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Shared decision making in hypertension: the impact of patient preferences on treatment choice
A A Montgomery1, J Harding, T Fahey
1Division of Primary Health Care, University of Bristol, Canynge Hall, Whiteladies Road, Bristol BS8 2PR, UK.
Insights
Patient preferences significantly influence hypertension treatment recommendations. Decision analysis incorporating patient values impacts medication decisions, highlighting the need for shared decision-making tools in hypertension management.
Area of Science:
- Cardiology
- Health Economics
- Decision Science
Background:
- Current hypertension guidelines focus on cardiovascular risk, not individual patient preferences.
- Patient values and preferences for health outcomes are crucial but often overlooked in hypertension treatment.
Purpose of the Study:
- To investigate how patient preferences affect hypertension treatment recommendations.
- To utilize individual decision analysis to explore the impact of patient values on medication decisions.
Main Methods:
- An observational study involving 52 hypertensive patients.
- Patient preferences were quantified using the standard gamble method.
- Decision analysis outcomes were compared with guideline-based recommendations (blood pressure, cardiovascular risk) and medication adherence.
Main Results:
- Individual patient preferences substantially altered treatment recommendations.
- Decision analysis recommended treatment for 56% of patients, differing significantly from guideline-based approaches (52% and 37%).
- No correlation was found between decision analysis outcomes and medication adherence.
Conclusions:
- Quantifying patient preferences and employing decision analysis can influence antihypertensive medication recommendations.
- This approach shows promise as a shared decision-making tool for hypertension management.
- Further research is warranted to evaluate this method's utility in clinical practice.
Background:
Recent guidelines for treatment of hypertension advocate a multifactorial approach based on absolute risk of a cardiovascular event. However, this does not take any account of individual patient values or preferences for health outcomes that result from having hypertension.
Objective:
Our aim was to investigate the impact of patient preferences on treatment recommendations for hypertension using individual decision analysis.
Methods:
We carried out an observational study based on interviews with 52 hypertensive patients. Patient preferences were measured using the standard gamble method. Associations between outcome of the individual decision analyses (recommendation to accept or decline antihypertensive medication) and treatment guidelines based on blood pressure and absolute cardiovascular risk were investigated. Adherence to medication during the 6 months following the interview was also assessed.
Results:
Individual patient preferences have a substantial impact on the proportion of patients for whom drug treatment would be recommended. In 52 patients interviewed, decision analysis indicated that 29 [56%, 95% confidence interval (CI) 41--70] should be treated, compared with 27 (52%, 38--66) using a cardiovascular risk of > or =10% over 5 years and 19 (37%, 24--51) using a systolic blood pressure of > or =160 mmHG: There was marked disagreement between the decision analysis and these recommendations (kappas 0.18 or less). There was no relationship between outcome of the decision analysis and adherence to medication [chi-square (1 d.f.) = 0.5, P = 0.5].
Conclusions:
Quantifying patients' preferences and using decision analysis as a shared decision-making aid appears to have an impact on whether patients would be recommended for antihypertensive medication. Further evaluation of this method as a shared decision-making tool is warranted.