Agent-based modelling for health economic evaluations and healthcare policy decisions

In this talk, we will introduce agent-based models (ABMs) and their use in economic evaluation of healthcare interventions. ABMs are often used in theoretical approaches with explanatory goals in mind. However, the flexibility of ABMs along with their ability to integrate diverse data sources also lends to a data-driven approach that can be used to model healthcare with predictive goals, to inform policy and decision making. That is the realm of health-economics, which has been primarily concerned with measuring the effectiveness, value, and efficiency of healthcare systems, services, and interventions. However, increasing demand for evidence-based decision making globally is driving a need for innovation in the field. For example, most trial data on the efficacy of interventions comes from high income countries, and we need to contextualize evaluations to consider local populations and healthcare systems. Furthermore, we have new goals and criteria in mind: The United Nation’s Sustainable Development Goals have highlighted the importance of measuring the distribution of health in the population and the fairness of interventions. Working with ABMs provides modelling flexibility that can help in these areas. Our goal is to understand whether and how ABMs can contribute to healthcare evaluations and planning in sub-Saharan Africa and globally. We will use IndiaSim—a data-driven ABM of the Indian population and its utilization of the healthcare system—and its application in economic evaluations as an example. IndiaSim has been used to publish evaluations of interventions such as public financing of epilepsy treatment, developing water and sanitation infrastructure to reduce the burden of diarrheal disease, and expanding India’s Universal Immunization Programme. We will reflect on the challenges posed by working with data-driven ABMs; these challenges are particularly acute in low- and middle-income countries, where data is often limited. We will also suggest useful resources for beginning to work with ABMs

Agent-based modelling for health economic evaluations and healthcare policy decisions

In this talk, we will introduce agent-based models (ABMs) and their use in economic evaluation of healthcare interventions. ABMs are often used in theoretical approaches with explanatory goals in mind. However, the flexibility of ABMs along with their ability to integrate diverse data sources also lends to a data-driven approach that can be used to model healthcare with predictive goals, to inform policy and decision making. That is the realm of health-economics, which has been primarily concerned with measuring the effectiveness, value, and efficiency of healthcare systems, services, and interventions. However, increasing demand for evidence-based decision making globally is driving a need for innovation in the field. For example, most trial data on the efficacy of interventions comes from high income countries, and we need to contextualize evaluations to consider local populations and healthcare systems. Furthermore, we have new goals and criteria in mind: The United Nation’s Sustainable Development Goals have highlighted the importance of measuring the distribution of health in the population and the fairness of interventions. Working with ABMs provides modelling flexibility that can help in these areas. Our goal is to understand whether and how ABMs can contribute to healthcare evaluations and planning in sub-Saharan Africa and globally. We will use IndiaSim—a data-driven ABM of the Indian population and its utilization of the healthcare system—and its application in economic evaluations as an example. IndiaSim has been used to publish evaluations of interventions such as public financing of epilepsy treatment, developing water and sanitation infrastructure to reduce the burden of diarrheal disease, and expanding India’s Universal Immunization Programme. We will reflect on the challenges posed by working with data-driven ABMs; these challenges are particularly acute in low- and middle-income countries, where data is often limited. We will also suggest useful resources for beginning to work with ABMs

Potential impact of introducing the pneumococcal conjugate vaccine into national immunization programmes : an economic-epidemiological analysis using data from India

Pneumococcal pneumonia causes an estimated 105,000 child deaths in India annually. The planned introduction of the serotype-based pneumococcal conjugate vaccine (PCV) is expected to avert child deaths, but the high cost of PCV relative to current vaccines provided under the Universal Immunization Programme has been a concern. Cost-effectiveness studies from high-income countries are not readily comparable because of differences in the distribution of prevalent serotypes, population, and health systems. We used IndiaSim, an agent-based simulation model representative of the Indian population and health system, to model the dynamics of Streptococcus pneumoniae. We estimate that PCV13 introduction would cost approximately $240 million and avert$48.7 million in out-of-pocket expenditures and 34,800 (95% confidence interval [CI] 29,600–40,800) deaths annually assuming coverage levels and distribution similar to DPT (diphtheria, pertussis, and tetanus) vaccination (~77%). Introducing the vaccine protects the population, especially the poorest wealth quintile, from potentially catastrophic expenditure. The net-present value of predicted money-metric value of insurance for 20 years of vaccination is $160,000 (95$151,000–$168,000) per 100,000 under-fives, and almost half of this protection is for the bottom wealth quintile ($78,000; 95% CI 70,800—84,400). Extending vaccination to 90% coverage averts additional lives and provides additional financial risk protection. Our estimates are sensitive to immunity parameters in our model; however, our assumptions are conservative, and if willingness to pay per years of life lost (YLL) averted is $228 or greater then introducing the vaccine is more cost-effective than our baseline (no vaccination) in more than 95% of simulations

