Developing a Conversational agent (Chatbot) for Individuals Ambivalent about Quitting Smoking: A Study Protocol (Preprint)

BACKGROUND

Cigarette smoking is the leading preventable cause of disease and death in the United States. Despite the availability of a plethora of evidence-based smoking cessation resources, less than one-third of individuals who smoke seek cessation services, and individuals using these services are often those who are actively contemplating quitting smoking. There is a distinct dearth of low-cost, scalable interventions to support smokers not ready to quit (ambivalent smokers). Such interventions can assist in gradually promoting smoking behavior changes in this target population until motivation to quit arises, at which time they can be navigated to existing evidence-based smoking cessation interventions. Conversational agents or chatbots could provide cessation education and support to ambivalent smokers to build motivation and navigate them to evidence-based resources when ready to quit.

OBJECTIVE

The goal of our study is to test the proof-of-concept of the development and preliminary feasibility and acceptability of a smoking cessation support chatbot.

METHODS

We will accomplish our study aims in 2 phases. In phase 1, we will survey 300 ambivalent smokers to determine their preferences and priorities for a smoking cessation support chatbot. A "forced-choice experiment" will be administered to understand participants' preferred characteristics (attributes) of the proposed chatbot prototype. The data gathered will be used to program the prototype. In phase 2, we will invite 25 individuals who smoke to use the developed prototype. For this phase, participants will receive an overview of the chatbot and be encouraged to use the chatbot and engage and interact with the programmed attributes and components for a 2-week period.

RESULTS

At the end of phase 1, we anticipate identifying key attributes that ambivalent smokers prefer in a smoking cessation support chatbot. At the end of phase 2, chatbot acceptability and feasibility will be assessed. The study was funded in June 2022, and data collection for both phases of the study is currently ongoing. We expect study results to be published by December 2023.

CONCLUSIONS

Study results will yield a smoking behavior change chatbot prototype developed for ambivalent smokers that will be ready for efficacy testing in a larger study.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/44041.

Patient and Public Preferences for Coordinated Care in Switzerland: Development of a Discrete Choice Experiment

Objective

Our objective was to develop and test a discrete choice experiment (DCE) eliciting public and patient preferences for better-coordinated care in Switzerland.

Methods

We applied a multistage mixed-methods procedure using qualitative and quantitative approaches. First, to identify attributes, we performed a review of the DCE literature in healthcare with a focus on chronic care. Next, attribute selection involved stakeholders (N = 7) from various healthcare sectors to select the most relevant and actionable attributes, followed by three organized focus groups involving the general public and patients (N = 21) to verify the selection and the clarity of the DCE tasks and explanations. Finally, we conducted an online pilot in the target population to test the survey and obtain priors for a final six tested attributes to refine the final design of the experiment.

Results

After identifying an initial 33 attributes, a final list of six attributes was selected following stakeholder involvement and the three focus groups involving the target population. At the online pilot-testing stage with 301 participants, the majority of respondents found the DCE choice tasks socially relevant for Switzerland but challenging. The quality of the answers was relatively high. Most attributes had signs matching those in the literature and focus group discussions.

Conclusion

This article will be useful to researchers designing DCEs from a broad health policy perspective. The multistage approach involving a range of stakeholders was essential for the development of a DCE that is relevant for policy makers and well-accepted by the general public and patients.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40271-021-00568-2.

Understanding Treatment Preferences of Australian Patients Living with Treatment-Resistant Depression

BACKGROUND

There is evidence of improved adherence and treatment outcomes when patients' treatment preferences are considered, and shared decision making is utilized.

PURPOSE

We aimed to better understand treatment preferences among Australians with treatment-resistant depression (TRD), focusing on the specific treatment attributes that people value (such as effectiveness, risk of side effects and cost) and their relative importance. The risk-benefit trade-offs that characterize treatment choices were also examined.

PATIENTS AND METHODS

An online survey of 75 patients with experience of TRD was conducted, consisting of two discrete choice experiment (DCE) components - a medication DCE and a treatment plan DCE. Participants were able to prioritize and trade off different features of medications and treatment plans. Additional questions aimed to better define this population group, which in Australia is poorly understood.

RESULTS

In both DCEs, two distinct latent classes were identified. In the medication DCE, the classes were distinguished by willingness to consider new treatment alternatives. Participants in class 1 were reluctant to give up current treatment, while those in the slightly larger class 2 preferred new treatment options. In both classes, treatment effectiveness and cost were the greatest contributors to preference. Similar behavior was seen in the treatment plan DCE, with the larger class more likely to choose a new plan over their current treatment arrangement. Participants preferred medications that were low-cost, taken orally, had a high percentage improvement in mood symptoms, high rate of remission and low risk of weight gain. A similar result was found in preferences for treatment plans such that plans with the greatest effectiveness and lowest cost were most favorable.

