How to prepare a systematic review of economic evaluations for informing evidence-based healthcare decisions: data extraction, risk of bias, and transferability (part 3/3)

Introduction: This article is part of the series “How to Prepare a Systematic Review (SR) of Economic Evaluations (EE) for Informing Evidence-based Healthcare Decisions” in which a five-step-approach for conducting a SR of EE is proposed. Areas covered: This paper explains the data extraction process, the risk of bias assessment and the transferability of EEs by means of a narrative review and expert opinion. SRs play a critical role in determining the comparative cost-effectiveness of healthcare interventions. It is important to determine the risk of bias and the transferability of an EE. Expert commentary: Over the past decade, several criteria lists have been developed. This article aims to provide recommendations on these criteria lists based on the thoroughness of development, feasibility, overall quality, recommendations of leading organizations, and widespread use

PND44 Eliciting Patients’ Preferences for Epilepsy Diagnostics: A Discrete Choice Experiment

Background: Diagnosing epilepsy is a lengthy and burdensome process for patients and their family. Although the need for a more patient-centered approach in clinical practice is widely acknowledged, empirical evidence regarding patient preferences for diagnostic modalities in epilepsy is missing. The objectives of this study were 1) to identify to what extent important attributes of diagnostic procedures in epilepsy affect preferences for a procedure, 2) to determine the relative importance of these attributes, and 3) to calculate overall utility scores for routine electroencephalography (EEG) and magnetoencephalography (MEG) recordings. Methods: A discrete choice experiment was performed to determine patients' preferences, which involved presentation of pairwise choice tasks regarding hypothetical scenarios. Scenarios varied along six attributes: "way of measuring brain activity", "duration", "freedom of movement", "travel time", "type of additional examination", and "chance of additional examination". Choice tasks were constructed using a statistically efficient design, and the questionnaire contained 15 unique unlabeled choice tasks. Mixed multinomial logistic regression was used to estimate patients' preferences. Results: A total of 289 questionnaires were included in the analysis. McFadden's pseudo R-2 showed a model fit of 0.28, and all attributes were statistically significant. Heterogeneity in preferences was present for all attributes. "Freedom of movement" and "Chance of additional examination" were perceived as the most important attributes. Overall utility scores did not substantially differ between routine EEG and MEG. Conclusion: This study suggests that the identified attributes are important in determining patients' preference for epilepsy diagnostics. It can be concluded that MEG is not necessarily more patient-friendly than a routine EEG in primary diagnostics and, regarding additional diagnostics, patients have a strong preference for long-term 24-h EEG over EEG after sleep deprivation. Furthermore, barring substantial heterogeneity within the parameters in mind, our study suggests that it is important to take individual preferences into account in medical decision-making. (C) 2013 Elsevier Inc. All rights reserved

Economic Evaluation of an Internet-Based Preventive Cognitive Therapy With Minimal Therapist Support for Recurrent Depression

__Background__ Major depressive disorder (MDD) is highly recurrent and has a significant disease burden. Although the effectiveness of internet-based interventions has been established for the treatment of acute MDD, little is known about their cost effectiveness, especially in recurrent MDD. __Objectives__ Our aim was to evaluate the cost effectiveness and cost utility of an internet-based relapse prevention program (mobile cognitive therapy, M-CT). __Methods__ The economic evaluation was performed alongside a single-blind parallel group randomized controlled trial. Participants were recruited via media, general practitioners, and mental health care institutions. In total, 288 remitted individuals with a history of recurrent depression were eligible, of whom 264 were randomly allocated to M-CT with minimal therapist support added to treatment as usual (TAU) or TAU alone. M-CT comprised 8 online lessons, and participants were advised to complete 1 lesson per week. The economic evaluation was performed from a societal perspective with a 24-month time horizon. The health outcomes were number of depression-free days according to Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, (DSM-IV) criteria assessed with the Structured Clinical Interview for DSM-IV axis I disorders by blinded interviewers after 3, 12, and 24 months. Quality-adjusted life years (QALYs) were self-assessed with the three level version of the EuroQol Five Dimensional Questionnaire (EQ-5D-3L). Costs were assessed with the Trimbos and Institute for Medical Technology Assessment Questionnaire on Costs Associated with Psychiatric Illness (TiC-P). Incremental cost-effectiveness ratios were calculated and cost-effectiveness planes and cost-effectiveness acceptability curves were displayed to assess the probability that M-CT is cost effective compared to TAU. __Results__ Mean total costs over 24 months were €8298 (US $9415) for M-CT and €7296 (US$8278) for TAU. No statistically significant differences were found between M-CT and TAU regarding depression-free days and QALYs (P=.37 and P=.92, respectively). The incremental costs were €179 (US $203) per depression-free day and €230,816 (US$261,875) per QALY. The cost-effectiveness acceptability curves suggested that for depression-fr

