Measuring burden of disease in both asthma and COPD by merging the ACQ and CCQ: less is more?

Symptoms of asthma and COPD often overlap, and both diseases can co-exist in one patient. The asthma control questionnaire (ACQ) and clinical COPD questionnaire (CCQ) were developed to assess disease burden in respectively asthma or COPD. This study explores the possibility of creating a new questionnaire to assess disease burden in all obstructive lung diseases by integrating and reducing questions of the ACQ and CCQ. Data of patients with asthma, COPD and asthma-COPD overlap (ACO) were collected from a primary and secondary care center. Patients completed ACQ and CCQ on the same day. Linear regression tested correlations. Principal Component Analysis (PCA) was used for item reduction. The secondary cohort with asthma and COPD patients was used for initial question selection (development cohort). These results were reproduced in the primary care cohort and secondary cohort of patients with ACO. The development cohort comprised 252 patients with asthma and 96 with COPD. Correlation between ACQ and CCQ in asthma was R = 0.82, and in COPD R = 0.83. PCA determined a selection of 9 questions. Reproduction in primary care data (asthma n = 1110, COPD n = 1041, ACO = 355) and secondary care data of ACO patients (n = 53) resulted in similar correlations and PCA-derived selection of questions. In conclusion, PCA determined a selection of nine questions of the ACQ and CCQ: working title 'the Obstructive Lung Disease Questionnaire'. These results suggest that this pragmatic set of questions might be sufficient to assess disease burden in obstructive lung disease in both primary as secondary care.

Cost-effectiveness of remote haemodynamic monitoring by an implantable pulmonary artery pressure monitoring sensor (CardioMEMS-HF system) in chronic heart failure in the Netherlands.

AIMS: Remote haemodynamic monitoring with an implantable pulmonary artery (PA) sensor has been shown to reduce heart failure (HF) hospitalizations and improve quality of life. Cost-effectiveness analyses studying the value of remote haemodynamic monitoring in a European healthcare system with a contemporary standard care group are lacking. METHODS AND RESULTS: A Markov model was developed to estimate the cost-effectiveness of PA-guided therapy compared to the standard of care based upon patient-level data of the MONITOR-HF trial performed in the Netherlands in patients with chronic HF (New York Heart Association class III and at least one previous HF hospitalization). Cost-effectiveness was measured as the incremental cost per quality-adjusted life year (QALY) gained from the Dutch societal perspective with a lifetime horizon which encompasses a wide variety of costs including costs of hospitalizations, monitoring time, telephone contacts, laboratory assessments, and drug changes in both treatment groups. In the base-case analysis, PA-guided therapy increased costs compared to standard of care by €12 121. The QALYs per patient for PA-guided therapy and standard of care was 4.07 and 3.481, respectively, reflecting a gain of 0.58 QALYs. The resulting incremental cost-effectiveness ratio was €20 753 per QALY, which is below the Dutch willingness-to-pay threshold of €50 000 per QALY gained for HF. CONCLUSIONS: The current cost-effectiveness study suggests that remote haemodynamic monitoring with PA-guided therapy on top of standard care is likely to be cost-effective for patients with symptomatic moderate-to-severe HF in the Netherlands.

Implementing integrated care guidelines in asthma and COPD: It ain't easy!

Objective: To evaluate the implementation of a guideline-based, integrated, standardised, personal approach in patients with Chronic Obstructive Pulmonary Disease (COPD) or Asthma in a real-life situation. Methods: Patients at the outpatient clinic of the department of pulmonary disease were included in a controlled cohort study, comparing the use of diagnostic items and 'Personalised care plans' (PCPs) in patients with obstructive lung disease before (2013) and after (2015) implementation of a personalised diagnostic pathway. Results were compared with reference data (2016) from two control hospitals that used the same guidelines but did not implement this pathway. Results: 100 patients were selected for all three cohorts. After implementing the diagnostic pathway in 2015, 35 % of patients visited attended all pre-planned appointments, whereas 65 % of patients did not: they were diagnosed using usual care. Factors contributing to patients not attending the diagnostic care pathway were: the logistical complexity and intensity of the 2-day pathway, patients willingness to participate in a personalised pathway, and low social economic status or low literacy. After the implementation of the pathway, a significant improvement was seen in the number of PCPs (P < 0.001) and the number of diagnostic items registered recorded in the patients' electronic medical records (P < 0.001). Conclusion: Implementing a standardised diagnostic pathway in a real-life population significantly improved the number of personalised care plans, demonstrating that the implementation of holistic care planning is feasible in this population. Nevertheless, the pathway needs further improvements to maximize the number of patients benefitting from it, including logistical streamlining, removing unnecessary diagnostic tools, and increasing the focus on low literacy. Additionally, we found that implementing existing guidelines in a real life context is complex. Therefore, it is required to prioritize the translation of current guidelines into every-day practice, before expanding existing guidelines and protocols.