CONCLUSION

Patient preferences should routinely be considered and discussed to guide informed decisions regarding the value of new and existing medications for TRD and how they sit in the context of treatment plans.

Mental health service preferences of patients and providers: a scoping review of conjoint analysis and discrete choice experiments from global public health literature over the last 20 years (1999-2019)

BACKGROUND

In designing, adapting, and integrating mental health interventions, it is pertinent to understand patients' needs and their own perceptions and values in receiving care. Conjoint analysis (CA) and discrete choice experiments (DCEs) are survey-based preference-elicitation approaches that, when applied to healthcare settings, offer opportunities to quantify and rank the healthcare-related choices of patients, providers, and other stakeholders. However, a knowledge gap exists in characterizing the extent to which DCEs/CA have been used in designing mental health services for patients and providers.

METHODS

We performed a scoping review from the past 20 years (2009-2019) to identify and describe applications of conjoint analysis and discrete choice experiments. We searched the following electronic databases: Pubmed, CINAHL, PsychInfo, Embase, Cochrane, and Web of Science to identify stakehold,er preferences for mental health services using Mesh terms. Studies were categorized according to pertaining to patients, providers and parents or caregivers.

RESULTS

Among the 30 studies we reviewed, most were published after 2010 (24/30, 80%), the majority were conducted in the United States (11/30, 37%) or Canada (10/30, 33%), and all were conducted in high-income settings. Studies more frequently elicited preferences from patients or potential patients (21/30, 70%) as opposed to providers. About half of the studies used CA while the others utilized DCEs. Nearly half of the studies sought preferences for mental health services in general (14/30, 47%) while a quarter specifically evaluated preferences for unipolar depression services (8/30, 27%). Most of the studies sought stakeholder preferences for attributes of mental health care and treatment services (17/30, 57%).

CONCLUSIONS

Overall, preference elicitation approaches have been increasingly applied to mental health services globally in the past 20 years. To date, these methods have been exclusively applied to populations within the field of mental health in high-income countries. Prioritizing patients' needs and preferences is a vital component of patient-centered care - one of the six domains of health care quality. Identifying patient preferences for mental health services may improve quality of care and, ultimately, increase acceptability and uptake of services among patients. Rigorous preference-elicitation approaches should be considered, especially in settings where mental health resources are scarce, to illuminate resource allocation toward preferred service characteristics especially within low-income settings.

Exploring Community-Based Options for Reducing Youth Crime

BackTrack is a multi-component, community-based intervention designed to build capacity amongst 14–17-year-old high risk young people. The aim of the current study seeks to explore community value and preferences for reducing youth crime and improving community safety using BackTrack in a rural setting in Armidale, New South Wales, Australia. The study design used discrete choice experiments (DCEs), designed in accordance with the 10-item checklist outlined by the International Society for Pharmacoeconomics and Outcomes Research. The DCE was pilot tested on 43 participants to test feasibility and comprehension. A revised version of the survey was subsequently completed by 282 people over a 12-day period between 30 May 2016 and 10 June 2016, representing a survey response rate of 35%. Ninety per cent of respondents were residents of Armidale, the local rural town where BackTrack was implemented. The DCE generated results that consistently demonstrated a preference for social programs to address youth crime and community safety in the Armidale area. Respondents chose BackTrack over Greater Police Presence 75% of the time with an annual benefit of Australian dollars (AUD) 150 per household, equivalent to a community benefit of AUD 2.04 million. This study estimates a strong community preference for BackTrack relative to more policing (a community willing to pay equivalent to AUD 2.04 million) highlighting the clear value of including community preferences when evaluating community-based programs for high-risk young people.

Patient-Centered Preference Assessment to Improve Satisfaction With Care Among Patients With Localized Prostate Cancer: A Randomized Controlled Trial

PURPOSE

To study the effectiveness of the Patient Preferences for Prostate Cancer Care (PreProCare) intervention in improving the primary outcome of satisfaction with care and secondary outcomes of satisfaction with decision, decision regret, and treatment choice among patients with localized prostate cancer.

METHODS

In this multicenter randomized controlled study, we randomly assigned patients with localized prostate cancer to the PreProCare intervention or usual care. Outcomes were satisfaction with care, satisfaction with decision, decision regret, and treatment choice. Assessments were performed at baseline and at 3, 6, 12, and 24 months, and were analyzed using repeated measures. We compared treatment choice across intervention groups by prostate cancer risk categories.

