Adaptive Conjoint Analysis as individual preference assessment tool: feasibility through the internet and reliability of preferences

Patient Preferences for Postmastectomy Breast Reconstruction

Importance

Up to 40% of women experience dissatisfaction after breast reconstruction due to unexpected outcomes that are poorly aligned with personal preferences. Identifying what attributes patients value when considering surgery could improve shared decision-making. Adaptive choice-based conjoint (ACBC) analysis can elicit individual-level treatment preferences.

Objectives

To identify which attributes of breast reconstruction are most important to women considering surgery and to describe how these attributes differ by those who prefer flap vs implant reconstruction.

Design, Setting, and Participants

This web-based, cross-sectional study was conducted from March 1, 2022, to January 31, 2023, at Duke University and between June 1 and December 31, 2022, through the Love Research Army with ACBC analysis. Participants were 105 women at Duke University with a new diagnosis of or genetic predisposition to breast cancer who were considering mastectomy with reconstruction and 301 women with a history of breast cancer or a genetic predisposition as identified through the Love Research Army registry.

Main Outcomes and Measures

Relative importance scores, part-worth utility values, and maximum acceptable risks were estimated.

Results

Overall, 406 women (105 from Duke University [mean (SD) age, 46.3 (10.5) years] and 301 from the Love Research Army registry [mean (SD) age, 59.2 (11.9) years]) participated. The attribute considered most important was the risk of abdominal morbidity (mean [SD] relative importance [RI], 28% [11%]), followed by chance of major complications (RI, 25% [10%]), number of additional operations (RI, 23% [12%]), appearance of the breasts (RI, 13% [12%]), and recovery time (RI, 11% [7%]). Most participants (344 [85%]) preferred implant-based reconstruction; these participants cared most about abdominal morbidity (mean [SD] RI, 30% [11%]), followed by the risk of complications (mean [SD], RI, 26% [11%]) and additional operations (mean [SD] RI, 21% [12%]). In contrast, participants who preferred flap reconstruction cared most about additional operations (mean [SD] RI, 31% [15%]), appearance of the breasts (mean [SD] RI, 27% [16%]), and risk of complications (mean [SD] RI, 18% [6%]). Factors independently associated with choosing flap reconstruction included being married (odds ratio [OR], 2.30 [95% CI, 1.04-5.08]; P = .04) and higher educational level (college education; OR, 2.43 [95% CI, 1.01-5.86]; P = .048), while having an income level of greater than $75 000 was associated with a decreased likelihood of choosing the flap profile (OR, 0.45 [95% CI, 0.21-0.97]; P = .01). Respondents who preferred flap appearance were willing to accept a mean (SD) increase of 14.9% (2.2%) chance of abdominal morbidity (n = 113) or 6.4% (4.8%) chance of complications (n = 115).

Conclusions and Relevance

This study provides information on how women value different aspects of their care when making decisions for breast reconstruction. Future studies should assess how decision aids that elicit individual-level preferences can help tailor patient-physician discussions to focus preoperative counseling on factors that matter most to each patient and ultimately improve patient-centered care.

The Role of Web-Based Adaptive Choice-Based Conjoint Analysis Technology in Eliciting Patients' Preferences for Osteoarthritis Treatment

OBJECTIVE

To assess the feasibility of using adaptive choice-based conjoint (ACBC) analysis to elicit patients' preferences for pharmacological treatment of osteoarthritis (OA), patients' satisfaction with completing the ACBC questionnaire, and factors associated with questionnaire completion time.

METHODS

Adult patients aged 18 years and older with a medical diagnosis of OA, experiencing joint pain in the past 12 months, and living in the Northeast of England participated in the study. The participants completed a web-based ACBC questionnaire about their preferences regarding pharmaceutical treatment for OA using a touchscreen laptop independently, and accordingly, the questionnaire completion time was measured. Moreover, the participants completed a pen-and-paper feedback form about their experience in completing the ACBC questionnaire.

