scholarly journals Problems and Promises of Health Technologies: The Role of Early Health Economic Modeling

2019 ◽  
Vol 8 (10) ◽  
pp. 575-582 ◽  
Author(s):  
Janneke P.C. Grutters ◽  
Tim Govers ◽  
Jorte Nijboer ◽  
Marcia Tummers ◽  
Gert Jan van der Wilt ◽  
...  
Keyword(s):  
Health Economic ◽  
Cost Effectiveness ◽  
Cost Savings ◽  
Cost Effective ◽  
Economic Modeling ◽  
Potential Cost ◽  
Health Technologies ◽  
Potential Benefits ◽  
Secondary Analyses ◽  
Early Health

Background: To assess whether early health economic modeling helps to distinguish those healthcare innovations that are potentially cost-effective from those that are not potentially cost-effective. We will also study what information is retrieved from the health economic models to inform further development, research and implementation decisions. Methods: We performed secondary analyses on an existing database of 32 health economic modeling assessments of 30 innovations, performed by our group. First, we explored whether the assessments could distinguish innovations with potential cost-effectiveness from innovations without potential cost-effectiveness. Second, we explored which recommendations were made regarding development, implementation and further research of the innovation. Results: Of the 30 innovations, 1 (3%) was an idea that was not yet being developed and 14 (47%) were under development. Eight (27%) innovations had finished development, and another 7 (23%) innovations were on the market. Although all assessments showed that the innovation had the potential to become cost-effective, due to improved patient outcomes, cost savings or both, differences were found in the magnitude of the potential benefits, and the likelihood of reaching this potential. The assessments informed how the innovation could be further developed or positioned to maximize its cost-effectiveness, and informed further research. Conclusion: The early health economic assessments provided insight in the potential cost-effectiveness of an innovation in its intended context, and the associated uncertainty. None of the assessments resulted in a firm ‘no-go’ recommendation, but recommendations could be provided on further research and development in order to maximize value for money.

scholarly journals Modeling in Early Stages of Technology Development: Is an Iterative Approach Needed? Comment on "Problems and Promises of Health Technologies: The Role of Early Health Economic Modeling"

2019 ◽  
Author(s):  
Michael F. Drummond
Keyword(s):  
Health Economic ◽  
Technology Development ◽  
Integrated Approach ◽  
Economic Modeling ◽  
Future Research ◽  
Iterative Approach ◽  
Health Technologies ◽  
Early Health ◽  
The Cost

A recent paper by Grutters et al makes the case for early health economic modeling in the development of health technologies. A number of examples of the value of early modeling are given, with analyses being performed at different stages in the development of several non-drug health technologies. This commentary acknowledges the contribution of the paper by Grutters et al and argues for an iterative and integrated approach to early modeling, assessing the cost-effectiveness of the technology, the value of future research and the interaction with the manufacturer’s pricing and revenue expectations.

scholarly journals Evaluating the potential costs and impact of digital health technologies for tuberculosis treatment support

2018 ◽  
Vol 52 (5) ◽  
pp. 1801363 ◽  
Author(s):  
Ntwali Placide Nsengiyumva ◽  
Benjamin Mappin-Kasirer ◽  
Olivia Oxlade ◽  
Mayara Bastos ◽  
Anete Trajman ◽  
...  
Keyword(s):  
Digital Health ◽  
Cost Savings ◽  
Cost Effective ◽  
Multidrug Resistant ◽  
Potential Cost ◽  
Health Technologies ◽  
Life Years ◽  
Message Service ◽  
Latent Tb ◽  
Latent Tb Infection

Ensuring adherence and support during treatment of tuberculosis (TB) is a major public health challenge. Digital health technologies could help improve treatment outcomes. We considered their potential cost and impact on treatment for active or latent TB in Brazil.Decision analysis models simulated two adult cohorts with 1) drug-susceptible active TB, and 2) multidrug-resistant TB, and two cohorts treated with isoniazid for latent TB infection (LTBI): 1) close contacts of persons with active TB, and 2) others newly diagnosed with LTBI. We evaluated four digital support strategies: two different medication monitors, synchronous video-observed therapy (VOT), and two-way short message service (SMS). Comparators were standard directly observed treatment for active TB and self-administered treatment for LTBI. Projected outcomes included costs (2016 US dollars), plus active TB cases and disability-adjusted life years averted among persons with LTBI.For individuals with active TB, medication monitors and VOT are projected to lead to substantial (up to 58%) cost savings, in addition to alleviating inconvenience and cost to patients of supervised treatment visits. For LTBI treatment, SMS and medication monitors are projected to be the most cost-effective interventions. However, all projections are limited by the scarcity of published estimates of clinical effect for the digital technologies.

