Applied Health Economics and Health Policy最新文献

Background

Depression in adolescents and young adults is common and causes considerable disease burden while hampering their development, leading to adverse consequences in later life. Although treatment is available, young people are a vulnerable group regarding uptake and completion of treatment. To improve this, insight into youth’s preferences for treatment is essential.

Objective

The aim of this study was to investigate patient preferences for depression treatment in a Dutch sample aged 16–24 years using a discrete choice experiment (DCE).

Methods

The study was conducted in The Netherlands between October 2018 and June 2019, and included 236 adolescents and young adults with current depressive symptoms or previous treatment. The DCE included five attributes (treatment type, frequency of appointment, waiting time, effectiveness, evaluation of therapeutic alliance) with corresponding levels. Results were analysed using latent class analysis.

Results

Results show a general preference for individual psychotherapy, treatment with high frequency, high effectiveness, short waiting time and a standard evaluation of the therapeutic alliance (‘click’ with the therapist) early in treatment. Latent class analysis revealed three different patterns of preferences regarding treatment type and willingness to engage in therapy. The first class showed a strong preference for individual therapy. The second class, including relatively older, higher educated and treatment-experienced participants, preferred high frequency treatment and was more open to different forms of therapy. The third class, including lower educated, younger and treatment-naïve adolescents showed reluctance to engage in therapy overall and in group therapy specifically.

Conclusion

In this DCE, three classes could be identified that share similar preferences regarding treatment effectiveness, waiting time and evaluation of the therapeutic alliance, but varied considerably in their preference for treatment type (individual, group, or combined psychotherapy) and their willingness to engage. The results from this study may inform mental health care providers and institutions and help optimize professional care for adolescents and young adults with depressive symptoms, improving engagement in this vulnerable group.

Participatory value evaluation (PVE) has recently been introduced in the field of health as a new method to elicit stated preferences for public policies. PVE is a method in which respondents in a choice experiment are presented with various policy options and their attributes, and are asked to compose their portfolio of preference given a public-resource constraint. This paper aims to illustrate PVE’s potential for informing healthcare decision making and to position it relative to established preference-elicitation methods. We first describe PVE and its theoretical background. Next, by means of a narrative review of the eight existing PVE applications within and outside the health domain, we illustrate the different implementations of the main features of the method. We then compare PVE to several established preference-elicitation methods in terms of the structure and nature of the choice tasks presented to respondents. The portfolio-based choice task in a PVE requires respondents to consider a set of policy alternatives in relation to each other and to make trade-offs subject to one or more constraints, which more closely resembles decision making by policymakers. When using a flexible budget constraint, respondents can trade-off their private income with public expenditures. Relative to other methods, a PVE may be cognitively more demanding and is less efficient; however, it seems a promising complementary method for the preference-based assessment of health policies. Further research into the feasibility and validity of the method is required before researchers and policymakers can fully appreciate the advantages and disadvantages of the PVE as a preference-elicitation method.

Introduction

Consumers may purchase commercial diagnostic tests (CDT) without prior doctor consultation. This paper analyzes three CDT markets—commercial cholesterol tests (CCT), direct-to-consumer genetic health tests (DGT) and total body scans (TBS)—in the context of the universal, collectively financed health care system of the Netherlands.

Methods

An online willingness-to-pay (WTP) questionnaire was sent to a representative sample of 1500 Dutch consumers. Using contingent valuation (CV) methodology, an array of bids for three self-tests were presented to the respondents. The results were extrapolated to the Dutch population and compared to current prices and follow-up medical utilization, allowing analysis from a societal perspective.

Results

Overall, 880 of 1500 respondents completed the questionnaire (response rate 59%). Of the respondents, 26–44% were willing to pay a positive amount for the CDT. Willingness-to-pay was correlated to age and household income, but not to health status or prior experience with these tests. At mean current prices of €29 for CCT, €229 for DGT and €1,650 for TBS, 3.3%, 2.5%, and 1.1%, were willing to purchase a CCT, DGT, and TBS, respectively. All three CDT resulted in net costs to the health system, estimated at €5, €16, and €44 per test, respectively. Reducing volumes by 90,000 CCTs (19%), 19,000 DGTs (5%) and 4,000 TBSs (2.5%) in 2019 would optimize welfare.

Conclusion

Most respondents were unwilling to consume CDT at any price or only if the CDT were provided for free. However, for a small group of consumers, societal costs exceed private benefits. Therefore, CDT regulation could provide small welfare gains.

Background and Objective

Deep brain stimulation (DBS) is an established treatment for Parkinson’s disease (PD) in patients with advanced motor symptoms with an inadequate response to pharmacotherapies. Despite its effectiveness, the cost effectiveness of DBS remains a subject of debate. This systematic review aims to update and synthesize evidence on the cost effectiveness of DBS for PD.

