Operational modelling and its potential for facilitating in-country policy decision making on uptake and implementation of new tools

Newly developed diagnostic tools and algorithms face a number of barriers in effective implementation. Policy makers need to make rational decisions on whether to go ahead and invest in new innovations for health and how. Should a new diagnostic test replace or be used in combination with an existing method? What are the access costs to patients? Is it affordable and practical for the health system to continue to provide the new tool? What is the impact on community transmission? Failure to address these issues could lead to poor performance outcomes, unsustainable implementation and wasted resources.

Applied health research can help provide policy makers with the evidence they need in decision making with regard to the implementation of new and improved diagnostic tools and approaches. The Impact Assessment Framework, first described by Mann et al. in 2010, provides a checklist which permits researchers and policy makers to formulate questions and conduct research to answer those questions to provide a strong and comprehensive evidence base. The Framework consists of five layers: effectiveness, equity, health system, scale up and horizon scanning. Whilst the accuracy of a test may be known from trials (effectiveness) it may not always be clear which patients will benefit most e.g. will poorer patients be able to access the test (equity)? How does the broad health economic appraisal translate to each of the building blocks of the health system (health system)? How does the evidence from context-specific trials apply to the health system of a nation (scale up)? What about newer innovations yet to be endorsed by WHO (horizon scanning)?

Operational modelling, described by Professor Bertie Squire and Ivor Langley from the Liverpool School of Tropical Medicine in this HEART talk, provides a visual, cheap, adaptable and relatively rapid method of assessing the impact of scaling-up a new health innovation. Operational modeling can take account of interactions within the system e.g. bottlenecks that occur in the health system because of an interaction which can limit the capacity of a system. Cost-effectiveness of various scenarios can be assessed. Visualisation of the health system enables managers and policy makers to understand how accurate the model is and to validate its true representation of the system. Operational modelling can also be linked to transmission modelling. For example, the incidence of a disease will depend on how long the community is exposed to the disease which will depend on how long diagnosis takes.

Operational modelling was recently applied to assess the patient, health system and population effects of Xpert MTB/RIF and alternative diagnostics for tuberculosis in Tanzania (Langley et al. Lancet Global Health 2014). Integrated operational and transmission modelling predicted that full roll out of the new tuberculosis diagnostic text Xpert is a cost-effective option and has the potential to substantially reduce the national tuberculosis burden. The model also estimates the substantial level of funding that will need to be mobilized to translate this into sustained clinical practice over the medium term.

Prof Squire and Ivor Langley summarise that operational modelling is a practical and useful tool used in a relatively short time space to enable national decision makers to decide on whether and how to take up a new health innovation. The model permits policy makers to see how a new test may play out and suit their context. The model makes use of available data and uses estimates where data is lacking. Sensitivity to the estimates can be performed in order to provide evidence on where additional data collection is required to improve estimates.

About the speakers

Ivor Langley is an Operational Research Analyst working at LSTM since 2010. Previously he worked in Operational Research and related statistical modelling in manufacturing, retailing and as a consultant for over 14 years. He also worked for over nine years for a company that specializes in the process simulation software which he uses for his current research work.

Bertie Squire is a Professor of Clinical Tropical Medicine and Director of the Centre for Applied Health Research and Delivery at LSTM. Bertie’s research interests include improving access to services for the poor, including diagnosis and clinical care and collaborating with multiple disciplines to apply operational, implementation and health systems research to provide new solutions to major health challenges.

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