RESULTS

Between January 2014 and March 2015, 743 patients with localized prostate cancer were recruited and randomly assigned to receive PreProCare (n = 372) or usual care (n = 371). For the general satisfaction subscale, improvement at 24 months from baseline was significantly different between groups ( P < .001). For the intervention group, mean scores at 24 months improved by 0.44 (SE, 0.06; P < .001) from baseline. This improvement was 0.5 standard deviation, which was clinically significant. The proportion reporting satisfaction with decision and no regret increased over time and was higher for the intervention group, compared with the usual care group at 24 months ( P < .05). Among low-risk patients, a higher proportion of the intervention group was receiving active surveillance, compared with the usual care group ( P < .001).

CONCLUSION

Our patient-centered PreProCare intervention improved satisfaction with care, satisfaction with decision, reduced regrets, and aligned treatment choice with risk category. The majority of our participants had a high income, with implications for generalizability. Additional studies can evaluate the effectiveness of PreProCare as a mechanism for improving clinical and patient-reported outcomes in different settings.

Women's Preferences for Maternal Healthcare Services in Bangladesh: Evidence from a Discrete Choice Experiment

Despite substantial improvements in several maternal health indicators, childbearing and birthing remain a dangerous experience for many women in Bangladesh. This study assessed the relative importance of maternal healthcare service characteristics to Bangladeshi women when choosing a health facility to deliver their babies. The study used a mixed-methods approach. Qualitative methods (expert interviews, focus group discussions) were initially employed to identify and develop the characteristics which most influence a women's decision making when selecting a maternal health service facility. A discrete choice experiment (DCE) was then constructed to elicit women's preferences. Women were shown choice scenarios representing hypothetical health facilities with nine attributes outlined. The women were then asked to rank the attributes they considered most important in the delivery of their future babies. A Hierarchical Bayes method was used to measure mean utility parameters. A total of 601 women completed the DCE survey. The model demonstrated significant predictive strength for actual facility choice for maternal health services. The most important attributes were the following: consistent access to a female doctor, the availability of branded drugs, respectful provider attitudes, a continuum of maternal healthcare including the availability of a C-section delivery and lesser waiting times. Attended maternal healthcare utilisation rates are low despite the access to primary healthcare facilities. Further implementation of quality improvements in maternal healthcare facilities should be prioritised.

Patient-Centered Approach to Develop the Patient's Preferences for Prostate Cancer Care (PreProCare) Tool

Objectives. To describe the development of our Patient Preferences for Prostate Cancer Care (PreProCare) tool to aid patient-centered treatment decision among localized prostate cancer patients. Methods. We incorporated patient and provider experiences to develop a patient preference elicitation tool using adaptive conjoint analysis. Our patient-centered approach used systematic literature review, semistructured patient interviews, and provider focus groups to determine the treatment attributes most important for decision making. The resulting computer-based PreProCare tool was pilot tested in a clinical setting. Results. A systematic review of 56 articles published between 1995 and 2015 yielded survival, cancer recurrence, side effects, and complications as attributes of treatment options. We conducted one-on-one interviews with 50 prostate cancer survivors and 5 focus groups of providers. Patients reported anxiety, depression, treatment specifics, and caregiver burden as important for decision making. Providers identified clinical characteristics as important attribute. Input from stakeholders' advisory group, physicians, and researchers helped finalize 15 attributes for our PreProCare preference assessment tool. Conclusion. The PreProCare tool was developed using a patient-centered approach and may be a feasible and acceptable preference clarification intervention for localized prostate cancer patients. The PreProCare tool may translate into higher participant engagement and self-efficacy, consistent with patients' personal values.

Differences in Perceptions of Major Depressive Disorder Symptoms and Treatment Priorities Between Patients and Health Care Providers Across the Acute, Post-Acute, and Remission Phases of Depression

Limited data exist on concordance between patients' and health care providers' (HCPs) perceptions regarding symptoms of major depressive disorder (MDD) and treatment priorities, particularly across disease phases. This study examined concordance during the acute, post-acute, and remission phases of MDD. In an online survey, 2,008 patients responded based on their experience with MDD, and 1,046 HCPs responded based on their clinical experience treating patients with MDD. Questions included symptom frequency and severity, treatment priorities, and impact on psychosocial functioning. Patients reported more frequently mood, physical, and cognitive symptoms than HCPs in the post-acute and remission phases and greater impact on psychosocial functioning. Patients reported that all these symptoms require high treatment priority across the phases of MDD, generally to a greater extent than HCPs. Patients also gave high emphasis to addressing impairment in psychosocial functioning early in the treatment course. A substantial difference in the effectiveness of treating symptoms of MDD between patients and HCPs was observed. This is the first study to quantify, broadly, differences in perceptions of MDD symptom prevalence, severity, and treatment priorities across MDD phases, and the study findings highlight a need for improved communication between patients and HCPs about symptoms, their impact on psychosocial functioning, and treatment priorities across phases.

