Applied Health Economics and Health Policy最新文献

Objective: Anxiety and depression are prevalent in young people. Web-based mental health interventions (W-MHIs) have the potential to reduce anxiety and depression, yet the level of engagement remains low. This study aims to elicit young people's preferences towards W-MHIs and the relative importance of intervention attributes in influencing choice.

Methods: A discrete choice experiment (DCE) was conducted online among young people aged 18-25 years who lived in Australia, self-reported experiences of anxiety and/or depression in the past 12 months and had an intention to use W-MHIs and/or previous experience with W-MHIs for managing anxiety and/or depression. Participants were recruited via social media and Deakin University notice boards. The DCE design comprised six attributes, including out-of-pocket cost, access to trained instructors (e.g., therapists, coaches) to help users stay engaged with the intervention, total time required to complete the intervention, initial screening, quizzes within the W-MHIs to check user's understanding about the intervention content, and communication with other users. The DCE design consisted of three blocks, each with eight unlabelled choice tasks, each with two alternatives. Data were analysed using a mixed logit model.

Results: One hundred ninety-nine participants completed the DCE (mean age: 21.43 ± 2.29 years, 64.32% female). Lower cost, access to instructors, and moderate time required to complete the intervention (5 h) were significant facilitators. The W-MHIs including audio- or video-call access to instructors were 23 percentage points more likely to be chosen than those without and W-MHI with a moderate completion time (5 h) was 18 percentage points more likely to be chosen than one with a shorter time (2 h).

Conclusion: Our results highlight that low-cost W-MHIs with access to trained instructors and moderate completion time could increase uptake. More research is required to confirm these findings and examine whether these preferences vary across different population characteristics.

Introduction: The growth of scientific literature in health economics and policy represents a challenge for researchers conducting literature reviews. This study explores the adoption of a machine learning (ML) tool to enhance title and abstract screening. By retrospectively assessing its performance against the manual screening of a recent scoping review, we aimed to evaluate its reliability and potential for streamlining future reviews.

Methods: ASReview was utilised in 'Simulation Mode' to evaluate the percentage of relevant records found (RRF) during title/abstract screening. A dataset of 10,246 unique records from three databases was considered, with 135 relevant records labelled. Performance was assessed across three scenarios with varying levels of prior knowledge (PK) (i.e., 5, 10, or 15 records), using both sampling and heuristic stopping criteria, with 100 simulations conducted for each scenario.

Results: The ML tool demonstrated strong performance in facilitating the screening process. Using the sampling criterion, median RRF values stabilised at 97% with 25% of the sample screened, saving reviewers approximately 32 working days. The heuristic criterion showed similar median values, but greater variability due to premature conclusions upon reaching the threshold. While higher PK levels improved early-stage performance, the ML tool's accuracy stabilised as screening progressed, even with minimal PK.

Conclusions: This study highlights the potential of ML tools to enhance the efficiency of title and abstract screening in health economics and policy literature reviews. To fully realise this potential, it is essential for regulatory bodies to establish comprehensive guidelines that ensure ML-assisted reviews uphold rigorous evidence quality standards, thereby enhancing their integrity and reliability.

Objectives: To measure socioeconomic-related inequality in perceived unmet needs for financial reasons for mental health care in Spain and to assess socioeconomic-related inequity in access to mental health professionals and psychotropic drugs.

Methods: We used data from the Spanish adult sample of the European Health Interview Survey for 2014 and 2020. Corrected concentration indices were used to measure socioeconomic-related inequalities in unmet needs for financial reasons and inequity in access to mental health care. Social class, based on the occupation of the breadwinner, was used as a proxy of socioeconomic status. A decomposition analysis was performed to determine the variables that explain inequalities and to identify inequity in access.

Results: Unmet need for mental health care for financial reasons significantly concentrate on the worse-off, except for women in 2020. A reduction of inequality is observed along the study period. Socioeconomic disadvantage is associated with lower access to mental health consultations, despite also with higher need. This pro-rich inequity is significant for women in 2014, and for both sexes-although much higher for females-in 2020. In contrast, we found pro-poor inequity in women's access to psychotropic drugs in 2020, suggesting partial substitution of specialized health care with psychotropic drugs prescribed in primary care for the financially worse-off.

Conclusions: Barriers to accessing specialized mental health care should be reduced for those in need, particularly for disadvantaged women. A better access to therapy could also help to reduce their consumption of psychotropic drugs. Addressing access inequities requires different strategies for men and women, as the relevance of their determinants varies by gender.

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.