Discrete choice experiment versus swing-weighting: A head-to-head comparison of diabetic patient preferences for glucose-monitoring devices.

INTRODUCTION: Limited evidence exists for how patient preference elicitation methods compare directly. This study compares a discrete choice experiment (DCE) and swing-weighting (SW) by eliciting preferences for glucose-monitoring devices in a population of diabetes patients. METHODS: A sample of Dutch adults with type 1 or 2 diabetes (n = 459) completed an online survey assessing their preferences for glucose-monitoring devices, consisting of both a DCE and a SW exercise. Half the sample completed the DCE first; the other half completed the SW first. For the DCE, the relative importance of the attributes of the devices was determined using a mixed-logit model. For the SW, the relative importance of the attributes was based on ranks and points allocated to the 'swing' from the worst to the best level of the attribute. The preference outcomes and self-reported response burden were directly compared between the two methods. RESULTS: Participants reported they perceived the DCE to be easier to understand and answer compared to the SW. Both methods revealed that cost and precision of the device were the most important attributes. However, the DCE had a 14.9-fold difference between the most and least important attribute, while the SW had a 1.4-fold difference. The weights derived from the SW were almost evenly distributed between all attributes. CONCLUSIONS: The DCE was better received by participants, and generated larger weight differences between each attribute level, making it the more informative method in our case study. This method comparison provides further evidence of the degree of method suitability and trustworthiness.

How Can a Bundled Payment Model Incentivize the Transition from Single-Disease Management to Person-Centred and Integrated Care for Chronic Diseases in the Netherlands?

To stimulate the integration of chronic care across disciplines, the Netherlands has implemented single-disease management programmes (SDMPs) in primary care since 2010; for example, for COPD, type 2 diabetes mellitus, and cardiovascular diseases. These disease-specific chronic care programmes are funded by bundled payments. For chronically ill patients with multimorbidity or with problems in other domains of health, this approach was shown to be less fit for purpose. As a result, we are currently witnessing several initiatives to broaden the scope of these programmes, aiming to provide truly person-centred integrated care (PC-IC). This raises the question if it is possible to design a payment model that would support this transition. We present an alternative payment model that combines a person-centred bundled payment with a shared savings model and pay-for-performance elements. Based on theoretical reasoning and results of previous evaluation studies, we expect the proposed payment model to stimulate integration of person-centred care between primary healthcare providers, secondary healthcare providers, and the social care domain. We also expect it to incentivise cost-conscious provider-behaviour, while safeguarding the quality of care, provided that adequate risk-mitigating actions, such as case-mix adjustment and cost-capping, are taken.

Diabetes patient preferences for glucose-monitoring technologies: results from a discrete choice experiment in Poland and the Netherlands.

INTRODUCTION: New glucose-monitoring technologies have different cost-benefit profiles compared with traditional finger-prick tests, resulting in a preference-sensitive situation for patients. This study aimed to assess the relative value adults with diabetes assign to device attributes in two countries. RESEARCH DESIGN AND METHODS: Adults with type 1 or 2 diabetes from the Netherlands (n=226) and Poland (n=261) completed an online discrete choice experiment. Respondents choose between hypothetical glucose monitors described using seven attributes: precision, effort to check, number of finger pricks required, risk of skin irritation, information provided, alarm function and out-of-pocket costs. Panel mixed logit models were used to determine attribute relative importance and to calculate expected uptake rates and willingness to pay (WTP). RESULTS: The most important attribute for both countries was monthly out-of-pocket costs. Polish respondents were more likely than Dutch respondents to choose a glucose-monitoring device over a standard finger prick and had higher WTP for a device. Dutch respondents had higher WTP for device improvements in an effort to check and reduce the number of finger pricks a device requires. CONCLUSION: Costs are the primary concern of patients in both countries when choosing a glucose monitor and would likely hamper real-world uptake. The costs-benefit profiles of such devices should be critically reviewed.

