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Predicting health care needs and costs at HIV/AIDS clinics in India

The spread of HIV/AIDS in India has been rapid. Current estimates suggest there are 4.1 million people living with HIV/AIDS. NGOs set up to help over-stretched and under-funded government hospitals have found themselves battling the disease with dwindling funds. The challenge is to find sources of funding to care for HIV/AIDS patients whilst dealing with the uncertainty of future health care costs in clinics and hospitals.

Researchers from the UK's University of Southampton addressed this problem by developing a simulation model. They worked under the guidance of health planners and clinicians at three different organisations in Mumbai: the Indian Health Organisation, which conducts AIDS awareness programmes and works with the city’s sex workers; the Unison Medicare research centre, a private clinic which attracts primarily middle class patients, and G. T. Hospital, a government funded hospital whose AIDS clinic typically attracts patients who cannot afford expensive private care.

In this paper the authors describe the model, which was designed to help predict the progress of the HIV epidemic and to calculate associated health care costs. They employed a simulation model, TOCHSIM, developed by the operational research group at the University of Southampton. The model is adapted to reflect the natural history of the disease and the diverse variety of subgroups of the Indian population. To allocate costs to individual patients, the researchers defined 'packages' of care, which include various tests and treatments. This enables it to take account of the variation in resource needs between patients. Once developed, the model was used to predict future numbers of patients and associated costs over 10 years.

The following example illustrates the use of the model for the Unison Medicare clinic:

Patients were divided into two subgroups, a high income and a low income group.
Patient records were used to classify patients into one of four clinical states.
An annual HIV/AIDS incidence growth rate of 5 percent was assumed.
Care packages were defined and the clinic provided costs for the various tests and drugs that it offers to its patients.
Doctors provided expert knowledge on the time, during a month, that patients take to move from one clinical state to the next.
The simulation predicted the numbers of patients in each clinical state over a 10 year period.

Data of this kind can help clinic managers to plan for the future health care needs of patients. They may also be a useful resource to help obtain future government or NGO funding to meet the predicted costs. The model also:

permits the use of user-defined variables, and is therefore flexible enough to be potentially used throughout India
helps clinics to examine different scenarios and to highlight mismatches between expected costs and existing levels of financial provision.

It is currently difficult to predict the likely growth rate of the epidemic as the model is limited by the inaccuracy of data on the incidence of HIV/AIDS in India. As the collection of data improves, it may be possible to adapt the model to predict incidence rates. This would enable clinics to predict numbers of new patients with greater accuracy.

Source(s):
‘A decision support system for the care of HIV and AIDS patients in India’, European Journal of Operational Research 147: 187-197, by P. R. Harper and A. K. Shahani, 2003

id21 Research Highlight: 23 March 2005

Further Information:
Paul R. Harper
School of Mathematics
University of Southampton
Highfield
Southampton SO17 1BJ
UK

Tel: +44 (0) 23 8059 2660
Fax: +44 (0) 23 8059 5147
Contact the contributor: p.r.harper@maths.soton.ac.uk

University of Southampton, UK

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