Valuing benefits to inform a clinical trial in pharmacy : do differences in utility measures at baseline affect the effectiveness of the intervention?

Psychometric performance of EQ-5D-5L and SF-6Dv2 in patients with lymphoma in China

AIM

To assess and compare the measurement properties of EQ-5D-5L and SF-6Dv2 among lymphoma patients in China.

METHODS

A face-to-face survey of Chinese lymphoma patients was conducted at baseline (all types) and follow-up (diffuse large B-cell). EQ-5D-5L and SF-6Dv2 health utility scores (HUSs) were calculated using the respective Chinese value sets. Ceiling effect was assessed by calculating the percentage of respondents reporting the optimal health state. Convergent validity of EQ-5D-5L and SF-6Dv2 was assessed using the Spearman rank correlation coefficient (r) with QLQ-C30 as a calibration standard. Known-groups validity of the two HUSs was evaluated by comparing their scores of patients with different conditions; and their sensitivity was further assessed in the known-groups using relative efficiency (RE). Test-retest reliability and responsiveness was tested using ICC and standardized response mean (SRM), respectively.

RESULTS

Altogether 200 patients were enrolled at baseline and 78 were followed up. No ceiling effect was found for SF-6Dv2 compared to 24.5% for EQ-5D-5L. Correlation between the two HUSs and with QLQ-C30 score was strong (r > 0.5). Each dimension of EQ-5D-5L and SF-6Dv2 had moderate or greater correlations with similar dimensions of QLQ-C30 (r > 0.35). Both EQ-5D-5L and SF-6Dv2 could only a minority known-groups, and the latter may have better sensitivity. EQ-5D-5L had better test-retest reliability (ICC = 0.939); while both of them were responsive to patients with worsened and improved clinical status.

CONCLUSIONS

EQ-5D-5L and SF-6Dv2 were found to have good convergent validity and responsiveness, while EQ-5D-5L had better test-retest reliability and higher ceiling effect. Not enough evidence indicates which of the two measures has better known-group validity and sensitivity.

Conceptualising 'Benefits Beyond Health' in the Context of the Quality-Adjusted Life-Year: A Critical Interpretive Synthesis

There is growing interest in extending the evaluative space of the quality-adjusted life-year framework beyond health. Using a critical interpretive synthesis approach, the objective was to review peer-reviewed literature that has discussed non-health outcomes within the context of quality-adjusted life-years and synthesise information into a thematic framework. Papers were identified through searches conducted in Web of Science, using forward citation searching. A critical interpretive synthesis allows for the development of interpretations (synthetic constructs) that go beyond those offered in the original sources. The final output of a critical interpretive synthesis is the synthesising argument, which integrates evidence from across studies into a coherent thematic framework. A concept map was developed to show the relationships between different types of non-health benefits. The critical interpretive synthesis was based on 99 papers. The thematic framework was constructed around four themes: (1) benefits affecting well-being (subjective well-being, psychological well-being, capability and empowerment); (2) benefits derived from the process of healthcare delivery; (3) benefits beyond the recipient of care (spillover effects, externalities, option value and distributional benefits); and (4) benefits beyond the healthcare sector. There is a wealth of research concerning non-health benefits and the evaluative space of the quality-adjusted life-year. Further dialogue and debate are necessary to address conceptual and normative challenges, to explore the societal willingness to sacrifice health for benefits beyond health and to consider the equity implications of different courses of action.

Socio-demographic, clinical characteristics and utilization of mental health care services associated with SF-6D utility scores in patients with mental disorders: contributions of the quantile regression

PURPOSE

Health-related quality of life (HRQoL) is a widely used concept in the assessment of health care. Some generic HRQoL instruments, based on specific algorithms, can generate utility scores which reflect the preferences of the general population for the different health states described by the instrument. This study aimed to investigate the relationships between utility scores and potentially associated factors in patients with mental disorders followed in inpatient and/or outpatient care settings using two statistical methods.

METHODS

Patients were recruited in four psychiatric sectors in France. Patient responses to the SF-36 generic HRQoL instrument were used to calculate SF-6D utility scores. The relationships between utility scores and patient socio-demographic, clinical characteristics, and mental health care utilization, considered as potentially associated factors, were studied using OLS and quantile regressions.