Stratification of COPD patients towards personalized medicine: reproduction and formation of clusters.

BACKGROUND: The global initiative for chronic obstructive lung disease (GOLD) 2020 emphasizes that there is only a weak correlation between FEV1, symptoms and impairment of the health status of patients with chronic obstructive pulmonary disease (COPD). Various studies aimed to identify COPD phenotypes by cluster analyses, but behavioral aspects besides smoking were rarely included. METHODS: The aims of the study were to investigate whether (i) clustering analyses are in line with the classification into GOLD ABCD groups; (ii) clustering according to Burgel et al. (Eur Respir J. 36(3):531-9, 2010) can be reproduced in a real-world COPD cohort; and (iii) addition of new behavioral variables alters the clustering outcome. Principal component and hierarchical cluster analyses were applied to real-world clinical data of COPD patients newly referred to secondary care (n = 155). We investigated if the obtained clusters paralleled GOLD ABCD subgroups and determined the impact of adding several variables, including quality of life (QOL), fatigue, satisfaction relationship, air trapping, steps per day and activities of daily living, on clustering. RESULTS: Using the appropriate corresponding variables, we identified clusters that largely reflected the GOLD ABCD groups, but we could not reproduce Burgel's clinical phenotypes. Adding six new variables resulted in the formation of four new clusters that mainly differed from each other in the following parameters: number of steps per day, activities of daily living and QOL. CONCLUSIONS: We could not reproduce previously identified clinical COPD phenotypes in an independent population of COPD patients. Our findings therefore indicate that COPD phenotypes based on cluster analysis may not be a suitable basis for treatment strategies for individual patients.

Value Insider Season 1 Episode 4: How are Costs Measured, and How are CEAs Constructed and Used? (CEA) [Podcast].

How is a cost-effectiveness analysis constructed and used? In this episode of the Value Insider podcast, host Mike Chambers speaks with Prof. Maureen Rutten-van Mölken about economic evaluations in healthcare and how value is considered in these evaluations. Prof. Rutten-van Mölken is professor of Economic Evaluation of Innovations for Health at the Erasmus University Rotterdam in the Netherlands. She leads the Erasmus HTA department and is Scientific Director of the Institute for Medical Technology Assessment (iMTA). Prof Rutten-van Mölken explains how comparative assessments can help us understand which treatments offer the best value-for-money as reimbursement can only be allocated to a selection of all possible treatments.

Improved survival of non-small cell lung cancer patients after introducing patient navigation: A retrospective cohort study with propensity score weighted historic control.

OnkoNetwork is a patient navigation program established in the Moritz Kaposi General Hospital to improve the timeliness and completeness of cancer investigations and treatment. The H2020 SELFIE consortium selected OnkoNetwork as a promising integrated care initiative in Hungary and conducted a multicriteria decision analysis based on health, patient experience, and cost outcomes. In this paper, a more detailed analysis of clinical impacts is provided in the largest subgroup, non-small cell lung cancer (NSCLC) patients. A retrospective cohort study was conducted, enrolling new cancer suspect patients with subsequently confirmed NSCLC in two annual periods, before and after OnkoNetwork implementation (control and intervention cohorts, respectively). To control for selection bias and confounding, baseline balance was improved via propensity score weighting. Overall survival was analyzed in univariate and multivariate weighted Cox regression models and the effect was further characterized in a counterfactual analysis. Our analysis included 123 intervention and 173 control NSCLC patients from early to advanced stage, with significant between-cohort baseline differences. The propensity score-based weighting resulted in good baseline balance. A large survival benefit was observed in the intervention cohort, and intervention was an independent predictor of longer survival in a multivariate analysis when all baseline characteristics were included (HR = 0.63, p = 0.039). When post-baseline variables were included in the model, belonging to the intervention cohort was not an independent predictor of survival, but the survival benefit was explained by slightly better stage distribution and ECOG status at treatment initiation, together with trends for broader use of PET-CT and higher resectability rate. In conclusion, patient navigation is a valuable tool to improve cancer outcomes by facilitating more timely and complete cancer diagnostics. Contradictory evidence in the literature may be explained by common sources of bias, including the wait-time paradox and adjustment to intermediate outcomes.