Patient priorities and the doorknob phenomenon in primary care: Can technology improve disclosure of patient stressors?

OBJECTIVE

Patients with multiple chronic conditions face many stressors (e.g. financial, safety, transportation stressors) that are rarely prioritized for discussion with the primary care provider (PCP). In this pilot randomized controlled trial we examined the effects of a novel technology-based intervention called Customized Care on stressor disclosure.

METHODS

The main outcomes were stressor disclosure, patient confidence and activation, as assessed by self-report and observational methods (transcribed and coded audio-recordings of the office visit).

RESULTS

Sixty patients were enrolled. Compared with care as usual, intervention patients were 6 times more likely to disclose stressors to the PCP (OR=6.16, 95% CI [1.53, 24.81], p=0.011) and reported greater stressor disclosure confidence (exp[B]=1.06, 95% CI [1.01, 1.12], p=0.028). No differences were found in patient activation or the length of the office visit.

CONCLUSION

Customized Care improved the likelihood of stressor disclosure without affecting the length of the PCP visit.

PRACTICE IMPLICATIONS

Brief technology-based interventions, like Customized Care could be made available through patient portals, or on smart phones, to prime patient-PCP discussion about difficult subjects, thereby improving the patient experience and efficiency of the visit.

Patient Preferences of a Low-Income Hispanic Population for Mental Health Services in Primary Care

We used a discrete-choice conjoint experiment to model the mental health services preferences of patients of a federally-qualified health center serving a primarily low-income, Hispanic farmworker population in southwestern Arizona. The two attributes that had the largest influence on patient choices (i.e., received the highest importance scores) were where patients receive these services and the language and cultural awareness of the provider who prescribed their treatment. Simulations indicated that the clinic could substantially improve its patients' welfare with even a single change. The single most effective change in terms of patient preferences would be to offer behavioral health services onsite.

Preferences for Depression Treatment Including Internet-Based Interventions: Results From a Large Sample of Primary Care Patients

Background: To date, little is known about treatment preferences for depression concerning new media. This study aims to (1) investigate treatment preferences for depression including internet-based interventions and (2) examine subgroup differences concerning age, gender and severity of depression as well as patient-related factors associated with treatment preferences. Methods: Data were derived from the baseline assessment of the @ktiv-trial. Depression treatment preferences were assessed from n = 641 primary care patients with mild to moderate depression regarding the following treatments: medication, psychotherapy, combined treatment, alternative treatment, talking to friends and family, exercise, self-help literature, and internet-based interventions. Depression severity was specified by GPs according to ICD-10 criteria. Ordinal logistic regression models were conducted to identify associated factors of treatment preferences. Results: Patients had a mean age of 43.9 years (SD = 13.8) and more than two thirds (68.6%) were female. About 43% of patients had mild depression while 57% were diagnosed with moderate depression. The majority of patients reported strong preferences for psychotherapy, talking to friends and family, and exercise. About one in five patients was very likely to consider internet-based interventions in case of depression. Younger patients expressed significantly stronger treatment preferences for psychotherapy and internet-based interventions than older patients. The most salient factors associated with treatment preferences were the patients' education and perceived self-efficacy. Conclusions: Patients with depression report individually different treatment preferences.Our results underline the importance of shared decision-making within primary care. Future studies should investigate treatment preferences for different types of internet-based interventions.

Methods for Incorporating Patient Preferences for Treatments of Depression in Community Mental Health Settings

We developed three methods (rating, ranking, and discrete choice) for identifying patients' preferred depression treatments based on their prioritization of specific treatment attributes (e.g., medication side effects, psychotherapy characteristics) at treatment intake. Community mental health patients with depressive symptoms participated in separate studies of predictive validity (N = 193) and short-term (1-week) stability (N = 40). Patients who received non-preferred initial treatments (based on the choice method) switched treatments significantly more often than those who received preferred initial treatments. Receiving a non-preferred treatment at any point (based on rating and choice methods) was a significant predictor of longer treatment duration. All three methods demonstrated good short-term stability.

A Comparison of Methods for Capturing Patient Preferences for Delivery of Mental Health Services to Low-Income Hispanics Engaged in Primary Care

BACKGROUND

Consideration of patient preferences regarding delivery of mental health services within primary care may greatly improve access and quality of care for the many who could benefit from those services.

OBJECTIVES

This project evaluated the feasibility and usefulness of adding a consumer-products design method to qualitative methods implemented within a community-based participatory research (CBPR) framework.

