Modelling the impacts of new diagnostic tools for tuberculosis in developing countries to enhance policy decisions
Health Care Management Science
Clinical Group, Liverpool School of Tropical Medicine, Liverpool, United Kingdom; National Tuberculosis and Leprosy Programme, Ministry of Health and Social Welfare, Dar es Salaam, Tanzania; Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan
The introduction and scale-up of new tools for the diagnosis of Tuberculosis (TB) in developing countries has the potential to make a huge difference to the lives of millions of people living in poverty. To achieve this, policy makers need the information to make the right decisions about which new tools to implement and where in the diagnostic algorithm to apply them most effectively. These decisions are difficult as the new tools are often expensive to implement and use, and the health system and patient impacts uncertain, particularly in developing countries where there is a high burden of TB. The authors demonstrate that a discrete event simulation model could play a significant part in improving and informing these decisions. The feasibility of linking the discrete event simulation to a dynamic epidemiology model is also explored in order to take account of longer term impacts on the incidence of TB. Results from two diagnostic districts in Tanzania are used to illustrate how the approach could be used to improve decisions. © 2012 The Author(s).
algorithm; article; clinical pathway; cost benefit analysis; decision making; developing country; economics; health care delivery; health care policy; human; lung tuberculosis; management; microbiology; organization and management; sputum; theoretical model; time; Algorithms; Cost-Benefit Analysis; Critical Pathways; Decision Making; Delivery of Health Care; Developing Countries; Health Policy; Humans; Models, Theoretical; Policy Making; Sputum; Time Factors; Tuberculosis, Pulmonary