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Updated: Jul 17, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
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Applying a multiple screening program aided by a guideline-driven computerized decision support system - a pilot

Jou-Wei Lin1, Pei-Lun Chu, Jyh-Ming Liou

  • 1National Taiwan University Hospital Yun-Lin Branch, Dou-Liou City, Taiwan.

Journal of the Formosan Medical Association = Taiwan Yi Zhi
|February 7, 2007
PubMed
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This study developed a computer-aided system to improve preventive care uptake in outpatient settings. The program successfully facilitated screenings and provided cost-effectiveness data for public health policy.

Area of Science:

  • Health Informatics
  • Preventive Medicine
  • Public Health Policy

Background:

  • Preventive services are crucial for reducing morbidity and mortality but often underutilized.
  • Outpatient settings present opportunities to integrate preventive care interventions.
  • Computerized decision support systems can enhance the delivery of preventive recommendations.

Purpose of the Study:

  • To develop and implement a workflow for a computerized decision support system in an outpatient setting.
  • To evaluate the impact of this system on facilitating preventive care.
  • To assess the cost-effectiveness of the implemented preventive screening program.

Main Methods:

  • A questionnaire-based system triggered production rules for screening eligibility (coronary risk, diabetes, hypertension, cancers, etc.).

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  • Patients received tailored health information and were scheduled for clinic visits and screenings.
  • Physicians received clinical reminders, and program effectiveness was measured by life-years saved and cost-effectiveness.

    • Main Results:

    • Over a 2-month period, 482 individuals were identified for preventive interventions.
    • The program facilitated consultations and screenings.
    • Estimated cost-effectiveness ranged from $30,000 to $40,000 per life-year saved.

    Conclusions:

    • A computer-aided screening program based on US Preventive Services Task Force recommendations was successfully implemented.
    • The system provided valuable insights into local epidemiology.
    • Findings have implications for future health policy development in Taiwan.