International Journal on Science and Technology

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Leveraging Artificial Intelligence, Data Analysis, and Computer Science in Primary Care: Enhancing Electronic Health Records for Improved Patient Outcomes

Author(s) Dimitra Tzamaria, Evangelia Petaniti, Chrysoula I. Liakou, Markos Plytas
Country United States
Abstract The integration of artificial intelligence (AI) with primary care elements, including data analytics and computer science, facilitates transformative electronic health record (EHR) management, ultimately enhancing patient outcomes. Modern healthcare systems increasingly rely on electronic records for sustainable data storage, efficient retrieval, and the secure distribution of health information. However, the full potential of EHRs remains unrealized due to three primary challenges: fragmented information systems, incomplete clinical documentation, and inefficient healthcare workflows. The implementation of AI-driven solutions and advanced data analytics can mitigate these issues by enhancing data integration and providing healthcare professionals with actionable insights, thereby supporting more informed clinical decision-making.

AI algorithms are capable of processing vast healthcare datasets to identify patterns that can predict patient outcomes, assisting healthcare providers in making precise, data-driven clinical decisions. Predictive analytics tools facilitate the early identification of patients at risk of developing chronic conditions, enabling timely intervention and significantly altering disease trajectories. Additionally, natural language processing (NLP) technologies convert unstructured healthcare data—such as physician notes and patient assessments—into structured, analyzable formats, improving the overall utility of healthcare information systems. These advancements streamline data management while allowing healthcare professionals to allocate more time to direct patient care rather than administrative tasks.

The interoperability of EHR systems improves when healthcare providers apply computer science principles to develop integrated infrastructures that enable seamless data exchange across disparate platforms. The implementation of unified patient information management strategies fosters continuity of care while reducing redundancies and minimizing system errors. Emerging technological advancements present numerous benefits for healthcare operations, facilitating large-scale data analysis for scientific research and evidence-based policy development. The strategic integration of AI, data analytics, and computer science into primary care EHR systems will drive superior patient outcomes, optimize clinical workflows, and enhance adaptability to evolving healthcare demands.
Keywords Artificial Intelligence, Data Analysis, Computer Science, Primary Care, Electronic Health Records, Patient Outcomes, Predictive Analytics, Natural Language Processing, Interoperability, Healthcare Systems, Digital Solutions, Health Data Management, Clinical Decision-Making, Chronic Conditions, Early Interventions, Unstructured Data, Structured Formats, Workflow Efficiency, Data Integration, Continuity of Care, Healthcare Providers, Patient Information, Administrative Tasks, Public Health Initiatives, Research, Policy-Making, Health System, Data Exchange, Stakeholders, Health Technology.
Field Medical / Pharmacy
Published In Volume 16, Issue 1, January-March 2025
Published On 2025-03-18
Cite This Leveraging Artificial Intelligence, Data Analysis, and Computer Science in Primary Care: Enhancing Electronic Health Records for Improved Patient Outcomes - Dimitra Tzamaria, Evangelia Petaniti, Chrysoula I. Liakou, Markos Plytas - IJSAT Volume 16, Issue 1, January-March 2025. DOI 10.71097/IJSAT.v16.i1.2572
DOI https://doi.org/10.71097/IJSAT.v16.i1.2572
Short DOI https://doi.org/g88r9r
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