RESULTS

Twenty participants aged 40 years and older, 65% females, 75% had knee OA, and suffering from OA for more than 5 years participated in the study. About 60% of participants reported completing a computerized questionnaire in the past. About 85% of participants believed that the ACBC task helped them in making decisions regarding their OA medications, and 95% agreed or strongly agreed that they would be happy to complete a similar ACBC questionnaire in the future. The average questionnaire completion time was 16 min (range 10-24 min). The main factors associated with longer questionnaire completion time were older age, never using a computer in the past, and no previous experience in completing a questionnaire.

CONCLUSIONS

The ACBC analysis is a feasible and efficient method to elicit patients' preferences for pharmacological treatment of OA, which could be used in clinical settings to facilitate shared decision-making and patient-centered care. The ACBC questionnaire completion consumes a significantly longer time for elderly participants, who never used a computer, and never completed any questionnaire previously. Therefore, the contribution of patients and public involvement (PPI) group in the development of the ACBC questionnaire could facilitate participants' understanding and satisfaction with the task. Future research including patients with different chronic conditions may provide more useful information about the efficiency of ACBC analysis in eliciting patients' preferences for osteoarthritis treatment.

Patient Preferences for Treatment Outcomes in Oncology with a Focus on the Older Patient-A Systematic Review

Simple Summary

In oncology, treatment outcomes can be competing, which means that one treatment could benefit one outcome, like survival, and negatively influence another, like independence. The choice of treatment therefore depends on the patient’s preference for outcomes, which needs to be assessed explicitly. Especially in older patients, patient preferences are important. Our systematic review summarizes all studies that assessed patient preferences for various treatment outcome categories. A total of 28 studies with 4374 patients were included, of which only six studies included mostly older patients. Although quality of life was only included in half of the studies, overall quality of life (79%) was most frequently prioritized as highest or second highest, followed by overall survival (67%), progression- and disease-free survival (56%), absence of severe or persistent treatment side effects (54%), treatment response (50%), and absence of transient short-term side effects (16%). In shared decision-making, these results can be used by healthcare professionals to better tailor the information provision and treatment recommendations to the individual patient.

Abstract

For physicians, it is important to know which treatment outcomes are prioritized overall by older patients with cancer, since this will help them to tailor the amount of information and treatment recommendations. Older patients might prioritize other outcomes than younger patients. Our objective is to summarize which outcomes matter most to older patients with cancer. A systematic review was conducted, in which we searched Embase and Medline on 22 December 2020. Studies were eligible if they reported some form of prioritization of outcome categories relative to each other in patients with all types of cancer and if they included at least three outcome categories. Subsequently, for each study, the highest or second-highest outcome category was identified and presented in relation to the number of studies that included that outcome category. An adapted Newcastle–Ottawa Scale was used to assess the risk of bias. In total, 4374 patients were asked for their priorities in 28 studies that were included. Only six of these studies had a population with a median age above 70. Of all the studies, 79% identified quality of life as the highest or second-highest priority, followed by overall survival (67%), progression- and disease-free survival (56%), absence of severe or persistent treatment side effects (54%), and treatment response (50%). Absence of transient short-term side effects was prioritized in 16%. The studies were heterogeneous considering age, cancer type, and treatment settings. Overall, quality of life, overall survival, progression- and disease-free survival, and severe and persistent side effects of treatment are the outcomes that receive the highest priority on a group level when patients with cancer need to make trade-offs in oncologic treatment decisions.

Clarifying Values: An Updated and Expanded Systematic Review and Meta-Analysis

Background

Patient decision aids should help people make evidence-informed decisions aligned with their values. There is limited guidance about how to achieve such alignment.

Purpose

To describe the range of values clarification methods available to patient decision aid developers, synthesize evidence regarding their relative merits, and foster collection of evidence by offering researchers a proposed set of outcomes to report when evaluating the effects of values clarification methods.

Data Sources

MEDLINE, EMBASE, PubMed, Web of Science, the Cochrane Library, and CINAHL.

Study Selection

We included articles that described randomized trials of 1 or more explicit values clarification methods. From 30,648 records screened, we identified 33 articles describing trials of 43 values clarification methods.

Data Extraction

Two independent reviewers extracted details about each values clarification method and its evaluation.