The impact of the involvement of a healthcare professional on the usage of an eHealth platform: a retrospective observational COPD study.

BACKGROUND: Ehealth platforms, since the outbreak of COVID-19 more important than ever, can support self-management in patients with Chronic Obstructive Pulmonary Disease (COPD). The aim of this observational study is to explore the impact of healthcare professional involvement on the adherence of patients to an eHealth platform. We evaluated the usage of an eHealth platform by patients who used the platform individually compared with patients in a blended setting, where healthcare professionals were involved. METHODS: In this observational cohort study, log data from September 2011 until January 2018 were extracted from the eHealth platform Curavista. Patients with COPD who completed at least one Clinical COPD Questionnaire (CCQ) were included for analyses (n = 299). In 57% (n = 171) of the patients, the eHealth platform was used in a blended setting, either in hospital (n = 128) or primary care (n = 29). To compare usage of the platform between patients who used the platform independently or with a healthcare professional, we applied propensity score matching and performed adjusted Poisson regression analysis on CCQ-submission rate. RESULTS: Using the eHealth platform in a blended setting was associated with a 3.25 higher CCQ-submission rate compared to patients using the eHealth platform independently. Within the blended setting, the CCQ-submission rate was 1.83 higher in the hospital care group than in the primary care group. CONCLUSION: It is shown that COPD patients used the platform more frequently in a blended care setting compared to patients who used the eHealth platform independently, adjusted for age, sex and disease burden. Blended care seems essential for adherence to eHealth programs in COPD, which in turn may improve self-management.

The disease burden of multimorbidity and its interaction with educational level.

INTRODUCTION: Policies to adequately respond to the rise in multimorbidity have top-priority. To understand the actual burden of multimorbidity, this study aimed to: 1) estimate the trend in prevalence of multimorbidity in the Netherlands, 2) study the association between multimorbidity and physical and mental health outcomes and healthcare cost, and 3) investigate how the association between multimorbidity and health outcomes interacts with socio-economic status (SES). METHODS: Prevalence estimates were obtained from a nationally representative pharmacy database over 2007-2016. Impact on costs was estimated in a fixed effect regression model on claims data over 2009-2015. Data on physical and mental health and SES were obtained from the National Health Survey in 2017, in which the Katz-10 was used to measure limitations in activities of daily living (ADL) and the Mental Health Inventory (MHI) to measure mental health. SES was approximated by the level of education. Generalized linear models (2-part models for ADL) were used to analyze the health data. In all models an indicator variable for the presence or absence of multimorbidity was included or a categorical variable for the number of chronic conditions. Interactions terms of multimorbidity and educational level were added into the previously mentioned models. RESULTS: Over the past ten years, there was an increase of 1.6%-point in the percentage of people with multimorbidity. The percentage of people with three or more conditions increased with +2.1%-point. People with multimorbidity had considerably worse physical and mental health outcomes than people without multimorbidity. For the ADL, the impact of multimorbidity was three times greater in the lowest educational level than in the highest educational level. For the MHI, the impact of multimorbidity was two times greater in the lowest than in the highest educational level. Each additional chronic condition was associated with a greater worsening in health outcomes. Similarly, for costs, where there was no evidence of a diminishing impact of additional conditions either. In patients with multimorbidity total healthcare costs were on average €874 higher than in patients with a single morbidity. CONCLUSION: The impact of multimorbidity on health and costs seems to be greater in the sicker and lower educated population.

How to Address Uncertainty in Health Economic Discrete-Event Simulation Models: An Illustration for Chronic Obstructive Pulmonary Disease.

