Ngoc Do_Venetoclax plus Obinutuzumab vs Chlorambucil plus Obinutuzumab_Cost-Effectiveness Analysis Model.xlsm

The excel model details all the assumptions, data inputs, data sources, and data analysis codes used to output the results represented in our article titled: "Cost-effectiveness of Venetoclax plus Obinutuzumab versus Chlorambucil plus Obinutuzumab for the first-line treatment of adult patients with chronic lymphocytic leukemia - an extended social view." Please see the Data appendix file to view detailed description of the model

VenO vs ClbO Model.xlsm

This is an excel model about cost-effectiveness analysis on VenO vs. ClbO for treatment-naive CLL patients under the Dutch extented societal perspective

Ngoc Do_Venetoclax plus Obinutuzumab vs Chlorambucil plus Obinutuzumab_Cost-Effectiveness Analysis Model.xlsm

The excel model details all the assumptions, data inputs, data sources, and data analysis codes used to output the results represented in our article titled: "Cost-effectiveness of Venetoclax plus Obinutuzumab versus Chlorambucil plus Obinutuzumab for the first-line treatment of adult patients with chronic lymphocytic leukemia - an extended social view." Please see the Data appendix file to view detailed description of the model

Additional file 2: Table S2. of The increasing importance of a continence nurse specialist to improve outcomes and save costs of urinary incontinence care: an analysis of future policy scenarios

Breakdown of the budgetary impact over a period of 3Â years. (XLSX 12Â kb

The increasing importance of a continence nurse specialist to improve outcomes and save costs of urinary incontinence care: an analysis of future policy scenarios

Abstract Background In an ageing population, it is inevitable to improve the management of care for community-dwelling elderly with incontinence. A previous study showed that implementation of the Optimum Continence Service Specification (OCSS) for urinary incontinence in community-dwelling elderly with four or more chronic diseases results in a reduction of urinary incontinence, an improved quality of life, and lower healthcare and lower societal costs. The aim of this study was to explore future consequences of the OCSS strategy of various healthcare policy scenarios in an ageing population. Methods We adapted a previously developed decision analytical model in which the OCSS new care strategy was operationalised as the appointment of a continence nurse specialist located within the general practice in The Netherlands. We used a societal perspective including healthcare costs (healthcare providers, treatment costs, insured containment products, insured home care), and societal costs (informal caregiving, containment products paid out-of-pocket, travelling expenses, home care paid out-of-pocket). All outcomes were computed over a three-year time period using two different base years (2014 and 2030). Settings for future policy scenarios were based on desk-research and expert opinion. Results Our results show that implementation of the OSCC new care strategy for urinary incontinence would yield large health gains in community dwelling elderly (2030: 2592–2618 QALYs gained) and large cost-savings in The Netherlands (2030: health care perspective: €32.4 Million - €72.5 Million; societal perspective: €182.0 Million - €250.6 Million). Savings can be generated in different categories which depends on healthcare policy. The uncertainty analyses and extreme case scenarios showed the robustness of the results. Conclusions Implementation of the OCSS new care strategy for urinary incontinence results in an improvement in the quality of life of community-dwelling elderly, a reduction of the costs for payers and affected elderly, and a reduction in time invested by carers. Various realistic policy scenarios even forecast larger health gains and cost-savings in the future. More importantly, the longer the implementation is postponed the larger the savings foregone. The future organisation of healthcare affects the category in which the greatest savings will be generated

The increasing importance of a continence nurse specialist to improve outcomes and save costs of urinary incontinence care: an analysis of future policy scenarios

Abstract Background In an ageing population, it is inevitable to improve the management of care for community-dwelling elderly with incontinence. A previous study showed that implementation of the Optimum Continence Service Specification (OCSS) for urinary incontinence in community-dwelling elderly with four or more chronic diseases results in a reduction of urinary incontinence, an improved quality of life, and lower healthcare and lower societal costs. The aim of this study was to explore future consequences of the OCSS strategy of various healthcare policy scenarios in an ageing population. Methods We adapted a previously developed decision analytical model in which the OCSS new care strategy was operationalised as the appointment of a continence nurse specialist located within the general practice in The Netherlands. We used a societal perspective including healthcare costs (healthcare providers, treatment costs, insured containment products, insured home care), and societal costs (informal caregiving, containment products paid out-of-pocket, travelling expenses, home care paid out-of-pocket). All outcomes were computed over a three-year time period using two different base years (2014 and 2030). Settings for future policy scenarios were based on desk-research and expert opinion. Results Our results show that implementation of the OSCC new care strategy for urinary incontinence would yield large health gains in community dwelling elderly (2030: 2592–2618 QALYs gained) and large cost-savings in The Netherlands (2030: health care perspective: €32.4 Million - €72.5 Million; societal perspective: €182.0 Million - €250.6 Million). Savings can be generated in different categories which depends on healthcare policy. The uncertainty analyses and extreme case scenarios showed the robustness of the results. Conclusions Implementation of the OCSS new care strategy for urinary incontinence results in an improvement in the quality of life of community-dwelling elderly, a reduction of the costs for payers and affected elderly, and a reduction in time invested by carers. Various realistic policy scenarios even forecast larger health gains and cost-savings in the future. More importantly, the longer the implementation is postponed the larger the savings foregone. The future organisation of healthcare affects the category in which the greatest savings will be generated

Additional file 2: Table S2. of The increasing importance of a continence nurse specialist to improve outcomes and save costs of urinary incontinence care: an analysis of future policy scenarios