RESEARCH DESIGN

Discrete-choice conjoint experiment (DCE) added to systematic focus group data collection and analysis.

SUBJECTS

Focus group data were collected from 64 patients of a Federally-Qualified Health Center (FQHC) serving a predominantly low-income Hispanic population. A total of 604 patients in the waiting rooms of the FQHC responded to the DCE.

MEASURES

The DCE contained 15 choice tasks that each asked respondents to choose between three mental health services options described by the levels of two (of eight) attributes based on themes that emerged from focus group data.

RESULTS

The addition of the DCE was found to be feasible and useful in providing distinct information on relative patient preferences compared with the focus group analyses alone. According to market simulations, the package of mental health services guided by the results of the DCE was preferred by patients.

CONCLUSIONS

Unique patterns of patient preferences were uncovered by the DCE and these findings were useful in identifying pragmatic solutions to better address the mental health service needs of this population. However, for this resource-intensive method to be adopted more broadly, the scale of the primary care setting and/or scope of the issue addressed have to be relatively large.

Participant Preferences for Pharmacologic Chronic Pain Treatment Trial Characteristics: An ACTTION Adaptive Choice-Based Conjoint Study

Barriers to clinical trial recruitment can delay study completion, potentially resulting in increased costs and an unrepresentative sample. In the current study of 150 participants with chronic pain, we used a computerized adaptive choice-based conjoint survey that included 8 characteristics that may affect enrollment in pharmacologic pain treatment trials (ie, treatment allocation, frequency of pain ratings, treatment administration method, current medications, number of study visits, availability of evening and weekend visits, invasiveness of laboratory procedures, payment). These data were analyzed using Sawtooth Software ver. 8.4.8 (Sawtooth Software, Inc, Orem, UT), which identifies the characteristics that dominate participants' decisions across multiple sets of potential trials. Three characteristics had the largest relative importance in participants' trial preferences: 1) invasiveness of required laboratory procedures (ie, 22%), with no procedures or blood tests preferred over ice-water sensory testing or skin biopsy; 2) ability to continue current pain medications (21%); and 3) payment for study participation (21%), with higher payment preferred. The fourth most important characteristic was number of study visits (13%), with participants preferring fewer in-person visits and more phone contacts. Understanding the preferences of potential participants is an important step toward enhancing enrollment in pain treatment trials.

PERSPECTIVE

This article presents the preferences of individuals with chronic pain conditions regarding modifiable pain treatment trial characteristics (eg, number of study visits, payment, treatment allocation). These findings may help to improve enrollment into analgesic clinical trials and in turn accelerate the development of new pain treatments.

The Relevance of the Affordable Care Act for Improving Mental Health Care

Provisions of the Affordable Care Act provide unprecedented opportunities for expanded access to behavioral health care and for redesigning the provision of services. Key to these reforms is establishing mental and substance abuse care as essential coverage, extending Medicaid eligibility and insurance parity, and protecting insurance coverage for persons with preexisting conditions and disabilities. Many provisions, including Accountable Care Organizations, health homes, and other structures, provide incentives for integrating primary care and behavioral health services and coordinating the range of services often required by persons with severe and persistent mental health conditions. Careful research and experience are required to establish the services most appropriate for primary care and effective linkage to specialty mental health services. Research providing guidance on present evidence and uncertainties is reviewed. Success in redesign will follow progress building on collaborative care and other evidence-based practices, reshaping professional incentives and practices, and reinvigorating the behavioral health workforce.

Treatment preference and patient centered prostate cancer care: Design and rationale

Prostate cancer is a slow progressing cancer that affects millions of men in the US. Due to uncertainties in outcomes and treatment complications, it is important that patients engage in informed decision making to choose the "optimal treatment". Patient centered care that encompasses informed decision-making can improve treatment choice and quality of care. Thus, assessing patient treatment preferences is critical for developing an effective decision support system. The objective of this patient-centered randomized clinical trial was to study the comparative effectiveness of a conjoint analysis intervention compared to usual care in improving subjective and objective outcomes in prostate cancer patients. We identified preferred attributes of alternative prostate cancer treatments that will aid in evaluating attributes of treatment options. In this two-phase study, in Phase 1 we used mixed methods to develop an adaptive conjoint task instrument. The conjoint task required the patients to trade-off attributes associated with treatments by assessing their relative importance. Phase 2 consisted of a randomized controlled trial of men with localized prostate cancer. We analyzed the effect of conjoint task intervention on the association between preferences, treatment and objective and subjective outcomes. Our conjoint task instrument can lead to a values-based patient-centered decision aid tool and help tailor treatment decision making to the values of prostate cancer patients. This will ultimately improve clinical decision making, clinical policy process, enhance patient centered care and improve prostate cancer outcomes.