Mapping of the World Health Organization's Disability Assessment Schedule 2.0 to disability weights using the Multi-Country Survey Study on Health and Responsiveness

OBJECTIVES: To develop and test an internationally applicable mapping function for converting WHODAS‐2.0 scores to disability weights, thereby enabling WHODAS‐2.0 to be used in cost‐utility analyses and sectoral decision‐making. METHODS: Data from 14 countries were used from the WHO Multi‐Country Survey Study on Health and Responsiveness, administered among nationally representative samples of respondents aged 18+ years who were non‐institutionalized and living in private households. For the combined total of 92,006 respondents, available WHODAS‐2.0 items (for both 36‐item and 12‐item versions) were mapped onto disability weight estimates using a machine learning approach, whereby data were split into separate training and test sets; cross‐validation was used to compare the performance of different regression and penalized regression models. Sensitivity analyses considered different imputation strategies and compared overall model performance with that of country‐specific models. RESULTS: Mapping functions converted WHODAS‐2.0 scores into disability weights; R‐squared values of 0.700–0.754 were obtained for the test data set. Penalized regression models reached comparable performance to standard regression models but with fewer predictors. Imputation had little impact on model performance. Model performance of the generic model on country‐specific test sets was comparable to model performance of country‐specific models. CONCLUSIONS: Disability weights can be generated with good accuracy using WHODAS 2.0 scores, including in national settings where health state valuations are not directly available, which signifies the utility of WHODAS as an outcome measure in evaluative studies that express intervention benefits in terms of QALYs gained

Mapping of the World Health Organization's Disability Assessment Schedule 2.0 to disability weights using the Multi-Country Survey Study on Health and Responsiveness

Objectives To develop and test an internationally applicable mapping function for converting WHODAS-2.0 scores to disability weights, thereby enabling WHODAS-2.0 to be used in cost-utility analyses and sectoral decision-making. Methods Data from 14 countries were used from the WHO Multi-Country Survey Study on Health and Responsiveness, administered among nationally representative samples of respondents aged 18+ years who were non-institutionalized and living in private households. For the combined total of 92,006 respondents, available WHODAS-2.0 items (for both 36-item and 12-item versions) were mapped onto disability weight estimates using a machine learning approach, whereby data were split into separate training and test sets; cross-validation was used to compare the performance of different regression and penalized regression models. Sensitivity analyses considered different imputation strategies and compared overall model performance with that of country-specific models. Results Mapping functions converted WHODAS-2.0 scores into disability weights; R-squared values of 0.700-0.754 were obtained for the test data set. Penalized regression models reached comparable performance to standard regression models but with fewer predictors. Imputation had little impact on model performance. Model performance of the generic model on country-specific test sets was comparable to model performance of country-specific models. Conclusions Disability weights can be generated with good accuracy using WHODAS 2.0 scores, including in national settings where health state valuations are not directly available, which signifies the utility of WHODAS as an outcome measure in evaluative studies that express intervention benefits in terms of QALYs gained

Economic evaluation of deep brain stimulation compared with vagus nerve stimulation and usual care for patients with refractory epilepsy: A lifetime decision analytic model

Objectives This study was undertaken to estimate the cost-effectiveness of deep brain stimulation (DBS) compared with vagus nerve stimulation (VNS) and care as usual (CAU) for adult patients with refractory epilepsy from a health care perspective using a lifetime decision analytic model. Methods A Markov decision analytic model was constructed to estimate the lifetime cost-effectiveness of DBS compared with VNS and CAU. Transition probabilities were estimated from a randomized controlled trial, and assumptions were made in consensus with an expert panel. Primary outcomes were expressed as incremental costs per quality-adjusted life-year (QALY) and per responder. Univariate and probabilistic sensitivity analyses were conducted to characterize parameter uncertainty. Results In DBS, 28.4% of the patients were responders, with an average of 21.38 QALYs per patient and expected lifetime health care costs of euro187 791. VNS had fewer responders (22.3%), fewer QALYs (20.70), and lower lifetime costs (euro156 871). CAU had the fewest responders (6.2%), fewest QALYs (18.74), and lowest total health care costs (euro64 670). When comparing with CAU, incremental cost-effectiveness ratios (ICERs) showed that costs per QALY gained were slightly lower for DBS (euro46 640) than for VNS (euro47 155). When comparing DBS with VNS, an incremental cost per additional QALY gained of euro45 170 was found for DBS. Sensitivity analyses showed that ICERs were heavily dependent on assumptions regarding loss to follow-up in the respective clinical trial. Significance This study suggests that, given current limited evidence, VNS and DBS are potentially cost-effective treatment strategies compared to CAU for patients with refractory epilepsy. However, results for DBS were heavily impacted by assumptions made to extrapolate nonresponse from the original trial. More stringent assumptions regarding nonresponse resulted in an ICER just above an acceptable willingness to pay threshold. Given the uncertainty surrounding the effectiveness of DBS and the large impact of assumptions related to nonresponse, further empirical research is needed to reduce uncertainty

