A tutorial on value-based adaptive designs: Could a value-based sequential two-arm design have created more health economic value for the Big CACTUS trial?

OBJECTIVES: Value-based trials aim to maximize the expected net benefit by balancing technology adoption decisions and clinical trial costs. Adaptive trials offer additional efficiency. This paper provides guidance on determining whether a value-based sequential design is the best option for an adaptive two-arm trial, illustrated through a case study. METHODS: We outline four steps for the value-based sequential approach. The case study re-evaluates the Big CACTUS trial design using pilot trial data and a model-based health economic analysis. Expected net benefit is computed for (a) original fixed design, (b) value-based design with fixed sample size, and (c) optimal value-based sequential design with adaptive stopping. We compare pre-trial modelling with actual Big CACTUS trial results. RESULTS: Over ten years, the adoption decision would impact approximately 215,378 patients. Pre-trial modelling shows that the expected net benefit minus costs is (a) £102m for the original fixed design, (b) £107m (+5.3% higher) for the value-based design with optimal fixed sample size, and (c) £109m (+6.7% higher) for the optimal value-based sequential design with maximum sample size of 435 per arm. Post hoc analysis using actual Big CACTUS trial data indicates that the value-adaptive trial with a maximum sample size of 95 participant pairs wouldn't have stopped early. Bootstrap simulations reveal a 9.76% probability of early completion with n=95, compared to 31.50% with n=435. CONCLUSIONS: The four-step approach to value-based sequential two-arm design with adaptive stopping was successfully implemented. Further application of value-based adaptive approaches could be useful to assess efficiency of alternative study designs.

A quality improvement study on how a simulation model can help decision making on organization of ICU wards.

BACKGROUND: Intensive Care Unit (ICU) capacity management is essential to provide high-quality healthcare for critically ill patients. Yet, consensus on the most favorable ICU design is lacking, especially whether ICUs should deliver dedicated or non-dedicated care. The decision for dedicated or non-dedicated ICU design considers a trade-off in the degree of specialization for individual patient care and efficient use of resources for society. We aim to share insights of a model simulating capacity effects for different ICU designs. Upon request, this simulation model is available for other ICUs. METHODS: A discrete event simulation model was developed and used, to study the hypothetical performance of a large University Hospital ICU on occupancy, rejection, and rescheduling rates for a dedicated and non-dedicated ICU design in four different scenarios. These scenarios either simulate the base-case situation of the local ICU, varying bed capacity levels, potential effects of reduced length of stay for a dedicated design and unexpected increased inflow of unplanned patients. RESULTS: The simulation model provided insights to foresee effects of capacity choices that should be made. The non-dedicated ICU design outperformed the dedicated ICU design in terms of efficient use of scarce resources. CONCLUSIONS: The choice to use dedicated ICUs does not only affect the clinical outcome, but also rejection- rescheduling and occupancy rates. Our analysis of a large university hospital demonstrates how such a model can support decision making on ICU design, in conjunction with other operation characteristics such as staffing and quality management.

Giving more detailed information about health insurance encourages consumers to choose compromise options.

Introduction: To investigate how the provision of additional information about the health events and procedures covered by a healthcare plan affect the level of coverage chosen by young adults taking their first full time job. Methods: University students were recruited for a study at two behavioral laboratories (one located at the University of Toronto and the other located at INSEAD-Sorbonne University in Paris) in which they imagine they are making choices about the healthcare coverage associated with the taking a new job in Chicago, Illinois. Every participant made choices in four categories: Physician Care, Clinical Care, Hospital Care, and Dental Care. Participants were randomly assigned to one of two conditions: Low Detail or High Detail coverage information and they chose between three levels of coverage: Basic, Enhanced, and Superior. The study took place in March 2017 with 120 students in Toronto and 121 students in Paris. Results: The provision of more detailed information about the health events and procedures covered by a healthcare plan leads to a compromise effect in which participants shift their choices significantly towards Enhanced (moderate coverage) from Basic (low coverage) and Superior (high coverage). The compromise effect was observed at both locations; however, Paris participants choose significantly higher levels of coverage than Toronto participants. Discussion: Providing more detail to employees about the health events and procedures covered by a healthcare plan will increase the fraction of employees who choose the intermediate level of coverage. It is beyond the scope of this study to conclude whether this is good or bad; however, in a context where employees gravitate to either insufficient or excessive coverage, providing additional detail may reduce these tendencies.

Interventions to reduce the risk of surgically transmitted Creutzfeldt-Jakob disease: a cost-effective modelling review.

