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Updated: Apr 23, 2026

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General Practitioner and FRAX(®) (computer-based algorithm).

Raffaella Michieli1, Anna Maria Carraro2

  • 1National Secretary, Italian College of General Practitioner, Firenze, Italy.

Clinical Cases in Mineral and Bone Metabolism : the Official Journal of the Italian Society of Osteoporosis, Mineral Metabolism, and Skeletal Diseases
|October 7, 2014
PubMed
Summary

Osteoporotic fractures are a major cause of disability. This study aims to develop a new, cost-effective tool for General Practitioners to predict fracture risk in Italy, improving patient identification and care.

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Area of Science:

  • Gerontology
  • Public Health
  • Epidemiology

Background:

  • Osteoporotic fractures are a leading cause of disability and rising public health costs globally.
  • Current methods for identifying high-risk individuals, like Dual Energy X-ray Absorptiometry (DEXA), have limitations in cost and accessibility.
  • Existing risk prediction tools, such as WHO's FRAX®, face barriers in primary care settings, including limited database integration for General Practitioners.

Purpose of the Study:

  • To develop and validate a novel prognostic score for osteoporotic fractures specifically for use in Italian General Practice.
  • To establish a risk map for osteoporotic fractures within the Italian primary care context.
  • To provide a more accessible and potentially lower-cost alternative to current fracture risk assessment methods.

Main Methods:

Keywords:
FRAXHealth Search Database (HSD)fracturesosteoporosisprevention

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  • Utilizing the Health Search - CSD Longitudinal Patients Database (HSD) in Italy for data.
  • Developing and validating a computer-based prognostic score for osteoporotic fractures.
  • Focusing on data relevant to primary care settings and General Practitioners.

Main Results:

  • The study aims to create a dynamic and adaptable risk prediction tool.
  • The developed score will be validated for accuracy and sensitivity in identifying patients at high risk of fragility fractures.
  • A comprehensive risk map for osteoporotic fractures in Italy will be established.

Conclusions:

  • A validated prognostic score and risk map could significantly enhance the identification of individuals at high risk for osteoporotic fractures in Italian primary care.
  • This tool could support timely interventions, reduce disability, and potentially lower public health costs associated with fractures.
  • The research addresses the need for dynamic, accessible, and cost-effective fracture risk prediction models tailored for General Practitioners.