About

Victoria L. Tiase, PhD, RN, FAMIA, FNAP, FAAN, FAHSE, is an Assistant Professor of Biomedical Informatics and Nursing at the University of Utah. She is a nurse informaticist with expertise in leading electronic health record (EHR) implementations, integrating patient-generated health data, and mentoring digital health startups. Dr. Tiase serves on the boards of the Alliance for Nursing Informatics, AMIA, and Friends of NINR, and was appointed as the informatics expert to the National Academy of Medicine’s Future of Nursing 2030 Committee, focusing on the nurse’s role in using technology to address disparities, promote health equity, and foster healthier communities. Her current research involves the computational modeling of nursing workload to improve systems, structures, and policies supporting a diverse nursing workforce. She completed her BSN at the University of Virginia, MSN at Columbia University, and PhD from the University of Utah.

Research topics

• Data Mining
• Computer Science
• Data science
• Medicine
• Database

Selected publications

• Bridging the Gap Between Potential and Practice

  CIN Computers Informatics Nursing · 2026-02-09

  articleOpen accessSenior author

  BACKGROUND: Generative artificial intelligence (GAI) has emerged as a transformative tool in health care, particularly with the integration of large language models (LLMs) into electronic health record (EHR) systems. These tools have the potential to enhance clinical decision-making, increase efficiencies, and decrease time in the EHR. However, despite expanding availability, adoption in nursing practice remains limited. This integrative review aimed to synthesize the literature and explore barriers related to the integration of GAI tools into nursing practice. METHODS: We conducted an integrative search of peer-reviewed literature published between November 2022 and July 2025 to examine the current evidence while assessing for methodological quality. The retrieved articles were screened for title, abstract, and full text eligibility. We synthesized themes related to GAI adoption by nurses, focusing on ethical, educational, and workflow-related factors that influence use. RESULTS: A total of 10 studies met criteria including 7 qualitative descriptive design, 2 case reports, and 1 experimental clinical trial. Four key barriers emerged: educational gaps, ethical concerns, data transparency issues, and workflow misalignment contributing to nurses' hesitancy to engage with GAI tools. Recommendations include involvement of nurses in the design, implementation, and evaluation of GAI tools and mandatory AI curricula in nursing education. CONCLUSIONS: Overcoming barriers requires nurse involvement in GAI design efforts, targeted education, and governance models that foster trust and usability. Nurse-centered integration of GAI tools has the potential to advance workforce efficiencies while preserving patient safety.

  PublisherDOI

• Gaps and solutions for equitable telemedicine delivery to patients with limited English proficiency: a qualitative study

  Research Square · 2026-04-24

  preprintOpen accessSenior author
  PublisherOA PDFDOI

• Barriers and Enablers for Sustaining Nurse-Led Use of Clinical Decision Support Tools for Antibiotic Stewardship: Qualitative Study

  JMIR Nursing · 2026-01-21

  articleOpen access1st authorCorresponding

  Background: Clinical decision support (CDS) tools embedded in electronic health records in the form of integrated clinical prediction rules provide a potentially effective intervention to reduce inappropriate antibiotic prescribing for acute respiratory infections. However, their effectiveness has been limited by workflow barriers and low adoption by health care providers. Nurses are well positioned to implement evidence-based protocols using CDS tools. In a multicenter randomized controlled trial, a nurse-led implementation strategy for acute respiratory infection integrated clinical prediction rules was evaluated for use in primary care and urgent care settings. Objective: This study aimed to examine nurse and nurse leader perspectives on the sustainability of an electronic health record-integrated CDS tool for antibiotic stewardship and explored factors influencing its potential long-term integration into ambulatory nursing practice beyond the clinical trial. Methods: We interviewed 22 nurses and nurse leaders from 37 clinics across 3 academic medical centers that participated in the clinical trial. Two semistructured interview guides, one for nurses and one for nursing leadership, were developed to understand the barriers and facilitators to implementing a decision aid tool for nurses and to elicit challenges specific to nursing interactions with the CDS tool. Interviews were recorded and transcribed. Using thematic content analysis and iterative coding, our team collaboratively identified emerging themes related to sustainability and refined the results with consensus. Results: Five themes emerged: (1) importance of staffing stability and capacity, (2) impact of dedicated clinic resource availability, (3) variable nurse readiness with CDS-guided clinical care, (4) influence of openness to change and a nurse-supportive clinic culture, and (5) ongoing need for training and support. Specific recommendations for future actions were also noted. Conclusions: Our findings revealed specific barriers and facilitators to the sustainability of a CDS tool from the nursing perspective that can inform further implementation of nurse-led delegation protocols in the ambulatory setting. Future solutions should consider mapping physical workflows, scheduling specific to nurse visits, continuing education, and treating cough and sore throat as 2 distinct processes.