Nutzung von Conjoint-Analysen zur Messung von Therapiezielpräferenzen aus Patientenperspektive in der Behandlung psychischer Störungen

Hintergrund: Im Zuge der wachsenden Bedeutung von Ansätzen zur Patientenorientierung und -partizipation in der Gesundheitsversorgung gewinnt die Bestimmung subjektiver Therapiezielpräferenzen unterschiedlicher Akteure (Patienten, Behandler, Angehörige) zunehmend an Forschungsinteresse. Stated-Preference-Methods ermöglichen die systematische Untersuchung speziell patientenorientierter Fragestellungen. Ziele der Studie: Identifikation und Beschreibung (nach formalen, methodischen und inhaltlichen Merkmalen) von Studien mit Stated-Preference-Methods (Conjoint Measurements, Conjoint Analysis, Discrete Choice Experiments) in der Versorgung von Patienten mit psychischen Störungen mit dem Ziel, eine Bewertung zur Anwendbarkeit der Methode (Potential, Nutzen, Grenzen) in zukünftiger patientenorienterter Forschung abzuleiten. Methode: Systematische Literaturrecherche mit folgenden Studieneinschlusskriterien: Participants: Interventionen zur Behandlung von Patienten mit psychischer Störung; Intervention: psychotherapeutische, psychiatrische, hausärztliche Behandlungen (stationär, teil-stationär, ambulant); Comparison: Studien mit keiner (Ein-Gruppen-Design) oder mindestens einer Kontrollgruppe; Outcomes: conjoint-spezifische Angaben zu Nutzenwerten. Ergebnisse: Conjoint-Analysen werden in unterschiedlichen Forschungsdesigns und unter heterogenen Rahmenbedingungen (Stichprobe, Störungsbild, Setting, Intervention, Zieldimension) zur Messung von Therapiezielpräferenzen eingesetzt. Die Erstellung des Conjoint-Designs erfolgt in der Regel reduziert (orthogonal), mithilfe von Softwarepaketen, die Erhebung als Fragebogen. Schlussfolgerungen: Conjoint-Analysen ermöglichen differenzierte Aussagen über Therapiepräferenzstrukturen auf Basis relationaler Beurteilungsszenarien und stellen damit eine fundiertere Basis zur Verbesserung der Patientenorientierung in der Gesundheitsversorgung zur Verfügung. Die Befundlage belegt, dass sich die Methode zur Untersuchung patientenorientierter Fragestellungen (mehrheitlich zu Pharmakotherapie und Kombinationsbehandlung) in der Versorgung psychischer Störungen (depressive Störungen, ADHS, Schizophrenie, bipolare Störungen, Tabak- und Alkoholabhängigkeit und chronische Schmerzen) eignet. Allerdings ist der erfolgreiche Einsatz der Methodik an einige Voraussetzungen geknüpft (u. a. Unabhängigkeit der betrachteten Therapiezielaspekte, Designkomplexität). Forschungsbedarf besteht u. a. im Hinblick auf bisher nicht untersuchte Störungsbilder (u. a. somatoforme, Angst-, Ess-, Persönlichkeitsstörungen) und Interventionen (u. a. reine Psychotherapie, störungsspezifische Behandlungen).

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.

Developing emergency department-based education about emergency contraception: adolescent preferences

OBJECTIVES

The objective was to identify adolescent preferences for emergency department (ED)-based education about emergency contraception.

METHODS

This was a cross-sectional computerized survey, using adaptive conjoint analysis (ACA). Patients were eligible if they were females ages 14 through 19 years old and were seeking care in one of two urban EDs. Patients were excluded if they were too ill to participate in the survey or if they were non-English speaking. Participants completed a computerized survey that used ACA, a technique that can be used to assess patients' relative preferences for services. ACA uses the individual's answers to update and refine questions through trade-off comparisons, so that each respondent answers a customized set of questions. The survey assessed preferences for the following attributes of emergency contraception education: who should deliver the education, if anyone (e.g., nurse, doctor); how the education should be delivered (e.g., by a person or via video); how often the education should be offered if patients were to frequent the ED (e.g., every time or only when asking for it); length (e.g., 5 minutes, 10 minutes); and chief complaint that would trigger the education (e.g., headache or stomach pain).

RESULTS

A total of 223 patients were enrolled (37.2% at Hospital 1 and 62.8% at Hospital 2). The mean (±SD) age of the participants was 16.1 (±1.3) years. Just over half (55%) reported a history of sexual activity; 8% reported a history of pregnancy. Overall, the participants preferred education that was delivered by a person, specifically a doctor or nurse. They preferred a slightly longer education session and preferred education directed at patients seeking care in the ED for complaints potentially related to sexual activity.

