Data analysis
REGRESSION
Demographics and case-mix variables were summarized using descriptive statistics. We assessed the quality of responses by evaluating the internal validity of the data and looking for respondents who always chose the alternative profile with the best level of one attribute in all 4 choice sets because preferences that are dominated by a single attribute can bias model estimation.DCE data were analyzed in IBM SPSS Statistics (v.26) by conditional logit regression using the COXREG procedure. The primary choice for this model assumed intervention trial patients shared many baseline characteristics since they all had to meet pre-defined inclusion criteria, and they had experienced the same standardized patient care collaborative intervention, thereby reducing the risk of preference heterogeneity and variance across choice tasks [Dummy variables were used to analyze categorical attributes with reference levels identified in Trade-offs between attributes can be demonstrated by using utility scores (V), calculated by using the following equation:
The model fit was assessed by log-likelihood and the chi-square value for the difference between the full and null models.We calculated the relative importance of each attribute which is the ratio of each attribute’s utility range (difference between the highest and lowest utility value) to the sum of the utility range for all attributes.We used the ratio of the coefficient for the attribute of interest (βCIs of marginal WTA for each attribute level were estimated using the parametric bootstrap method with 1,000 replications, as suggested by Krinsky and Robb and quoted by Hole [We calculated the aggregate WTA annual cost to the NHS for a policy change from the reference case (usual care) to the most preferred scenario in post-estimation welfare analysis using the compensating variation methodology [The welfare change in moving from the reference case (usual care) to the “best” case scenario (ideal intervention) was incorporated into a CBA framework.Baseline and 6-month trial costs are reported elsewhere [Although we estimated preferences from the perspective of both intervention and control patients, mean WTA was compared to estimated annual incremental costs using Net Benefit (WTA—costs) from the perspective of intervention patients. We chose this as it could be argued that the relevant WTP (or WTA) should come from the individuals who were part of the intervention group because the control group may lack a firm understanding of the collaborative care model [