Electronic Health Records

Healthcare is changing fast and it’s not just about new hospitals or more doctors. It’s about how smart technology like AI is helping us focus more on people, not paperwork. InterSystems just launched IntelliCare, a next-generation AI-powered Electronic Health Record (EHR) system that’s set to transform the way healthcare works. Unveiled at HIMSS25 and already rolling out in tech-forward countries like Thailand, IntelliCare was built to make healthcare faster, smarter, and more human. It simplifies everything from scheduling and billing to medical records, letting doctors spend less time typing and more time talking to patients.

So what does this mean for the future of EHRs and for the Philippines? IntelliCare shows what’s possible when AI meets real healthcare needs. It solves common problems we face today like too much data entry, poor system integration, and wasted time. With features like natural language commands, instant patient summaries, and automated billing codes, it proves that EHRs don’t have to slow us down—they can help us move forward. As the Philippines pushes toward digital health transformation, tools like IntelliCare could be the missing link between better patient care and a smoother, smarter health system.

Who Can Use These Topics

This research is ideal for students and professionals pursuing the following courses or strands:

College Programs:

• BS in Health Information Management (HIM)

• BS in Nursing

• BS in Health Informatics

• BS in Health Administration

• BS in Public Health

• BS in Information Technology

• BS Computer Science

Senior High School Strands:

• Science, Technology, Engineering, Mathematics (STEM)

• Humanities and Social Sciences (HUMSS)

• Information and Communications Technology (TVL-ICT)

• General Academic Strand (GAS)

Why This Topic Needs Research

Despite its global momentum, the implementation of EHRs still faces several critical research gaps, particularly in low- and middle-income countries like the Philippines:

• Lack of strategies for legacy system integration: Although the study examined EHR systems across Tanzanian primary healthcare, it revealed a gap in understanding how to integrate older systems like MTUHA while improving data analysis capabilities. Future research should assess strategies for combining digital and paper-based records while building staff capacity in data interpretation (Mwogosi & Mambile, 2024).

• Unclear regulatory guidance for AI-enhanced EHR systems; While some privacy-preserving strategies exist, there remains little guidance on securing large language model (LLM)-based EHR tools when dealing with unstructured clinical data. Future research should develop scalable, context-aware solutions that balance patient privacy and analytic performance (Jonnagaddala & Wong, 2025).

• Limited evidence of long-term EHR impacts on care quality: Although EHR benefits are well-documented, few studies have evaluated their long-term effect on care quality, provider satisfaction, or interoperability with tools like telemedicine and AI. Future studies should focus on outcome-based analysis of digital systems (Adeniyi et al., 2024).

• Gaps in cross-border interoperability frameworks: While global standards exist, practical application in resource-limited environments is rarely studied. Future research should assess blockchain-based security, legal frameworks, and pilot models for international data exchange (Igwama et al., 2024).

• Challenges in AI summarization of clinical records: Although generative AI shows potential in EHR summarization, hallucinations and inconsistencies remain. Future work should explore prompt engineering techniques and test models across diverse health scenarios (Alkhalaf et al., 2024).

• Missing links between system use and measurable outcomes in PH settings: Although EHR user acceptance in the Philippines is high, studies have yet to link usage with outcomes like reduced patient wait times or improved care continuity. More research is needed on quality-of-care indicators in low-resource settings (De Mesa et al., 2024).

• Behavioral and motivational barriers to long-term adoption: Usage spikes during health crises (e.g., COVID-19) don't guarantee sustained engagement. Future studies should explore behavioral drivers, gamification, and user feedback loops to support consistent EHR use (Acacio-Claro et al., 2024).

• Lack of longitudinal studies on physician usage patterns: Many studies focus on technical readiness, but few track actual EHR usage over time or differentiate between public and private hospitals. Researchers were encouraged to explore user behavior through mixed methods and assess the role of digital literacy (Derecho et al., 2024).

Feasibility & Challenges by Target Group

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References

Acacio-Claro, P. J., Estuar, M. R. J. E., Villamor, D. A. R., Bautista, M. C. G., Pulmano, C. E., & Sugon Jr, Q. M. (2024). Understanding adoption of Electronic Medical Records (EMRs) during a health emergency: an analysis of EMR usage logs from rural health facilities in the Philippines. Acta Medica Philippina, 58(22), 7.

Adeniyi, A. O., Arowoogun, J. O., Chidi, R., Okolo, C. A., & Babawarun, O. (2024). The impact of electronic health records on patient care and outcomes: A comprehensive review. World Journal of Advanced Research and Reviews, 21(2), 1446-1455.

Alkhalaf, M., Yu, P., Yin, M., & Deng, C. (2024). Applying generative AI with retrieval augmented generation to summarize and extract key clinical information from electronic health records. Journal of biomedical informatics, 156, 104662.

De Mesa, R. Y. H., Galingana, C. L. T., Tan-Lim, C. S. C., Javelosa, M. A. U., Panganiban, J. M. S., Fabian, N. M. C., ... & Dans, A. L. (2024). Facing the digital frontier: exploring user acceptance of electronic health records in an urban, rural and remote setting in the Philippines. BMJ Open Quality, 13(2), e002621.

Derecho, K. C., Cafino, R., Aquino-Cafino, S. L., Isla Jr, A., Esencia, J. A., Lactuan, N. J., ... & Velasco, L. C. P. (2024). Technology adoption of electronic medical records in developing economies: A systematic review on physicians’ perspective. Digital Health, 10, 20552076231224605.

Igwama, G. T., Olaboye, J. A., Maha, C. C., Ajegbile, M. D., & Abdul, S. (2024). Integrating electronic health records systems across borders: Technical challenges and policy solutions. International Medical Science Research Journal, 4(7), 788-796.

Jonnagaddala, J., & Wong, Z. S. Y. (2025). Privacy preserving strategies for electronic health records in the era of large language models. npj Digital Medicine, 8(1), 34.

Mwogosi, A., & Mambile, C. (2025). Insights into the current state of electronic health records adoption and utilisation in Tanzanian public primary healthcare facilities: a survey study. Records Management Journal, 35(1), 75-93.

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