An essential part of translating a body of evidence into a clinical recommendation within the GRADE framework is the consideration of patients' values and preferences. Not only should the likely treatment preferences and values placed on outcomes among the patient population be considered; if there is likely a great amount of variability within these, this may also influence the ultimate strength of recommendation.
Guideline panels and public health decision-makers may use self-reported patient survey data to better understand the range of patient values and preferences when formulating recommendations or policies. However, like all sources of evidence, patient surveys may be at risk for specific sources of bias which can ultimately affect the results. What should decision-makers look out for when applying patient survey data to a recommendation for care? In a recently published paper, Santesso and colleagues propose a practical guide for finding, interpreting, and applying patient data to better inform healthcare decision-making.
|Click to enlarge.|
Because 97% of published surveys have been found to use the words "survey" or "questionnaire" in the title, the authors suggest using these terms in title, abstract, and topic fields when conducting a search for relevant data. When assessing the risk of bias of a given survey, decision-makers should ask whether the population was adequately representative of the patient population in question, taking care to consider the use of random sampling and the potential impact of nonresponse. A survey should also be assessed for whether it measures the intended constructs adequately. Survey authors should report the variability around reported measures whenever possible, and these data can be used to judge the overall variability in patient values and preferences. Finally, decision-makers should take care to discern how directly the survey data applies to the patient population in question; the table of survey respondent characteristics is a useful place from which to draw judgments of directness.
Using these helpful and practical points of guidance, guideline panel members and clinical decision-makers can better inform their retrieval, critical appraisal, and application of patient survey data to important healthcare questions, ultimately resulting in more informed guidelines and policies.
Santesso N, Akl E, Bhandari M, Busse JW, Cook DJ, Greenhalgh T, Muti P, Schünemann H, and Guyatt G. (2020). A practical guide for using a survey about attitudes and behaviors to inform health care decision making. J Clin Epidemiol 128:93-100.
Manuscript available from the publisher's website here.