CONCLUSIONS

Adolescents have specific preferences for how education about emergency contraception would best serve their needs. This information can inform clinicians as they work to improve adolescents' knowledge about pregnancy prevention and emergency contraception in particular.

Genomic testing to determine drug response: measuring preferences of the public and patients using Discrete Choice Experiment (DCE)

Background

The extent to which a genomic test will be used in practice is affected by factors such as ability of the test to correctly predict response to treatment (i.e. sensitivity and specificity of the test), invasiveness of the testing procedure, test cost, and the probability and severity of side effects associated with treatment.

Methods

Using discrete choice experimentation (DCE), we elicited preferences of the public (Sample 1, N = 533 and Sample 2, N = 525) and cancer patients (Sample 3, N = 38) for different attributes of a hypothetical genomic test for guiding cancer treatment. Samples 1 and 3 considered the test/treatment in the context of an aggressive curable cancer (scenario A) while the scenario for sample 2 was based on a non-aggressive incurable cancer (scenario B).

Results

In aggressive curable cancer (scenario A), everything else being equal, the odds ratio (OR) of choosing a test with 95% sensitivity was 1.41 (versus a test with 50% sensitivity) and willingness to pay (WTP) was $1331, on average, for this amount of improvement in test sensitivity. In this scenario, the OR of choosing a test with 95% specificity was 1.24 times that of a test with 50% specificity (WTP = $827). In non-aggressive incurable cancer (scenario B), the OR of choosing a test with 95% sensitivity was 1.65 (WTP = $1344), and the OR of choosing a test with 95% specificity was 1.50 (WTP = $1080). Reducing severity of treatment side effects from severe to mild was associated with large ORs in both scenarios (OR = 2.10 and 2.24 in scenario A and B, respectively). In contrast, patients had a very large preference for 95% sensitivity of the test (OR = 5.23).

Conclusion

The type and prognosis of cancer affected preferences for genomically-guided treatment. In aggressive curable cancer, individuals emphasized more on the sensitivity rather than the specificity of the test. In contrast, for a non-aggressive incurable cancer, individuals put similar emphasis on sensitivity and specificity of the test. While the public expressed strong preference toward lowering severity of side effects, improving sensitivity of the test had by far the largest influence on patients’ decision to use genomic testing.

Patient preferences for outcomes of depression treatment in Germany: a choice-based conjoint analysis study

BACKGROUND

In general, treatment efficacy in depressed patients is evaluated mainly based on the core symptoms of depression. However, patients might consider different outcomes. This study used choice-based conjoint analysis (CBC) to evaluate patient preferences for depression treatment outcomes.

METHODS

Adult subjects from Germany, currently or previously on antidepressant treatment, were presented with 18 pairs of hypothetical treatment outcome scenarios, differing in eight attributes (2-3 factor levels each): depressed mood, loss of interest and enjoyment, loss of energy/fatigue, sleep disturbance, feelings of guilt, depression-related pain, treatment duration, side effects after 2 weeks. Attributes and factor levels were defined by literature review, expert consultations, and in-depth subject interviews. Data were analyzed using multinomial logit modeling; individual part-worth utilities were estimated using hierarchical Bayes routines.

RESULTS

Two hundred twenty-seven subjects (89.4% currently treated with antidepressants, 30.0% with depression-related pain) completed the survey. They valued the relative importance of outcomes as follows: loss of energy/fatigue 18.5%, side effects after 2 weeks 14.2%, loss of interest and enjoyment 13.5%, depression-related pain 12.0%, sleep disturbance 12.0%, feelings of guilt 11.5%, treatment duration 9.9%, depressed mood 8.5%.

LIMITATIONS

Participants were not required to meet ICD-10 or DSM-IV criteria for depression and had heterogeneous disease severity.

CONCLUSIONS

CBC analysis was able to reveal patient preferences for outcomes of depression treatment. Subjects valued the ability to cope with activities of everyday living highest. They considered being free of depression-related pain and side effects more important than being free of depressed mood. These findings should be considered when making treatment decisions.

Towards personalizing treatment for depression : developing treatment values markers

BACKGROUND

While 'personalized medicine' commonly refers to genetic markers or profiles associated with pharmacological treatment response, tailoring treatments to patient preferences and values is equally important.

OBJECTIVE

To describe and demonstrate a method to develop 'values markers,' or profiles based on the relative importance of attributes of depression treatment.

STUDY DESIGN

Discrete choice analysis was used to assess individuals' relative preferences for features of depression treatment. Preference profiles were developed using latent profile analysis.

