Dataset Information

Appraising patient preference methods for decision-making in the medical product lifecycle: an empirical comparison.

ABSTRACT:

Background

Incorporating patient preference (PP) information into decision-making has become increasingly important to many stakeholders. However, there is little guidance on which patient preference assessment methods, including preference exploration (qualitative) and elicitation (quantitative) methods, are most suitable for decision-making at different stages in the medical product lifecycle (MPLC). This study aimed to use an empirical approach to assess which attributes of PP assessment methods are most important, and to identify which methods are most suitable, for decision-makers' needs during different stages in the MPLC.

Methods

A four-step cumulative approach was taken: 1) Identify important criteria to appraise methods through a Q-methodology exercise, 2) Determine numerical weights to ascertain the relative importance of each criterion through an analytical hierarchy process, 3) Assess the performance of 33 PP methods by applying these weights, consulting international health preference research experts and review of literature, and 4) Compare and rank the methods within taxonomy groups reflecting their similar techniques to identify the most promising methods.

Results

The Q-methodology exercise was completed by 54 stakeholders with PP study experience, and the analytical hierarchy process was completed by 85 stakeholders with PP study experience. Additionally, 17 health preference research experts were consulted to assess the performance of the PP methods. Thirteen promising preference exploration and elicitation methods were identified as likely to meet decision-makers' needs. Additionally, eight other methods that decision-makers might consider were identified, although they appeared appropriate only for some stages of the MPLC.

Conclusions

This transparent, weighted approach to the comparison of methods supports decision-makers and researchers in selecting PP methods most appropriate for a given application.

SUBMITTER: Whichello C

PROVIDER: S-EPMC7304129 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Publications

Appraising patient preference methods for decision-making in the medical product lifecycle: an empirical comparison.

Whichello Chiara C Levitan Bennett B Juhaeri Juhaeri J Patadia Vaishali V DiSantostefano Rachael R Pinto Cathy Anne CA de Bekker-Grob Esther W EW

BMC medical informatics and decision making 20200619 1

<h4>Background</h4>Incorporating patient preference (PP) information into decision-making has become increasingly important to many stakeholders. However, there is little guidance on which patient preference assessment methods, including preference exploration (qualitative) and elicitation (quantitative) methods, are most suitable for decision-making at different stages in the medical product lifecycle (MPLC). This study aimed to use an empirical approach to assess which attributes of PP assessm ...[more]

PMID: 32560655

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Project description:BackgroundShared decision-making is the gold standard for good clinical practice, and thus, psychometric instruments have been established to assess patients' generic preference for participation (e.g., the Autonomy Preference Index, API). However, patients' preferences may vary depending on the specific disease and with respect to the specific decision context. With a modified preference index (API-Uro), we assessed patients' specific participation preference in preference-sensitive decisions pertaining to urological cancer treatments and compared this with their generic participation preference.MethodsIn Study 1, we recruited (N = 469) urological outpatients (43.1% urooncological) at a large university hospital. Participation preference was assessed with generic measures (API and API case vignettes) and with the disease-specific API-Uro (urooncological case vignettes describing medical decisions of variable difficulty). A polychoric exploratory factor analysis was used to establish factorial validity and reduce items. In Study 2, we collected data from N = 204 bladder cancer patients in a multicenter study to validate the factorial structure with confirmatory factor analysis. Differences between the participation preference for different decision contexts were analyzed.ResultsStudy 1: Scores on the specific urooncological case vignettes (API-Uro) correlated with the generic measure (r = .44) but also provided incremental information. Among the disease-specific vignettes of the API-Uro, there were two factors with good internal consistency (α ≥ .8): treatment versus diagnostic decisions. Patients desired more participation for treatment decisions (77.8%) than for diagnostic decisions (22%), χ2(1) = 245.1, p ≤ .001. Study 2: Replicated the correlation of the API-Uro with the API (r = .39) and its factorial structure (SRMR = .08; CFI = .974). Bladder cancer patients also desired more participation for treatment decisions (57.4%) than for diagnostic decisions (13.3%), χ²(1) =84, p ≤ .001.ConclusionsThe desire to participate varies between treatment versus diagnostic decisions among urological patients. This underscores the importance of assessing participation preference for specific contexts. Overall, the new API-Uro has good psychometric properties and is well suited to assess patients' preferences. In routine care, measures of participation preference for specific decision contexts may provide incremental, allowing clinicians to better address their patients' individual needs.

