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Area of Science:

  • Public Health Informatics
  • Health Disparities Research
  • Data-Driven Interventions

Background:

  • Precision prevention emerges as a critical public health trend.
  • It leverages informatics for targeted interventions and improved health outcomes.
  • The COVID-19 pandemic underscored the need to address health disparities.

Purpose of the Study:

  • To summarize recent advancements in precision prevention.
  • To highlight the role of informatics in enabling targeted public health strategies.
  • To explore the relationship between precision prevention and precision medicine.

Main Methods:

  • A narrative review approach was employed due to limited literature on "Precision Prevention."
  • Related search terms and complementary expertise were combined.
  • Sub-topics were refined based on prior knowledge and targeted searches.

Main Results:

  • An overview of precision prevention, its origins, and relation to precision medicine.
  • Discussion of data types, collection methods, and modalities for precision prevention.
  • Highlights the HL7 Gravity Project for standardizing social determinants of health data.
  • Demonstrates data application across clinical care, human services outreach, and health policy.

Conclusions:

  • Precision prevention is vital for targeting interventions to specific populations at optimal times.
  • Novel data collection, use, and dissemination are essential for optimizing interventions.
  • The international informatics community's expertise is crucial for advancing precision prevention.