Using conjoint analysis to elicit preferences for health care.
Ontology highlight
ABSTRACT:
SUBMITTER: Ryan M
PROVIDER: S-EPMC1118112 | biostudies-literature | 2000 Jun
REPOSITORIES: biostudies-literature
Publications
Using conjoint analysis to elicit preferences for health care.
BMJ (Clinical research ed.) 20000601 7248
Similar Datasets
Project description:We used conjoint analysis-a method that assesses complex decision making-to quantify patients' choices when selecting an osteoporosis therapy. While 60% of people prioritized medication efficacy when deciding among treatments, the remaining 40% highly valued factors other than efficacy, suggesting the need for personalized shared decision-making tools.IntroductionIn this study, we aimed to examine patient decision-making surrounding osteoporosis medications using conjoint analysis.MethodsWe enrolled osteoporosis patients at an academic medical center to complete an online conjoint exercise which calculated each patient's relative importance score of 6 osteoporosis medication attributes (higher = greater relative importance in decision-making). We used latent class analysis to identify distinct segments of patients with similar choice patterns and then used logistic regression to determine if demographics and osteoporosis disease features were associated with latent class assignment.ResultsOverall, 304 participants completed the survey. The rank order of medication attributes by importance score was the following: efficacy at preventing hip fractures (accounted for 31.0% of decision making), mode of administration (17.5%); risk of serious side effects (16.6%); dose frequency (13.9%); efficacy at preventing spine fractures (12.5%); risk of non-serious side effects (8.4%). We found that 60.9% of the cohort prioritized medication efficacy as their top factor when selecting among the therapies. Being a college graduate, having stronger beliefs on the necessity of using medications for osteoporosis, and never having used osteoporosis medicines were the only factors associated with prioritizing medication efficacy for fracture prevention over the other factors in the decision-making process.ConclusionsWhile about 60% of patients prioritized efficacy when selecting an osteoporosis therapy, the remaining 40% valued other factors more highly. Furthermore, individual patient characteristics and clinical factors did not reliably predict patient decision making, suggesting that development and implementation of shared decision-making tools is warranted.
| S-EPMC10787002 | biostudies-literature
Project description:BackgroundWhile patients' preferences in primary care have been examined in numerous conjoint analyses, there has been little systematic effort to synthesise the findings. This review aimed to identify, to organise and to assess the strength of evidence for the attributes and factors associated with preference heterogeneity in conjoint analyses for primary care outpatient visits.MethodsWe searched five bibliographic databases (PubMed, Embase, PsycINFO, Econlit and Scopus) from inception until 15 December 2021, complemented by hand-searching. We included conjoint analyses for primary care outpatient visits. Two reviewers independently screened papers for inclusion and assessed the quality of all included studies using the checklist by ISPOR Task Force for Conjoint Analysis. We categorized the attributes of primary care based on Primary Care Monitoring System framework and factors based on Andersen's Behavioural Model of Health Services Use. We then assessed the strength of evidence and direction of preference for the attributes of primary care, and factors affecting preference heterogeneity based on study quality and consistency in findings.ResultsOf 35 included studies, most (82.4%) were performed in high-income countries. Each study examined 3-8 attributes, mainly identified through literature reviews (n = 25). Only six examined visits for chronic conditions, with the rest on acute or non-specific / other conditions. Process attributes were more commonly examined than structure or outcome attributes. The three most commonly examined attributes were waiting time for appointment, out-of-pocket costs and ability to choose the providers they see. We identified 24/58 attributes with strong or moderate evidence of association with primary care uptake (e.g., various waiting times, out-of-pocket costs) and 4/43 factors with strong evidence of affecting preference heterogeneity (e.g., age, gender).ConclusionsWe found 35 conjoint analyses examining 58 attributes of primary care and 43 factors that potentially affect the preference of these attributes. The attributes and factors, stratified into evidence levels based on study quality and consistency, can guide the design of research or policies to improve patients' uptake of primary care. We recommend future conjoint analyses to specify the types of visits and to define their attributes clearly, to facilitate consistent understanding among respondents and the design of interventions targeting them. Word Count: 346/350 words.Trial registrationOn Open Science Framework: https://osf.io/m7ts9.
