Patient Perspectives on the Value of Patient Preference Information in Regulatory Decision Making: A Qualitative Study in Swedish Patients with Rheumatoid Arthritis.

Background There is increasing interest in involving patient preferences for benefits and risks in regulatory decision making. Therefore, it is essential to identify patient perspectives regarding the value of patient preference information (PPI). Objectives The aim of this study was to explore how patients with rheumatoid arthritis (RA) value the use of PPI in regulatory decision making regarding medical products. Methods Regulators and patients with RA were interviewed to gather initial insights into opinions on the use of PPI in regulatory decisions regarding medical products. The interviews were used to draft and validate the interview guide for focus groups with patients with RA. Participants were purposively sampled in collaboration with the Swedish Rheumatism Association in Stockholm and Uppsala. Each focus group consisted of three to six patients (18 in total). All interviews were audio-recorded, transcribed verbatim, and analysed using content analysis. Results According to the participants, PPI could lead to regulators considering patients’ needs, lifestyles and well-being when making decisions. PPI was important in all stages of the medical product lifecycle. Participants reported that, when participating in a preference study, it is important to be well-informed about the use of the study and the development, components, administration, and risks related to the medical products. Conclusions Patients thought PPI could be valuable to consider in regulatory decisions. It is essential for patients to be well-informed when asked for their preferences. Research on information materials to inform patients in preference studies is needed to increase the value of PPI in regulatory decision making

Prosocial Behaviour and Antibiotic Resistance:Evidence from a Discrete Choice Experiment

Introduction: The health of a community depends on the health of its individuals; therefore, individual health behaviour can implicitly affect the health of the entire community. This is particularly evident in the case of infectious diseases. Because the level of prosociality in a community might determine the effectiveness of health programmes, prosocial behaviour may be a crucial disease-control resource. This study aimed to extend the literature on prosociality and investigate the role of altruism in antibiotic decision making. Methods: A discrete choice experiment was conducted to assess the influence of altruism on the general public’s preferences regarding antibiotic treatment options. The survey was completed by 378 Swedes. Latent class analysis models were used to estimate antibiotic treatment characteristics and preference heterogeneity. A three-class model resulted in the best model fit, and altruism significantly impacted preference heterogeneity. Results: Our findings suggest that people with higher altruism levels had more pronounced preferences for treatment options with lower contributions to antibiotic resistance and a lower likelihood of treatment failure. Furthermore, altruism was statistically significantly associated with sex, education, and health literacy. Conclusions: Antibiotic awareness, trust in healthcare systems, and non-discriminatory priority setting appear to be structural elements conducive to judicious and prosocial antibiotic behaviour. This study suggests that prosocial messages could help to decrease the demand for antibiotic treatments.</p

Mimicking Real-Life Decision Making in Health: Allowing Respondents Time to Think in a Discrete Choice Experiment

Objective: To empirically test the impact of allowing respondents time to think (TTT) about their choice options on the outcomes of a discrete choice experiments (DCE). Methods: In total, 613 participants of the Swedish CArdioPulmonary bioImage Study (SCAPIS) completed a DCE questionnaire that measured their preferences for receiving secondary findings of a genetic test. A Bayesian D-efficient design with 60 choice tasks divided over 4 questionnaires was used. Each choice task contained 2 scenarios with 4 attributes: type of disease, disease penetrance probability, preventive opportunities, and effectiveness of prevention. Respondents were randomly allocated to the TTT or no TTT (NTTT) sample. Latent class models (LCMs) were estimated to determine attribute-level values and their relative importance. In addition, choice certainty, attribute-level interpretation, choice consistency, and potential uptake rates were compared between samples. Results: In the TTT sample, 92% of the respondents (245 of 267) indicated they used the TTT period to (1) read the information they received (72%) and (2) discuss with their family (24%). In both samples, respondents were very certain about their choices. A 3-class LCM was fitted for both samples. Preference reversals were found for 3 of the 4 attributes in one class in the NTTT sample (34% class-membership probability). Relative importance scores of the attributes differed between the 2 samples, and significant scale effects indicating higher choice consistency in TTT sample were found. Conclusions: Offering respondents TTT influences decision making and preferences. Developers of future DCEs regarding complex health-related decisions are advised to consider this approach to enhance the validity of the elicited preferences

The preferences of users of electronic medical records in hospitals: Quantifying the relative importance of barriers and facilitators of an innovation

Background: Currently electronic medical records (EMRs) are implemented in hospitals, because of expected benefits for quality and safety of care. However the implementation processes are not unproblematic and are slower than needed. Many of the barriers and facilitators of the adoption of EMRs are identified, but the relative importance of these factors is still undetermined. This paper quantifies the relative importance of known barriers and facilitators of EMR, experienced by the users (i.e., nurses and physicians in hospitals).Methods: A discrete choice experiment (DCE) was conducted among physicians and nurses. Participants answered ten choice sets containing two scenarios. Each scenario included attributes that were based on previously identified barriers in the literature: data entry hardware, technical support, attitude head of department, performance feedback, flexibility of interface, and decision support. Mixed Multinomial Logit analysis was used to determine the relative importance of the attributes.Results: Data on 148 nurses and 150 physicians showed that high flexibility of the interface was the factor with highest relative importance in their preference to use an EMR. For nurses this attribute was followed by support from the head of department, presence of performance feedback from the EMR and presence of decisions support. While for physicians this ordering was different: presence of decision support was relatively more important than performance feedback and support from the head of department.Conclusion: Considering the prominent wish of all the intended users for a flexible interface, currently used EMRs only partially comply with the needs of the users, indicating the need for closer incorporation of user needs during development stages of EMRs. The differences in priorities amongst nurses and physicians show that different users have different needs during the implementation of innovations. Hospital management may use this information to design implementation trajectories to fit the needs of various user groups

Can healthcare choice be predicted using stated preference data?

Lack of evidence about the external validity of Discrete Choice Experiments (DCEs)-sourced preferences inhibits greater use of DCEs in healthcare decision-making. This study examines the external validity of such preferences, unravels its determinants, and provides evidence of whether healthcare choice is predictable. We focused on influenza vaccination and used a six-step approach: i) literature study, ii) expert interviews, iii) focus groups, iv) survey including a DCE, v) field data, and vi) in-depth interviews with respondents who showed discordance between stated choices and actual healthcare utilization. Respondents without missing values in the survey and the actual healthcare utilization (377/499 = 76%) were included in the analyses. Random-utility-maximization and random-regret-minimization models were used to analyze the DCE data, whereas the in-depth interviews combined five scientific theories to explain discordance.

A socially interdependent choice framework for social influences in healthcare decision-making:a study protocol

OBJECTIVES: Current choice models in healthcare (and beyond) can provide suboptimal predictions of healthcare users' decisions. One reason for such inaccuracy is that standard microeconomic theory assumes that decisions of healthcare users are made in a social vacuum. Healthcare choices, however, can in fact be (entirely) socially determined. To achieve more accurate choice predictions within healthcare and therefore better policy decisions, the social influences that affect healthcare user decision-making need to be identified and explicitly integrated into choice models. The purpose of this study is to develop a socially interdependent choice framework of healthcare user decision-making.DESIGN: A mixed-methods approach will be used. A systematic literature review will be conducted that identifies the social influences on healthcare user decision-making. Based on the outcomes of a systematic literature review, an interview guide will be developed that assesses which, and how, social influences affect healthcare user decision-making in four different medical fields. This guide will be used during two exploratory focus groups to assess the engagement of participants and clarity of questions and probes. The refined interview guide will be used to conduct the semistructured interviews with healthcare professionals and users. These interviews will explore in detail which, and how, social influences affect healthcare user decision-making. Focus group and interview transcripts will be analysed iteratively using a constant comparative approach based on a mix of inductive and deductive coding. Based on the outcomes, a social influence independent choice framework for healthcare user decision-making will be drafted. Finally, the Delphi technique will be employed to achieve consensus about the final version of this choice framework.ETHICS AND DISSEMINATION: This study was approved by the Erasmus School of Health Policy and Management Research Ethics Review Committee (ESHPM, Rotterdam, The Netherlands; reference ETH2122-0666).</p

