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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.

Background Decision-Analytic cost-effectiveness (CE) models combine many parameters, often obtained after meta-Analysis. Aim We compared different methods of mixed-Treatment comparison (MTC) to combine transition and event probabilities derived from several trials, especially with respect to health-economic (HE) outcomes like (quality adjusted) life years and costs. Methods Trials were drawn from a simulated reference population, comparing two of four fictitious interventions. The goal was to estimate the CE between two of these. The amount of heterogeneity between trials was varied in scenarios. Parameter estimates were combined using direct comparison, MTC methods proposed by Song and Puhan, and Bayesian generalized linear fixed effects (GLMFE) and random effects models (GLMRE). Parameters were entered into a Markov model. Parameters and HE outcomes were compared

Background: The costs of performing research are an important input in value of information (VOI) analyses but are difficult to assess. Objective: The aim of this study was to investigate the costs of research, serving two purposes: (1) estimating research costs for use in VOI analyses; and (2) developing a costing tool to support reviewers of grant proposals in assessing whether the proposed budget is realistic. Methods: For granted study proposals from the Netherlands Organization for Health Research and Development (ZonMw), type of study, potential cost drivers, proposed budget, and general characteristics were extracted. Regression analysis was conducted in an attempt to generate a ‘predicted budget’ for certain combinations of cost drivers, for implementation in the costing tool. Results: Of 133 drug-related research grant proposals, 74 were included for complete data extraction. Because an association between cost drivers and budgets was not confirmed, we could not generate a predicted budget based on regression analysis, but only historic reference budgets given certain study characteristics. The costing tool was designed accordingly, i.e. with given selection criteria the tool returns the range of budgets in comparable studies. This range can be used in VOI analysis to estimate whether the expected net benefit of sampling will be positive to decide upon the net value of future research. Conclusion: The absence of association between study characteristics and budgets may indicate inconsistencies in the budgeting or granting process. Nonetheless, the tool generates useful information on historical budgets, and the option to formally relate VOI to budgets. To our knowledge, this is the first attempt at creating such a tool, which can be complemented with new studies being granted, enlarging the underlying database and keeping estimates up to date.

Evaluations of healthcare interventions, e.g. new drugs or other new treatment strategies, commonly include a cost-effectiveness analysis (CEA) that is based on the application of health economic (HE) models. As end users, patients are important stakeholders regarding the outcomes of CEAs, yet their knowledge of HE model development and application, or their involvement therein, is absent. This paper considers possible benefits and risks of patient involvement in HE model development and application for modellers and patients. An exploratory review of the literature has been performed on stakeholder-involved modelling in various disciplines. In addition, Dutch patient experts have been interviewed about their experience in, and opinion about, the application of HE models. Patients have little to no knowledge of HE models and are seldom involved in HE model development and application. Benefits of becoming involved would include a greater understanding and possible acceptance by patients of HE model application, improved model validation, and a more direct infusion of patient expertise. Risks would include patient bias and increased costs of modelling. Patient involvement in HE modelling seems to carry several benefits as well as risks. We claim that the benefits may outweigh the risks and that patients should become involved.

Background: A trade-off exists between building confidence in health-economic (HE) decision models and the use of scarce resources. We aimed to create a practical tool providi

__Abstract__ At its heart, health technology assessment (HTA) is very simple. It compares two or more alternative courses of action, often pharmaceutical interventions, in terms of both their costs and health outcomes.1 One of the interventions will have better health outcomes, for example fewer number of exacerbations, longer survival or a better quality of life. This usually comes at an extra cost, often in the way of a higher price for the intervention. HTA makes this exchange between costs and effects explicit. The idea that costs are an important element to take into account, does not come naturally to many health care workers. Doctors, nurses, and other health care workers do everything they can to help patients improve their lives. The interventions these patients need are provided in a large part by companies developing and producing the necessary drugs and devices. Health care scientists and epidemiologists try to make sense of what constitutes health, what illness is and how disease is spread. Their focus is purely on the patient: what does he or she need? Choices between treatment options are usually a consideration between availability, possible side effects, and patient characteristics. If a new medication comes on the market, doctors are often eager to treat patients with this newest treatment option. With the focus on the patient in front of them, health care workers usually do not look beyond the operating room or treatment room. An oncologist wants to treat all patients to the best of his or her ability, no matter the costs of the intervention. Budgetary constraints are not, and should not, be part of the decision making process of a health care worker when dealing with an individual patient. Cost considerations should be taken into account at a more aggregate level in the clinical guidelines, written by their organizations. In this way, HTA separates health care workers from these concerns in their daily practice, which are in the public and politi

