Exploring the Factors that Drive Clinical Negligence Claims: Stated Preferences of Those Who Have Experienced Unintended Harm.

BACKGROUND: Better understanding of the factors that influence patients to make a financial claim for compensation is required to inform policy decisions. This study aimed to assess the relative importance of factors that influence those who have experienced a patient safety incident (PSI) to make a claim for compensation. METHOD: Participants completed an online discrete choice experiment (DCE) involving 10 single profile tasks where they chose whether or not to file a claim. DCE data were modelled using logistic, mixed logit and latent class regressions; scenario analyses, external validity, and willingness to accept were also conducted. RESULTS: A total of 1029 participants in the United Kingdom responded to the survey. An appropriate apology and a satisfactory investigation reduced the likelihood of claiming. Respondents were more likely to claim if they could hold those responsible accountable, if the process was simple and straightforward, if the compensation amount was higher, if the likelihood of compensation was high or uncertain, if the time to receive a decision was quicker, and if they used the government compensation scheme. Men are more likely to claim for low impact PSIs. DISCUSSION AND CONCLUSIONS: The actions taken by the health service after a PSI, and people's perceptions about the probability of success and the size of potential reward, can influence whether a claim is made. Results show the importance of giving an appropriate apology and conducting a satisfactory investigation. This stresses the importance around how patients are treated after a PSI in influencing the clinical negligence claims that are made.

The impact of adult children living at home on the well-being of Spanish parents: Evidence from panel data.

Despite the prevalence of co-residence of adult children and their parents across Europe, there is only limited empirical evidence on the impact of such living arrangements on well-being. This paper investigates the impact of adult children living in the household on the well-being of Spanish parents aged 50-75. Using three waves of panel data from the Spanish Survey of Household Finances we assess whether the impact on parental well-being differs depending on the age of the child, and whether the effect depends on the gender of the parent. We find that there is a negative impact on parents' well-being of older adult children (aged 30 or over) living in the household, while cohabitation with younger children (aged 18-29) is not found to affect parental well-being. When analysing the impact on mothers and fathers separately we find that the negative effect of older children living in the household is driven by a significant reduction in the well-being of mothers, with no evidence of a corresponding effect on fathers. The negative effect on mothers' well-being seems to be related to co-residence with older sons rather than older daughters.

A Discrete Choice Experiment to Elicit General Population Preferences Around the Factors Influencing the Choice to Make Clinical Negligence Claims.

OBJECTIVES: This article determines public stated preferences around different factors that influence the choice to make clinical negligence claims against a national healthcare system. METHODS: A large online survey was conducted using a discrete choice experiment (DCE) with the UK general population (N = 1013). DCE tasks involved a single profile and participants chose whether to make a claim for compensation (yes/no) after one of 3 randomly allocated patient safety incident (PSI) "scenarios" of different severities (mild, moderate, severe). DCE attributes described the actions of the healthcare system after a PSI and characteristics of the clinical negligence claims process. The data were modeled separately for each scenario (mild, moderate, severe) using logistic regression. Marginal effects and the probability of making a claim in a baseline case were estimated. RESULTS: Probability of choosing to claim was reduced by receipt of an apology, investigation and prevention of recurrence of the PSI, and longer time until claim decision and increased by an easy and straightforward claims process and high chance of compensation and for the mild scenario higher compensation amounts. Marginal effects and baseline case probabilities differed by scenario severity. CONCLUSIONS: The results suggest the actions of the healthcare system after a PSI and characteristics of the claims process have a larger impact on the probability of making a claim for milder PSIs. For more severe PSIs, a larger probability of making a claim was observed, and the choice was less influenced by the actions of the healthcare system after the PSI and characteristics of the claims process.

Valuing quality in mental healthcare: A discrete choice experiment eliciting preferences from mental healthcare service users, mental healthcare professionals and the general population.