  PublisherDOI

• MyLungHealth, a Patient-Facing Education Tool for Lung Cancer Screening: Qualitative User-Centered Design Study

  JMIR Formative Research · 2026-05-21

  articleOpen access

  Background: Lung cancer remains the leading cause of cancer-related mortality worldwide, with low-dose computed tomography screening demonstrating an approximately 20% reduction in mortality among high-risk individuals. Despite this benefit, screening prevalence remains suboptimal, with often less than 20% of eligible individuals reported to be up to date on screening. Shared decision-making is essential for effective lung cancer screening (LCS) implementation, with decision aids shown to enhance patient knowledge and engagement. Objective: The aim of this study is to identify patient preferences, concerns, and design considerations through qualitative evaluation of MyLungHealth, a personalized patient-facing educational tool for LCS integrated with electronic health records, and to describe how these findings informed iterative design modifications. Methods: We employed qualitative research methods through focus groups (n=34) and individual interviews (n=18) with individuals who met screening eligibility criteria. Participants were recruited from the University of Utah Health and New York University Langone Health between May and December 2023. Feedback was analyzed using Braun and Clarke's thematic analysis principles. Results: Six themes were organized into three overarching domains. Domain A included interpretation and impact of personalized risk information: theme 1, difficulties interpreting risk information, and theme 2, varied impacts of risk information on motivation. Domain B included autonomy, privacy, and user interface preferences: theme 3, desire for autonomy and control over personal health data, and theme 4, preference for straightforward language and multiple information formats. Domain C included integration with clinical workflows and patient portal systems: theme 5, expectations for integration with health care provider workflows, and theme 6, mixed experiences with personal health record systems. These insights led to key design modifications, including simplified risk presentation, multimodal content delivery options (video and text), and implementation of electronic health record alerts for clinicians. Conclusions: The user-centered design process for MyLungHealth revealed important considerations for developing effective patient education tools for LCS. The findings highlighted the need for simplified risk presentation, personalized information delivery, and integration with clinical workflows. These findings underscore the importance of balancing comprehensive risk communication with user accessibility.

  PublisherOA PDFDOI

• Translating Nursing Data into Computational Metrics: An Evaluation Guideline for Inpatient Intravenous and Subcutaneous Insulin Management

  PubMed Central · 2025-05-22

  articleOpen access
  Publisher

• Nursing Performance Using Clinical Prediction Rules for Acute Respiratory Infection Management: A Case-Based Simulation

  Applied Clinical Informatics · 2025-09-15

  articleOpen access1st authorCorresponding

  Overuse and misuse of antibiotics is an urgent health care problem and one of the key factors in antibiotic resistance. Validated clinical prediction rules have shown effectiveness in guiding providers to an appropriate diagnosis and identifying when antibiotics are the recommended choice for treatment.We aimed to study the relative ability of registered nurses using clinical prediction rules to guide the management of acute respiratory infections in a simulated environment compared with practicing primary care physicians.We evaluated a case-based simulation of the diagnosis and treatment for acute respiratory infections using clinical prediction rules. As a secondary outcome, we examined nursing self-efficacy by administering a survey before and after case evaluations. Participants included 40 registered nurses from three academic medical centers and five primary care physicians as comparators. Participants evaluated six simulated case studies, three for patients presenting with cough symptoms, and three for sore throat.Compared with physicians, nurses determined risk and treatment for simulated sore throat cases using clinical prediction rules with 100% accuracy in low-risk sore throat cases versus 80% for physicians. We found great variability in the accuracy of the risk level and appropriate treatment for cough cases. Nurses reported slight increases in self-efficacy from baseline to postcase evaluation suggesting further information is needed to understand correlation.Clinical prediction rules used by nurses in sore throat management workflows can guide accurate diagnosis and treatment in simulated cases, while cough management requires further exploration. Our results support the future implementation of automated prediction rules in a clinical decision support tool and a thorough examination of their effect on clinical practice and patient outcomes.

