Estimating the costs of induced abortion in Uganda: a model-based analysis

BMC Public Health. 2011 Dec 6:11:904. doi: 10.1186/1471-2458-11-904.


Background: The demand for induced abortions in Uganda is high despite legal and moral proscriptions. Abortion seekers usually go to illegal, hidden clinics where procedures are performed in unhygienic environments by under-trained practitioners. These abortions, which are usually unsafe, lead to a high rate of severe complications and use of substantial, scarce healthcare resources. This study was performed to estimate the costs associated with induced abortions in Uganda.

Methods: A decision tree was developed to represent the consequences of induced abortion and estimate the costs of an average case. Data were obtained from a primary chart abstraction study, an on-going prospective study, and the published literature. Societal costs, direct medical costs, direct non-medical costs, indirect (productivity) costs, costs to patients, and costs to the government were estimated. Monte Carlo simulation was used to account for uncertainty.

Results: The average societal cost per induced abortion (95% credibility range) was $177 ($140-$223). This is equivalent to $64 million in annual national costs. Of this, the average direct medical cost was $65 ($49-86) and the average direct non-medical cost was $19 ($16-$23). The average indirect cost was $92 ($57-$139). Patients incurred $62 ($46-$83) on average while government incurred $14 ($10-$20) on average.

Conclusion: Induced abortions are associated with substantial costs in Uganda and patients incur the bulk of the healthcare costs. This reinforces the case made by other researchers--that efforts by the government to reduce unsafe abortions by increasing contraceptive coverage or providing safe, legal abortions are critical.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Abortion, Induced / economics*
  • Costs and Cost Analysis / methods
  • Female
  • Health Expenditures / statistics & numerical data
  • Hospital Costs* / statistics & numerical data
  • Humans
  • Medical Audit / economics
  • Monte Carlo Method
  • Pregnancy
  • Prospective Studies
  • Uganda