Users' guides to the medical literature: XX. Integrating research evidence with the care of the individual patient. Evidence-Based Medicine Working Group
- 1Mount Sinai Hospital, Suite 431, 600 University Ave, Toronto, Ontario, Canada, M5G 1X5 sstraus@mtsinai.on.ca
- 0Mount Sinai Hospital, Suite 431, 600 University Ave, Toronto, Ontario, Canada, M5G 1X5 sstraus@mtsinai.on.ca
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View abstract on PubMed
Summary
This summary is machine-generated.Clinicians should integrate patient values into treatment decisions alongside risk-benefit analyses. This joint decision-making process enhances personalized medical care by considering individual patient preferences and outcomes.
Area Of Science
- Medical Decision Making
- Clinical Practice Guidelines
- Patient-Centered Care
Background
- Clinicians utilize research, risk estimates, and guidelines for patient care.
- Patient values are crucial for effective treatment decisions but often overlooked.
- Real-world patients differ quantitatively, not qualitatively, from study participants.
Purpose Of The Study
- To propose incorporating patient values into clinical decision-making.
- To emphasize the importance of joint clinical decision-making.
- To highlight the quantitative differences between study populations and individual patients.
Main Methods
- Utilizing patient baseline risk estimates and clinical prediction guidelines.
- Quantifying potential benefits and harms of therapeutic alternatives.
- Employing Number Needed to Treat (NNT) and Number Needed to Harm (NNH) for patient-specific estimates.
Main Results
- Joint decision-making involves disclosing risks/benefits, exploring patient values, and making the decision.
- Patient-specific risk estimates can be generated using NNT and NNH.
- Recognizing quantitative differences between average study patients and individual patients is key.
Conclusions
- Clinicians must incorporate patient values into decision-making for optimal care.
- Understanding patient-specific risks and benefits is essential.
- Personalized medicine requires a synthesis of clinical data and patient preferences.
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