Data Synthesis

Compared to control conditions or to implicit values clarification methods, explicit values clarification methods decreased the frequency of values-incongruent choices (risk difference, –0.04; 95% confidence interval [CI], –0.06 to –0.02; P < 0.001) and decisional conflict (standardized mean difference, –0.20; 95% CI, –0.29 to –0.11; P < 0.001). Multicriteria decision analysis led to more values-congruent decisions than other values clarification methods (χ² = 9.25, P = 0.01). There were no differences between different values clarification methods regarding decisional conflict (χ² = 6.08, P = 0.05).

Limitations

Some meta-analyses had high heterogeneity. We grouped values clarification methods into broad categories.

Conclusions

Current evidence suggests patient decision aids should include an explicit values clarification method. Developers may wish to specifically consider multicriteria decision analysis. Future evaluations of values clarification methods should report their effects on decisional conflict, decisions made, values congruence, and decisional regret.

Comparing internet and face-to-face surveys as methods for eliciting preferences for social care-related quality of life: evidence from England using the ASCOT service user measure

PURPOSE

Traditionally, researchers have relied on eliciting preferences through face-to-face interviews. Recently, there has been a shift towards using internet-based methods. Different methods of data collection may be a source of variation in the results. In this study, we compare the preferences for the Adult Social Care Outcomes Toolkit (ASCOT) service user measure elicited using best-worst scaling (BWS) via a face-to-face interview and an online survey.

METHODS

Data were collected from a representative sample of the general population in England. The respondents (face-to-face: n = 500; online: n = 1001) completed a survey, which included the BWS experiment involving the ASCOT measure. Each respondent received eight best-worst scenarios and made four choices (best, second best, worst, second worst) in each scenario. Multinomial logit regressions were undertaken to analyse the data taking into account differences in the characteristics of the two samples and the repeated nature of the data.

RESULTS

We initially found a number of small significant differences in preferences between the two methods across all ASCOT domains. These differences were substantially reduced-from 15 to 5 out of 30 coefficients being different at the 5% level-and remained small in value after controlling for differences in observable and unobservable characteristics of the two samples.

CONCLUSIONS

This comparison demonstrates that face-to-face and internet surveys may lead to fairly similar preferences for social care-related quality of life when differences in sample characteristics are controlled for. With or without a constant sampling frame, studies should carefully design the BWS exercise and provide similar levels of clarification to participants in each survey to minimise the amount of error variance in the choice process.

Patient explicit consideration of tradeoffs in decision making about rectal cancer treatment: benefits for decision process and quality of life

Introduction: Patient preferences are often not discussed in treatment decisions in oncology. We introduced an online values clarification method (VCM) to help newly diagnosed rectal cancer patients participate in shared decision making about short-course preoperative radiotherapy. Material and Methods: We offered a link to the VCM to a subset of consecutive patients before the pretreatment consultation with the radiation oncologist. Consultations were audiotaped and coded for expressions of patient preferences. Patients were asked to complete pre- and post-consultation questionnaires. Questionnaires assessed values clarity, decision regret and presence and impact of fecal incontinence and sexual problems. Results: Of 135 patients who had their consultation audiotaped and completed questionnaires, 35 received and accessed the VCM-link. Patients in the VCM-group slightly more often expressed preferences during consultations. Questionnaire data showed that patients in the VCM-group did not differ in how clear their values were, but experienced lower regret and less impact of treatment harms at 6 months follow-up; differences were non-significant but in the same direction at 12 months. Discussion: This is the first study to assess the effect of an adaptive conjoint analysis-based VCM on actual patient-clinician communication, and long-term decision regret and impact of treatment harms. Being explicitly invited to think about treatment benefits and harms seems to help patients to live with treatment consequences.

Individual Value Clarification Methods Based on Conjoint Analysis: A Systematic Review of Common Practice in Task Design, Statistical Analysis, and Presentation of Results

BACKGROUND

There is an increased practice of using value clarification exercises in decision aids that aim to improve shared decision making. Our objective was to systematically review to which extent conjoint analysis (CA) is used to elicit individual preferences for clinical decision support. We aimed to identify the common practices in the selection of attributes and levels, the design of choice tasks, and the instrument used to clarify values.

METHODS

We searched Scopus, PubMed, PsycINFO, and Web of Science to identify studies that developed a CA exercise to elicit individual patients' preferences related to medical decisions. We extracted data on the above-mentioned items.

