Using system dynamics modelling to assess the economic efficiency of innovations in the public sector - a systematic review.

BACKGROUND: Decision-makers for public policy are increasingly utilising systems approaches such as system dynamics (SD) modelling, which test alternative interventions or policies for their potential impact while accounting for complexity. These approaches, however, have not consistently included an economic efficiency analysis dimension. This systematic review aims to examine how, and in what ways, system dynamics modelling approaches incorporate economic efficiency analyses to inform decision-making on innovations (improvements in products, services, or processes) in the public sector, with a particular interest in health. METHODS AND FINDINGS: Relevant studies (n = 29) were identified through a systematic search and screening of four electronic databases and backward citation search, and analysed for key characteristics and themes related to the analytical methods applied. Economic efficiency analysis approaches within SD broadly fell into two categories: as embedded sub-models or as cost calculations based on the outputs of the SD model. Embdedded sub-models within a dynamic SD framework can reveal a clear allocation of costs and benefits to periods of time, whereas cost calculations based on the SD model outputs can be useful for high-level resource allocation decisions. CONCLUSIONS: This systematic review reveals that SD modelling is not currently used to its full potential to evaluate the technical or allocative efficiency of public sector innovations, particularly in health. The limited reporting on the experience or methodological challenges of applying allocated efficiency analyses with SD, particularly with dynamic embedded models, hampers common learning lessons to draw from and build on. Further application and comprehensive reporting of this approach would be welcome to develop the methodology further.

Using a decision support systems computer simulation model to examine HIV and tuberculosis: the Russian Federation.

The aim of this paper is to describe the development and use of a computer simulation model that can be used as a Decision Support System (DSS) to tackle the critical public health issues of HIV and HIV-related tuberculosis in the Russian Federation. This country has recently witnessed an explosion of HIV infections and a worrying spread of the Multi-Drug Resistant form of Tuberculosis (MDRTB). The conclusions drawn are that a high population coverage with Highly Active Anti-Retroviral Treatment (HAART) (75% or higher), allied with high MDRTB cure rates, reduces cumulative deaths by 60%, with limited impact below this level. This research offers a simulation model that can be applied as a DSS by public health officials to inform policy making. By doing so, ways of controlling the spread of HIV and MDRTB and reduce mortality from these serious public health threats is provided.

High coverage with HAART is required to substantially reduce the number of deaths from tuberculosis: system dynamics simulation.

We used a system dynamics simulation model of the transmission dynamics of drug-sensitive tuberculosis (DSTB), multidrug-resistant tuberculosis (MDRTB) and HIV to estimate the impact of coverage with highly active antiretroviral therapy (HAART) and different cure rates for MDRTB in settings of explosive HIV epidemics and high MDRTB levels. Population coverage levels at 0%, 25%, 50%, 75% and 100% for HAART, and 5% and 80% of MDRTB treatment cure rates were simulated over a 10-year period and cumulative deaths from tuberculosis and HIV-associated tuberculosis were estimated for populations with latent tuberculosis, DSTB, MDRTB, HIV and HIV-associated tuberculosis. Depending on levels of HAART population coverage, increasing MDRTB cure rates from 5% to 80% reduces cumulative tuberculosis deaths by 1% and 13%. High population coverage with HAART (75% or higher), allied with high MDRTB cure rates, reduces cumulative deaths by 60%, with limited impact below this level. High coverage with HAART is required to substantially reduce the number of deaths from tuberculosis.

Impact of joined-up HIV harm reduction and multidrug resistant tuberculosis control programmes in Estonia: System dynamics simulation model.

In Eastern Europe and Central Asia (ECA) the control of tuberculosis, multidrug resistant tuberculosis (MDRTB) and human immunodeficiency virus (HIV) poses important public health challenges. We used system dynamics simulation to determine impact on cumulative HIV/AIDS, tuberculosis and HIV-associated-tuberculosis deaths, over 20 years, of harm-reduction programmes to reduce needle-sharing and injection-frequency amongst injecting drug users (IDUs) and multidrug resistant tuberculosis (MDRTB) control in a population with an explosive HIV epidemic in IDUs and high MDRTB prevalence. We estimate that the number of HIV-associated-deaths will decline by 30% with effective harm-reduction programmes but double if these are ineffective. In our model, effective MDRTB and HIV control reduces cumulative tuberculosis deaths by 54%, cumulative MDRTB deaths 15-fold and cumulative HIV-associated-tuberculosis-deaths 2-fold. Effective MDRTB control, without effective harm-reduction programmes, only reduce tuberculosis deaths by 22%. However, effective harm-reduction programme with a poor MDRTB control reduce cumulative tuberculosis deaths by 34%, MDRTB by 14% and HIV-associated-tuberculosis by 56%. Even with good control programmes for drug sensitive TB, neglecting harm reduction and MDRTB control will result in 50% more tuberculosis-related deaths than if both are effectively addressed. Effective harm-reduction programmes reduces cumulative deaths from tuberculosis more substantively than effective MDRTB control. Our finding have important policy implications for communicable disease policies in post-Soviet countries, which need to substantially change if they are to effectively address the emerging HIV and MDRTB epidemics.