Applied Health Economics and Health Policy最新文献

Background

Midwives are essential in achieving universal health coverage targets and the health targets of the Sustainable Development Goals, yet a significant global shortfall exists in the midwifery workforce. Economic evaluations of midwifery are scarce but can assist in supporting evidence-informed decision-making for sustainable and equitable health care for women and girls.

Objectives

This review aimed to systematically identify, map and report on available literature regarding economic evaluations conducted on midwifery service provision and the midwifery workforce in all settings.

Methods

A scoping review was conducted following the Joanna Briggs Institute methodology. A comprehensive search strategy was developed and run in six health databases. Peer-reviewed studies and unpublished research theses conducting economic evaluations on midwifery service provision or midwifery workforce strategies were included. Sources were limited to English-language literature published in the past 20 years. Identified sources were screened and reviewed, and data from included sources were extracted, reviewed, mapped and synthesised to report findings. Quality appraisal was conducted on all included sources using the Joanna Briggs Institute Critical Appraisal Checklist for Economic Evaluations.

Results

A total of 32 studies were included in the review. Most were from high-income countries (26/32), and very few were from low- and middle-income countries (6/32). The quality of included studies varied greatly. Under half of the studies conducted full economic evaluations (15/32), and the remainder were partial economic evaluations (17/32). Most studies evaluated midwifery service provision (29/32) through either midwife-led models of care (15/29) or by place of birth (13/29), mostly for low-risk women (23/29) from the perspective of healthcare funders. Evaluation of midwifery education programs was less common, and these were all conducted in low- and middle-income countries (3/32). Most studies concluded that midwifery service provision was cost-saving, cost-effective or cost-beneficial.

Conclusions

Our review identified a significant gap in economic evaluation of midwifery from low- and middle-income countries. However, there is ongoing need for robust, quality economic evaluations on midwifery service provision and workforce strategies in all global regions. Such studies would further support health policymakers and governments to make evidence-informed decisions to address midwifery workforce shortages and provision of evidence-based and respectful care that meets the healthcare needs of women and girls.

Background and Objective

The utility of genome-wide sequencing is often quantified in terms of its diagnostic yield. Although obtaining a diagnosis is a fundamental aspect of value, service users also value broader clinical, informational, process and psychological factors in the provision of genomic testing. This study aims to value genome-wide sequencing from the user perspective in Scotland.

Methods

A survey was developed and administered to 1014 patients and families with experience of genome-wide sequencing to diagnose a rare condition in Scotland. Participants’ willingness to pay for genomic testing was elicited using a contingent valuation payment card. The survey included two genomic-related patient-reported outcome measures: (i) the Personal Utility Scale (PrU) to generate scores for the personal utility of genome-wide sequencing; and (ii) a subscale of the Feelings About Genomic Testing Results (FACTOR) questionnaire to measure negative psychological outcomes. Data were also collected on participants’ prior experiences of genomic testing services. A double-hurdle regression model investigated the predictors of patients' willingness to pay for genomic testing.

Results

Of the 1014 invitations sent, 171 contingent valuation questionnaires were returned. Diagnosed participants reported higher personal utility on PrU than undiagnosed participants. However, both groups reported similar negative psychological outcomes on FACTOR. Diagnosed participants were willing to pay £2043 for genome-wide sequencing, compared with £835 for undiagnosed participants. Diagnostic status, waiting time for results and FACTOR scores (negative psychological outcomes) influenced users’ valuations of genome-wide sequencing.

Conclusions

Obtaining a diagnosis is a fundamental component of utility in the provision of genomic testing. However, there is still value to those who do not receive a diagnosis. These results have implications for service delivery, such as providing targeted pre-test and post-test genetic counselling, and investing in efficient genome sequencing pipelines to reduce waiting times. Valuing the user experience of genomic testing aligns with patient-centred approaches to the provision of healthcare.