Combining system dynamics and agent-based models to study transmission of healthcare-associated infections in long-term care facilities

Transmission of healthcare-associated infections (HAIs) in long-term care facilities (LTCFs) possesses many distinct characteristics that are not well understood. While HAIs are primarily disseminated via contacts between healthcare workers and patients in hospitals, patient-patient and patient-visitor contacts play an important role in spreading HAIs in LTCFs. The increased risk of transmission through these routes results from frequent aggregation of residents in common areas and family visitation. Additionally, the elderly population living in LTCFs who are frequently readmitted to a hospital might acquire colonization or infection of resistant organisms while being hospitalised and transmit these organisms to other residents when returning to the LTCF and vice versa. Systems simulation modelling methods including system dynamics (SD), discreteevent simulation and agent-based models (ABM) have long been used to study the problems of HAIs in hospitals. However, the existing models do not capture the impacts of patient-patient and patient-visitor contacts and frequent hospital readmission of residents upon transmission of HAIs in LTCFs. Therefore, we develop a hybrid simulation model that combines the methodological strengths of SD and ABM to address this gap. ABM is used to model the transmission of HAIs in LTCFs taking into account heterogeneous contacts between individuals. The spread of HAIs in a hospital whose patients are transferred to and from the LTCF is modelled using SD. Information exchange between the SD and ABM components includes data on the number of patients transferred from one setting to the other, and their status of infection

Challenges of infection prevention and control in Scottish long-term care facilities

Residents living in long-term care facilities (LTCFs) are at high risk of contracting healthcare-associated infections (HAIs). The unique operational and cultural characteristics of LTCFs and the currently evolving models of healthcare delivery in Scotland create great challenges for infection prevention and control (IPC). Existing literature that discusses the challenges of infection control in LTCFs focuses on operational factors within a facility and does not explore the challenges associated with higher levels of management and the lack of evidence to support IPC practices in this setting. 1-7 Here, we provide a broader view of challenges faced by LTCFs in the context of the current health and social care models in Scotland. Many of these challenges are also faced in the rest of the United Kingdom and internationally

Self-enforcing regional vaccination agreements

In a highly interconnected world, immunizing infections are a transboundary problem, and their control and elimination require international cooperation and coordination. In the absence of a global or regional body that can impose a universal vaccination strategy, each individual country sets its own strategy. Mobility of populations across borders can promote free-riding, because a country can benefit from the vaccination efforts of its neighbours, which can result in vaccination coverage lower than the global optimum. Here we explore whether voluntary coalitions that reward countries that join by cooperatively increasing vaccination coverage can solve this problem. We use dynamic epidemiological models embedded in a game-theoretic framework in order to identify conditions in which coalitions are self-enforcing and therefore stable, and thus successful at promoting a cooperative vaccination strategy. We find that countries can achieve significantly greater vaccination coverage at a lower cost by forming coalitions than when acting independently, provided a coalition has the tools to deter free-riding. Furthermore, when economically or epidemiologically asymmetric countries form coalitions, realized coverage is regionally more consistent than in the absence of coalitions

Reduced burden of childhood diarrheal diseases through increased access to water and sanitation in India : a modeling analysis

Each year, more than 300,000 children in India under the age of five years die from diarrheal diseases. Clean piped water and improved sanitation are known to be effective in reducing the mortality and morbidity burden of diarrhea but are not yet available to close to half of the Indian population. In this paper, we estimate the health benefits (reduced cases of diarrheal incidence and deaths averted) and economic benefits (measured by out-of-pocket treatment expenditure averted and value of insurance gained) of scaling up the coverage of piped water and improved sanitation among Indian households to a near-universal 95% level. We use IndiaSim, a previously validated, agent-based microsimulation platform to model disease progression and individual demographic and healthcare-seeking behavior in India, and use an iterative, stochastic procedure to simulate health and economic outcomes over time. We find that scaling up access to piped water and improved sanitation could avert 43,352 (95% uncertainty range [UR] 42,201-44,504) diarrheal episodes and 68 (95% UR 62-74) diarrheal deaths per 100,000 under-5 children per year, compared with the baseline. We estimate a saving of (in 2013 US$)$357,788 (95% $345,509-$370,067) in out-of-pocket diarrhea treatment expenditure, and $1646 (95$1603-$1689) in incremental value of insurance per 100,000 under-5 children per year over baseline. The health and financial benefits are highly progressive, i.e. they reach poorer households more. Thus, scaling up access to piped water and improved sanitation can lead to large and equitable reductions in the burden of childhood diarrheal diseases in India