  PublisherOA PDFDOI

• Enhancement of Patient-Centered Lung Cancer Screening

  JAMA Oncology · 2025-12-26 · 3 citations

  articleOpen access

  Importance: Lung cancer screening (LCS) with low-dose computed tomography (CT) remains underused in the US, partly because of incomplete smoking history documentation in electronic health records (EHRs) and limited time for shared decision-making in primary care. Objective: To determine whether a patient-facing, EHR-integrated tool combined with clinician-facing clinical decision support improves the identification of LCS-eligible patients and the ordering of low-dose CT compared with clinician-facing tools alone. Design, Setting, and Participants: This pragmatic, unstratified, randomized clinical trial with parallel groups was conducted from March 29, 2024, to March 28, 2025, at primary care clinics at University of Utah Health and New York University Langone Health. Adults aged 50 to 79 years with a documented smoking history, an active patient portal account, and a primary care visit in the preceding year were included. Study 1 enrolled patients with uncertain LCS eligibility (10 to 19 pack-years, unknown pack-years, or missing quit date); study 2 enrolled patients with documented eligibility (20 or more pack-years and currently smoking or quit smoking within 15 years). Interventions: The control included the clinician-facing Decision Precision+ tool (preventive care reminders and a shared decision-making tool). The intervention included the Decision Precision+ tool as well as the MyLungHealth tool, which collected detailed smoking history (study 1) and delivered personalized education and risk/benefit information (studies 1 and 2) via the patient portal in English and Spanish. Main Outcomes and Measures: The primary outcomes were the proportion of patients newly identified as eligible for LCS (study 1) and low-dose CT ordering rates (study 2) over 12 months. Analyses used intention-to-treat mixed-effects logistic regression. Results: There were 31 303 randomized participants, including 26 729 in study 1 (13 144 [49.2%] female; 13 580 [50.8%] male; median [IQR] age, 62 [55-69] years) and 4574 in study 2 (2230 [48.8%] female; 2344 [51.2%] male; median [IQR] age, 63 [56-69] years). In study 1, the MyLungHealth tool increased new LCS eligibility identification (635 of 13 412 [4.7%] vs 308 of 13 317 [2.3%]; adjusted odds ratio, 2.19; 95% CI, 1.99-2.42; P < .001). In study 2, low-dose CT ordering was higher in the intervention arm (474 of 2312 [20.5%] vs 434 of 2262 [19.2%]; adjusted odds ratio, 1.16; 95% CI, 1.04-1.30; P = .008). Conclusions and Relevance: In this randomized clinical trial, integrating a patient-centered tool into primary care EHR workflows increased the identification of patients eligible for LCS and the ordering of low-dose CTs. The relative increases in these primary outcomes were substantial, but absolute increases were more modest. Research on more intensive interventions is warranted to evaluate their ability to further improve LCS screening. Trial Registration: ClinicalTrials.gov Identifier: NCT06338592.

  PublisherOA PDFDOI

• Advancing Digital Access to Physical Therapy via Virtual and Extended Reality Technology: Prototype Development and Usability Evaluation