Background. Evaluation of personalized treatment options requires health economic models that include multiple patient characteristics. Patient-level discrete-event simulation (DES) models are deemed appropriate because of their ability to simulate a variety of characteristics and treatment pathways. However, DES models are scarce in the literature, and details about their methods are often missing. Methods. We describe 4 challenges associated with modeling heterogeneity and structural, stochastic, and parameter uncertainty that can be encountered during the development of DES models. We explain why these are important and how to correctly implement them. To illustrate the impact of the modeling choices discussed, we use (results of) a model for chronic obstructive pulmonary disease (COPD) as a case study. Results. The results from the case study showed that, under a correct implementation of the uncertainty in the model, a hypothetical intervention can be deemed as cost-effective. The consequences of incorrect modeling uncertainty included an increase in the incremental cost-effectiveness ratio ranging from 50% to almost a factor of 14, an extended life expectancy of approximately 1.4 years, and an enormously increased uncertainty around the model outcomes. Thus, modeling uncertainty incorrectly can have substantial implications for decision making. Conclusions. This article provides guidance on the implementation of uncertainty in DES models and improves the transparency of reporting uncertainty methods. The COPD case study illustrates the issues described in the article and helps understanding them better. The model R code shows how the uncertainty was implemented. For readers not familiar with R, the model's pseudo-code can be used to understand how the model works. By doing this, we can help other developers, who are likely to face similar challenges to those described here.

The risk of overestimating cost savings from hospital-at-home schemes: A literature review.

BACKGROUND: The concept of hospital-at-home means that home treatment is provided to patients who would otherwise have been treated in the hospital. This may lead to lower costs, but estimates of savings may be overstated if inpatient hospital costs are priced incorrectly. OBJECTIVE: The objective of this study was to evaluate the quality of cost analyses of hospital-at-home studies for acute conditions published from 1996 through 2019 and to present an overview of evidence. DESIGN: Literature review DATA SOURCES: The PubMed and NHS EED databases were searched. REVIEW METHODS: The overall quality of studies was evaluated based on Quality of Health Economic Studies (QHES) score, design, sample size, alignment of cost calculation with study perspective, time horizon, use of tariffs or real resource use and clarity of calculations. Furthermore, we systematically assessed whether cost savings were likely to be overestimated, based on criteria about the costing of inpatient hospital days, informal care costs and bias. RESULTS: We identified 48 studies. The average QHES score was 60 out of a maximum of 100 points. Almost all studies violated one or more criteria for the risk of overestimation of cost savings. The most frequent problems were the use of average unit prices per inpatient day (not taking into account the decreasing intensity of care) and biased designs. Most studies found cost differences in favour of hospital-at-home; the range varied from savings of €8773 to a cost increase of €2316 per patient. CONCLUSION: Overall quality of studies was not good, with some exceptions. Many cost savings were probably overestimated.

Exploring characteristics of COPD patients with clinical improvement after integrated disease management or usual care: post-hoc analysis of the RECODE study.

BACKGROUND: The cluster randomized controlled trial on (cost-)effectiveness of integrated chronic obstructive pulmonary disease (COPD) management in primary care (RECODE) showed that integrated disease management (IDM) in primary care had no effect on quality of life (QOL) in COPD patients compared with usual care (guideline-supported non-programmatic care). It is possible that only a subset of COPD patients in primary care benefit from IDM. We therefore examined which patients benefit from IDM, and whether patient characteristics predict clinical improvement over time. METHOD: Post-hoc analyses of the RECODE trial among 1086 COPD patients. Logistic regression analyses were performed with baseline characteristics as predictors to examine determinants of improvement in QOL, defined as a minimal decline in Clinical COPD Questionnaire (CCQ) of 0.4 points after 12 and 24 months of IDM. We also performed moderation analyses to examine whether predictors of clinical improvement differed between IDM and usual care. RESULTS: Regardless of treatment type, more severe dyspnea (MRC) was the most important predictor of clinically improved QOL at 12 and 24 months, suggesting that these patients have most room for improvement. Clinical improvement with IDM was associated with female gender (12-months) and being younger (24-months), and improvement with usual care was associated with having a depression (24-months). CONCLUSIONS: More severe dyspnea is a key predictor of improved QOL in COPD patients over time. More research is needed to replicate patient characteristics associated with clinical improvement with IDM, such that IDM programs can be offered to patients that benefit the most, and can potentially be adjusted to meet the needs of other patient groups as well. TRIAL REGISTRATION: Netherlands Trial Register, NTR2268. Registered 31 March 2010.