High and sustained healthcare quality is important worldwide, though health policy may prioritise the achievement of certain aspects of quality over others. This study determines the relative importance of different aspects of mental healthcare quality to different stakeholders by eliciting preferences in a UK sample using a discrete choice experiment (DCE). DCE attributes were generated using triangulation between policy documents and mental healthcare service user and mental healthcare professional views, whilst ensuring attributes were measurable using available data. Ten attributes were selected: waiting times; ease of access; person-centred care; co-ordinated approach; continuity; communication, capacity and resources; treated with dignity and respect; recovery focus; inappropriate discharge; quality of life (QoL). The DCE was conducted online (December 2018 to February 2019) with mental healthcare service users (n = 331), mental healthcare professionals (n = 510), and members of the general population (n = 1018). Respondents' choices were analysed using conditional logistic regression. Relative preferences for each attribute were generated using the marginal rate of substitution (MRS) with QoL as numeraire. Across all stakeholders, being treated with dignity and respect was of high importance. A coordinated approach was important across all stakeholders, whereas communication had higher relative importance for healthcare professionals and service users and ease of access had higher relative importance for the general population. This implies that policy could be affected by the choice of whose preferences (service users, healthcare professionals or general population) to use, since this impacts on the relative value and implied ranking of different aspects of mental healthcare quality.

Patient Preferences for Longer or More Frequent In-Center Hemodialysis Regimens: A Multicenter Discrete Choice Study.

RATIONALE & OBJECTIVE: Longer and more frequent hemodialysis sessions are associated with both benefits and harms. However, their relative importance to patients and how they influence acceptability for patients have not been quantified. STUDY DESIGN: Discrete-choice experiment in which a scenario followed by 12 treatment choice sets were presented to patients in conjunction with varying information about the clinical impact of the treatments offered. SETTING & PARTICIPANTS: Patients with kidney failure treated with maintenance dialysis for≥1 year in 5 UK kidney centers. PREDICTORS: Length and frequency of hemodialysis sessions and their prior reported associations with survival, quality of life, need for fluid restriction, hospitalization, and vascular access complications. OUTCOME: Selection of longer (4.5 hours) or more frequent (4 sessions per week) hemodialysis regimens versus remaining on 3 sessions per week with session lengths of 4 hours. ANALYTICAL APPROACH: Multinomial mixed effects logistic regression estimating the relative influence of different levels of the predictors on the selection of longer and more frequent dialysis, controlling for patient demographic characteristics. RESULTS: Among 183 prevalent in-center hemodialysis patients (mean age of 63.7 years, mean dialysis vintage of 4.7 years), 38.3% (70 of 183) always chose to remain on regimens of 3 sessions per week with session duration of 4 hours. Depicted associations of increasing survival and quality of life, reduced need for fluid restriction, and avoiding additional access complications were all significantly associated with choosing longer or more frequent treatment regimens. Younger age, fatigue, previous experience of vascular access complications, absence of heart failure, and shorter travel time to dialysis centers were associated with preference for 4 sessions per week. Patients expressed willingness to trade up to 2 years of life to avoid regimens of 4 sessions per week or access complications. After applying estimated treatment benefits and harms from existing literature, the fully adjusted model revealed that 27.1% would choose longer regimens delivered 3 times per week and 34.3% would choose 4 hours 4 times per week. Analogous estimates for younger fatigued patients living near their unit were 23.5% and 62.5%, respectively. LIMITATIONS: Estimates were based on stated preferences rather than observed behaviors. Predicted acceptance of regimens was derived from data on treatment benefits and harms largely sourced from observational studies. CONCLUSIONS: Predicted acceptance of longer and more frequent hemodialysis regimens substantially exceeds their use in current clinical practice. These findings underscore the need for robust data on clinical effectiveness of these more intensive regimens and more extensive consideration of patient choice in the selection of dialysis regimens.

Manipulating the 5 Dimensions of the EuroQol Instrument: The Effects on Self-Reporting Actual Health and Valuing Hypothetical Health States.

