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Related Concept Videos

Preventive Healthcare Services01:30

Preventive Healthcare Services

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Preventive healthcare services keep people healthy via frequent check-ups, screening, and counseling. They primarily aid in disease prevention rather than treating an acute or chronic illness. Preventive treatment also keeps individuals productive and energetic, allowing them to work well into their retirement years. Examples of preventive care services include:
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Methods of Documentation VII: EMR01:30

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Electronic Medical Records (EMRs) primarily center around electronically documenting patients' health information within a single healthcare organization or practice. They contain essential clinical data related to a patient's medical history, diagnoses, medications, treatment plans, lab results, and other pertinent information relevant to the specific encounter or episode of care. EMRs are designed to streamline documentation and workflow processes within individual healthcare...
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Combination Therapies and Personalized Medicine02:50

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Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
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The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
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Health Information Technology (HIT)
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Purpose of Health Records II01:19

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Health records serve various essential purposes in the healthcare system. Here are some key purposes:
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Related Experiment Video

Updated: Sep 12, 2025

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
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A Computational Framework for Tailored Preventive Care Recommendations Using Electronic Health Records.

Xiao Luo1,2, Jess Zeleke1, Rachel Kate Puckett1

  • 1Department of Management Science and Information Systems, Oklahoma State University, Oklahoma, USA.

Studies in Health Technology and Informatics
|August 8, 2025
PubMed
Summary
This summary is machine-generated.

Preventive care is vital for public health and managing costs. This study introduces an AI framework using electronic health records and guidelines to create personalized preventive care recommendations, moving beyond generic advice.

Keywords:
EHRLarge Language ModelsPersonalized Care Plans

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Area of Science:

  • Health Informatics
  • Artificial Intelligence in Healthcare
  • Preventive Medicine

Background:

  • Healthcare systems are largely reactive, with 90% of expenditures linked to chronic and mental health conditions.
  • Current preventive care clinical decision support (CDS) in electronic health records (EHRs) uses a "one-size-fits-all" approach, neglecting patient-specific risk factors.
  • Social and environmental determinants of health significantly impact outcomes, yet are underutilized in preventive care strategies.

Purpose of the Study:

  • To develop a computational framework for personalized preventive care recommendations.
  • To integrate U.S. Preventive Services Task Force (USPSTF) guidelines with patient-specific EHR data.
  • To leverage artificial intelligence (AI) for analyzing complex health data and generating tailored advice.

Main Methods:

  • Developing a computational framework integrating preventive care guidelines and EHR data.
  • Extracting patient-specific risk factors (family history, social history, ethnicity, chronic conditions) from EHRs.
  • Utilizing AI to analyze USPSTF guidelines and patient data for personalized recommendations.

Main Results:

  • A novel framework for personalized preventive care recommendations has been developed.
  • The system integrates diverse patient data, including social determinants of health, for tailored advice.
  • Justifications for recommendations are provided, grounded in both EHR data and established guidelines.

Conclusions:

  • Personalized preventive care, informed by AI and comprehensive patient data, is crucial for improving public health.
  • This AI-driven approach enhances preventive strategies beyond traditional, generic methods.
  • The framework offers a pathway to more effective and individualized disease prevention in healthcare systems.