Early cost-utility analysis of tissue-engineered heart valves compared to bioprostheses in the aortic position in elderly patients.

OBJECTIVES: Aortic valve disease is the most frequent indication for heart valve replacement with the highest prevalence in elderly. Tissue-engineered heart valves (TEHV) are foreseen to have important advantages over currently used bioprosthetic heart valve substitutes, most importantly reducing valve degeneration with subsequent reduction of re-intervention. We performed early Health Technology Assessment of hypothetical TEHV in elderly patients (≥ 70 years) requiring surgical (SAVR) or transcatheter aortic valve implantation (TAVI) to assess the potential of TEHV and to inform future development decisions. METHODS: Using a patient-level simulation model, the potential cost-effectiveness of TEHV compared with bioprostheses was predicted from a societal perspective. Anticipated, but currently hypothetical improvements in performance of TEHV, divided in durability, thrombogenicity, and infection resistance, were explored in scenario analyses to estimate quality-adjusted life-year (QALY) gain, cost reduction, headroom, and budget impact. RESULTS: Durability of TEHV had the highest impact on QALY gain and costs, followed by infection resistance. Improved TEHV performance (- 50% prosthetic valve-related events) resulted in lifetime QALY gains of 0.131 and 0.043, lifetime cost reductions of €639 and €368, translating to headrooms of €3255 and €2498 per hypothetical TEHV compared to SAVR and TAVI, respectively. National savings in the first decade after implementation varied between €2.8 and €11.2 million (SAVR) and €3.2-€12.8 million (TAVI) for TEHV substitution rates of 25-100%. CONCLUSIONS: Despite the relatively short life expectancy of elderly patients undergoing SAVR/TAVI, hypothetical TEHV are predicted to be cost-effective compared to bioprostheses, commercially viable and result in national cost savings when biomedical engineers succeed in realising improved durability and/or infection resistance of TEHV.

Clinical outcome and cost-effectiveness of a 1-year nutritional intervention programme in COPD patients with low muscle mass: The randomized controlled NUTRAIN trial.

BACKGROUND AND AIMS: The efficacy of nutritional intervention to enhance short- and long-term outcomes of pulmonary rehabilitation in COPD is still unclear, hence this paper aims to investigate the clinical outcome and cost-effectiveness of a 12-month nutritional intervention strategy in muscle-wasted COPD patients. METHODS: Prior to a 4-month pulmonary rehabilitation programme, 81 muscle-wasted COPD patients (51% males, aged 62.5 ± 0.9 years) with moderate airflow obstruction (FEV1 55.1 ± 2.2% predicted) and impaired exercise capacity (Wmax 63.5 ± 2.4% predicted) were randomized to 3 portions of nutritional supplementation per day (enriched with leucine, vitamin D and polyunsaturated fatty acids) [NUTRITION] or PLACEBO (phase 1). In the unblinded 8-month maintenance phase (phase 2), both groups received structured feedback on their physical activity level assessed by accelerometry. NUTRITION additionally received 1 portion of supplemental nutrition per day and motivational interviewing-based nutritional counselling. A 3-month follow-up (phase 3) was included. RESULTS: After 12 months, physical capacity measured by quadriceps muscle strength and cycle endurance time were not different, but physical activity was higher in NUTRITION than in PLACEBO (Δ1030 steps/day, p = 0.025). Plasma levels of the enriched nutrients (p < 0.001) were higher in NUTRITION than PLACEBO. Trends towards weight gain in NUTRITION and weight loss in PLACEBO led to a significant between-group difference after 12 months (Δ1.54 kg, p = 0.041). The HADS anxiety and depression scores improved in NUTRITION only (Δ-1.92 points, p = 0.037). Generic quality of life (EQ-5D) was decreased in PLACEBO but not in NUTRITION (between-group difference after 15 months 0.072 points, p = 0.009). Overall motivation towards exercising and healthy eating was high and did not change significantly after 12 months; only amotivation towards healthy eating yielded a significant between-group difference (Δ1.022 points, p = 0.015). The cost per quality-adjusted life-year after 15 months was EUR 16,750. CONCLUSIONS: Nutritional intervention in muscle-wasted patients with moderate COPD does not enhance long-term outcome of exercise training on physical capacity but ameliorates plasma levels of the supplemented nutrients, total body weight, physical activity and generic health status, at an acceptable increase of costs for patients with high disease burden.