RESULTS

Eight studies were identified. Studies included a fixed set of 4-8 attributes, which were predetermined by interviews, focus groups, or literature review. All studies used adaptive conjoint analysis (ACA) for their choice task design. Furthermore, all studies provided patients with their preference results in real time, although the type of outcome that was presented to patients differed (attribute importance or treatment scores). Among studies, patients were positive about the ACA exercise, whereas time and effort needed from clinicians to facilitate the ACA exercise were identified as the main barriers to implementation.

DISCUSSION

There is only limited published use of CA exercises in shared decision making. Most studies resembled each other in design choices made, but patients received different feedback among studies. Further research should focus on the feedback patients want to receive and how the CA results fit within the patient-physician dialogue.

Impact of Survey Administration Mode on the Results of a Health-Related Discrete Choice Experiment: Online and Paper Comparison

BACKGROUND

Electronic data collection is increasingly being used for discrete choice experiments (DCEs).

OBJECTIVES

To study whether paper or electronic administration results in measurement effects.

METHODS

Respondents were drawn from the same sample frame (an Internet panel) and completed a nearly identical DCE survey either online or on paper during the same period. A DCE on preferences for basic health insurance served as a case study. We used panel mixed logit models for the analysis.

RESULTS

In total, 898 respondents completed the survey: 533 respondents completed the survey online, whereas 365 respondents returned the paper survey. There were no significant differences with respect to sociodemographic characteristics between the respondents in both samples. The median response time was shorter for the online sample than for the paper sample, and a smaller proportion of respondents from the online sample were satisfied with the number of choice sets. Although some willingness- to-pay estimates were higher for the online sample, the elicited preferences for basic health insurance characteristics were similar between both modes of administration.

CONCLUSIONS

We find no indication that online surveys yield inferior results compared with paper-based surveys, whereas the price per respondent is lower for online surveys. Researchers might want to include fewer choice sets per respondent when collecting DCE data online. Because our findings are based on a nonrandomized DCE that covers one health domain only, research in other domains is needed to support our findings.

Understanding Preferences for Treatment After Hypothetical First-Time Anterior Shoulder Dislocation: Surveying an Online Panel Utilizing a Novel Shared Decision-Making Tool

Background:

Although surgical management of a first-time anterior shoulder dislocation (FTASD) can reduce the risk of recurrent dislocation, other treatment characteristics, costs, and outcomes are important to patients considering treatment options. While patient preferences, such as those elicited by conjoint analysis, have been shown to be important in medical decision-making, the magnitudes or effects of patient preferences in treating an FTASD are unknown.

Purpose:

To test a novel shared decision-making tool after sustained FTASD. Specifically measured were the following: (1) importance of aspects of operative versus nonoperative treatment, (2) respondents’ agreement with results generated by the tool, (3) willingness to share these results with physicians, and (4) association of results with choice of treatment after FTASD.

Study Design:

Cross-sectional study; Level of evidence, 3.

Methods:

A tool was designed and tested using members of Amazon Mechanical Turk, an online panel. The tool included an adaptive conjoint analysis exercise, a method to understand individuals’ perceived importance of the following attributes of treatment: (1) chance of recurrent dislocation, (2) cost, (3) short-term limits on shoulder motion, (4) limits on participation in high-risk activities, and (5) duration of physical therapy. Respondents then chose between operative and nonoperative treatment for hypothetical shoulder dislocation.

Results:

Overall, 374 of 501 (75%) respondents met the inclusion criteria, of which most were young, active males; one-third reported prior dislocation. From the conjoint analysis, the importance of recurrent dislocation and cost of treatment were the most important attributes. A substantial majority agreed with the tool’s ability to generate representative preferences and indicated that they would share these preferences with their physician. Importance of recurrence proved significantly predictive of respondents’ treatment choices, independent of sex or age; however, activity level was important to previous dislocators. A total of 125 (55%) males and 33 (23%) females chose surgery after FTASD, as did 37% of previous dislocators compared with 45% of nondislocators.

Conclusion:

When given thorough information about the risks and benefits, respondents had strong preferences for operative treatment after an FTASD. Respondents agreed with the survey results and wanted to share the information with providers. Recurrence was the most important attribute and played a role in decisions about treatment.

