Comparison of the SF-6D and the EQ-5D in patients with coronary heart disease

BACKGROUND: The SF-6D was derived from the SF-36. A single summary score is obtained allegedly preserving the descriptive richness and sensitivity to change of the SF-36 into utility measurement. We compared the SF-6D and EQ-5D on domain content, scoring distribution, pre-treatment and change scores. METHODS: The SF-6D and the EQ-5D were completed prior to intervention and 1, 3, 6 and 12 months post-intervention in a study enrolling 561 patients with symptomatic coronary stenosis. Patients were randomized to off-pump coronary artery bypass surgery (CABG), standard on-pump CABG, or percutaneous transluminal coronary angioplasty (PTCA). Baseline and change over time scores were compared using parametric and non-parametric tests. RESULTS: The relative contribution of similar domains measuring daily functioning to the utility scores differed substantially. SF-6D focused more on social functioning, while EQ-5D gave more weight to physical functioning. Pain and mental health had similar contributions. The scoring range of the EQ-5D was twice the range of the SF-6D. Before treatment, EQ-5D and SF-6D mean scores appeared similar (0.64 versus 0.63, p = 0.09). Median scores, however, differed substantially (0.69 versus 0.60), a difference exceeding the minimal important difference of both instruments. Agreement was low, with an intra-class correlation of 0.45. Finally, we found large differences in measuring change over time. The SF-6D recorded greater intra-subject change in the PTCA-group. Only the EQ-5D recorded significant change in the CABG-groups. In the latter groups changes in SF-6D domains cancelled each other out. CONCLUSION: Although both instruments appear to measure similar constructs, the EQ-5D and SF-6D are quite different. The low agreement and the differences in median values, scoring range and sensitivity to change after intervention show that the EQ-5D and SF-6D yield incomparable scores in patients with coronary heart disease

Using Multicriteria Decision Analysis to Support Research Priority Setting in Biomedical Translational Research Projects

Translational research is conducted to achieve a predefined set of economic or societal goals. As a result, investment decisions on where available resources have the highest potential in achieving these goals have to be made. In this paper, we first describe how multicriteria decision analysis can assist in defining the decision context and in ensuring that all relevant aspects of the decision problem are incorporated in the decision making process. We then present the results of a case study to support priority setting in a translational research consortium aimed at reducing the burden of disease of type 2 diabetes. During problem structuring, we identified four research alternatives (primary, secondary, tertiary microvascular, and tertiary macrovascular prevention) and a set of six decision criteria. Scoring of these alternatives against the criteria was done using a combination of expert judgement and previously published data. Lastly, decision analysis was performed using stochastic multicriteria acceptability analysis, which allows for the combined use of numerical and ordinal data. We found that the development of novel techniques applied in secondary prevention would be a poor investment of research funds. The ranking of the remaining alternatives was however strongly dependent on the decision maker’s preferences for certain criteria

Identifying Frequent Health Care Users and Care Consumption Patterns:Process Mining of Emergency Medical Services Data

Background: Tracing frequent users of health care services is highly relevant to policymakers and clinicians, enabling them to avoid wasting scarce resources. Data collection on frequent users from all possible health care providers may be cumbersome due to patient privacy, competition, incompatible information systems, and the efforts involved. Objective: This study explored the use of a single key source, emergency medical services (EMS) records, to trace and reveal frequent users’ health care consumption patterns. Methods: A retrospective study was performed analyzing EMS calls from the province of Drenthe in the Netherlands between 2012 and 2017. Process mining was applied to identify the structure of patient routings (ie, their consecutive visits to hospitals, nursing homes, and EMS). Routings are used to identify and quantify frequent users, recognizing frail elderly users as a focal group. The structure of these routes was analyzed at the patient and group levels, aiming to gain insight into regional coordination issues and workload distributions among health care providers. Results: Frail elderly users aged 70 years or more represented over 50% of frequent users, making 4 or more calls per year. Over the period of observation, their annual number and the number of calls increased from 395 to 628 and 2607 to 3615, respectively. Structural analysis based on process mining revealed two categories of frail elderly users: low-complexity patients who need dialysis, radiation therapy, or hyperbaric medicine, involving a few health care providers, and high-complexity patients for whom routings appear chaotic. Conclusions: This efficient approach exploits the role of EMS as the unique regional “ferryman,” while the combined use of EMS data and process mining allows for the effective and efficient tracing of frequent users’ utilization of health care services. The approach informs regional policymakers and clinicians by quantifying and detailing frequent user consumption patterns to support subsequent policy adaptations

Head-to-Head Comparison of EQ-5D-3L and EQ-5D-5L Health Values

The EQ-5D is a widely used preference-based instrument to measure health-related quality of life. Some methodological drawbacks of its three-level version (EQ-5D-3L) prompted development of a new format (EQ-5D-5L). There is no clear evidence that the new format outperforms the standard version.The objective of this study was to make a head-to-head comparison of the EQ-5D-3L and EQ-5D-5L in a discrete choice model setting giving special attention to the consistency and logical ordering of coefficients for the attribute levels and to the differences in health-state values.Using efficient designs, 240 pairs of EQ-5D-3L health states and 240 pairs of EQ-5D-5L health states were generated in a pairwise choice format. The study included 3698 Dutch general population respondents, analyzed their responses using a conditional logit model, and compared the values elicited by EQ-5D-3L and EQ-5D-5L for different health states.No inconsistencies or illogical ordering of level coefficients were observed in either version. The proportion of severe health states with low values was higher in the EQ-5D-5L than in the EQ-5D-3L, and the proportion of mild/moderate states was lower in the EQ-5D-5L than in the EQ-5D-3L. Moreover, differences were observed in the relative weights of the attributes.Overall distribution of health-state values derived from a large representative sample using the same measurement framework for both versions showed differences between the EQ-5D-3L and EQ-5D-5L. However, even small differences in the phrasing (language) of the descriptive system or in the valuation protocol can produce differences in values between these two versions.</p

Letter to the editor, "Validation and clinical value of the MANAGE-PD tool:A clinician-reported tool to identify Parkinson's disease patients inadequately controlled on oral medications"

The MANAGE-PD tool may help general neurologists in deciding whether a patient with advanced Parkinson's disease should be referred for an advanced therapy. Although the development and clinical validation of MANAGE-PD would appear to serve an important need, we urge the reader to be aware of several methodological concerns.</p