Methods

To identify full economic evaluations that compared the cost effectiveness of DBS with other best medical treatments, a comprehensive search was conducted of the PubMed, Embase, Scopus, and Tufts Cost-Effective Analysis registry databases. The selected papers were systematically reviewed, and the results were summarized. For the quality appraisal, we used the modified economic evaluations bias checklist. The review protocol was a priori registered with PROSPERO, CRD42022345508.

Results

Sixteen identified cost-utility analyses that reported 19 comparisons on the use of DBS for PD were systematically reviewed. The studies were primarily conducted in high-income countries and employed Markov models. The costs considered were direct costs: surgical expenses, calibration, pulse generator replacement, and annual drug expenses. The majority of studies used country-specific thresholds. Fourteen comparisons from 12 studies reported on the cost effectiveness of DBS compared to best medical treatments. Eleven comparisons reported DBS as cost effective based on incremental cost-utility ratio results.

Conclusions

The cost effectiveness of DBS for PD varies by time horizon, costs considered, threshold utilized, and stage of PD progression. Standardizing approaches and comparing DBS with other treatments are needed for future research on effective PD management.

Background and Objective

Adding gene expression profiles (GEPs) to the current diagnostic work-up of aggressive large B-cell lymphomas may lead to the reclassification of patients, treatment changes and improved outcomes. A GEP test is in development using TempO-Seq^® technology to distinguish Burkitt lymphoma (BL) and primary mediastinal large B-cell lymphoma (PMBCL) from diffuse large B-cell lymphoma (DLBCL), and to classify patients with DLBLC and to predict the benefit of (e.g.) adding bortezomib to R-CHOP therapy (RB-CHOP). This study aims to estimate the potential impact of a GEP test on costs and health outcomes to inform pricing and evidence generation strategies.

Methods

Three decision models were developed comparing diagnostic strategies with and without GEP signatures over a lifetime horizon using a UK health and social care perspective. Inputs were taken from a recent clinical trial, literature and expert opinion. We estimated the maximum price of the test using a threshold of Great Britain Pound (GBP) 30,000 per quality-adjusted life-year (QALY). Sensitivity analyses were conducted.

Results

The estimated maximum threshold price for a combined test to be cost effective is GBP 15,352. At base-case values, the BL signature delivers QALY gains of 0.054 at an additional cost of GBP 275. This results in a net monetary benefit at a threshold of GBP 30,000 per QALY of GBP 1345. For PMBCL, the QALY gain was 0.0011 at a cost saving of GBP 406 and the net monetary benefit was GBP 437. The hazard ratio for the impact of treating BL less intensively must be at least 1.2 for a positive net monetary benefit. For identifying patients with the DLBCL subtype responsive to bortezomib, QALY gain was 0.2465 at a cost saving of GBP 6175, resulting in a net monetary benefit of GBP 13,570. In a probabilistic sensitivity analysis using 1000 simulations, a testing strategy was superior to a treat all with R-CHOP strategy in 81% of the simulations and with a cost saving in 92% assuming a cost price of zero.

Conclusions

Our estimates show that the combined test has a high probability of being cost effective. There is good quality evidence for the benefit of subtyping DLBCL but the evidence on the number of patients reclassified to or from BL and PMBCL and the impact of a more precise diagnosis and the cost of treatment is weak. The developers can use the price estimate to inform a return on investment calculations. Evidence will be required of how well the TempO-Seq^® technology performs compared to the testing GEP technology used for subtyping in the recent clinical trial. For BL and PMBCL elements of the test, evidence would be required of the number of patients reclassified and improved costing information would be useful. The diagnostic and therapeutic environment in haematological malignancies is fast moving, which increases the risk for developers of diagnostic tests.

Background

Self-reported service use informs resource utilisation and cost estimates, though its validity for use within economic evaluations is uncertain.

Objective

The aim of this study is to assess agreement in health resource-use measurement between self-reported and administrative data across different resource categories, over time and between different recall periods by subgroups among Australians living with psychosis.

Methods

Data were obtained for 104 participants with psychotic disorders from a randomised controlled trial. Agreement between self-reported resource-use questionnaires and administrative data on community-based services and medication use was assessed through estimating differences of group mean number of visits and medications used and intraclass correlation coefficients (ICC) over multiple time periods.

Results

ICC showed moderate agreement across most time periods for general practitioners, psychiatrists and mental health medications. No clear trends were discernible over time, between varying lengths of recall periods nor across participant subgroups.

Conclusion

Despite poor agreement, when measuring visits to psychologists and other health professionals, small overall differences in group mean number of visits indicate that self-reported data may still be valid for use in economic evaluations in people living with psychosis.