title: Risk-based versus alternative algorithms for antibiotic prophylaxis among women seeking early suction abortion: a cost-effectiveness simulation.
abstract: BACKGROUND
  Particularly in resource-poor settings, simple, inexpensive, and cost-effective algorithms are needed to direct antibiotic prophylaxis to prevent sequelae of infections with Chlamydia trachomatis, Neisseria gonorrhoeae, and bacterial vaginosis-associated organisms among women undergoing abortion.
  
  
  OBJECTIVE
  To assess the prevalence of and risk factors for infections among women seeking abortion in Bali, Indonesia, and to use these data in designing a cost-effective risk-based prophylaxis algorithm.
  
  
  METHODS
  A cross-sectional analysis and data-based simulation of risk-based and alternative prophylaxis algorithms were performed.
  
  
  RESULTS
  The risk-based algorithm would have provided prophylaxis to 70% (95% CI, 53-83%) of women with cervical infection, 64% (95% CI, 54-74%) of those with bacterial vaginosis, and 57% (95% CI, 42-72%) of those with trichomoniasis. For cervical infection, the algorithm was more cost effective than all others evaluated. The cost-effectiveness was acceptable for bacterial vaginosis.
  
  
  CONCLUSIONS
  Risk-based algorithms may be cost effective in identifying women likely to benefit from preabortion prophylaxis. Prospective evaluation is needed to validate these findings.
authors.affiliation: Department of Preventive Medicine and Biometrics, Uniformed Services University of the Health Sciences, Bethesda, Maryland, USA.
authors.forename: H B
authors.initials: HB
authors.lastname: Friedman
authors.forename: T L
authors.initials: TL
authors.lastname: Gift
authors.forename: I
authors.initials: I
authors.lastname: Susanti
authors.forename: J N
authors.initials: JN
authors.lastname: Wasserheit
mesh_terms: D000028:Abortion, Induced / Q000009:adverse effects*; D000328:Adult; D000465:Algorithms; D019072:Antibiotic Prophylaxis / Q000191:economics*; D003362:Cost-Benefit Analysis; D003430:Cross-Sectional Studies; D003663:Decision Trees; D005260:Female; D006801:Humans; D007214:Indonesia / Q000453:epidemiology; D008507:Medically Underserved Area; D016017:Odds Ratio; D000292:Pelvic Inflammatory Disease / Q000209:etiology / Q000517:prevention & control*; D011247:Pregnancy; D011261:Pregnancy Trimester, First; D015995:Prevalence; D012307:Risk Factors; D011795:Surveys and Questionnaires; D014247:Trichomonas Vaginitis / Q000453:epidemiology*; D002577:Uterine Cervical Diseases / Q000453:epidemiology*; D016585:Vaginosis, Bacterial / Q000453:epidemiology*