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

2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Lytske Bakker ◽  
Katerina Vaporidi ◽  
Jos Aarts ◽  
William Redekop
Keyword(s):  
Intensive Care ◽  
Cost Effectiveness ◽  
Real Time ◽  
Cost Savings ◽  
Cost Effective ◽  
Potential Cost ◽  
Lifetime Horizon ◽  
Scenario Analyses ◽  
Life Years ◽  
The Impact

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.

scholarly journals Clinical biomarker innovation: when is it worthwhile?

2019 ◽  
Vol 57 (11) ◽  
pp. 1712-1720
Author(s):  
Anouck Kluytmans ◽  
Jaap Deinum ◽  
Kevin Jenniskens ◽  
Antonius Eduard van Herwaarden ◽  
Jolein Gloerich ◽  
...  
Keyword(s):  
Health Economic ◽  
Diagnostic Accuracy ◽  
Cost Effective ◽  
Economic Modeling ◽  
Added Value ◽  
Life Years ◽  
Clinical Biomarker ◽  
Early Health ◽  
Aldosterone To Renin Ratio ◽  
Effective Product

Abstract Background Choosing which biomarker tests to select for further research and development is not only a matter of diagnostic accuracy, but also of the clinical and monetary benefits downstream. Early health economic modeling provides tools to assess the potential effects of biomarker innovation and support decision-making. Methods We applied early health economic modeling to the case of diagnosing primary aldosteronism in patients with resistant hypertension. We simulated a cohort of patients using a Markov cohort state-transition model. Using the headroom method, we compared the currently used aldosterone-to-renin ratio to a hypothetical new test with perfect diagnostic properties to determine the headroom based on quality-adjusted life-years (QALYs) and costs, followed by threshold analyses to determine the minimal diagnostic accuracy for a cost-effective product. Results Our model indicated that a perfect diagnostic test would yield 0.027 QALYs and increase costs by €43 per patient. At a cost-effectiveness threshold of €20,000 per QALY, the maximum price for this perfect test to be cost-effective is €498 (95% confidence interval [CI]: €275–€808). The value of the perfect test was most strongly influenced by the sensitivity of the current biomarker test. Threshold analysis showed the novel test needs a sensitivity of at least 0.9 and a specificity of at least 0.7 to be cost-effective. Conclusions Our model-based approach evaluated the added value of a clinical biomarker innovation, prior to extensive investment in development, clinical studies and implementation. We conclude that early health economic modeling can be a valuable tool when prioritizing biomarker innovations in the laboratory.

scholarly journals Early Health Economic Modelling – Optimizing Development for Medical Device Developers? Comment on "Problems and Promises of Health Technologies: The Role of Early Health Economic Modeling"

2019 ◽  
Author(s):  
Conor Teljeur ◽  
Máirín Ryan
Keyword(s):  
Health Economic ◽  
Early Stage ◽  
Data Gathering ◽  
Economic Modeling ◽  
Economic Modelling ◽  
Negative Consequences ◽  
Health Technologies ◽  
Stage Of Development ◽  
Early Health

Abstract This commentary considers the positive and negative consequences of early economic modelling and explores potential future directions. Early economic modelling offers device manufacturers an opportunity to assess the potential value of an innovation at an early stage of development. Early modelling can direct resources into potentially viable technologies and reduce investment in technologies with limited prospect of value. However, it is unclear whether early modelling is sufficiently specific to identify innovations with low value. It may be that early modelling is more useful for directing data gathering to reduce decision uncertainty. Early modelling is of primary benefit to the manufacturer and may have both positive and negative consequences for reimbursement processes that should be considered

scholarly journals Expanding the Role of Early Health Economic Modelling in Evaluation of Health Technologies Comment on "Problems and Promises of Health Technologies: The Role of Early Health Economic Modeling"

2020 ◽  
Author(s):  
Carlo Federic ◽  
Aleksandra Torbica
Keyword(s):  
Health Economic ◽  
Early Stage ◽  
Economic Modeling ◽  
Evaluation Framework ◽  
Economic Modelling ◽  
Health Technologies ◽  
Innovative Methods ◽  
Healthcare Decision Making ◽  
Early Health

In this commentary, we discuss early stage assessments of innovative medical technologies both in terms of methods applied as well as their use in healthcare decision-making. We argue that cost-effectiveness alone may be too reductive if taken as the only decision rule, and it would benefit from being used within a broader evaluation framework. We discuss innovative methods which may contribute to better estimate the potential costs and consequences of a technology in the absence of solid clinical data, as frequently the case in early assessments. Finally, we comment on the potential synergies which may take place should early economic models be used not only by technology developers alone but as a negotiating base during early dialogues with health technology assessment (HTA) bodies.

scholarly journals Transforming Disciplinary Traditions Comment on "Problems and Promises of Health Technologies: The Role of Early Health Economic Modeling"