Older Cancer Patients' User Experiences With Web-Based Health Information Tools: A Think-Aloud Study

Background

Health information is increasingly presented on the Internet. Several Web design guidelines for older Web users have been proposed; however, these guidelines are often not applied in website development. Furthermore, although we know that older individuals use the Internet to search for health information, we lack knowledge on how they use and evaluate Web-based health information.

Objective

This study evaluates user experiences with existing Web-based health information tools among older (≥ 65 years) cancer patients and survivors and their partners. The aim was to gain insight into usability issues and the perceived usefulness of cancer-related Web-based health information tools.

Methods

We conducted video-recorded think-aloud observations for 7 Web-based health information tools, specifically 3 websites providing cancer-related information, 3 Web-based question prompt lists (QPLs), and 1 values clarification tool, with colorectal cancer patients or survivors (n=15) and their partners (n=8) (median age: 73; interquartile range 70-79). Participants were asked to think aloud while performing search, evaluation, and application tasks using the Web-based health information tools.

Results

Overall, participants perceived Web-based health information tools as highly useful and indicated a willingness to use such tools. However, they experienced problems in terms of usability and perceived usefulness due to difficulties in using navigational elements, shortcomings in the layout, a lack of instructions on how to use the tools, difficulties with comprehensibility, and a large amount of variety in terms of the preferred amount of information. Although participants frequently commented that it was easy for them to find requested information, we observed that the large majority of the participants were not able to find it.

Conclusions

Overall, older cancer patients appreciate and are able to use cancer information websites. However, this study shows the importance of maintaining awareness of age-related problems such as cognitive and functional decline and navigation difficulties with this target group in mind. The results of this study can be used to design usable and useful Web-based health information tools for older (cancer) patients.

Design Features of Explicit Values Clarification Methods

Background. Values clarification is a recommended element of patient decision aids. Many different values clarification methods exist, but there is little evidence synthesis available to guide design decisions. Purpose. To describe practices in the field of explicit values clarification methods according to a taxonomy of design features. Data Sources. MEDLINE, all EBM Reviews, CINAHL, EMBASE, Google Scholar, manual search of reference lists, and expert contacts. Study Selection. Articles were included if they described 1 or more explicit values clarification methods. Data Extraction. We extracted data about decisions addressed; use of theories, frameworks, and guidelines; and 12 design features. Data Synthesis. We identified 110 articles describing 98 explicit values clarification methods. Most of these addressed decisions in cancer or reproductive health, and half addressed a decision between just 2 options. Most used neither theory nor guidelines to structure their design. “Pros and cons” was the most common type of values clarification method. Most methods did not allow users to add their own concerns. Few methods explicitly presented tradeoffs inherent in the decision, supported an iterative process of values exploration, or showed how different options aligned with users’ values. Limitations. Study selection criteria and choice of elements for the taxonomy may have excluded values clarification methods or design features. Conclusions. Explicit values clarification methods have diverse designs but can be systematically cataloged within the structure of a taxonomy. Developers of values clarification methods should carefully consider each of the design features in this taxonomy and publish adequate descriptions of their designs. More research is needed to study the effects of different design features.

Discrete choice experiments in health economics: a review of the literature

BACKGROUND

Discrete choice experiments (DCEs) are increasingly used in health economics to address a wide range of health policy-related concerns.

OBJECTIVE

Broadly adopting the methodology of an earlier systematic review of health-related DCEs, which covered the period 2001-2008, we report whether earlier trends continued during 2009-2012.

METHODS

This paper systematically reviews health-related DCEs published between 2009 and 2012, using the same database as the earlier published review (PubMed) to obtain citations, and the same range of search terms.