| S-EPMC9463739 | biostudies-literature
Project description:BackgroundTofacitinib, an oral Janus kinase inhibitor approved for the treatment of rheumatoid arthritis (RA), provides patients with an alternative to subcutaneously or intravenously administered biologic disease-modifying antirheumatic drugs (DMARDs). Little is known about patient preference for novel RA treatments.ObjectiveTo investigate patient preferences for attributes associated with RA treatments.MethodsA choice-based conjoint survey was mailed to 1400 randomly selected commercially insured patients (aged 21-80 years) diagnosed with RA, who were continuously enrolled from May 1, 2012, through April 30, 2013, and had ≥2 medical claims for International Classification of Diseases, Ninth Revision, Clinical Modification diagnosis code 714.0 and no previous biologic DMARD use. Treatment attributes included route of administration; monthly out-of-pocket cost; frequency of administration; ability to reduce daily joint pain and swelling; likelihood of serious adverse events; improvement in the ability to perform daily tasks; and medication burden. Mean attribute importance scores were calculated after adjusting for patient demographics (eg, age, sex, years since diagnosis) using a hierarchical Bayes model. Patient preferences for each treatment attribute were ranked by the importance score. Part-worth utilities (ie, preference scores) were used to perform a conjoint market simulation.ResultsA total of 380 patients (response rate, 27.1%) returned the survey. Their mean age (± standard deviation) was 54.9 (± 9.3) years. Nonrespondents were 2 years younger (mean, 52.9 years; P = .002) but did not differ significantly from respondents in known clinical characteristics. After adjustment for demographic characteristics, mean patients' ranking of treatment attribute importance, in decreasing order, was route of administration, 34.1 (± 15.5); frequency of administration, 16.4 (± 6.8); serious adverse events, 12.0 (± 9.3); cost, 10.1 (± 6.2); medication burden, 9.8 (± 8.2); joint pain reduction, 8.9 (± 3.8); and daily tasks improvement, 8.8 (± 4.7). For the route of administration attribute, the part-worth utility was highest for the oral route. Conjoint simulation results showed that 56.4% of respondents would prefer an oral route of administration.ConclusionBased on this survey completed by 380 patients with RA, commercially insured patients with RA consider the route of administration to be the most important attribute of their RA treatment. In this study, the majority (56.4%) of patients preferred the oral route of administration over other routes. Understanding patient preferences may help to inform provider and payer decisions in treatment selection that may enhance patient adherence to therapy.
| S-EPMC4856233 | biostudies-literature
Project description:The increase in virtual conferences during the COVID-19 pandemic provided unexpected advantages such as increased accessibility, while also creating concern about the effectiveness of online networking and career development. Given that a variety of conference attributes are impacted by changes in conference format, we sought to investigate how plastic surgeons prioritize key aspects of conference conduct.MethodsWe sent a survey based on conjoint analysis, a statistical method for evaluating consumer preferences, to active members of the American Society of Plastic Surgeons. Respondents were asked to choose between pairs of conference options, each with unique attributes. Their answers were used to calculate feature importance values and utility coefficients for the conference attributes. Subgroup analyses were conducted based on demographic factors.ResultsA total of 263 respondents completed the survey. Respondents were mostly White (181 individuals [68.8%]) and men (186 [70.7%]). Nearly half (122 [46.4%]) had been practicing 20 or more years. Conference attributes with the highest feature importance values (SDs) were cost of attendance (30.4% [14.2%]) and conference format (28.8% [14.2%]). Equity initiatives (14.5% [10.1%]), reimbursement for cost (11.1% [5.7%]), and opportunities for networking (9.5% [6.0%]) had intermediate feature importance values. Environmental impact had the lowest feature importance (5.7% [3.8%]).ConclusionsSurgeons' conference preferences depend highly on format and the presence of equity initiatives, both of which can be incorporated or modified in future conferences to ensure inclusive and successful events. Meanwhile, environmental impact is less important to surgeons, suggesting a pressing need to bring sustainability issues to their attention.