Background. The EQ-5D instrument has 5 dimensions. This article reports on the effects of manipulating a) the order in which the 5 dimensions are presented (appearing first v. last), b) splitting of the composite dimensions ("pain or discomfort" and "anxiety or depression"), and c) removing or "bolting off" 1 of the 5 EQ-5D dimensions at a time. The effects were examined in 2 contexts: 1) self-reporting health and 2) health state valuations. Methods. Three different types of discrete choice experiments (DCE) including a duration attribute were designed. An online survey with 12 subtypes, each with 10 DCE tasks, was designed and completed by 2494 members of the UK general public. Results. Of the 3 manipulations in the self-reporting context, only b) splitting anxiety or depression had a significant effect. In the health state valuation context, b) splitting level 5 pain or discomfort (relative to pain) and splitting level 5 anxiety or depression (relative to anxiety) had significant effects as did c) bolting off dimensions. Conclusions. We find that the values given to certain health dimensions are sensitive to the way in which it is described and the other health dimensions presented. Of particular interest is the effect of splitting composite dimensions: a given EQ-5D(-5L) profile may mean different things depending on whether the profile is used to self-report one's health or to value hypothetical states, so that the health state values of EQ-5D(-5L) in population tariffs may not correspond to the states that patients self-report themselves in.

An exploration of the non-iterative time trade-off method to value health states.

Time Trade-Off (TTO) usually relies on "iteration," which is susceptible to bias. Discrete Choice Experiment with duration (or DCETTO ) is free of such bias, but respondents find this cognitively more challenging. This paper explores non-iterative TTO with or without lead time: NI(LT)TTO. In NI(LT)TTO, respondents see a series of independent pairwise choices without iteration (similar to DCETTO ), but one of the two scenarios always involves full health for a shorter duration (similar to TTO). We compare three different "types" of NI(LT)TTO relative to DCETTO . Each type is presented in two "modes": (a) verbally tabulated (as in a DCE) and (b) with visual aids (as in a TTO). The study has 8 survey variants, each with 12 experimental choice tasks and a 13th task with a logically determined answer. Data on the 12 experimental choices from an online survey of 6,618 respondents are modelled, by variant, using conditional logistic regressions. The results indicate that NI(LT)TTO is feasible, but some relatively mild states appear to have implausibly low predicted values, and the range of predicted values is much narrower than in DCETTO . The presentation of NI(LT)TTO tasks needs further improvement.

Allocating external financing for health: a discrete choice experiment of stakeholder preferences.

Most donors of external financing for health use allocation policies to determine which countries are eligible to receive financial support and how much support each should receive. Currently, most of these policies place a great deal of weight on income per capita as a determinant of aid allocation but there is increasing interest in putting more weight on other country characteristics in the design of such policies. It is unclear, however, how much weight should be placed on other country characteristics. Using an online discrete choice experiment designed to elicit preferences over country characteristics to guide decisions about the allocation of external financing for health, we find that stakeholders assign a great deal of importance to health inequalities and the burden of disease but put very little weight on income per capita. We also find considerable variation in preferences across stakeholders, with people from low- and middle-income countries putting more weight on the burden of disease and people from high-income countries putting more weight on health inequalities. These findings suggest that stakeholders put more weight on burden of disease and health inequalities than on income per capita in evaluating which countries should received external financing for health and that that people living in aid recipient may have different preferences than people living in donor countries. Donors may wish to take these differences in preferences in mind if they are reconsidering their aid allocation policies.

Discrete Choice Experiments: A Guide to Model Specification, Estimation and Software.

We provide a user guide on the analysis of data (including best-worst and best-best data) generated from discrete-choice experiments (DCEs), comprising a theoretical review of the main choice models followed by practical advice on estimation and post-estimation. We also provide a review of standard software. In providing this guide, we endeavour to not only provide guidance on choice modelling but to do so in a way that provides a 'way in' for researchers to the practicalities of data analysis. We argue that choice of modelling approach depends on the research questions, study design and constraints in terms of quality/quantity of data and that decisions made in relation to analysis of choice data are often interdependent rather than sequential. Given the core theory and estimation of choice models is common across settings, we expect the theoretical and practical content of this paper to be useful to researchers not only within but also beyond health economics.