BACKGROUND: Creutzfeldt-Jakob disease is a fatal neurological disease caused by abnormal infectious proteins called prions. Prions that are present on surgical instruments cannot be completely deactivated; therefore, patients who are subsequently operated on using these instruments may become infected. This can result in surgically transmitted Creutzfeldt-Jakob disease. OBJECTIVE: To update literature reviews, consultation with experts and economic modelling published in 2006, and to provide the cost-effectiveness of strategies to reduce the risk of surgically transmitted Creutzfeldt-Jakob disease. METHODS: Eight systematic reviews were undertaken for clinical parameters. One review of cost-effectiveness was undertaken. Electronic databases including MEDLINE and EMBASE were searched from 2005 to 2017. Expert elicitation sessions were undertaken. An advisory committee, convened by the National Institute for Health and Care Excellence to produce guidance, provided an additional source of information. A mathematical model was updated focusing on brain and posterior eye surgery and neuroendoscopy. The model simulated both patients and instrument sets. Assuming that there were potentially 15 cases of surgically transmitted Creutzfeldt-Jakob disease between 2005 and 2018, approximate Bayesian computation was used to obtain samples from the posterior distribution of the model parameters to generate results. Heuristics were used to improve computational efficiency. The modelling conformed to the National Institute for Health and Care Excellence reference case. The strategies evaluated included neither keeping instruments moist nor prohibiting set migration; ensuring that instruments were kept moist; prohibiting instrument migration between sets; and employing single-use instruments. Threshold analyses were undertaken to establish prices at which single-use sets or completely effective decontamination solutions would be cost-effective. RESULTS: A total of 169 papers were identified for the clinical review. The evidence from published literature was not deemed sufficiently strong to take precedence over the distributions obtained from expert elicitation. Forty-eight papers were identified in the review of cost-effectiveness. The previous modelling structure was revised to add the possibility of misclassifying surgically transmitted Creutzfeldt-Jakob disease as another neurodegenerative disease, and assuming that all patients were susceptible to infection. Keeping instruments moist was estimated to reduce the risk of surgically transmitted Creutzfeldt-Jakob disease cases and associated costs. Based on probabilistic sensitivity analyses, keeping instruments moist was estimated to on average result in 2.36 (range 0-47) surgically transmitted Creutzfeldt-Jakob disease cases (across England) caused by infection occurring between 2019 and 2023. Prohibiting set migration or employing single-use instruments reduced the estimated risk of surgically transmitted Creutzfeldt-Jakob disease cases further, but at considerable cost. The estimated costs per quality-adjusted life-year gained of these strategies in addition to keeping instruments moist were in excess of £1M. It was estimated that single-use instrument sets (currently £350-500) or completely effective cleaning solutions would need to cost approximately £12 per patient to be cost-effective using a £30,000 per quality-adjusted life-year gained value. LIMITATIONS: As no direct published evidence to implicate surgery as a cause of Creutzfeldt-Jakob disease has been found since 2005, the estimations of potential cases from elicitation are still speculative. A particular source of uncertainty was in the number of potential surgically transmitted Creutzfeldt-Jakob disease cases that may have occurred between 2005 and 2018. CONCLUSIONS: Keeping instruments moist is estimated to reduce the risk of surgically transmitted Creutzfeldt-Jakob disease cases and associated costs. Further surgical management strategies can reduce the risks of surgically transmitted Creutzfeldt-Jakob disease but have considerable associated costs. STUDY REGISTRATION: This study is registered as PROSPERO CRD42017071807. FUNDING: This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 24, No. 11. See the NIHR Journals Library website for further project information.

The aims of this report were to summarise evidence relating to surgically transmitted Creutzfeldt­Jakob disease and to explore the value for money of strategies to reduce the chance of any future surgically transmitted Creutzfeldt­Jakob disease cases. Current recommendations include keeping sets of surgical instruments together for high-risk operations and using separate instruments for people born after 1996. The project involved reviewing published papers, speaking with experts and building a computer model. The literature reviews found that Creutzfeldt­Jakob disease occurs in around 1­2 per million people and that no definite cases of surgically transmitted Creutzfeldt­Jakob disease have been observed since the 1970s. The reviews also looked for information on the possibility of patients being infected with Creutzfeldt­Jakob disease after having surgery on high-risk tissues, such as the brain and the back of the eye. They found that there was a great deal of uncertainty regarding who might have Creutzfeldt­Jakob disease, but not yet have symptoms, as well as the risk of transmission and the ability of strategies to reduce this risk. The computer model aimed to estimate value for money of different strategies to reduce the risks of surgically transmitted Creutzfeldt­Jakob disease. However, the reviews found that some of the numbers needed for the model were not known, so experts were asked to estimate this information instead along with the range of possible values. This information included the effectiveness of different cleaning practices and the chances of infected tissue being transmitted between patients undergoing high-risk surgery. The model found that keeping surgical instruments moist prior to cleaning was likely to save money and reduce the chance of future surgically transmitted Creutzfeldt­Jakob disease cases. However, additional measures, such as using only sets of single-use instruments, ensuring that instruments were kept together in their sets or using separate instruments for those born after 1996, appeared to be poor value for money.

The impact of changes in intensive care organization on patient outcome and cost-effectiveness-a narrative review.