2019 ◽  
Author(s):  
Pascale Lehoux ◽  
Hudson Silva
Keyword(s):  
Health Economic ◽  
Early Stage ◽  
Policy Research ◽  
Economic Modeling ◽  
Health Technologies ◽  
Societal Challenges ◽  
Health Innovations ◽  
Early Health ◽  
Value Of Health

Grutters et al show that economic assessments can inform the development of new health technologies at an early stage. This is an important contribution to health services and policy research, which implies a "shift away" from the more traditional forms of academic health economic modeling. Because transforming established disciplinary traditions is both valuable and demanding, we invite scholars to further the discussion on how the value of health innovations should be appraised in view of today’s societal challenges.

scholarly journals Increasing the Price of Alcohol as an Obesity Prevention Measure: The Potential Cost-Effectiveness of Introducing a Uniform Volumetric Tax and a Minimum Floor Price on Alcohol in Australia

Nutrients ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 603
Author(s):  
Ella Robinson ◽  
Phuong Nguyen ◽  
Heng Jiang ◽  
Michael Livingston ◽  
Jaithri Ananthapavan ◽  
...  
Keyword(s):  
Cost Effectiveness ◽  
Obesity Prevention ◽  
Cost Savings ◽  
Cost Effective ◽  
Alcoholic Beverages ◽  
Alcohol Intervention ◽  
Potential Cost ◽  
Uncertainty Interval ◽  
Floor Price ◽  
Life Years

The objective of this study was to estimate, from an obesity prevention perspective, the cost-effectiveness of two potential policies that increase the price of alcohol in Australia: a volumetric tax applied to all alcohol (Intervention 1) and a minimum unit floor price (Intervention 2). Estimated changes in alcoholic drink consumption and corresponding changes in energy intake were calculated using the 2011–12 Australian Health Survey data, published price elasticities, and nutrition information. The incremental changes in body mass index (BMI), BMI-related disease outcomes, healthcare costs, and Health Adjusted Life Years (HALYs) were estimated using a validated model. Costs associated with each intervention were estimated for government and industry. Both interventions were estimated to lead to reductions in mean alcohol consumption (Intervention 1: 20.7% (95% Uncertainty Interval (UI): 20.2% to 21.1%); Intervention 2: 9.2% (95% UI: 8.9% to 9.6%)); reductions in mean population body weight (Intervention 1: 0.9 kg (95% UI: 0.84 to 0.96); Intervention 2: 0.45 kg (95% UI: 0.42 to 0.48)); HALYs gained (Intervention 1: 566,648 (95% UI: 497,431 to 647,262); Intervention 2: 317,653 (95% UI: 276,334 to 361,573)); and healthcare cost savings (Intervention 1: $5.8 billion (B) (95% UI: $5.1B to $6.6B); Intervention 2: $3.3B (95% UI: $2.9B to $3.7B)). Intervention costs were estimated as $24M for Intervention 1 and $30M for Intervention 2. Both interventions were dominant, resulting in health gains and cost savings. Increasing the price of alcohol is likely to be cost-effective from an obesity prevention perspective in the Australian context, provided consumers substitute alcoholic beverages with low or no kilojoule alternatives.

Analytical decision model for the cost-effective management of solitary pulmonary nodules.

1998 ◽  
Vol 16 (6) ◽  
pp. 2113-2125 ◽  
Author(s):  
S S Gambhir ◽  
J E Shepherd ◽  
B D Shah ◽  
E Hart ◽  
C K Hoh ◽  
...  
Keyword(s):  
Cost Effectiveness ◽  
Decision Analysis ◽  
Cost Savings ◽  
Pulmonary Nodules ◽  
Cost Effective ◽  
Solitary Pulmonary Nodules ◽  
Potential Cost ◽  
Positron Emission ◽  
The Cost ◽  
Analysis Models

PURPOSE AND METHODS Multiple strategies are currently being used to manage patients who present with indeterminate solitary pulmonary nodules (SPN). We have used decision-analysis models to assess the cost-effectiveness of various strategies for the diagnosis and management of SPN. Four decision strategies were compared: a wait and watch strategy, a surgery strategy, a computed tomography (CT)-based strategy, and a CT-plus-positron emission tomography (PET) strategy. An incremental cost-effectiveness ratio (ICER) was used to compare all strategies to the wait and watch strategy. RESULTS A CT-plus-PET strategy was the most cost-effective over a large pretest likelihood (probability of having a malignant nodule), with a range of 0.12 to 0.69. Furthermore, within this likelihood range, the potential cost savings of using the CT-plus-PET strategy over the CT strategy ranged from $91 to $2,200 per patient. This translates to a yearly national savings of approximately $62.7 million. CONCLUSION Decision-analysis modeling indicates the potential cost-effectiveness of [18F]2-fluoro-2-deoxy-D-glucose (FDG)-PET in the management of SPN. Furthermore, the decision trees developed can be used to model various features of the management of SPN, including modeling the cost-effectiveness of other newly emerging technologies.

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