# Validation of an Immersive Virtual Reality Based Experiential Learning Simulator to Improve Medication Administration Safety Skills of Registered Nurses

> **NIH NIH R03** · UT SOUTHWESTERN MEDICAL CENTER · 2020 · $59,783

## Abstract

PROJECT SUMMARY
In 2019, the normalization, anticipation, and preparation for seasonal flu routinely occurring from October to
December radically changed with the presence of the SARS-CoV-2 virus and the subsequent announcement by
the World Health Organization of the novel coronavirus disease 19 (COVID-19) pandemic in March of 2020.
Total cases of COVID-19 in the United States has grown to over 4 million. Research and data continue to emerge
as to how COVID-19 is severely impacting infection control safety and testing practices among frontline
healthcare professionals. These frontline healthcare professionals are practicing in acute and chronic healthcare
facilities, working within emergency response systems, and preparing pre-licensure students within academic
healthcare programs of study. In 2014, the Infectious Diseases Society, Society for Healthcare Epidemiology of
America, and The Joint Commission recognized the urgency to reduce healthcare-associated infections. The
original compendium of protocols remains as a 2020 Hospital National Patient Safety goal, and infection control
guidelines have been updated to reflect changes in precaution measures necessitated by COVID-19. Previous
educational training with lectures, cues, checklists; audits; observation with feedback; and implementation of
infection control programs have sought to improve protocol compliance and knowledge on proper fit and use of
personal protective equipment. However, these educational modalities and just-in-time training sessions have
not been sustainable in improving practice behaviors. Additionally, these modalities do not realistically portray
the use standard and transmission-based precautions urgently needed at this time, especially when this
education is central to providing direct patient care such as administering medication administrations, obtaining
sterile nasal specimens necessary to diagnose COVID-19, and completing bedside procedures. Currently, an
increased prevalence of frontline healthcare professionals diagnosed with COVID-19 is alarming. Emerging
literature describes how recycled or new forms, correct selection, donning-doffing, and acceptance of personal
protective equipment are focal points for research. Moreover, the fear of this disease and significantly increased
mental stress related to the potential for self-infection exists. An effective training program with cognitive and
deliberate practice components to reinforce best infection control and transmission-based behaviors is a
necessity identified by the Centers for Disease Control and Prevention. We propose to develop an immersive
virtual reality simulator to train healthcare professionals to protect themselves when providing care to patients
with COVID-19. This is significant because knowledge and skills on standard and transmission-based infection
control practices can directly impact the spread and acquisition of this highly infectious disease among all
healthcare professionals and can impact...

## Key facts

- **NIH application ID:** 10436663
- **Project number:** 7R03EB026171-03
- **Recipient organization:** UT SOUTHWESTERN MEDICAL CENTER
- **Principal Investigator:** Kelly Rossler
- **Activity code:** R03 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $59,783
- **Award type:** 7
- **Project period:** 2019-09-01 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10436663

## Citation

> US National Institutes of Health, RePORTER application 10436663, Validation of an Immersive Virtual Reality Based Experiential Learning Simulator to Improve Medication Administration Safety Skills of Registered Nurses (7R03EB026171-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10436663. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*