Factors influencing general practitioners' decisions about cardiovascular disease risk reassessment: findings from

Shannon McKinn1,2, Carissa Bonner1,2, Jesse Jansen1,2

  • 1Screening and Test Evaluation Program (STEP), Sydney School of Public Health, The University of Sydney, Sydney, NSW, Australia.

BMC Family Practice
|August 7, 2016
PubMed

Insights

General practitioners (GPs) frequently reassess cardiovascular disease (CVD) risk, often sooner than guidelines suggest. This practice may lead to overtreatment and increased healthcare costs, highlighting a need for adherence to evidence-based intervals.

Area of Science:

  • Cardiology
  • General Practice
  • Health Services Research

Background:

  • Cardiovascular disease (CVD) risk reassessment intervals lack clear guidelines, leading to practice variations.
  • Overly frequent reassessments risk overtreatment and healthcare strain; infrequent ones risk neglecting high-risk patients.

Purpose of the Study:

  • To investigate factors influencing general practitioners' (GPs) decisions on cardiovascular disease (CVD) risk reassessment intervals.
  • To understand the rationale behind GP choices for primary CVD risk reassessment timing.

Main Methods:

  • Combined quantitative (questionnaire with hypothetical cases) and qualitative (semi-structured interviews) data from Australian GPs.
  • Experimental study involved 144 GPs varying patient risk factors; interview study included 25 GPs analyzed thematically.

Main Results:

  • GPs indicated reassessing most patients within 6 months, with 48% reassessed in under 3 months, regardless of absolute risk (AR).
  • Interviews revealed reassessment intervals were influenced by patient motivation, demand, risk factors, and GP attitudes, including psychosocial benefits and medication preparation.

Conclusions:

  • Significant variation exists in GP reassessment intervals, diverging from Australian guidelines.
  • Shorter reassessment intervals for low-moderate AR patients may lead to unnecessary costs and overtreatment, contradicting optimal monitoring research.
Abstract

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