Optimal subscription models to pay for antibiotics

Novel subscription payment schemes are one of the approaches being explored to tackle the threat of antimicrobial resistance. Under these schemes, some or all of the payment is made via a fixed "subscription" payment, which provides a funder unlimited access to the treatment for a specific duration, rather than relying purely on a price per pill. Subscription-based schemes guarantee pharmaceutical firms income that incentivises investment in developing new antibiotics, and can promote responsible stewardship. From the pharmaceutical perspective, revenue is disassociated from sales, removing benefits from push marketing strategies. We investigate this from the funder perspective, and consider that the funder plays a key role in promoting responsible antibiotic stewardship by choosing the price per pill for providers such that this encourages appropriate antibiotic use. This choice determines the payment structure, and we investigate the impact of this choice through the lens of social welfare. We present a mathematical model of subscription payment schemes, explicitly featuring fixed and volume-based payment components for a given treatment price. Total welfare returned at a societal level is then estimated (incorporating financial costs and monetised benefits). We consider a practical application of the model to development of novel antibiotic treatment for Gonorrhoea, and examine the optimal treatment price under different parameterisations. Specifically, we analyse two contrasting scenarios - one where a new antibiotic's prioritised role is reducing transmission, and one where a more pressing requirement is conserving the antibiotic as an effective last defence. Critically, this analysis demonstrates that effective roll-out of a subscription payment scheme for a new antibiotic requires a comprehensive assessment of the benefits gained from treatment. We discuss the insights this work presents on the nature of these payment schemes, and how these insights can enable decision-makers to take the first steps in determining effective structuring of subscription payment schemes

Ambulatory emergency care

Background Emergency Department (ED) crowding is an increasing problem internationally. Causes are complex but analysis in the UK points to patients waiting for admission or discharge predominating as opposed to increasing attendances or inappropriate use of services . Clinical teams specialising in Acute Medicine in the UK promote a model of care to manage patients without the need for admission into a hospital bed and limit attendance to ED - Ambulatory Emergency Care (AEC) . The Netherlands, Australia & New Zealand have taken a similar route by developing Acute Medicine as a speciality with Acute Medical Units (AMU) delivering care as an alternative to ED, but they have yet to evolve the model to provide AEC to the same spectrum of medical conditions as seen in the UK . This work evaluates what international teams looking to adopt the AEC model to improve ED flow and outcomes can learn from the UK experience. Methods International, systematic literature search of current evidence base in the delivery of AEC:-Emergency Care flowSystem-wide flow-System-wide costs-Patients outcomes - clinical & experience-Enablers and barriers to successful models-Comparable international models Results Search results did not yield many papers for review or to accommodate a full international comparison. Published evidence around AEC is lacking and, as a result, and there are no agreed measures of successful models of AEC. Evidence of success is limited to case studies, conference proceedings and local audit. Yearly snap-shop audit in the UK appear to show improvement in conversion of patients from in-patient to AEC assessment on arrival to hospital (bypassing beds) following uptake of the model, but no data concerning direct impact on system-wide or ED flow was available. No robust cost-effectiveness studies were found. Published evidence of patient satisfaction is limited to online, anecdotal reports, but the majority of reports are positive with most dissatisfaction resulting from lack of communication and long waiting times . Clinical outcomes are confined to indirect system-wide measures with no published evidence of clinical or quality outcomes of use to evaluate AEC models for further learning. No published studies of the international application of AEC were found for comparison.  Conclusion AEC is promoted as best practice in the UK to minimise hospital admissions, improve emergency care flow, reduce costs of admission, prevent harm by avoiding admission, and provide patient-centred care according to clinical need and patient preference. Evidence of conversion of care from in-patient to out-patient is clear and the philosophy of AEC holds promise for preventing unnecessary hospital admission but the current evidence-base to support the intended flow, cost, clinical & quality outcomes is lacking, highlighting the need for research in this emerging, internationally important field of practice

Interfaces between SD and ABM modules in a hybrid model

Modelers in various disciplines have applied system dynamics (SD) and agent-based models (ABM) to support decision-makers in managing complex adaptive systems. Combining these methods in a hybrid simulation offers an opportunity to overcome the challenges that modelers face using SD or ABM alone. It also provides a complementary view and rich insight into the problems that modelers investigate. Hence, this approach can offer solutions to a plethora of systems problems. One of the limitations of existing frameworks that guide the process of combining SD and ABM is the lack of detailed guidance describing how the two methods can interact and exchange information. This paper provides guidance for interfacing these simulation modeling methods in a hybrid simulation. In this guidance, we describe interface approaches to exchanging information for different types of information flow between SD and ABM