  JMIR Formative Research · 2025-12-05

  articleOpen access1st authorCorresponding

  Background: The United States faces significant challenges in physical therapy (PT) access due to high demand, a shortage of professionals, and patient-related obstacles, which can adversely affect recovery and function. Limited access to PT may lead to increased dependence on medications for pain management, highlighting the need for nonpharmacologic options to reduce opioid overprescribing. Low back pain, a leading cause of disability and high medical costs, is a common reason for requiring PT following surgery. Studies have shown that virtual reality (VR)-guided movements can improve motor function and reduce pain intensity. Objective: The objective of this study was to design, develop, and evaluate a VR-based prototype for individualized postoperative PT for patients recovering from back surgery to investigate its potential to improve convenience, access, and health outcomes in future research. Methods: Study methods involved participatory design and development of VR software for PT back exercises using the design box method, an inductive, problem-oriented collaborative design approach. A usability evaluation of the resulting prototype was conducted with patients recovering from back surgery using a think-aloud protocol and usability survey. Results: Six participants evaluated the VR prototype and reported usability challenges that included mismatched VR boundaries, limited familiarity with VR, and difficulties with the headset and hand controls. The System Usability Scale resulted in a total usability score of 58.3 out of 100, indicating a below-average score (68 being average). Conclusions: In the design and evaluation of a VR-based PT prototype, we found that while participants were enthusiastic, they faced usability challenges due to insufficient instructions and difficulties operating the VR device, highlighting the need for effective onboarding and extensive prototype testing to improve accessibility and engagement in health care. Future evaluations will investigate disparities among different groups to ensure accessibility and effectiveness for all users.

  PublisherDOI

• Innovative Technologies

  CIN Computers Informatics Nursing · 2025-08-07

  articleOpen access1st authorCorresponding
  PublisherDOI

• Barriers and Enablers for Sustaining Nurse-Led Use of Clinical Decision Support Tools for Antibiotic Stewardship: A qualitative analysis (Preprint)

  2025-09-04

  articleOpen access1st authorCorresponding

  <sec> <title>BACKGROUND</title> Clinical decision support (CDS) tools embedded in electronic health records (EHRs) in the form of integrated clinical prediction rules (iCPRs) provide a potentially effective intervention to reduce inappropriate antibiotic prescribing for acute respiratory infections (ARIs). Still, their effectiveness has been limited by workflow barriers and low adoption by healthcare providers. Nurses are well-positioned to implement evidence-based protocols using clinical decision support (CDS) tools. In a multicenter randomized controlled trial, a nurse-led implementation strategy for ARI iCPRs was evaluated for use in primary care and urgent care settings. </sec> <sec> <title>OBJECTIVE</title> After trial completion, this study examined nurse and nurse leader perspectives on the sustainability of an EHR-integrated clinical decision support tool for antibiotic stewardship and explored factors influencing its potential long-term integration into ambulatory nursing practice. </sec> <sec> <title>METHODS</title> We interviewed 22 nurses and nurse leaders from clinics that participated in the clinical trial. Two semi-structured interview guides, one for nurses and one for nursing leadership, were developed to understand the barriers and facilitators to implementing a decision-aid tool for nurses and to elicit challenges specific to nursing interactions with the CDS tool. Interviews were recorded and transcribed. Using thematic content analysis and iterative coding, our team collaboratively identified emerging themes related to sustainability and refined the results with consensus. </sec> <sec> <title>RESULTS</title> Five themes emerged: 1) importance of staffing stability and capacity; 2) impact of dedicated clinic resource availability; 3) variable nurse readiness with CDS-guided clinical care; 4) influence of openness to change and a nurse-supportive clinic culture; and 5) ongoing need for training and support. Specific recommendations for future actions were also noted. </sec> <sec> <title>CONCLUSIONS</title> Our findings revealed specific barriers and facilitators to the sustainability of a CDS tool from the nursing perspective that can inform further implementation of nurse-led delegation protocols in the ambulatory setting. Future solutions should consider mapping physical workflows, scheduling specific to nurse visits, continuing education, and treating cough and sore throat as two distinct processes. </sec>

  PublisherOA PDFDOI

Frequent coauthors

• David K. Vawdrey

  30 shared

• Gilad J. Kuperman

  Astellas Pharma (China)

  29 shared

• Jane M. Carrington

  Carrington College

  22 shared

• Kimberly Shea

  University of Arizona

  21 shared

• Nicolette Estrada

  University of California, San Diego

  21 shared

• Katherine Sward

  University of Utah

  21 shared

• Mollie Cummins

  18 shared

• Patricia S. Meisner

  Columbia University

  16 shared

Education

• PhD, College of Nursing

  University of Utah

  2020