Economic evaluation of deep brain stimulation compared with vagus nerve stimulation and usual care for patients with refractory epilepsy: A lifetime decision analytic model

Objectives This study was undertaken to estimate the cost-effectiveness of deep brain stimulation (DBS) compared with vagus nerve stimulation (VNS) and care as usual (CAU) for adult patients with refractory epilepsy from a health care perspective using a lifetime decision analytic model. Methods A Markov decision analytic model was constructed to estimate the lifetime cost-effectiveness of DBS compared with VNS and CAU. Transition probabilities were estimated from a randomized controlled trial, and assumptions were made in consensus with an expert panel. Primary outcomes were expressed as incremental costs per quality-adjusted life-year (QALY) and per responder. Univariate and probabilistic sensitivity analyses were conducted to characterize parameter uncertainty. Results In DBS, 28.4% of the patients were responders, with an average of 21.38 QALYs per patient and expected lifetime health care costs of euro187 791. VNS had fewer responders (22.3%), fewer QALYs (20.70), and lower lifetime costs (euro156 871). CAU had the fewest responders (6.2%), fewest QALYs (18.74), and lowest total health care costs (euro64 670). When comparing with CAU, incremental cost-effectiveness ratios (ICERs) showed that costs per QALY gained were slightly lower for DBS (euro46 640) than for VNS (euro47 155). When comparing DBS with VNS, an incremental cost per additional QALY gained of euro45 170 was found for DBS. Sensitivity analyses showed that ICERs were heavily dependent on assumptions regarding loss to follow-up in the respective clinical trial. Significance This study suggests that, given current limited evidence, VNS and DBS are potentially cost-effective treatment strategies compared to CAU for patients with refractory epilepsy. However, results for DBS were heavily impacted by assumptions made to extrapolate nonresponse from the original trial. More stringent assumptions regarding nonresponse resulted in an ICER just above an acceptable willingness to pay threshold. Given the uncertainty surrounding the effectiveness of DBS and the large impact of assumptions related to nonresponse, further empirical research is needed to reduce uncertainty

Relevance of barriers and facilitators in the use of health technology assessment in Colombia

Objectives: Several studies, mostly from developed countries, have identified barriers and facilitators with regard to the uptake of health technology assessment (HTA). This study elicited, using best-worst scaling (BWS), what HTA experts in Colombia consider to be the most important barriers and facilitators in the use of HTA, and makes a comparison to results from the Netherlands. Methods: Two object case surveys (one for barriers, one for facilitators) were conducted among 18 experts (policymakers, health professionals, PhD students, senior HTA-researchers) from Colombia. Seven respondents were employees of the national HTA agency Instituto de Evaluación Tecnológica de Salud (IETS). In total, 22 barriers and 19 facilitators were included. In each choice task, participants were asked to choose the most and least important barrier/facilitator from a set of five. Hierarchical Bayes modeling was used to compute the mean relative importance scores (RIS) for each factor, and a subgroup analysis was conducted to assess differences between IETS and non-IETS respondents. The final ranking was further compared to the results from a similar study conducted in the Netherlands. Results: The three most important barriers (RIS >6.00) were “Inadequate presentation format”, “Absence of policy networks”, and “Insufficient legal support”. The six most important facilitators (RIS >6.00) were “Appropriate timing”, “Clear presentation format”, “Improving longstanding relation”, “Appropriate incentives”, “Sufficient qualified human resources”, and “Availability to relevant HTA research”. The perceived relevance of the barriers and facilitators differed slightly between IETS and non-IETS employees, while the differences between the rankings in Colombia and the Netherlands were substantial. Conclusion: The study suggests that barriers and facilitators related to technical aspects of processing HTA reports and to the contact and interaction between researchers and policymakers had the greatest importance in Colombia. © 2018 Informa UK Limited, trading as Taylor and Francis Group