowski A. Laboratory-based vascular anastomosis training: a randomized controlled trial evaluating the effects of bench model
fidelity and level of training on skill acquisition. J Vasc Surg
39. Martin JA, Regehr G, Reznick R, MacRae H, Murnaghan J, Hutchison C, et al. Objective structured assessment of technical skill
(OSATS) for surgical residents. Br J Surg
40. Robinson WP, Baril DT, Taha O, Schanzer A, Larkin AC, Bismuth J, et al. Simulation
-based training to teach open abdominal aortic aneurysm repair to surgical residents requires dedicated faculty instruction. J Vasc Surg
41. Black SA, Harrison RH, Horrocks EJ, Pandey VA, Wolfe JH. Competence assessment of senior vascular trainees using a carotid endarterectomy bench model
. Br J Surg
42. Lauscher JC, Ritz JP, Stroux A, Buhr HJ, Gröne J. A new surgical trainer (BOPT) improves skill transfer for anastomotic techniques in gastrointestinal surgery into the operating room: a prospective randomized trial. World J Surg
43. Abdulal S, Onyekwelu O. An alternative model for teaching tendon repair and surgical skills in plastic surgery. JPRAS
44. Abdulmajed MI, Thomas M, Shergill IS. A new training model for adult circumcision. J Surg Educ
45. Abe M, Tabuchi K, Goto M, Uchino A. Model-based surgical planning and simulation
of cranial base surgery. Neurol Med Chir (Tokyo)
1998;38(11):746–750; discussion 750–1.
46. Adams F, Qiu T, Mark A, Fritz B, Kramer L, Schlager D, et al. Soft 3D-printed phantom of the human kidney with collecting system. Ann Biomed Eng
47. Sanders AJ, Warntjes P, Geelkerken RH, Mastboom WJ, Klaase JM, Rödel SG, Luursema JM, Kommers PA, Verwey WB, van Houten FJ, Kunst EE. Open surgery
in VR: inguinal hernia repair according to Lichtenstein. Stud Health Technol Inform
48. O'Toole RV, Playter RR, Krummel TM, Blank WC, Cornelius NH, Roberts WR, et al. Measuring and developing suturing technique with a virtual reality surgical simulator. J Am Coll Surg
49. Gladstone HB, Raugi GJ, Berg D, Berkley J, Weghorst S, Ganter M. Virtual reality for dermatologic surgery: virtually a reality in the 21st century. J Am Acad Dermatol
2000;42(1 Pt 1):106–112.
50. Agha RA, Fowler AJ. The role and validity of surgical simulation
. Int Surg
51. Carter FJ, Schijven MP, Aggarwal R, Grantcharov T, Francis NK, Hanna GB, et al. Consensus guidelines for validation of virtual reality surgical simulators. Simul Healthc
52. Schaefer JJ 3rd, Vanderbilt AA, Cason CL, Bauman EB, Glavin RJ, Lee FW, et al. Literature review: instructional design and pedagogy science in healthcare simulation
. Simul Healthc