TECH-VER: A Verification Checklist to Reduce Errors in Models and Improve Their Credibility.

BACKGROUND: In health economic literature, checklists or best practice recommendations on model validation/credibility always declare verification of the programmed model as a fundamental step, such as 'is the model implemented correctly and does the implementation accurately represent the conceptual model?' However, to date, little operational guidance for the model verification process has been given. In this study, we aimed to create an operational checklist for model users or reviewers to verify the technical implementation of health economic decision analytical models and document their verification efforts. METHODS: Literature on model validation, verification, programming errors and credibility was reviewed systematically from scientific databases. An initial beta version of the checklist was developed based on the checklists/tests identified from the literature and from authors' previous modeling/appraisal experience. Next, the first draft checklist was presented to a number of health economists on several occasions and was tested on different models (built in different software, developed by different stakeholders, including drug manufacturers, consultancies or academia), each time leading to an update of the checklist and culminating in the final version of the TECHnical VERification (TECH-VER) checklist, introduced in this paper. RESULTS: The TECH-VER necessitates a model reviewer (preferably independent), an executable and transparent model, its input sources, and detailed documentation (e.g. technical report/scientific paper) in which the conceptual model, its implementation, programmed model inputs, and results are reported. The TECH-VER checklist consists of five domains: (1) input calculations; (2) event-state (patient flow) calculations; (3) result calculations; (4) uncertainty analysis calculations; and (5) other overall checks (e.g. validity or interface). The first four domains reflect the verification of the components of a typical health economic model. For these domains, as a prerequisite of verification tests, the reviewer should identify the relevant calculations in the electronic model and assess the provided justifications for the methods used in the identified calculations. For this purpose, we recommend completeness/consistency checks. Afterwards, the verification tests can be conducted for the calculations in each of these stages by checking the correctness of the implementation of these calculations. For this purpose, the following type of tests are recommended in consecutive order: (i) black-box tests, i.e. checking if model calculations are in line with a priori expectations; (ii) white-box testing, i.e. going through the program code details line by line, or cell by cell (recommended for some crucial calculations and if there are some unexpected results from the black-box tests); and (iii) model replication/parallel programming (recommended only in certain situations, and if the issues related to the identified unexpected results from black-box tests could not be resolved through white-box testing). To reduce the time burden of model verification, we suggest a hierarchical order in tests i-iii, where going to the next step is necessary when the previous step fails. CONCLUSIONS: The TECH-VER checklist is a comprehensive checklist for the technical verification of decision analytical models, aiming to help identify model implementation errors and their root causes while improving the transparency and efficiency of the verification efforts. In addition to external reviews, we consider that the TECH-VER can be used as an internal training and quality control tool for new health economists, while developing their initial models. It is the authors' aim that the TECH-VER checklist transforms itself to an open-source living document, with possible future versions, or 'bolt-on' extensions for specific applications with additional 'fit-for-purpose' tests, as well as 'tips and tricks' and some demonstrative error examples. For this reason, the TECH-VER checklist and the list of black-box tests created in this paper and a few model verification examples is uploaded to an open access, online platform (github and the website of the institute), where other users will also be able to upload their original verification efforts and tests.

The Fold-in, Fold-out Design for DCE Choice Tasks: Application to Burden of Disease.