| S-EPMC9668553 | biostudies-literature
Project description: Not available
| S-EPMC10681187 | biostudies-literature
Project description:ObjectiveDespite their promise for increasing treatment precision, Personalized Trials (i.e., N-of-1 trials) have not been widely adopted. We aimed to ascertain patient preferences for Personalized Trials.Study design and settingWe recruited 501 adults with ≥2 common chronic conditions from Harris Poll Online. We used Sawtooth Software to generate 45 plausible Personalized Trial designs comprising combinations of eight key attributes (treatment selection, treatment type, clinician involvement, blinding, time commitment, self-monitoring frequency, duration, and cost) at different levels. Conditional logistic regression was used to assess relative importance of different attributes using a random utility maximization model.ResultsOverall, participants preferred Personalized Trials with no costs vs. $100 cost (utility difference 1.52 [standard error 0.07], P < 0.001) and with less vs. more time commitment/day (0.16 [0.07], P < 0.015) but did not hold preferences for the other six attributes. In subgroup analyses, participants ≥65 years, white, and with income ≤$50,000 were more averse to costs than their counterparts (P all <0.05).ConclusionTo optimize dissemination, Personalized Trial designers should seek to minimize out-of-pocket costs and time burden of self-monitoring. They should also consider adaptive designs that can accommodate subgroup differences in design preferences.
| S-EPMC6119511 | biostudies-literature
Project description:ObjectiveInnovative approaches are needed for assessing treatment preferences of individuals with schizophrenia. Conjoint analysis methods may help to identify preferences, but the usability and validity of these methods for individuals with schizophrenia remain unclear. This study examined computerized conjoint analysis for persons with schizophrenia and whether preferences for weight management programs predict service use.MethodsA computerized, patient-facing conjoint analysis system was developed through iterative consultation with 35 individuals with schizophrenia enrolled at a community mental health clinic. An additional 35 overweight participants with schizophrenia then used the system to choose among psychosocial weight management programs varying in four attributes: location (community or clinic), delivery mode (Internet or in person), leader (clinician or layperson), and training mode (individual or group). A multilevel logit model with partial preference data determined contributions of each attribute to groupwide preferences. Associations were studied between preferences and use of a psychosocial weight management group.ResultsConjoint analysis system usability was rated highly. Groupwide preferences were significantly influenced by location (p<0.001; clinic was preferred), leader (p=0.02; clinician was preferred), and training mode (p<0.001; group was preferred) but not delivery mode (p=0.68). Preferences did not correlate with age, gender, body mass index, illness severity, or subsequent program use. Participants described barriers to program attendance, including transportation, scheduling, privacy, psychiatric illness, and lack of motivation.ConclusionsComputerized conjoint analysis can produce valid assessments of treatment preferences of persons with schizophrenia and inform treatment development and implementation. Although preferences may affect treatment use, they are one of multiple factors.
| S-EPMC7920898 | biostudies-literature
Project description:IntroductionBest-worst scaling (BWS) is becoming increasingly popular to elicit preferences in health care. However, little is known about current practice and trends in the use of BWS in health care. This study aimed to identify, review and critically appraise BWS in health care, and to identify trends over time in key aspects of BWS.MethodsA systematic review was conducted, using Medline (via Pubmed) and EMBASE to identify all English-language BWS studies published up until April 2016. Using a predefined extraction form, two reviewers independently selected articles and critically appraised the study quality, using the Purpose, Respondents, Explanation, Findings, Significance (PREFS) checklist. Trends over time periods (≤2010, 2011, 2012, 2013, 2014 and 2015) were assessed further.ResultsA total of 62 BWS studies were identified, of which 26 were BWS object case studies, 29 were BWS profile case studies and seven were BWS multi-profile case studies. About two thirds of the studies were performed in the last 2 years. Decreasing sample sizes and decreasing numbers of factors in BWS object case studies, as well as use of less complicated analytical methods, were observed in recent studies. The quality of the BWS studies was generally acceptable according to the PREFS checklist, except that most studies did not indicate whether the responders were similar to the non-responders.ConclusionUse of BWS object case and BWS profile case has drastically increased in health care, especially in the last 2 years. In contrast with previous discrete-choice experiment reviews, there is increasing use of less sophisticated analytical methods.