Project description:BackgroundDual processing theory of human cognition postulates that reasoning and decision-making can be described as a function of both an intuitive, experiential, affective system (system I) and/or an analytical, deliberative (system II) processing system. To date no formal descriptive model of medical decision-making based on dual processing theory has been developed. Here we postulate such a model and apply it to a common clinical situation: whether treatment should be administered to the patient who may or may not have a disease.MethodsWe developed a mathematical model in which we linked a recently proposed descriptive psychological model of cognition with the threshold model of medical decision-making and show how this approach can be used to better understand decision-making at the bedside and explain the widespread variation in treatments observed in clinical practice.ResultsWe show that physician's beliefs about whether to treat at higher (lower) probability levels compared to the prescriptive therapeutic thresholds obtained via system II processing is moderated by system I and the ratio of benefit and harms as evaluated by both system I and II. Under some conditions, the system I decision maker's threshold may dramatically drop below the expected utility threshold derived by system II. This can explain the overtreatment often seen in the contemporary practice. The opposite can also occur as in the situations where empirical evidence is considered unreliable, or when cognitive processes of decision-makers are biased through recent experience: the threshold will increase relative to the normative threshold value derived via system II using expected utility threshold. This inclination for the higher diagnostic certainty may, in turn, explain undertreatment that is also documented in the current medical practice.ConclusionsWe have developed the first dual processing model of medical decision-making that has potential to enrich the current medical decision-making field, which is still to the large extent dominated by expected utility theory. The model also provides a platform for reconciling two groups of competing dual processing theories (parallel competitive with default-interventionalist theories).

Project description:Introduction: The Quality of Decision-Making Orientation Scheme (QoDoS) was developed to provide organisations involved in submission, approval and reimbursement of new medicines with a tool to improve the quality of their decision-making processes and is considered the most promising tool for such purpose. This study aimed to further establish the measurement properties of the QoDoS by evaluating its reliability (internal consistency and test-retest reliability) and relevance in the target population. Methods: The study participants consisted of 55 individuals recruited from pharmaceutical companies, regulatory and HTA agencies. It was designed as a longitudinal study with participants assessed on two different occasions, at baseline (test 1) and then 7 days later (test 2). Internal consistency reliability was assessed with Cronbach's alpha and the test-retest reliability was evaluated using the intraclass correlation coefficients (ICC) based on absolute agreement, 2 way mixed-effects model for the four QoDoS domains. The relevance of the QoDoS was evaluated by applying cognitive debriefing using five short feedback questions following test 1. Results: Test 1 was completed by 44 study participants (80% response rate) and test 2 was completed by 32 of the 44 individuals, resulting in a 73% response rate. Cronbach's alpha coefficient was greater than 0.7 across all the domains for test 1 and test 2, ranging from 0.71 to 0.79, indicating good consistency of responses. For the overall score across all 47 items, the Cronbach's alpha coefficient was 0.81 for test 1 and 0.86 for test 2, which is rated as very good. The four QoDoS domains showed moderate to strong reproducibility (ICC range: 0.63-0.86). The outcome of the cognitive debriefing from the 43 respondents (98% response rate) confirmed the relevance (95% agreement), language clarity (95%) and completeness of items (86%); the clarity of the scaling (91%) as well as spontaneity of responses (95%). Conclusion: These results provide strong support for the relevance and reliability of the QoDoS, which are key properties for future longitudinal and cross-sectional applications of the instrument when evaluating quality of decision making by those involved in the lifecycle of medicines.

Dataset Information

Appraising patient preference methods for decision-making in the medical product lifecycle: an empirical comparison.

Background

Methods

Results

Conclusions

Publications

Appraising patient preference methods for decision-making in the medical product lifecycle: an empirical comparison.

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