Background In discrete-choice experiments (DCEs), choice alternatives are described by attributes. The importance of each attribute can be quantified by analyzing respondents' choices. Estimates are valid only if alternatives are defined comprehensively, but choice tasks can become too difficult for respondents if too many attributes are included. Several solutions for this dilemma have been proposed, but these have practical or theoretical drawbacks and cannot be applied in all settings. The objective of the current article is to demonstrate an alternative solution, the fold-in, fold-out approach (FiFo). We use a motivating example, the ABC Index for burden of disease in chronic obstructive pulmonary disease (COPD). Methods Under FiFo, all attributes are part of all choice sets, but they are grouped into domains. These are either folded in (all attributes have the same level) or folded out (levels may differ). FiFo was applied to the valuation of the ABC Index, which included 15 attributes. The data were analyzed in Bayesian mixed logit regression, with additional parameters to account for increased complexity in folded-out questionnaires and potential differences in weight due to the folding status of domains. As a comparison, a model without the additional parameters was estimated. Results Folding out domains led to increased choice complexity for respondents. It also gave domains more weight than when it was folded in. The more complex regression model had a better fit to the data than the simpler model. Not accounting for choice complexity in the models resulted in a substantially different ABC Index. Conclusion Using a combination of folded-in and folded-out attributes is a feasible approach for conducting DCEs with many attributes.

Exploring the Impact of Adding a Respiratory Dimension to the EQ-5D-5L.

Objectives. To evaluate the impact of adding a respiratory dimension (a bolt-on dimension) to the EQ-5D-5L health state valuations. Methods. Based on extensive regression and principal component analyses, 2 respiratory bolt-on candidates were formulated: R1, limitations in physical activities due to shortness of breath, and R2, breathing problems. Valuation interviews for the selected bolt-ons were performed with a representative sample from the Dutch general public using the standardized interview protocol and software of the EuroQol group. Hybrid models based on the combined time-tradeoff (TTO) and discrete choice experiment (DCE) data were estimated to assess whether the 5 levels of the respiratory bolt-on led to significant changes in utility values. Results. For each bolt-on candidate, slightly more than 200 valuation interviews were conducted. Mean TTO values and DCE choice probabilities for health states with a level 4 or 5 for the respiratory dimension were significantly lower compared with the same health states in the Dutch EQ-5D-5L valuation study without the respiratory dimension. Results of hybrid models showed that for the bolt-on "limitations in physical activities," the utility decrements were significant for level 3 (-0.055), level 4 (-0.087), and level 5 (-0.135). For "breathing problems," the utility decrements for the same levels were greater (-0.086, -0.219, and -0.327, respectively). Conclusions. The addition of each of the 2 respiratory bolt-ons to the EQ-5D-5L had a significant effect on the valuation of health states with severe levels for the bolt-on. The bolt-on dimension "breathing problems" showed the greatest utility decrements and therefore seems the most appropriate respiratory bolt-on dimension.

Broadening the Perspective of Cost-Effectiveness Modeling in Chronic Obstructive Pulmonary Disease: A New Patient-Level Simulation Model Suitable to Evaluate Stratified Medicine.

OBJECTIVES: To develop a health economic model that included a great diversity of patient characteristics and outcomes for chronic obstructive pulmonary disease (COPD), which can be used to inform decisions about stratified medicine in COPD. METHODS: The choice of patient characteristics and outcomes to include in the model was based on 3 literature reviews on multidimensional prognostic COPD indices, COPD phenotypes, and treatment effects in subgroups. A conceptual model was constructed including 14 patient characteristics, 7 intermediate outcomes (lung function, physical activity, exercise capacity, symptoms, disease-specific quality of life, exacerbations, and pneumonias), and 3 final outcomes (mortality, quality-adjusted life-years [QALYs], and costs). Regression equations describing the statistical associations between the patient characteristics and intermediate and final outcomes were estimated using the longitudinal data of 5 large COPD trials (19,378 patients). A patient-level simulation model was developed in which individual patients from the baseline population of the 5 trials are sampled and their outcomes over lifetime are predicted based on the regression equations. RESULTS: The base-case analysis (single-arm simulation representing treatment with tiotropium) showed that patients had a mean lung function decline of 43 mL/year, 0.62 exacerbations/year, a worsening of their physical activity and quality of life with 1.48 and 1.10 points/year, a life expectancy of 11.2 years, 7.25 QALYs, and total lifetime costs of £24,891. Results for a selection of treatment scenarios and subgroups were shown to demonstrate the potential of the model. CONCLUSIONS: We developed a unique patient-level simulation model that can be used to evaluate COPD treatment options for a variety of subgroups.