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Personalized Disease Prevention (PDP): study protocol for a cluster-randomized clinical trial.

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A new tool helps prioritize preventive care for adults, aiming to improve health outcomes. This Personalized Disease Prevention (PDP) trial tests a decision aid for better quality-adjusted life expectancy.

Keywords:
Disease prevention, PrimaryMedicine, PreventivePatient-specific modelingPrecision medicinePrevention, PrimaryPreventive Health ServicesPreventive care

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Area of Science:

  • Preventive medicine
  • Health services research
  • Clinical decision support

Background:

  • The US Preventive Services Task Force recommends numerous preventive services for middle-aged adults.
  • Adhering to all recommended services can be challenging for patients and providers.
  • Prioritization of services is needed to optimize preventive care delivery.

Purpose of the Study:

  • To evaluate an evidence-based decision tool for prioritizing preventive services.
  • To determine if the tool improves quality-adjusted life expectancy for patients.
  • To assess patient and provider benefits from using the tool within electronic health records.

Main Methods:

  • A Phase III cluster-randomized clinical trial involving 60 primary care providers and 600 patients (aged 40-75).
  • Intervention group uses a decision tool individualized for patient risk factors; control group receives usual care.
  • Mixed-methods follow-up includes EHR data, patient/physician surveys, and qualitative interviews.

Main Results:

  • Hypothesis: Patients receiving the intervention will experience a greater increase in quality-adjusted life expectancy.
  • Data collection focuses on preventive care utilization, patient-reported outcomes, and provider experiences.
  • Analysis will compare outcomes between the intervention and usual care groups.

Conclusions:

  • The Personalized Disease Prevention (PDP) trial will assess a novel, holistic approach to preventive care.
  • The study aims to optimize the delivery of preventive services based on individual patient risk factors.
  • Findings could inform clinical practice and health policy regarding preventive service prioritization.