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A framework for tailoring clinical guidelines to comorbidity at the point of care

R Scott Braithwaite1, John Concato, Chung Chou Chang

  • 1Section of General Internal Medicine, Yale University School of Medicine, West Haven Veterans Affairs Connecticut Healthcare System, VACS 11 ACSL-G, 950 Campbell Ave, West Haven, CT 06516, USA. Ronald.braithwaite@va.gov

Insights

A new "payoff time" framework helps tailor clinical guidelines for patients with comorbidities. This method determines if screening benefits outweigh harms, potentially modifying guidelines for conditions like HIV and congestive heart failure.

Area of Science:

  • Clinical Medicine
  • Health Services Research
  • Biostatistics

Background:

  • Clinical guidelines often overlook patient comorbidities, necessitating modifications.
  • A quantitative approach is lacking to balance guideline benefits and risks in complex patient cases.

Purpose of the Study:

  • To introduce a novel framework using
  • payoff time
  • to objectively assess guideline applicability in patients with comorbidities.
  • To demonstrate the framework's utility by applying it to colorectal cancer screening guidelines for specific patient cohorts.

Main Methods:

  • Defined
  • payoff time
  • as the time until cumulative benefits exceed cumulative harms.
  • Compared guideline payoff times with comorbidity-adjusted life expectancy.
  • Applied the framework to colorectal cancer screening for men with human immunodeficiency virus (HIV) and women with congestive heart failure (CHF).

Main Results:

  • Colorectal cancer screening payoff times for 50-year-old men with HIV ranged from 1.9 to 5.0 years.
  • Payoff times for 60-year-old women with CHF ranged from 0.7 to 2.9 years.
  • Screening may benefit men with HIV, but could be harmful for some women with CHF depending on life expectancy.

Conclusions:

  • The
  • payoff time
  • calculation offers a feasible method for personalizing clinical guidelines.
  • This approach can help optimize guideline recommendations based on individual patient comorbidity profiles.
Abstract

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