RESULTS

A total of 179 health-related DCEs for 2009-2012 met the inclusion criteria for the review. We found a continuing trend towards conducting DCEs across a broader range of countries. However, the trend towards including fewer attributes was reversed, whilst the trend towards interview-based DCEs reversed because of increased computer administration. The trend towards using more flexible econometric models, including mixed logit and latent class, has also continued. Reporting of monetary values has fallen compared with earlier periods, but the proportion of studies estimating trade-offs between health outcomes and experience factors, or valuing outcomes in terms of utility scores, has increased, although use of odds ratios and probabilities has declined. The reassuring trend towards the use of more flexible and appropriate DCE designs and econometric methods has been reinforced by the increased use of qualitative methods to inform DCE processes and results. However, qualitative research methods are being used less often to inform attribute selection, which may make DCEs more susceptible to omitted variable bias if the decision framework is not known prior to the research project.

CONCLUSIONS

The use of DCEs in healthcare continues to grow dramatically, as does the scope of applications across an expanding range of countries. There is increasing evidence that more sophisticated approaches to DCE design and analytical techniques are improving the quality of final outputs. That said, recent evidence that the use of qualitative methods to inform attribute selection has declined is of concern.

A descriptive review on methods to prioritize outcomes in a health care context

BACKGROUND

Evidence synthesis has seen major methodological advances in reducing uncertainty and estimating the sizes of the effects. Much less is known about how to assess the relative value of different outcomes.

OBJECTIVE

To identify studies that assessed preferences for outcomes in health conditions.

METHODS

SEARCH STRATEGY

we searched MEDLINE, EMBASE, PsycINFO and the Cochrane Library in February 2014.

INCLUSION CRITERIA

eligible studies investigated preferences of patients, family members, the general population or healthcare professionals for health outcomes. The intention of this review was to include studies which focus on theoretical alternatives; studies which assessed preferences for distinct treatments were excluded.

DATA EXTRACTION

study characteristics as study objective, health condition, participants, elicitation method, and outcomes assessed in the study were extracted.

MAIN RESULTS

One hundred and twenty-four studies were identified and categorized into four groups: (1) multi criteria decision analysis (MCDA) (n = 71), (2) rating or ranking (n = 25), (3) utility eliciting (n = 5) and (4) studies comparing different methods (n = 23). The number of outcomes assessed by method group varied. The comparison of different methods or subgroups within one study often resulted in different hierarchies of outcomes.

CONCLUSIONS

A dominant method most suitable for application in evidence syntheses was not identified. As preferences of patients differ from those of other stakeholders (especially medical professionals), the choice of the group to be questioned is consequential. Further research needs to focus on validity and applicability of the identified methods.

Primary-care patients' trade-off preferences with regard to antidepressants

BACKGROUND

Antidepressants are frequently prescribed but results regarding their efficacy have been equivocal for different spectra of the severity continuum and their side-effects are often burdensome. Non-adherence is a likely consequence. The objective was therefore to examine patients' trade-offs between the efficacy, side-effects and other drawbacks of antidepressants and whether these trade-offs predicted non-adherence.

METHOD

Trade-offs from 225 antidepressant users, recruited through community pharmacies, were assessed with an Adaptive Conjoint Analysis (ACA) choice task that was customized to each individual patient. From the estimated utilities, relative importance scores of treatment properties were calculated. Non-adherence was measured through self-report and pharmacy refill data.

RESULTS

Relapse prevention and symptom relief were on average equally important. Side-effects were as important and the side-effect stomach and intestine complaints was on average even slightly more important than relapse prevention and symptom relief. Additional treatment with psychotherapy was preferred by 61% of the patients. A benefit/drawback ratio revealed that 18% of the patients did not consider the efficacy to outweigh the drawbacks. A higher benefit/drawback ratio was associated with a decreased odds of intentional non-adherence [odds ratio (OR) 0.2, 95% confidence interval (CI) 0.07-0.7, Wald = 6.7, p = 0.01).

CONCLUSIONS

For nearly one in five patients, the efficacy of antidepressants does not outweigh their drawbacks. Knowing patients' trade-offs is likely to aid both physicians and patients to identify important treatment preferences, to improve adherence and to make more deliberate decisions on whether or not to continue treatment.

Elderly patients' experiences using adaptive conjoint analysis software as a decision aid for osteoarthritis of the knee

BACKGROUND

Decision making in knee osteoarthritis, with many treatment options, challenges patients and physicians alike. Unfortunately, physicians cannot describe in detail each treatment's benefits and risks. One promising adjunct to decision making in osteoarthritis is adaptive conjoint analysis (ACA).