Using Discrete Choice Experiments with Duration to Model EQ-5D-5L Health State Preferences.

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.

GPs' implicit prioritization through clinical choices - evidence from three national health services.

We present results from an extensive discrete choice experiment, which was conducted in three countries (Norway, Scotland, and England) with the aim of disclosing stated prescription behaviour in different decision making contexts and across different cost containment cultures. We show that GPs in all countries respond to information about societal costs, benefits and effectiveness, and that they make trade-offs between them. The UK GPs have higher willingness to accept costs when they can prescribe medicines that are cheaper or more preferred by the patient, while Norwegian GPs tend to have higher willingness to accept costs for attributes regarding effectiveness or the doctors' experience. In general, there is a substantial amount of heterogeneity also within each country. We discuss the results from the DCE in the light of the GPs' two conflicting agency roles and what we know about the incentive structures and cultures in the different countries.

Response Patterns in Health State Valuation Using Endogenous Attribute Attendance and Latent Class Analysis.

Not accounting for simplifying decision-making heuristics when modelling data from discrete choice experiments has been shown potentially to lead to biased inferences. This study considers two ways of exploring the presence of attribute non-attendance (that is, respondents considering only a subset of the attributes that define the choice options) in a health state valuation discrete choice experiment. The methods used include the latent class (LC) and endogenous attribute attendance (EAA) models, which both required adjustment to reflect the structure of the quality-adjusted life year (QALY) framework for valuing health outcomes. We find that explicit consideration of attendance patterns substantially improves model fit. The impact of allowing for non-attendance on the estimated QALY weights is dependent on the assumed source of non-attendance. If non-attendance is interpreted as a form of preference heterogeneity, then the inferences from the LC and EAA models are similar to those from standard models, while if respondents ignore attributes to simplify the choice task, the QALY weights differ from those using the standard approach. Because the cause of non-attendance is unknown in the absence of additional data, a policymaker may use the range of weights implied by the two approaches to conduct a sensitivity analysis.

Accounting for Attribute-Level Non-Attendance in a Health Choice Experiment: Does it Matter?

An extensive literature has established that it is common for respondents to ignore attributes of the alternatives within choice experiments. In most of the studies on attribute non-attendance, it is assumed that respondents consciously (or unconsciously) ignore one or more attributes of the alternatives, regardless of their levels. In this paper, we present a new line of enquiry and approach for modelling non-attendance in the context of investigating preferences for health service innovations. This approach recognises that non-attendance may not just be associated with attributes but may also apply to the attribute's levels. Our results show that respondents process each level of an attribute differently: while attending to the attribute, they ignore a subset of the attribute's levels. In such cases, the usual approach of assuming that respondents either attend to the attribute or not, irrespective of its levels, is erroneous and could lead to misguided policy recommendations. Our results indicate that allowing for attribute-level non-attendance leads to substantial improvements in the model fit and has an impact on estimated marginal willingness to pay and choice predictions.

Testing a discrete choice experiment including duration to value health states for large descriptive systems: addressing design and sampling issues.

There is interest in the use of discrete choice experiments that include a duration attribute (DCETTO) to generate health utility values, but questions remain on its feasibility in large health state descriptive systems. This study examines the stability of DCETTO to estimate health utility values from the five-level EQ-5D, an instrument with depicts 3125 different health states. Between January and March 2011, we administered 120 DCETTO tasks based on the five-level EQ-5D to a total of 1799 respondents in the UK (each completed 15 DCETTO tasks on-line). We compared models across different sample sizes and different total numbers of observations. We found the DCETTO coefficients were generally consistent, with high agreement between individual ordinal preferences and aggregate cardinal values. Keeping the DCE design and the total number of observations fixed, subsamples consisting of 10 tasks per respondent with an intermediate sized sample, and 15 tasks with a smaller sample provide similar results in comparison to the whole sample model. In conclusion, we find that the DCETTO is a feasible method for developing values for larger descriptive systems such as EQ-5D-5L, and find evidence supporting important design features for future valuation studies that use the DCETTO.

