Polina Durneva, Ph.D.

Assistant Professor of Information Systems and Business Analytics, College of Business Administration Loyola Marymount University

  • Los Angeles CA

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Biography

Polina Durneva, PhD, completed a PhD program in Information Systems and Business Analytics at Florida International University in 2023. Following her doctoral studies, she served as an Assistant Professor of Management Information Systems at the University of Memphis from 2023 to 2025. Her research centers on three primary areas: consumer health informatics, artificial intelligence in healthcare, and health IT management. She employs mixed methods to examine how digital tools can support self-management, improve patient care, and foster positive health outcomes. In addition, she has contributed to projects in emerging domains such as virtual reality, blockchain, and management education. Her work has been presented at leading national and international conferences and published in major journals in health informatics and information systems. Beyond her research, Polina Durneva is passionate about teaching and mentorship. She has taught both undergraduate and graduate courses, including Business Statistics, Business Machine Learning, and Web Analytics. Her teaching is enriched by industry experience at organizations such as OGx Consulting, Pfizer, and Teacher Created Materials, which allows her to bridge academic theory with practical application.

Education

Florida International University

Ph.D.

Business Administration

2023

Information Systems and Business Analytics Concentration

Cornell College

B.A.

Business Analytics

2018

Areas of Expertise

Information Systems
Business Analytics
Health Informatics
Health IT
Artificial Intelligence
Mixed Methods

Industry Expertise

Management Consulting
Research
Business Services
IT Services/Consulting

Sample Talks

Generative AI in Healthcare: Enhancing Healthcare Delivery, Management, and Rebuilding Public Trust

This talk took place at American Public Health Association (APHA) Annual Meeting and Expo in October 2024. It explored how generative AI has the potential to enhance healthcare delivery and healthcare management. It also highlighted current generative AI use cases in healthcare organizations and provided insights into how generative AI can improve healthcare accessibility and continuity of care through patient-centered self-management interventions. Additionally, the presentation discussed the ethical considerations, including data privacy, transparency, and bias mitigation, among others, that are essential to building trust and ensuring the responsible integration of generative AI in healthcare systems.

Courses

Business Statistics and Analysis I

Taught at Florida International University

Web Analytics

Taught at the University of Memphis

Business Machine Learning I

Taught at the University of Memphis

Articles

Digital Health Technology Infrastructure Challenges to Support Health Equity in the United States: Scoping Review

Journal of Medical Internet Research

Roy, S., Lartey, S.T., Durneva, P., Jha, N., Ofori, M.A., Zeba, Z., Dockery, S., Scarboro, N.S., Taylor, M. and Joshi, A.

2025-09-15

The objectives of this scoping review are aimed at synthesizing information on DHT inequities by exploring evidence that describes DHT infrastructure needs focused on promoting health equity in the United States and identifying key challenges both at the individual or patient level and at the health service provider’s level. We adapted Arksey and O’Malley’s scoping review guidelines in our review. PubMed, Web of Science, CINAHL, and PsycINFO were searched. We also conducted supplementary searches on Google Scholar. The inclusion criteria were peer-reviewed publications that broadly conceptualize or analyze DHT infrastructure from a health equity perspective and the challenges of DHT requirements between 2020 and 2024. We have screened the full text of articles using eligibility criteria such as studies that were included if they examined DHT infrastructure in the United States from a health equity perspective, discussed health disparities resulting from DHT interventions, or investigated the variables influencing health inequities connected to DHT. Two researchers (SR and ZZ) evaluated each citation individually at the title and abstract levels. The thematic approach and qualitative analysis determined this scoping review’s outcome. Of the 628 research papers from the search, 27 were included in the analysis based on the inclusion criteria. In this review, we discussed factors such as older adult population, education, race, ethnicity, and socioeconomic status leading to health inequities in DHT. Patients and service providers face challenges related to health inequities in the use of DHT. The most common challenges for service providers were infrastructure and technical issues such as inadequate integration with existing workflows, user-unfriendly health information exchange interfaces, and lack of skilled staff, while for individuals or patients, this included limited broadband web-based access, cultural or linguistic appropriateness, and access to digital tools.

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Evaluating the Needs and Characteristics of Individuals of Low Socioeconomic Status Using Digital Health Technology to Address Health-Related Social Needs

JMIR Human Factors

Haydon, K., LeRouge, C., Durneva, P., Diaz Campo, M., & Brown, D.

2025-09-12

Social determinants of health (SDOH) are the conditions in which people are born, grow, live, work, and age, encompassing social and economic factors that shape health outcomes. There is an increasing call to leverage digital health technology (DHT) to address SDOH and health-related social needs and establish connections to resources and services. This study aimed to (1) identify the DHT-related characteristics of DHT users with low socioeconomic status (SES), (2) determine the needs and preferences of DHT users with low SES, and (3) explore how current SDOH-DHT addresses these needs and preferences in addressing their health-related social needs. We used a multiphase, mixed method, user-centered design approach. In phase 1, we developed a user profile based on a literature review, aggregate data, interviews with 26 low-SES individuals, and focus groups with 28 professionals. In phase 2, we conducted a landscape analysis of 17 existing SDOH-DHTs. DHT users of low SES had diverse social and technology characteristics. Five key themes emerged regarding user needs and preferences: (1) user-centered design, including multilingual support, visual guidance, and customization; (2) efficient, solution-based assessment of social risks, assets, and needs; (3) e-caring support features; (4) user education and feedback mechanisms; and (5) trust, privacy, and security. The landscape analysis revealed that current SDOH-DHT features do not adequately meet these needs.

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Visual communication of public health data: a scoping review

Frontiers in Digital Health

Ofori, M.A., Lartey, S., Durneva, P., Jha, N., Mittal, N., Roy, S., Zeba, Z., Dockery, S., Saulsberry-Scarboro, N., Taylor, M. & Joshi, A.

2025-04-23

This scoping review examined visualization tools and techniques used for effective public health data communication. Despite substantial investment in health data, challenges in data sharing and visualization hinder accessibility and understanding, particularly during emergencies like the COVID-19 pandemic. The review included 28 peer-reviewed studies published between 2020 and 2024 and identified 25 visualization types, including charts, maps, and specialized plots, created using tools like R, Python, Power BI, Tableau, and ArcGIS. These visualizations supported data interpretation across domains such as HIV prevention, health education, and policy-making. The findings highlight that combining dashboards and static visuals enhances public health communication, enabling better decision-making and improved health outcomes.

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