OBJECTIVE

To obtain insight into the experiences of elderly patients who use adaptive conjoint analysis to explore treatment options for their osteoarthritis.

DESIGN

Participants, all 65 and older, completed an ACA decision aid exploring their preferences with regard to the underlying attributes of osteoarthritis interventions. We used focus groups to obtain insight into their experiences using this software.

RESULTS

Content analysis distributed our participants' concerns into five areas. The predicted preferred treatment usually agreed with the individual's preference, but our participants experienced difficulty in four other domains: the choices presented by the software were sometimes confusing, the treatments presented were not the treatments of most interest, the researchers' claims about treatment characteristics were unpersuasive and cumulative overload sometimes developed.

CONCLUSION

Adaptive conjoint analysis presented special challenges to our elderly participants; we believe that their relatively low level of computer comfort was a significant contributor to these problems. We suggest that other researchers choose the software's treatments and present the treatment attributes with care. The next and equally vital step is to educate participants about what to expect, including the limitations in choice and apparent arbitrariness of the trade-offs presented by the software. Providing participants with a sample ACA task before undertaking the study task may further improve participant understanding and engagement.

Choosing between Hospitals

Objective. Publicly available information on hospital performance is increasing, with the aim to support consumers when choosing a hospital. Besides general hospital information and information on outcomes of care, there is increasing availability of systematically collected information on experiences of other patients. The aim of this study was to assess the influence of previous patients’ experiences relative to other information when choosing a hospital for surgical treatment. Methods. Three hundred thirty-seven patient volunteers and 280 healthy volunteers (response rate of 52.4% and 93.3%, respectively) filled out an Internet-based questionnaire that included an adaptive choice-based conjoint analysis. They were asked to select hospital characteristics they would use for future hospital choice, compare hospitals, and choose the overall best hospital. Based on the respondents’ choices, the relative importance (RI) of each hospital characteristic for each respondent was estimated using hierarchical Bayes estimation. Results. Information based on previous patients’ experience was considered at least as important as information provided by hospitals. “Report card regarding physician’s expertise” had the highest RI (16.83 [15.37–18.30]) followed by “waiting time for outpatient clinic appointment” (14.88 [13.42–16.34]) and “waiting time for surgery” (7.95 [7.12–8.78]). Patient and healthy volunteers considered the same hospital attributes to be important, except that patient volunteers assigned greater importance to “positive judgment about physician communication” (7.65 v. 5.80, P < 0.05) and lower importance to “complications” (2.56 v. 4.22, P < 0.05). Conclusion. Consumers consider patient experience–based information at least as important as hospital-based information. They rely most on information regarding physicians’ expertise, waiting time, and physicians’ communication when choosing a hospital.

Adaptive choice-based conjoint analysis: a new patient-centered approach to the assessment of health service preferences

Conjoint analysis (CA) has emerged as an important approach to the assessment of health service preferences. This article examines Adaptive Choice-Based Conjoint Analysis (ACBC) and reviews available evidence comparing ACBC with conventional approaches to CA. ACBC surveys more closely approximate the decision-making processes that influence real-world choices. Informants begin ACBC surveys by completing a build-your-own (BYO) task identifying the level of each attribute that they prefer. The ACBC software composes a series of attribute combinations clustering around each participant's BYO choices. During the Screener section, informants decide whether each of these concepts is a possibility or not. Probe questions determine whether attribute levels consistently included in or excluded from each informant's Screener section choices reflect 'Unacceptable' or 'Must Have' simplifying heuristics. Finally, concepts identified as possibilities during the Screener section are carried forward to a Choice Tournament. The winning concept in each Choice Tournament set advances to the next choice set until a winner is determined.A review of randomized trials and cross-over studies suggests that, although ACBC surveys require more time than conventional approaches to CA, informants find ACBC surveys more engaging. In most studies, ACBC surveys yield lower standard errors, improved prediction of hold-out task choices, and better estimates of real-world product decisions than conventional choice-based CA surveys.

Multi-criteria clinical decision support: A primer on the use of multiple criteria decision making methods to promote evidence-based, patient-centered healthcare

Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers.Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine "hard data" with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings.The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP).