Implausible states: prevalence of EQ-5D-5L states in the general population and its effect on health state valuation

The EQ-5D is made up of health state dimensions and levels, in which some combinations seem less “plausible” than others. If “implausible” states are used in health state valuation exercises, then respondents may have difficulty imagining them, causing measurement error. There is currently no standard solution: some valuation studies exclude such states, whereas others leave them in. This study aims to address 2 gaps in the literature: 1) to propose an evidence-based set of the least prevalent two-way combinations of EQ-5D-5L dimension levels and 2) to quantify the impact of removing perceived implausible states from valuation designs. For the first aim, we use data from 2 waves of the English General Practitioner Patient Survey (n = 1,639,453). For the second aim, we remodel a secondary data set of a Discrete Choice Experiment (DCE) with duration that valued EQ-5D-5L and compare across models that drop observations involving different health states: 1) implausible states as defined in the literature, 2) the least prevalent states identified in stage 1, and 3) randomly select states, alongside 4) a model that does not drop any observations. The results indicate that two-way combinations previously thought to be implausible actually exist among the general population; there are other combinations that are rarer, and removing implausible states from an experimental design of a DCE with duration leads to value sets with potentially different characteristics depending on the criterion of implausible states. We advise against the routine removal of implausible states from health state valuation studies

Using Discrete Choice Experiment with duration to model EQ-5D-5L health state preferences: Testing experimental design strategies

Background: Discrete choice experiments incorporating duration can be used to derive health state values for EQ-5D-5L. Yet, methodological issues relating to the duration attribute and the optimal way to select health states remain. The aims of this study were to: test increasing the number of duration levels and choice sets where duration varies (aim 1); compare designs with zero and non-zero prior values (aim 2); and investigate a novel, two-stage design to incorporate prior values (aim 3). Methods: Informed by zero and non-zero prior values, two efficient designs were developed, each consisting of 120 EQ-5D-5L health profile pairs with one of six duration levels (aims 1 and 2). Another 120 health state pairs were selected, with one of six duration levels allocated in a second stage based on existing estimated utility of the states (aim 3). An online sample of 2,002 members of the UK general population completed 10 choice sets each. Differences across the regression coefficients from the three designs were assessed. Results: The zero prior value design produced a model with coefficients that were generally logically ordered, but the non-zero prior value design resulted in a set of less ordered coefficients where some differed significantly. The two-stage design resulted in ordered and significant coefficients. The non-zero prior value design may include more “difficult” choice sets, based on the proportions choosing each profile. Conclusions: There is some indication of compromised “respondent efficiency”, suggesting that the use of non-zero prior values will not necessarily result in better overall precision. It is feasible to design discrete choice experiments in two stages by allocating duration values to EQ-5D-5L health state pairs based on estimates from prior studies

Antibiotic prescribing in primary healthcare: Dominant factors and trade-offs in decision-making

Background: This study aims to establish dominant factors influencing general practitioner (GP) decision-making on antibiotic prescribing in the Australian primary healthcare sector. Two research questions were posed: What influences antibiotic prescribing from the perspective of GPs? How do GPs trade-off on factors influencing antibiotic prescribing? Methods: An exploratory sequential mixed methods design was used, comprising semi-structured interviews followed by a discrete choice experiment (DCE). Ten GPs practising in Brisbane and Greater Brisbane, Queensland were interviewed in September/October 2015. Interview data were used to develop the DCE, which was conducted online from July–October 2016. Twenty-three GPs participated in the DCE. Results: Three main themes influencing antibiotic prescribing emerged from the semi-structured interviews: prescribing challenges, delayed antibiotic prescriptions, and patient expectations. From the DCE, “Duration of symptoms” and “Patient expectations” exerted the most influence on antibiotic prescribing. Taken together, these results suggest that key challenges to prudent antibiotic prescribing are: patient expectations, an important barrier which is surmountable; prescribing practices of medical colleagues, cultural memes and professional etiquette; and uncertainty of diagnosis coupled with patient expectations for antibiotics exert prescribing pressure on GPs. Conclusion: Patient expectation for antibiotics is the dominant modifiable factor influencing GP antibiotic prescribing behaviours. Key challenges to prudent antibiotic prescribing can be overcome through upskilling GPs to manage patient expectations efficaciously, and through two new emphases for public health campaigns—consumers have the power to reduce the use of antibiotics and the GP as a wise advocate for the patient

TESTING COMMITMENT COST THEORY IN CHOICE EXPERIMENTS

In choice experiments, it is commonly assumed that individuals make choices in static and certainty decision-making conditions. Real-world choices, however, are usually made in a dynamic setting. Committing a purchase decision under conditions of uncertainty might have a \u201cCommitment Cost\u201d (CC). In this study, we test CC theory using a nonhypothetical choice experiment. Specifically, we test whether choice behavior and willingness to pay estimates differ when individuals have the option to gain present or delayed information or reverse the transaction. Our results suggest that the construction of a dynamic decision context can be relevant in the design of choice experiments