Trading patients’ choice in providers for quality of maternity care? A discrete choice experiment amongst pregnant women

Background The introduction of bundled payment for maternity care, aimed at improving the quality of maternity care, may affect pregnant women’s choice in providers of maternity care. This paper describes a Dutch study which examined pregnant women’s preferences when choosing a maternity care provider. The study focused on factors that enhance the quality of maternity care versus (restricted) provider choice. Methods A discrete choice experiment was conducted amongst 611 pregnant women living in the Netherlands using an online questionnaire. The data were analysed with Latent Class Analyses. The outcome measure consisted of stated preferences in the discrete choice experiment. Included factors were: information exchange by care providers through electronic medical records, information provided by midwife, information provided by friends, freedom to choose maternity care provider and travel distance. Results Four different preference structures were found. In two of those structures, respondents found aspects of the maternity care related to quality of care more important than being able to choose a provider (provider choice). In the two other preference structures, respondents found provider choice more important than aspects related to quality of maternity care. Conclusions In a country with presumed high-quality maternity care like the Netherlands, about half of pregnant women prefer being able to choose their maternity care provider over organisational factors that might imply better quality of care. A comparable amount of women find quality-related aspects most important when choosing a maternity care provider and are willing to accept limitations in their choice of provider. These insights are relevant for policy makers in order to be able to design a bundled payment model which justify the preferences of all pregnant women

Discrete choice experiment versus swing-weighting:A head-to-head comparison of diabetic patient preferences for glucose-monitoring devices

Introduction Limited evidence exists for how patient preference elicitation methods compare directly. This study compares a discrete choice experiment (DCE) and swing-weighting (SW) by eliciting preferences for glucose-monitoring devices in a population of diabetes patients. Methods A sample of Dutch adults with type 1 or 2 diabetes (n = 459) completed an online survey assessing their preferences for glucose-monitoring devices, consisting of both a DCE and a SW exercise. Half the sample completed the DCE first; the other half completed the SW first. For the DCE, the relative importance of the attributes of the devices was determined using a mixed-logit model. For the SW, the relative importance of the attributes was based on ranks and points allocated to the ‘swing’ from the worst to the best level of the attribute. The preference outcomes and self-reported response burden were directly compared between the two methods. Results Participants reported they perceived the DCE to be easier to understand and answer compared to the SW. Both methods revealed that cost and precision of the device were the most important attributes. However, the DCE had a 14.9-fold difference between the most and least important attribute, while the SW had a 1.4-fold difference. The weights derived from the SW were almost evenly distributed between all attributes. Conclusions The DCE was better received by participants, and generated larger weight differences between each attribute level, making it the more informative method in our case study. This method comparison provides further evidence of the degree of method suitability and trustworthiness.</p

Patient Perspectives on the Value of Patient Preference Information in Regulatory Decision Making

Background: There is increasing interest in involving patient preferences for benefits and risks in regulatory decision making. Therefore, it is essential to identify patient perspectives regarding the value of patient preference information (PPI). Objectives: The aim of this study was to explore how patients with rheumatoid arthritis (RA) value the use of PPI in regulatory decision making regarding medical products. Methods: Regulators and patients with RA were interviewed to gather initial insights into opinions on the use of PPI in regulatory decisions regarding medical products. The interviews were used to draft and validate the interview guide for focus groups with patients with RA. Participants were purposively sampled in collaboration with the Swedish Rheumatism Association in Stockholm and Uppsala. Each focus group consisted of three to six patients (18 in total). All interviews were audio-recorded, transcribed verbatim, and analysed using content analysis. Results: According to the participants, PPI could lead to regulators considering patients’ needs, lifestyles and well-being when making decisions. PPI was important in all stages of the medical product lifecycle. Participants reported that, when participating in a preference study, it is important to be well-informed about the use of the study and the development, components, administration, and risks related to the medical products. Conclusions: Patients thought PPI could be valuable to consider in regulatory decisions. It is essential for patients to be well-informed when asked for their preferences. Research on information materials to inform patients in preference studies is needed to increase the value of PPI in regulatory decision making