Topic Areas - Centre for Health Economics, University of York

CHE will fund studentships in one or more of the following eight topic areas:

Topic 1: Combining modern causal inference and cost‐effectiveness analysis for HTA. (PDF , 116kb)

Summary:
Patient-level real-world data (RWD) can be analysed to complement (even substitute, unavailable) randomised controlled trial (RCT) evidence and are increasingly used to inform licensing and reimbursement decisions concerning novel healthcare technologies. Recent advances in causal inference methodology and changes in the regulatory landscape mean that RWD can now be used to answer a broad range of questions of relevance to patients, clinicians and policy makers. Examples include how to
(a) assess the generalisability and transportability of RCT evidence to routine clinical practice;
(b) evaluate dynamic treatment regimens;
(c) estimate individualised treatment effects.
This PhD aims to integrate modern causal inference (e.g. g-computation and targeted maximum likelihood estimation) and economic evaluation methods to enhance their contribution to HTA decision making. The candidate will learn how to analyse RWD and derive relevant parameters to answer questions such as those highlighted in (a) to (c) above and use them to inform cost-effectiveness analysis. The project is embedded within the Economics of Stratified, Personalised and Precision Medicine research programme at CHE and the student will benefit from exposure to relevant ideas and methods used in our portfolio of projects. We also expect opportunities for wider interactions with colleagues working on policy and programme evaluation.

Topic 2: Economic evaluation of policies and interventions to improve the capacity (PDF , 91kb) and efficiency of health systems

Supervisors: Dina Jankovic, Marta Soares, Simon Walker

Over recent years there has been growing pressure on health systems to improve their efficiency. This situation has been further exacerbated by the COVID-19 pandemic, where the increased strain on health systems has resulted in reduced capacity and longer waiting times. Policies and interventions are needed to help improve the capacity and efficiency of health systems. These could include, for example, alternative stratification approaches to prioritize certain patient groups, technological solutions (e.g. use of triage systems for reducing waiting times), increased staffing or task shifting.
To help inform decision-making, evidence on the resource requirements, costs, benefits and impacts on population health of the alternative policies is required. Economic evaluation provides a framework for helping to inform the decisions.However, standard approaches may not be appropriate for the evaluation of the policies targeting improving health system delivery. For example, they do not reflect multiple constraints on care (financial and non-financial) or interdependence of the different components of the system. As a result, novel approaches to economic evaluation bringing in insights from other fields, such as operational research, should be considered so that evidence on the impacts on population health can be generated.
The aim of this PhD is to develop approaches to the economic evaluation of policies and interventions to improve the capacity and efficiency of health systems. The PhD could focus on a range of topics within this broad area including: evaluation of different policies in a specific setting, advancing the methods for modelling health systems for the purpose of economic evaluation, advancing the methods for characterising uncertainty and generalisability in health system models.

Topic 3: In silico studies in HTA (PDF , 40kb)

Supervisors: Marta Soares, David Glyn

Medical developments are increasingly made using advanced computation, including artificial intelligence methods, modelling and simulation. An important advancement in this area relates to in-silico clinical trials (ISTs), trials performed on cohorts of virtual patients using individualised computer simulations. A recently published exemplar is the FD-PASS study [https://doi.org/10.1038/s41467-021-23998-w], that evaluated flow diverters (a medical device) in the treatment of unruptured intracranial aneurysms. This work showed that the in silico replicated the results of in vivo randomised controlled trials, and even offered additional information about populations more likely to experience device failure.
By contributing with evidence on the effectiveness of health care technologies, ISTs have the potential to replace/augment the current in vivo clinical research portfolio, and even extend it, for example, by examining treatment effects over a range of patient subgroups. This may have a number of implications for Health Technology Assessment (HTA), including early HTA supporting Research and Development (R&D). For example, ISTs could be used alongside early modelling to optimise product development and support the design of in-vivo clinical research, generating better-targeted, higher value products and ensuring a higher chance of success for clinical research. ISTs could also be used as evidence within HTA assessments supporting Regulation and Reimbursement (R&R), accelerating patients’ access to innovative technologies.
ISTs therefore have the potential to be transformative to HTA policy and practice but to date there has been no research exploring the expected economic and societal value of these studies within an HTA framework. This PhD aims to use decision modelling to start developing this area, exploring methodological aspects of relevance to ISTs, including the need to reflect judgements over the validity of these studies explicitly as decision uncertainty.

Topic 4: Judging exchangeability of evidence to support HTA (PDF , 43kb)

Supervisors: Marta Soares, Pedro Saramago, Dina Jankovic

Closely after obtaining regulatory license for particular indications, health technologies are typically appraised by health systems for clinical and economic value in a particular indication, to support funding decisions. This is called Health Technology Assessment (HTA). Standard practice is that the evidence supporting HTA is product- and indication-specific, with the main source being the clinical trial that supported the regulatory approval process.
By focussing on a product in a particular indication, HTA appraisals are often subjected to a high level of evidential uncertainty on final endpoints, even where considerable evidence exists i) on the same technology for other indications (multi-indication context), or ii) on similar technologies (e.g. of the same therapeutic class) within the same indication. An MRC funded project, starting in July 2022, will explore evidence synthesis approaches to make better use of evidence across, as well as within, indications in oncology. This implies the sharing of information across indications, which would reduce decision uncertainty across the existing indications and providing more realistic predictions of the value of the oncology drug in future indications. An important component of this MRC work will be to develop methods for the formal elicitation of the judgment of clinical experts to support multi-indication HTA.
The PhD studentship on offer here will aim to extend the methods development beyond that of the MRC project which specifically looks at multi-indication oncology drugs. The PhD could focus on exploring the plausibility, and value, of considering exchangeability of evidence i) across products, for example, in informing the extrapolations required for determining the value of advanced medical products like CAR-T technologies [https://doi.org/10.3310/hta21070]; ii) for non-indication specific, non-therapeutic technologies such as Multi-Cancer Early Detection (MCED) tests, or iii) for site-agnostic products, for which decision making is not indication-specific and present an evidence-base built on multi-indication basket trials [https://doi.org/10.3310/hta25760]. This is likely to require a focus on evidence synthesis methods and/or expert elicitation methods, and the integration of methods development in these areas with decision modelling.