Preparatory study for the revaluation of the EQ-5D tariff: methodology report.

BACKGROUND: EQ-5D is a widely used generic measure of health with a 'tariff', or preference weights, obtained from the general population, using time trade-off (TTO). PRET (Preparatory study for the Re-valuation of the EQ-5D Tariff project) contributes towards the methodology for its revaluation. METHODS: Stage 1 examined key assumptions typically involved in health-state valuations through a series of binary choice exercises, namely that health-state preferences are independent of (1) duration of the state; (2) whose health it is (i.e. perspective); (3) length of 'lead time' (a mechanism to value all states on the same scale, including those who are worse than being dead); (4) when health events take place (time preference); and (5) satisfaction associated with the state. Further topics addressed were (6) exhaustion of lead time in the worst state; (7) health-state valuation using discrete choice experiments (DCEs) with a duration attribute; and (8) binary choice administration of lead time - time trade-off (LT-TTO). Stage 1 consisted of an online survey with 6000 respondents. Stage 2 compared the results above to those of an identical survey conducted in 200 face-to-face computer-assisted personal interviews (CAPIs), covering topics (1) to (7). Stages 3 and 4 examined - in more detail and depth - issues taken from stage 1. Stage 3 consisted of CAPI surveys of a representative UK sample of 300, using examples of TTO, LT-TTO, and DCE with duration, each followed by extensive feedback questions. Stage 4 was a more intensive exercise involving a qualitative analysis of people's thought processes during both binary choice and iterative health-state valuation exercises. Data were collected through 'think-aloud' methods in 30 interviews of a convenience sample. RESULTS: Stage 1 found that health-state values are not independent of (1) duration of the state but there is no clear pattern; (2) whose health it is; (3) the duration of 'lead time' but there was no clear pattern; (4) when health events take place; or (5) satisfaction associated with the state. Furthermore, (6) exhaustion of lead time in the worst state was subject to substantial framing effects; (7) the five-level version of the EQ-5D (EQ-5D-5L) can be valued using DCE with duration as an attribute; and (8) binary choice LT-TTO can be administered in an online environment. Stage 2 found that although online surveys and CAPI surveys resulted in different compositions of respondents, at the aggregate, their responses to the experimental questions covering (1) to (7) above were not statistically significantly different from each other. Stages 3 and 4 found that TTO and LT-TTO were easier than DCE with duration; respondents did not necessarily trade across all attributes of EQ-5D; some respondents found it difficult to distinguish between the two worst levels of EQ-5D-5L, and some respondents may be thinking about the impact of their ill health on their family. CONCLUSIONS: In order for the National Institute for Health and Care Excellence to make the most appropriate decisions, the EQ-5D tariff needs to incorporate the latest understanding of health-state preferences. PRET contributed to the knowledge base on the conduct of health-state valuation studies. FUNDING: The Medical Research Council (MRC)-National Institute for Health Research (NIHR) Methodology Research Programme funded the PRET project (MRC ref. G0901500), and the EuroQol Group funded the PRET-AS project (Preparatory study for the Re-valuation of the EQ-5D Tariff project - Additional Sample) as an extension to the PRET project with formal agreement from the MRC.

When you can't have the cake and eat it too: a study of medical doctors' priorities in complex choice situations.

Available literature provides little insight into medical doctors' prescription choices when they are required to make complex trade-offs between different concerns such as treatment effect, costs, and patient preferences simultaneously. This study investigates this issue. It is based on a Discrete Choice Experiment (DCE) conducted with 571 Norwegian doctors, where the DCE captures preferences for medications described along five dimensions important for both clinical decision-making and prioritisation in the health sector. Although effectiveness is the most important determinant of choice in our study, doctors also put considerable weight on patients' preferences and on avoiding high total costs. The probability of choosing a particular medication increases when doctors have a positive experience with the medication. GPs value high clinical effectiveness less than hospital consultants do. They are also less concerned with patient preferences. For both groups of doctors it turns out that they are willing to make difficult trade-offs between attributes they are often assumed not to be willing to compromise on, like effectiveness or patient preferences, and cost measures - given that they have proper information about these attributes.

