Patient decision aids: A content analysis based on a decision tree structure

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Abstract

Introduction: This paper presents the preliminary results of a decision-tree analysis of Patient Decision Aids (PDA). PDAs are online or offline tools used to structure health information, elicit relevant values and emphasize the decision as a process, in ways that help patients make more informed health decisions individually or with relevant others. Method: Twenty PDAs are randomly selected from the International Patient Decision Aids Standards (IPDAS) (https://decisionaid.ohri.ca/AZlist.html) approved list. An evaluation tool is built bottom-up and top-down and results are described in terms of communicating uncertainty, completeness of the decision tree, ambiguous or misleading phrasing, overall strategies suggested within personal stories. Results: Twelve of the analyzed PDAs had branches of the decision tree which were not discussed in the tool and 6 had logically ambiguous phrasing. Many tools included dichotomous options, when the option range was wider. Several options were clustered within the "Do not take/Do not do" option and thus the PDA failed to provide all comparisons necessary to make a decision. Some tools employ expressions that do not differentiate between lack of information and known negative effects. Other tools provide unequal amounts or non-comparable bits of information about the options. Conclusion: These results indicate a very loose range of interpretations of what constitutes an option, a treatment, and a treatment option. It thus emphasizes a gap between theory and practice in the evaluation of PDAs. Future developments of PDA evaluation tools should keep track of missing decision tree branches, accurate communication of uncertainty, ambiguity, and lack of knowledge and consider using measures for evaluating the completeness of the option spectrum at an agreed period in time.

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APA

Gheondea-Eladi, A. (2019). Patient decision aids: A content analysis based on a decision tree structure. BMC Medical Informatics and Decision Making, 19(1). https://doi.org/10.1186/s12911-019-0840-x

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