PATIENTS OR OTHER PARTICIPANTS

Eighty-six adults participating in an internet-based discrete choice questionnaire.

MAIN OUTCOME MEASURE

Participants were presented with two depression scenarios representing mild and severe depression. For each scenario, they were asked to compare 18 choice sets based on the type of medication side effect (nausea, dizziness, and sexual dysfunction) and severity (mild, moderate, and severe); and for counseling frequency (once per week or every other week) and provider setting (the office of a mental health professional, primary care doctor, or spiritual counselor).

RESULTS

Three profiles were identified: profile 1 was associated with a preference for counseling and an avoidance of medication side effects; profile 2 with an avoidance of strong medication side effects and for receiving counseling in medical settings; and profile 3 with a preference for medication over counseling. When presented with a severe depression scenario, there was a higher prevalence for profile 1 and patients were more likely to prefer mental health over primary care and spiritual settings.

CONCLUSIONS

Values markers may provide a foundation for personalized medicine, and reflect current initiatives emphasizing patient-centered care. Next steps should assess whether values markers are predictive of treatment initiation and adherence.

Using the analytic hierarchy process to elicit patient preferences: prioritizing multiple outcome measures of antidepressant drug treatment

BACKGROUND AND OBJECTIVE

In health technology assessment, the evidence obtained from clinical trials regarding multiple clinical outcomes is used to support reimbursement claims. At present, the relevance of these outcome measures for patients is, however, not systematically assessed, and judgments on their relevance may differ among patients and healthcare professionals. The analytic hierarchy process (AHP) is a technique for multi-criteria decision analysis that can be used for preference elicitation. In the present study, we explored the value of using the AHP to prioritize the relevance of outcome measures for major depression by patients, psychiatrists and psychotherapists, and to elicit preferences for alternative healthcare interventions regarding this weighted set of outcome measures.

METHODS

Supported by the pairwise comparison technique of the AHP, a patient group and an expert group of psychiatrists and psychotherapists discussed and estimated the priorities of the clinical outcome measures of antidepressant treatment. These outcome measures included remission of depression, response to drug treatment, no relapse, (serious) adverse events, social function, no anxiety, no pain, and cognitive function. Clinical evidence on the outcomes of three antidepressants regarding these outcome measures was derived from a previous benefit assessment by the Institute for Quality and Efficiency in Health Care (IQWiG; Institut für Qualität und Wirtschaftlichkeit im Gesundheitswesen).

RESULTS

The most important outcome measures according to the patients were, in order of decreasing importance: response to drug treatment, cognitive function, social function, no anxiety, remission, and no relapse. The patients and the experts showed some remarkable differences regarding the relative importance of response (weight patients = 0.37; weight experts  = 0.05) and remission (weight patients = 0.09; weight experts = 0.40); however, both experts and patients agreed upon the list of the six most important measures, with experts only adding one additional outcome measure.

CONCLUSIONS

The AHP can easily be used to elicit patient preferences and the study has demonstrated differences between patients and experts. The AHP is useful for policy makers in combining multiple clinical outcomes of healthcare interventions grounded in randomized controlled trials in an overall health economic evaluation. This may be particularly relevant in cases where different outcome measures lead to conflicting results about the best alternative to reimburse. Alternatively, AHP may also support researchers in selecting (primary) outcome measures with the highest relevance.

Conjoint analysis applications in health--a checklist: a report of the ISPOR Good Research Practices for Conjoint Analysis Task Force

BACKGROUND

The application of conjoint analysis (including discrete-choice experiments and other multiattribute stated-preference methods) in health has increased rapidly over the past decade. A wider acceptance of these methods is limited by an absence of consensus-based methodological standards.

OBJECTIVE

The International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Good Research Practices for Conjoint Analysis Task Force was established to identify good research practices for conjoint-analysis applications in health.

METHODS

The task force met regularly to identify the important steps in a conjoint analysis, to discuss good research practices for conjoint analysis, and to develop and refine the key criteria for identifying good research practices. ISPOR members contributed to this process through an extensive consultation process. A final consensus meeting was held to revise the article using these comments, and those of a number of international reviewers.

RESULTS

Task force findings are presented as a 10-item checklist covering: 1) research question; 2) attributes and levels; 3) construction of tasks; 4) experimental design; 5) preference elicitation; 6) instrument design; 7) data-collection plan; 8) statistical analyses; 9) results and conclusions; and 10) study presentation. A primary question relating to each of the 10 items is posed, and three sub-questions examine finer issues within items.

CONCLUSIONS

Although the checklist should not be interpreted as endorsing any specific methodological approach to conjoint analysis, it can facilitate future training activities and discussions of good research practices for the application of conjoint-analysis methods in health care studies.