RESULTS

One hundred and seventy six patients were included. Women, severely ill patients and those hospitalized full-time tended to report lower utility scores, whereas psychotic disorders (as opposed to mood disorders) and part-time care were associated with higher scores. The quantile regression highlighted that the size of the associations between the utility scores and some patient characteristics varied along with the utility score distribution, and provided more accurate estimated values than OLS regression.

CONCLUSIONS

The quantile regression may constitute a relevant complement for the analysis of factors associated with utility scores. For policy decision-making, the association of full-time hospitalization with lower utility scores while part-time care was associated with higher scores supports the further development of alternatives to full-time hospitalizations.

Applying micro-costing methods to estimate the costs of pharmacy interventions: an illustration using multi-professional clinical medication reviews in care homes for older people

OBJECTIVES

Economic methods are underutilised within pharmacy research resulting in a lack of quality evidence to support funding decisions for pharmacy interventions. The aim of this study is to illustrate the methods of micro-costing within the pharmacy context in order to raise awareness and use of this approach in pharmacy research.

METHODS

Micro-costing methods are particularly useful where a new service or intervention is being evaluated and for which no previous estimates of the costs of providing the service exist. This paper describes the rationale for undertaking a micro-costing study before detailing and illustrating the process involved. The illustration relates to a recently completed trial of multi-professional medication reviews as an intervention provided in care homes. All costs are presented in UK£2012.

KEY FINDINGS

In general, costing methods involve three broad steps (identification, measurement and valuation); when using micro-costing, closer attention to detail is required within all three stages of this process. The mean (standard deviation; 95% confidence interval (CI) ) cost per resident of the multi-professional medication review intervention was £104.80 (50.91; 98.72 to 109.45), such that the overall cost of providing the intervention to all intervention home residents was £36,221.29 (95% CI, 32 810.81 to 39 631.77).

CONCLUSIONS

This study has demonstrated that micro-costing can be a useful method, not only for estimating the cost of a pharmacy intervention to feed into a pharmacy economic evaluation, but also as a source of information to help inform those designing pharmacy services about the potential time and costs involved in delivering such services.

Using QALYs in telehealth evaluations: a systematic review of methodology and transparency

Background

The quality-adjusted life-year (QALY) is a recognised outcome measure in health economic evaluations. QALY incorporates individual preferences and identifies health gains by combining mortality and morbidity into one single index number. A literature review was conducted to examine and discuss the use of QALYs to measure outcomes in telehealth evaluations.

Methods

Evaluations were identified via a literature search in all relevant databases. Only economic evaluations measuring both costs and QALYs using primary patient level data of two or more alternatives were included.

Results

A total of 17 economic evaluations estimating QALYs were identified. All evaluations used validated generic health related-quality of life (HRQoL) instruments to describe health states. They used accepted methods for transforming the quality scores into utility values. The methodology used varied between the evaluations. The evaluations used four different preference measures (EQ-5D, SF-6D, QWB and HUI3), and utility scores were elicited from the general population. Most studies reported the methodology used in calculating QALYs. The evaluations were less transparent in reporting utility weights at different time points and variability around utilities and QALYs. Few made adjustments for differences in baseline utilities. The QALYs gained in the reviewed evaluations varied from 0.001 to 0.118 in implying a small but positive effect of telehealth intervention on patient’s health. The evaluations reported mixed cost-effectiveness results.

Conclusion

The use of QALYs in telehealth evaluations has increased over the last few years. Different methodologies and utility measures have been used to calculate QALYs. A more harmonised methodology and utility measure is needed to ensure comparability across telehealth evaluations.

[Valuation of health-related quality of life and utilities in health economics]

Measuring health-related quality of life is an important aspect in economic evaluation of health programmes. The development of utility-based (preference-based) measures is advanced by the discipline of health economics. Different preference measures are applied for valuing health states to produce a weighted health state index. Those preference weights should be derived from a general population sample in case of resource allocation on a collective level (as in current valuation studies of the EuroQol group).