| S-EPMC5110583 | biostudies-literature
Project description:ObjectiveTo investigate individual preferences for physical activity (PA) attributes in adults with chronic knee pain, to identify clusters of individuals with similar preferences, and to identify whether individuals in these clusters differ by their demographic and health characteristics.DesignAn adaptive conjoint analysis (ACA) was conducted using the Potentially All Pairwise RanKings of all possible Alternatives (PAPRIKA) method to determine preference weights representing the relative importance of six PA attributes. Cluster analysis was performed to identify clusters of participants with similar weights. Chi-square and ANOVA were used to assess differences in individual characteristics by cluster. Multinomial logistic regression was used to assess associations between individual characteristics and cluster assignment.ResultsThe study sample included 146 participants; mean age 65, 72% female, 47% white, non-Hispanic. The six attributes (mean weights in parentheses) are: health benefit (0.26), enjoyment (0.24), convenience (0.16), financial cost (0.13), effort (0.11) and time cost (0.10). Three clusters were identified: Cluster 1 (n = 33): for whom enjoyment (0.35) is twice as important as health benefit; Cluster 2 (n = 63): for whom health benefit (0.38) is most important; and Cluster 3 (n = 50): for whom cost (0.18), effort (0.18), health benefit (0.17) and enjoyment (0.18) are equally important. Cluster 1 was healthiest, Cluster 2 most self-efficacious, and Cluster 3 was in poorest health.ConclusionsPatients with chronic knee pain have preferences for PA that can be distinguished effectively using ACA methods. Adults with chronic knee pain, clustered by PA preferences, share distinguishing characteristics. Understanding preferences may help clinicians and researchers to better tailor PA interventions.
| S-EPMC6348123 | biostudies-literature
Project description:IntroductionTo identify patient preference drivers related to the management of wet age-related macular degeneration (wet AMD).MethodsIn this cross-sectional study, a self-explicated 'conjoint analysis' survey was administered online to eligible patients with wet AMD (receiving anti-vascular endothelial growth factor [VEGF] treatment for at least 12 months) from the USA, Canada, UK, France, Spain, Germany, Italy, Japan, Taiwan, and Australia. The survey consisted of six domains with 21 attributes, which were selected on the basis of a literature review, social media listening, and tele-interviews/discussions with patients, clinical experts, and patient groups. Utility and relative importance scores were generated for each attribute and utility difference significance testing was performed using 'unequal variances t tests'. The Patient Activation Measure (PAM-13) questionnaire was administered to assess patients' knowledge, skill, and confidence in self-management.ResultsA total of 466 patients (mean age, 68 years; women, 54%; binocular wet AMD, 28%) with an average anti-VEGF treatment duration of 3.9 years completed the survey. The most important preference domains were 'treatment effects on vision' (non-significant) and 'vision-related symptom burdens' (p < 0.001), followed by 'treatment risk' (p < 0.05), 'impact on daily activities' (p < 0.05), 'burden of clinic/hospital visits' (p < 0.001), and 'impact on psychological well-being'. The five most important attributes in order of importance were clarity of vision, treatment effect on symptoms, quality of vision, time to treatment effect, and time to re-administration. The two most important attributes globally were also in the top three attributes across countries. The majority of participants in the study were level 3 or level 4 of the PAM-13 questionnaire.ConclusionsThis study identified the most important disease and treatment attributes to patients using patient-centred methods. The data showed the degree of harmonization of preferences across geographies and that participants actively adopt behaviours required for improved treatment outcomes. The identified preference drivers may inform future clinical development.
| S-EPMC9464751 | biostudies-literature