Background

No systematic country-level comparison has been undertaken between crosswalk- and EQ-VT-derived EQ-5D-5L value sets. Crosswalk values can differ from EQ-VT-based EQ-5D-5L value sets owing to valuation protocols, changes in societal preferences over time, and a change in the label of the highest level on mobility in moving from EQ-5D-3L to EQ-5D-5L. This study aimed to compare the five-level (5L) crosswalk and EQ-VT value sets to explore differences between them at the country level.

Methods

From the countries with both time trade-off (TTO)- or discrete choice experiment (DCE) + TTO-based EQ-5D-3L value sets and EQ-VT-based EQ-5D-5L value sets, 19 pairs of EQ-5D-3L/EQ-5D-5L sets were found. For each of these EQ-5D-3L value sets, 5L crosswalk sets were developed and compared with the corresponding national EQ-5D-5L valuation set using correlation analysis, ranges, values of specific states, Bland–Altman plots, and scatter plots. Three of the countries have EQ-5D-3L and EQ-5D-5L valuation data for the same set of respondents. These three cases were analyzed separately, as they provide a “true” test of the differences between the two value sets.

Results

Spearman correlation between the crosswalk and valuation sets ranged from 0.831 to 0.989, being below 0.9 in 11 pairs of value sets. The difference in the percentage of negative values ranged from +22.5 to −18.8%, and the difference in the ranges within each pair of value sets ranged from +42.7 to −18.4%. The average mean absolute difference of values (crosswalk versus EQ-VT) was 0.149. This was below 0.1 in only 5 of the 19 EQ-VT/crosswalk set pairs. For the states comprising one level 5 and four level 1s, no country preserved its ranking of importance of the five dimensions in moving from crosswalk to EQ-VT values. Most of the Bland–Altman plots and scatterplots revealed a pattern that placed states with the highest level on mobility as a separate band from other states.

Discussion

All of the criteria showed poor agreement between the crosswalk- and EQ-VT-based value sets. The differences in labels for the most extreme response option for the mobility dimension leads to substantial differences in values between these value sets.

Conclusions

Crosswalk and EQ-VT value sets should not be used interchangeably, except under circumstances where it is not possible or feasible to conduct a direct EQ-5D-5L valuation study.

GaitSmart (Dynamic Metrics Ltd) is a class I CE-marked sensor-based digital technology designed to measure lower limb movement via sensors placed on the body. GaitSmart aims to identify any problems with gait, and provide a personalised rehabilitation programme via the integrated vGym app. The company identified people referred for knee or hip replacement and people at risk of falling as potentially being able to benefit from GaitSmart. The clinical evidence identified was limited in its applicability to the scope of the assessment, and there was large variability in the comparators used in these studies and in the current care pathways, especially for people at risk of falls. There is some limited evidence that patients like the report generated by the technology and found it helpful in understanding their condition. Clinical experts thought GaitSmart had the potential to improve outcomes for patients and could be used in the community setting by a range of healthcare professionals. Economic modelling over a 1-year time horizon from a UK National Health Service (NHS) perspective for the falls model and a 17-week horizon for the rehabilitation model indicate that GaitSmart is cost saving; however, this is dependent on the model of standard care. Where GaitSmart is delivered by trained healthcare assistants, it would lead to a reduction in staff time costs compared to most alternative standard care options. Uncertainty is greater in the falls model given the high variability in standard care. In April 2024, the National Institute for Health and Care Excellence recommended that GaitSmart can be used to treat gait and mobility issues in adults at risk of falls, while more evidence is gathered. For adults having hip or knee replacements, access to GaitSmart should be via the company, research or non-core NHS funding, with appropriate management of any risks.

Objective

As societies emerge from the COVID-19 pandemic, governments are increasingly moving away from a focus on economic growth at any cost towards the principles of a wellbeing economy, focused on achieving a more equitable distribution of wealth and wellbeing. This study aimed to assess the relative importance to the Australian general public of the key principles of a wellbeing economy and to investigate heterogeneity in preferences between demographic subgroups.