The mortality rate of critically ill patients is high and the cost of the intensive (ICU) department is among the highest within the health-care industry. The cost will continue to increase because of the aging population in the western world. In the present review, we will discuss the impact of changes in ICU department organization on patient outcome and cost-effectiveness. The general perception that drug and treatment discoveries are the main drivers behind improved patient outcome within the health-care industry is in general not true. This is especially the case for the ICU department, in which the past decades' organizational changes were the main drivers behind the reduction of ICU mortality. These interventions were at the same time able to reduce cost, something which is rare for drug and treatment discoveries. The organization of the intensive care department has been changed over the past decades, resulting in better patient outcome and reduction of cost. Major changes are the implementation of the "closed format" and electronic patient record. Furthermore, we will present possible future options to improve the organization of the ICU department to further reduce mortality and cost such as pooling of dedicated ICU into mixed ICU and embedding business strategies such as lean and total quality management. Challenges are ahead as the ICU is taking up the largest share of national health-care expenditure, and with the aging of the population, this will continue to increase. Besides future improvements of organizational structures within the ICU, the focus should also be on the implementation of and compliance with proven beneficial organizational structures.

Mathematical model comparisons of potential non-typeable Haemophilus influenzae vaccine effects.

Vaccines to prevent acute otitis media (AOM) caused by non-typeable Haemophilus influenzae (NTHi) are under development. Because NTHi is highly variable and colonization rates are high, special vaccine characteristics and trial designs might be needed. We examined in mathematical models the equilibrium NTHi-caused AOM rate given hypothetical vaccines that generated immunity identical to corresponding maximal naturally acquired immunity. Vaccines were examined with single effects and combinations of immunity affecting (1) AOM rates given colonization (pathogenicity), (2) susceptibility to colonization, and (3) contagiousness given colonization. Percent reductions in AOM across all preschool children were (1) 34%, (2) 31%, (3) 9%, (1 and 2) 57%, (2 and 3) 50%, and (1, 2, and 3) 75%. Effects on children in daycare vs. not in daycare were (1) 18 vs. 48%, (2) -1 vs. 57%, (3) 13 vs. 5%, (1 and 2) 30 vs. 79%, (2 and 3) 33 vs. 60%, and (1, 2, and 3) 64 vs. 85%. Pure pathogenicity effects (1 alone) will need to be supplemented by transmission effects. The effects of susceptibility (2 alone) are diminished or negative because children protected against colonization have lower levels of immunity to (1) and (3) than unvaccinated children. For trials to predict population effects, both colonization and AOM outcomes must be studied and all three effects must be evaluated. This need arises because, unlike H. influenzae type B, high NTHi exposure diminishes cumulative vaccine effects and high colonization rates generate rapid accumulation of natural immunity that alters the indirect effects of vaccine immunity on transmission differently by age and daycare status.

A taxonomy of model structures for economic evaluation of health technologies.

Models for the economic evaluation of health technologies provide valuable information to decision makers. The choice of model structure is rarely discussed in published studies and can affect the results produced. Many papers describe good modelling practice, but few describe how to choose from the many types of available models. This paper develops a new taxonomy of model structures. The horizontal axis of the taxonomy describes assumptions about the role of expected values, randomness, the heterogeneity of entities, and the degree of non-Markovian structure. Commonly used aggregate models, including decision trees and Markov models require large population numbers, homogeneous sub-groups and linear interactions. Individual models are more flexible, but may require replications with different random numbers to estimate expected values. The vertical axis of the taxonomy describes potential interactions between the individual actors, as well as how the interactions occur through time. Models using interactions, such as system dynamics, some Markov models, and discrete event simulation are fairly uncommon in the health economics but are necessary for modelling infectious diseases and systems with constrained resources. The paper provides guidance for choosing a model, based on key requirements, including output requirements, the population size, and system complexity.

Breast cancer screening services: trade-offs in quality, capacity, outreach, and centralization.

This work combines and extends previous work on breast cancer screening models by explicitly incorporating, for the first time, aspects of the dynamics of health care states, program outreach, and the screening volume-quality relationship in a service system model to examine the effect of public health policy and service capacity decisions on public health outcomes. We consider the impact of increasing standards for minimum reading volume to improve quality, expanding outreach with or without decentralization of service facilities, and the potential of queueing due to stochastic effects and limited capacity. The results indicate a strong relation between screening quality and the cost of screening and treatment, and emphasize the importance of accounting for service dynamics when assessing the performance of health care interventions. For breast cancer screening, increasing outreach without improving quality and maintaining capacity results in less benefit than predicted by standard models.

Stochastic effects on endemic infection levels of disseminating versus local contacts.

The effects of two levels of mixing on endemic infection levels are shown to differ for identically conformed deterministic compartmental (DC) and stochastic compartmental (SC) models. Both DC and SC models give similar endemic levels when populations are large, immunity is short lived, and mixing is universal. But local transmissions and/or transient immunity decrease overall population infection levels in SC but not in DC models. DC models also fail to detect the greater effects of eliminating disseminating transmissions in comparison to eliminating local transmissions shown by SC models. These differences in model behavior arise because localities that encounter few infections from distant sites and that have stochastically low infection levels have decreased infection rates while localities with stochastically high levels of infection do not decrease the rate at which they lose infection. At the extreme this generates local stochastic die out with subsequent build up of susceptibility in SC but not DC models. This phenomenon should act upon all endemic infections that have changing geographic or social foci of infection. Neither standard epidemiological investigations nor sufficient-component cause models can capture these effects because they occur in the absence of differences between individuals.