Topic 5: Evaluation of payment systems aimed at producing coordinated (PDF , 5kb) and integrated health and social care

Supervisors: Martin Chalkley, Nils Gutacker, Luigi Siciliani

Patients with complex needs receive health and social care from several providers such as general practitioners, hospitals, and care homes. These providers often work independently and without strong coordination, which may lead to inefficiencies and sub-optimal patient outcomes. To encourage more integrated care, decisionmakers in the UK and internationally have begun to implement episodic or bundled payments that cover the entire patient care pathway. However, the properties and design of such incentive payments has received limited attention in the health economics literature so far.
This PhD thesis will investigate the effectiveness and cost-effectiveness of payment schemes that encourage integrated care. The student will apply advanced econometric methods for programme evaluation to micro-level health care data from the English NHS. There is also scope to develop contract theory applied to integrated care arrangements that incentivise better health outcomes, efficient and cost-effective use of resources, and encourages team effort across providers.

Topic 6: Improving methods to evaluate the causal impact of health policies (PDF , 37kb) on population health

Supervisors: Nils Gutacker, Noemi Kreif, Simon Walker

Much health economic research focusses on estimating causal effects of policies from observational data, referred to as programme or impact evaluation. However, these evaluations do not usually identify the full (i.e. long-term) health impacts of policies on affected individuals, nor do they reflect the opportunity costs of policies in terms of their impact on wider population health as a result of the resources expended. Such information is important for policymakers that need to decide whether to implement, amend or discontinue health care policies.
Extending programme evaluations to full economic evaluations presents numerous analytical challenges and there are still few applied examples. Challenges include understanding the mechanisms of action, establishing the causal impacts of distinct components of a policy as well as their interdependencies, reflecting heterogeneity in impacts across groups, and capturing the opportunity costs [2]. As part of the PhD project, the student will develop potential solutions to one or more of these analytical challenges, drawing on insights from microeconomics, econometrics, machine learning and decision-analytic modelling. These will be demonstrated through applied case studies of health care policies in the UK and internationally.

Topic 7: Differentiated Services for Emergency Health Care (PDF , 97kb)

Supervisors: Martin Chalkley, Rita Santos, Peter Sivey

Emergency care is an important part of the National Health Service. In England, emergency care is provided by a network of providers differentiated by specialty, levels of capacity and expertise, from major Accident and Emergency (A&E) departments to Children’s Emergency departments, Minor Injury Units, Urgent Care Centres, Older Persons Rapid Access Clinics, and Walk-in Centres. These alternative services differ by their staffing (eg led by emergency medicine consultants, general practitioners, or nurses), specialism (general or specialised on particular patients such as children or the elderly) and in their ability to respond to life-threatening emergencies. There is a lack of evidence on how these services complement each other or substitute for each other in local areas where other factors such as travel distance, waiting times and the availability of general practitioner services and other NHS services also impact on demand.
This PhD thesis will use econometric analysis underpinned by economic theory to study the impact of changes in the composition of the emergency services network in local areas on the volume and casemix of attendances to major A&E departments. For example, in an area where a local hospital has had its emergency services changed from a major A&E Department to a minor injury unit, how does this affect the patient casemix at other nearby A&E departments?

Topic 8: Encouraging healthy behaviour change to alleviate chronic illness (PDF , 45kb) in lower- and middle-income countries

Supervisors: Susan Griffin, Sumit Mazumdar

Abstract:
Noncommunicable diseases (NCDs) pose a growing challenge for lower- and middle-income countries (LMICs), which already suffer a disproportionate number of global cases of NCDs. Globally, NCDs cause 71% of all deaths, of which 77% (31.4 million) occur in LMICs. Simultaneously, LMICs are facing a disease burden transition. The shifts caused by growing economic prosperity such as urbanization, demographic transitions, and globalization are catalysts of NCD growth. Likewise, the growing NCD burden is likely to impede progress in poverty reduction in LMICs, where individuals face underprepared health systems and low financial protection from medical costs. In addition, the financial impact and disease burden of NCDs are both regressive, with the poor disproportionately affected.
While determinants of the rates of NCDs are complex, the major risk factors and immediate determinants are behavioural: tobacco use, physical inactivity, the harmful use of alcohol and unhealthy diets. Evidence suggests behaviour change interventions could offer scalable, low-cost solutions in low-capacity settings. However, there is insufficient evidence on the determinants of unhealthy habits in these settings and on the effectiveness of different interventions seeking to encourage healthy behaviours.
In this PhD project, we seek a candidate to contribute to this evidence base, using quantitative analysis methods to evaluate the determinants of healthy behaviours with relevance to chronic disease and analysing the effectiveness of possible interventions.

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