Breakdown of the budgetary impact over a period of 3Â years. (XLSX 12Â kb

The potential of real-time analytics to improve care for mechanically ventilated patients in the intensive care unit: an early economic evaluation

Abstract Background Mechanical ventilation services are an important driver of the high costs of intensive care. An optimal interaction between a patient and a ventilator is therefore paramount. Suboptimal interaction is present when patients repeatedly demand, but do not receive, breathing support from a mechanical ventilator (> 30 times in 3 min), also known as an ineffective effort event (IEEV). IEEVs are associated with increased hospital mortality prolonged intensive care stay, and prolonged time on ventilation and thus development of real-time analytics that identify IEEVs is essential. To assist decision-making about further development we estimate the potential cost-effectiveness of real-time analytics that identify ineffective effort events. Methods We developed a cost-effectiveness model combining a decision tree and Markov model for long-term outcomes with data on current care from a Greek hospital and literature. A lifetime horizon and a healthcare payer perspective were used. Uncertainty about the results was assessed using sensitivity and scenario analyses to examine the impact of varying parameters like the intensive care costs per day and the effectiveness of treatment of IEEVs. Results Use of the analytics could lead to reduced mortality (3% absolute reduction), increased quality adjusted life years (0.21 per patient) and cost-savings (€264 per patient) compared to current care. Moreover, cost-savings for hospitals and health improvements can be incurred even if the treatment’s effectiveness is reduced from 30 to 10%. The estimated savings increase to €1,155 per patient in countries where costs of an intensive care day are high (e.g. the Netherlands). There is considerable headroom for development and the analytics generate savings when the price of the analytics per bed per year is below €7,307. Furthermore, even when the treatment’s effectiveness is 10%, the probability that the analytics are cost-effective exceeds 90%. Conclusions Implementing real-time analytics to identify ineffective effort events can lead to health and financial benefits. Therefore, it will be worthwhile to continue assessment of the effectiveness of the analytics in clinical practice and validate our findings. Eventually, their adoption in settings where costs of an intensive care day are high and ineffective efforts are frequent could yield a high return on investment

The potential of real-time analytics to improve care for mechanically ventilated patients in the intensive care unit: an early economic evaluation

Abstract Background Mechanical ventilation services are an important driver of the high costs of intensive care. An optimal interaction between a patient and a ventilator is therefore paramount. Suboptimal interaction is present when patients repeatedly demand, but do not receive, breathing support from a mechanical ventilator (> 30 times in 3 min), also known as an ineffective effort event (IEEV). IEEVs are associated with increased hospital mortality prolonged intensive care stay, and prolonged time on ventilation and thus development of real-time analytics that identify IEEVs is essential. To assist decision-making about further development we estimate the potential cost-effectiveness of real-time analytics that identify ineffective effort events. Methods We developed a cost-effectiveness model combining a decision tree and Markov model for long-term outcomes with data on current care from a Greek hospital and literature. A lifetime horizon and a healthcare payer perspective were used. Uncertainty about the results was assessed using sensitivity and scenario analyses to examine the impact of varying parameters like the intensive care costs per day and the effectiveness of treatment of IEEVs. Results Use of the analytics could lead to reduced mortality (3% absolute reduction), increased quality adjusted life years (0.21 per patient) and cost-savings (€264 per patient) compared to current care. Moreover, cost-savings for hospitals and health improvements can be incurred even if the treatment’s effectiveness is reduced from 30 to 10%. The estimated savings increase to €1,155 per patient in countries where costs of an intensive care day are high (e.g. the Netherlands). There is considerable headroom for development and the analytics generate savings when the price of the analytics per bed per year is below €7,307. Furthermore, even when the treatment’s effectiveness is 10%, the probability that the analytics are cost-effective exceeds 90%. Conclusions Implementing real-time analytics to identify ineffective effort events can lead to health and financial benefits. Therefore, it will be worthwhile to continue assessment of the effectiveness of the analytics in clinical practice and validate our findings. Eventually, their adoption in settings where costs of an intensive care day are high and ineffective efforts are frequent could yield a high return on investment

Extrapolating empirical long-term survival data: the impact of updated follow-up data and parametric extrapolation methods on survival estimates in multiple myeloma

Abstract Background In economic evaluations, survival is often extrapolated to smooth out the Kaplan-Meier estimate and because the available data (e.g., from randomized controlled trials) are often right censored. Validation of the accuracy of extrapolated results can depend on the length of follow-up and the assumptions made about the survival hazard. Here, we analyze the accuracy of different extrapolation techniques while varying the data cut-off to estimate long-term survival in newly diagnosed multiple myeloma (MM) patients. Methods Empirical data were available from a randomized controlled trial and a registry for MM patients treated with melphalan + prednisone, thalidomide, and bortezomib- based regimens. Standard parametric and spline models were fitted while artificially reducing follow-up by introducing database locks. The maximum follow-up for these locks varied from 3 to 13 years. Extrapolated (conditional) restricted mean survival time (RMST) was compared to the Kaplan-Meier RMST and models were selected according to statistical tests, and visual fit. Results For all treatments, the RMST error decreased when follow-up and the absolute number of events increased, and censoring decreased. The decline in RMST error was highest when maximum follow-up exceeded six years. However, even when censoring is low there can still be considerable deviations in the extrapolated RMST conditional on survival until extrapolation when compared to the KM-estimate. Conclusions We demonstrate that both standard parametric and spline models could be worthy candidates when extrapolating survival for the populations examined. Nevertheless, researchers and decision makers should be wary of uncertainty in results even when censoring has decreased, and the number of events has increased