Measuring and testing for gender discrimination in physician pay: English family doctors.

In 2008 the income of female GPs was 70%, and their wages (income per hour) were 89%, of those of male GPs. We estimate Oaxaca decompositions using OLS models of wages and 2SLS models of income and propose a set of new direct tests for within workplace gender discrimination. The direct tests are based on a comparison of the differences in income of female and male GPs in practices with varying proportions of female GPs and with female or male senior partners. These tests provide only weak evidence for discrimination. We also propose a set of indirect tests for discrimination, including a comparison of a GP's actual income with the income they report as an acceptable reward for their job. The indirect tests provide no evidence for gender discrimination within practices.

Determinants of general practitioners' wages in England.

We analyse the determinants of annual net income and wages (net income/hours) of general practitioners (GPs) using data for 2271 GPs in England recorded during Autumn 2008. The average GP had an annual net income of £97,500 and worked 43 h per week. The mean wage was £51 per h. Net income and wages depended on gender, experience, list size, partnership size, whether or not the GP worked in a dispensing practice, whether they were salaried of self-employed, whether they worked in a practice with a nationally or locally negotiated contract, and the characteristics of the local population (proportion from ethnic minorities, rurality, and income deprivation). The findings have implications for pay discrimination by GP gender and ethnicity, GP preferences for partnership size, incentives for competition for patients, and compensating differentials for local population characteristics. They also shed light on the attractiveness to GPs in England of locally negotiated (personal medical services) versus nationally negotiated (general medical services) contracts.

What patients want from primary care consultations: a discrete choice experiment to identify patients' priorities.

PURPOSE: The consultation is fundamental to the delivery of primary care, but different ways of organizing consultations may lead to different patient experiences in terms of access, continuity, technical quality of care, and communication. Patients' priorities for these different issues need to be understood, but the optimal methods for assessing priorities are unclear. This study used a discrete choice experiment to assess patients' priorities. METHODS: We surveyed patients from 6 family practices in England. The patients chose between primary care consultations differing in attributes such as ease of access (wait for an appointment), choice (flexibility of appointment times), continuity (physician's knowledge of the patient), technical quality (thoroughness of physical examination), and multiple aspects of patient-centered care (interest in patient's ideas, inquiry about patient's social and emotional well-being, and involvement of patient in decision making). We used probit models to assess the relative priority patients placed on different attributes and to estimate how much they were willing to pay for them. RESULTS: Analyses were based on responses from 1,193 patients (a 53% response rate). Overall, patients were willing to pay the most for a thorough physical examination ($40.87). The next most valued attributes of care were seeing a physician who knew them well ($12.18), seeing a physician with a friendly manner ($8.50), having a reduction in waiting time of 1 day ($7.22), and having flexibility of appointment times ($6.71). Patients placed similar value on the different aspects of patient-centered care ($12.06-$14.82). Responses were influenced by the scenario in which the decision was made (minor physical problem vs urgent physical problem vs ambiguous physical or psychological problem) and by patients' demographic characteristics. CONCLUSIONS: Although patient-centered care is important to patients, they may place higher priority on the technical quality of care and continuity of care. Discrete choice experiments may be a useful method for assessing patients' priorities in health care.

Modelling heterogeneity in patients' preferences for the attributes of a general practitioner appointment.

This paper examines the distribution of preferences among respondents to a discrete choice experiment on the choice of general practitioner appointments. In addition to standard logit, mixed and latent class logit models are used to analyse the data from the choice experiment. It is found that there is significant preference heterogeneity for all the attributes in the experiment and that both the mixed and latent class models lead to significant improvements in fit compared to the standard logit model. Moreover, the distribution of preferences implied by the preferred mixed and latent class models is similar for many attributes.