Can Modeling of HIV Treatment Processes Improve Outcomes? Capitalizing on an Operations Research Approach to the Global Pandemic
Hollingsworth, Eric B.
O'Brien, Megan E.
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CitationXiong, Wei, Nathaniel Hupert, Eric B. Hollingsworth, Megan E. O'Brien, Jessica Fast, and William R. Rodriguez. 2008. Can modeling of HIV treatment processes improve outcomes? Capitalizing on an operations research approach to the global pandemic. BMC Health Services Research 8: 166.
AbstractBackground: Mathematical modeling has been applied to a range of policy-level decisions on resource allocation for HIV care and treatment. We describe the application of classic operations research (OR) techniques to address logistical and resource management challenges in HIV treatment scale-up activities in resource-limited countries. Methods: We review and categorize several of the major logistical and operational problems encountered over the last decade in the global scale-up of HIV care and antiretroviral treatment for people with AIDS. While there are unique features of HIV care and treatment that pose significant challenges to effective modeling and service improvement, we identify several analogous OR-based solutions that have been developed in the service, industrial, and health sectors. Results: HIV treatment scale-up includes many processes that are amenable to mathematical and simulation modeling, including forecasting future demand for services; locating and sizing facilities for maximal efficiency; and determining optimal staffing levels at clinical centers. Optimization of clinical and logistical processes through modeling may improve outcomes, but successful OR-based interventions will require contextualization of response strategies, including appreciation of both existing health care systems and limitations in local health workforces. Conclusion: The modeling techniques developed in the engineering field of operations research have wide potential application to the variety of logistical problems encountered in HIV treatment scale-up in resource-limited settings. Increasing the number of cross-disciplinary collaborations between engineering and public health will help speed the appropriate development and application of these tools.
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