Methods

An online survey was developed and delivered to a general public sample of 2042 Australian adults (aged 18 years and above). Respondents were invited to rank the key principles of a wellbeing economy (dignity, nature and climate, social connection, fairness and participation) plus two additional traditional economic indicators of societal success (‘economic growth’ and ‘economic prosperity’) in order of their relative importance for informing future policy directions. Data analysis was conducted using simple summative scoring, which involved the use of a point system allocated to rankings as a dependent variable. In addition, a rank-ordered logit model was used to explore preferences for the entire sample and subgroups defined by key socio-demographic characteristics.

Results

‘Dignity’ (people have enough to live in comfort, safety and happiness) and ‘fairness’ (equal opportunity for all Australians and the gap between richest and poorest greatly reduced) were ranked as the most important priorities for the total sample and for key socio-demographic subgroups differentiated by age, level of education and level of socio-economic advantage. Traditional economic indicators of societal success including ‘economic prosperity’ and ‘economic growth’ were considered important but generally ranked below the principles of ‘dignity’ and ‘fairness’.

Conclusions

The findings indicate that government movements away from traditional economic indicators and towards new broader wellbeing economy measures of societal success are likely to be supported by the general public.

Objective

To compare the performance of matching-adjusted indirect comparison (MAIC) and naïve indirect comparison (NIC) under a wide range of data scenarios on survival outcome.

Methods

A simulation study included 729 (3⁶) single-arm trial data scenarios, which were created by performing a three-level full factorial arrangement of six situational variables, including individual patient data (IPD) sample size, aggregate data (AgD) sample size, covariate strength, covariate correlation, covariate overlap, and relative treatment effect. In each scenario, 1000 repetitions of simulated datasets were generated using the Monte Carlo approach. MAIC and NIC methods were used to estimate the relative treatment effect of each simulated dataset. The performance was evaluated in terms of bias, empirical standard error (ESE), mean squared error (MSE), and confidence interval coverage, respectively.

Results

MAIC yielded relatively unbiased estimates of relative treatment effect compared with NIC in most scenarios, with better coverage and MSE but higher ESE. None of the situational variables had a significant impact on the bias and coverage of MAIC. However, increasing IPD sample size and covariate overlap significantly reduced the ESE and MSE of MAIC. In scenarios with low covariate overlap and high covariate strength, the bias of MAIC was larger and even greater than that of NIC.

Conclusions

The performance of MAIC consistently demonstrates advantage over NIC across various scenarios. MAIC often provides more unbiased estimates and achieves confidence interval coverage close to nominal values compared with NIC. While MAIC may exhibit higher ESE in specific scenarios, this additional uncertainty can offer a more accurate reflection of variability, enhancing the robustness of the results. Researchers should thoroughly comprehend the influencing factors and interactions affecting the performance of these methods and judiciously apply research findings.

Background

Sequential next-generation sequencing (NGS) testing has demonstrated cost-effectiveness in guiding targeted therapy with tyrosine kinase inhibitors (TKIs) for advanced non-small cell lung cancer (aNSCLC) in developed countries. However, its cost-effectiveness in developing countries remains uncertain.

Objective

The aim was to conduct a cost-utility analysis comparing sequential NGS testing with the current approach of single epidermal growth factor receptor (EGFR) testing combined with first-line targeted therapy, as implemented under Thailand's Universal Health Coverage scheme for aNSCLC.

Method

Hybrid decision tree and Markov models were developed to estimate the lifetime costs and quality-adjusted life years (QALYs) associated with each strategy. The models simulate cohorts of aNSCLC patients who receive platinum-based chemotherapy or TKIs based on identified gene alterations. Patients enter the model at 60 years of age. The incremental cost-effectiveness ratio (ICER) was computed from a societal perspective. The analysis employed a lifetime horizon and discounted costs and outcomes at a rate of 3%. Furthermore, uncertainty and scenario analyses were conducted.

