Browsing by Author "Johnson, F Reed"

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    Do You Want to Hear the Bad News? The Value of Diagnostic Tests for Alzheimer's Disease.
    (Value Health, 2016-01) Mühlbacher, Axel; Johnson, F Reed; Yang, Jui-Chen; Happich, Michael; Belger, Mark
    OBJECTIVE: The diagnosis of Alzheimer's disease (AD) remains difficult. Lack of diagnostic certainty or possible distress related to a positive result from diagnostic testing could limit the application of new testing technologies. The objective of this paper is to quantify respondents' preferences for obtaining AD diagnostic tests and to estimate the perceived value of AD test information. METHODS: Discrete-choice experiment and contingent-valuation questions were administered to respondents in Germany and the United Kingdom. Choice data were analyzed by using random-parameters logit. A probit model characterized respondents who were not willing to take a test. RESULTS: Most respondents indicated a positive value for AD diagnostic test information. Respondents who indicated an interest in testing preferred brain imaging without the use of radioactive markers. German respondents had relatively lower money-equivalent values for test features compared with respondents in the United Kingdom. CONCLUSIONS: Respondents preferred less invasive diagnostic procedures and tests with higher accuracy and expressed a willingness to pay up to €700 to receive a less invasive test with the highest accuracy.
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    Experimental measurement of preferences in health care using best-worst scaling (BWS): theoretical and statistical issues.
    (Health Econ Rev, 2016-12) Mühlbacher, Axel C; Zweifel, Peter; Kaczynski, Anika; Johnson, F Reed
    For optimal solutions in health care, decision makers inevitably must evaluate trade-offs, which call for multi-attribute valuation methods. Researchers have proposed using best-worst scaling (BWS) methods which seek to extract information from respondents by asking them to identify the best and worst items in each choice set. While a companion paper describes the different types of BWS, application and their advantages and downsides, this contribution expounds their relationships with microeconomic theory, which also have implications for statistical inference. This article devotes to the microeconomic foundations of preference measurement, also addressing issues such as scale invariance and scale heterogeneity. Furthermore the paper discusses the basics of preference measurement using rating, ranking and stated choice data in the light of the findings of the preceding section. Moreover the paper gives an introduction to the use of stated choice data and juxtaposes BWS with the microeconomic foundations.
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    Patient-Preference Diagnostics: Adapting Stated-Preference Methods to Inform Effective Shared Decision Making.
    (Medical decision making : an international journal of the Society for Medical Decision Making, 2022-07-29) Gonzalez Sepulveda, Juan Marcos; Johnson, F Reed; Reed, Shelby D; Muiruri, Charles; Hutyra, Carolyn A; Mather, Richard C

    Background

    While clinical practice guidelines underscore the need to incorporate patient preferences in clinical decision making, incorporating meaningful assessment of patient preferences in clinical encounters is challenging. Structured approaches that combine quantitative patient preferences and clinical evidence could facilitate effective patient-provider communication and more patient-centric health care decisions. Adaptive conjoint or stated-preference approaches can identify individual preference parameters, but they can require a relatively large number of choice questions or simplifying assumptions about the error with which preferences are elicited.

    Method

    We propose an approach to efficiently diagnose preferences of patients for outcomes of treatment alternatives by leveraging prior information on patient preferences to generate adaptive choice questions to identify a patient's proximity to known preference phenotypes. This information can be used for measuring sensitivity and specificity, much like any other diagnostic procedure. We simulated responses with varying levels of choice errors for hypothetical patients with specific preference profiles to measure sensitivity and specificity of a 2-question preference diagnostic.

    Results

    We identified 4 classes representing distinct preference profiles for patients who participated in a previous first-time anterior shoulder dislocation (FTASD) survey. Posterior probabilities of class membership at the end of a 2-question sequence ranged from 87% to 89%. We found that specificity and sensitivity of the 2-question sequences were robust to respondent errors. The questions appeared to have better specificity than sensitivity.

    Conclusions

    Our results suggest that this approach could help diagnose patient preferences for treatments for a condition such as FTASD with acceptable precision using as few as 2 choice questions. Such preference-diagnostic tools could be used to improve and document alignment of treatment choices and patient preferences.

    Highlights

    Approaches that combine patient preferences and clinical evidence can facilitate effective patient-provider communication and more patient-centric healthcare decisions. However, diagnosing individual-level preferences is challenging, and no formal diagnostic tools exist.We propose a structured approach to efficiently diagnose patient preferences based on prior information on the distribution of patient preferences in a population.We generated a 2-question test of preferences for the outcomes associated with the treatment of first-time anterior shoulder dislocation.The diagnosis of preferences can help physicians discuss relevant aspects of the treatment options and proactively address patient concerns during the clinical encounter.
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    Variation Among Patients With Crohn's Disease in Benefit vs Risk Preferences and Remission Time Equivalents.
    (Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association, 2019-05-14) Bewtra, Meenakshi; Reed, Shelby D; Johnson, F Reed; Scott, Frank I; Gilroy, Erin; Sandler, Robert S; Chen, Wenli; Lewis, James D
    BACKGROUND & AIMS:Patients with Crohn's disease (CD) must make decisions about their treatment. We aimed to quantify patients' preferences for different treatment outcomes and adverse events. We also evaluated the effects of latent class heterogeneity on these preferences. METHODS:An online stated-preference survey was completed by 812 individuals with CD in the Crohn's and Colitis Foundation Partners cohort (IBD Partners). Patients were given information on symptoms and severity of active disease; duration of therapy with corticosteroids; and risks of serious infection, cancer and surgery. Patients were asked to assume that their treatment was not working and to choose an alternative therapy. The primary outcome was remission-time equivalents (RTE) of a given duration of symptom severity or treatment-related risk. Latent class choice models identified groups of patients with dominant treatment-outcome preferences and associated patient characteristics with these groups. RESULTS:Latent class analysis demonstrated 3 distinct groups of survey responders whose choices were strongly influenced by avoidance of active symptoms (61%), avoidance of corticosteroid use (25%), or avoidance of risks of cancer, infection or surgery (14%) when choosing a therapy. Class membership was correlated with age, sex, mean short CD activity index score and corticosteroid avoidance. RTEs in each latent class differed significantly from the mean RTEs for the overall sample, although the symptom-avoidant class most closely approximated the overall sample. CONCLUSIONS:In an online survey of patients with CD, we found substantial heterogeneity in preference for medication efficacy and risk of harm. Physicians and regulators should therefore not assume that all patients have mean-value preferences-this could result in significant differences in health-technology assessment models.