__Abstract__ Purpose: Absence from work due to mental disorders is substantial. Additionally, long-term absence from work is associated with a reduced probability of return-to-work (RTW). Major depressive disorder (MDD) is a prevalent condition in Dutch occupational health care settings. An early estimate of the prognosis regarding RTW in patients with MDD could serve both as a point of departure for the identification of high-risk cases and as an instrument to monitor the course of the disorder and of RTW. In the current study, we aimed to assess the added value of health-related quality of life (Hrqol) and severity of depression to predict the time to RTW. Patients and methods: Data were derived from a prospective longitudinal study aimed to evaluate the cost effectiveness of a collaborative care treatment in sick-listed workers with MDD. We included demographic, job-related, and health-related variables. Severity of depression was measured using the Patient Health Questionnaire Depression Scale-9 (PHQ-9). HRQoL was measured using two generic preference-based instruments, the EuroQol 5-Dimension (EQ-5D™) and the Medical Outcomes Study Short Form Health Survey (SF-36). A survival model was constructed by applying different survival functions to assess the best fit for the data. Additionally, survival analyses were performed to assess the added value of the two HRQoL measures and depression severity for predicting RTW. Results: Females and older patients had a longer time to RTW. The same was true for patients with a full-time job and patients with more decision latitude. Patients in a management position and patients with more social support had a shorter time to RTW. Severity of depression was not predictive for the time to RTW. HRQoL measured by the SF-36 was a significant predictor for the time to RTW. Conclusion: HRQoL emerged as a significant predictor for the time to RTW. However, severity of depression was not predictive for the time to RTW. These results su

Purpose: Absence from work due to mental disorders is substantial. Additionally, long-term absence from work is associated with a reduced probability of return-to-work (RTW). Major depressive disorder (MDD) is a prevalent condition in Dutch occupational health care settings. An early estimate of the prognosis regarding RTW in patients with MDD could serve both as a point of departure for the identification of high-risk cases and as an instrument to monitor the course of the disorder and of RTW. In the current study, we aimed to assess the added value of health-related quality of life (HRQoL) and severity of depression to predict the time to RTW. Patients and methods: Data were derived from a prospective longitudinal study aimed to evaluate the cost effectiveness of a collaborative care treatment in sick-listed workers with MDD. We included demographic, job-related, and health-related variables. Severity of depression was measured using the Patient Health Questionnaire Depression Scale-9 (PHQ-9). HRQoL was measured using two generic preference-based instruments, the EuroQol 5-Dimension (EQ-5D™) and the Medical Outcomes Study Short Form Health Survey (SF-36). A survival model was constructed by applying different survival functions to assess the best fit for the data. Additionally, survival analyses were performed to assess the added value of the two HRQoL measures and depression severity for predicting RTW. Results: Females and older patients had a longer time to RTW. The same was true for patients with a full-time job and patients with more decision latitude. Patients in a management position and patients with more social support had a shorter time to RTW. Severity of depression was not predictive for the time to RTW. HRQoL measured by the SF-36 was a significant predictor for the time to RTW. Conclusion: HRQoL emerged as a significant predictor for the time to RTW. However, severity of depression was not predictive for the time to RT

Recently, several checklists systematically assessed factors that affect the transferability of costeffectiveness (CE) studies between jurisdictions. The role of the threshold value for a QALY has been given little consideration in these checklists, even though the importance of a factor as a cause of between country differences in CE depends on this threshold. In this paper, we study the impact of the willingness-to-pay (WTP) per QALY on the importance of transferability factors in the case of smoking cessation support (SCS). We investigated, for several values of the WTP, how differences between six countries affect the incremental net monetary benefit (INMB) of SCS. The investigated factors were demography, smoking prevalence, mortality, epidemiology and costs of smokingrelated diseases, resource use and unit costs of SCS, utility weights and discount rates. We found that when the WTP decreased, factors that mainly affect health outcomes became less important and factors that mainly effect costs became more important. With a WTP below €1,000, the factors most responsible for between country differences in INMB were resource use and unit costs of SCS and the costs of smoking-related diseases. Utility values had little impact. At a threshold above €10,000, between country differences were primarily due to different discount rates, utility weights and epidemiology of smoking-related diseases. Costs of smoking-related diseases had little impact. At all thresholds, demography had little impact. We concluded that, when judging the transferability of a CE study, we should consider the between country differences in WTP threshold values.