Findings

A sequential NGS testing strategy could identify an additional 19% of patients with biomarker-positive findings who subsequently received biomarker-driven targeted therapy compared to a single EGFR testing strategy. The number needed to screen to identify a single gene mutation and administer first-line TKI was six for the sequential NGS testing strategy. Compared to the single EGFR testing, the ICER of the sequential NGS testing strategy was 1,851,150 THB/QALY (US$51,335). At a willingness-to-pay threshold of 160,000 THB/QALY (US$4437), the single EGFR testing strategy demonstrated 100% cost-effectiveness. In contrast, the sequential NGS testing was not deemed cost-effective. The sensitivity of the ICER was influenced by the overall survival rates associated with anaplastic lymphoma kinase (ALK) inhibitors and platinum-based chemotherapy.

Interpretation

Sequential NGS testing identified a greater number of patients with aNSCLC eligible for targeted therapies, resulting in improved survival rates and enhanced QALYs compared to single EGFR testing. However, in the context of Thailand, sequential NGS testing was not cost-effective. The single EGFR testing strategy emerged as the most cost-effective option for guiding first-line targeted therapy.

Background

The quality-adjusted life year (QALY) is widely used to measure health outcome that combines the length of life and health-related quality of life (HRQoL). To be a reliable QALY measure, HRQoL measurements with a preference-based scoring algorithm need to be converted into health utilities on a scale from zero (dead) to one (perfect health). However, preference-based health utility data are often not available. We address this gap by developing a predictive model for health utilities.

Objectives

To develop a predictive model for health utilities using available demographic and morbidity variables in a health administrative dataset for non-institutionalised populations in Ontario, Canada.

Methods

The data were obtained from the 2009 to 2010 Canadian Community Health Survey containing Health Utilities Index Mark3 (HUI3), a generic multi-attribute preference-based health utility instrument linked with Ontario health administrative (OHA) data that were collected for administrative or billing purposes for patient encounters with the health care system. We employed four regression models (linear, Tobit, single-part beta mixture, and two-part beta mixture) and a calibration technique to identify the best-fit regression model.

Results

Our findings indicate that the two-part beta mixture model is the best-fit for predicting health utilities in the OHA data. The proposed predictive model reflects the original distribution of HUI3 in the population.

Conclusion

Our proposed predictive model generates reasonably accurate health utility predictions from OHA data. Our model-based prediction approach is a useful strategy for real-world applications, particularly when preference-based utility data are unavailable.

Economic evaluations of obesity interventions are critical to informing policymakers and clinical practitioners about best-value prevention and treatment interventions. However, existing studies often fail to measure appropriate outcomes over sufficient time periods and to adequately address the complexity of data, environments and outcomes. An international, multidisciplinary workshop in Ireland (May 2023) addressed these issues through scientific presentations on obesity modelling, group discussions and interactive small-group exercises. Nineteen presenters and participants co-created a list of research needs, priorities and strategies for the long-term study of obesity and its complications. To support availability of relevant outcome and cost data for health economic analyses, participants highlighted a need to define standards for data collection, data sharing, modelling, and integrating a systems perspective. For example, regarding data collection, careful consideration must be given to selecting valid and relevant health-related outcomes for determining future health risk. Although these issues have been previously highlighted, they remain critical barriers to comprehensive economic obesity studies. To identify best-value obesity interventions, researchers should prioritise strategies to overcome these barriers. This includes early engagement with multidisciplinary stakeholders to integrate diverse perspectives. Developing infrastructure to support international collaborations between researchers, policymakers and patient representatives was also recommended. Additionally, establishing best-practice guidelines could help researchers navigate the complexities of obesity data, environments and outcomes, particularly in data-scarce research environments. The creation of a core outcomes set for obesity would standardise measures for economic evaluations, thereby facilitating more robust cross-country comparisons of intervention effects and improving the evidence base and overall quality of future obesity research.