title: Optimal allocation of testing dollars: the example of HIV counseling, testing, and referral.
abstract: BACKGROUND
  Health screening programs can be represented as a pathway of sequential processes: offering a test, obtaining consent, conducting the test, providing results, and linking to appropriate care. Using the example of HIV testing, the authors explore the optimal targeting of funds within this pathway.
  
  
  METHODS
  The authors develop a microsimulation of HIV testing services and decompose the likelihood that an unidentified HIV-infected person will receive care into the probability of testing [P(test)] and the probability of follow-up [P(follow)] defined as returning for results and linking to care. The authors examine the clinical impact and cost-effectiveness of alternative investments in these component probabilities.
  
  
  RESULTS
  At 1% undiagnosed HIV prevalence, cost-effectiveness ratios for HIV testing cluster around $33,000/QALY (quality-adjusted life year) gained. A program with a yield of 0.16 via P(test)=0.20 and P(follow)=0.80 has a cost-effectiveness ratio of $32,900/QALY compared with $36,300/QALY for a program where P(test)=0.80 and P(follow)=0.20. Interventions that improve the probability of success in later stages in the testing pathway [P(follow)] are more cost-effective than investments devoted to earlier stages [P(test)].
  
  
  CONCLUSIONS
  Equivalent pathway outcomes in a screening program do not confer equal value. Limited screening resources are best targeted toward returning for results and linkage among those already identified with disease rather than offering testing to additional people.
authors.affiliation: Division of Infectious Disease, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston 02114, USA. rwalensky@partners.org
authors.forename: Rochelle P
authors.initials: RP
authors.lastname: Walensky
authors.forename: Milton C
authors.initials: MC
authors.lastname: Weinstein
authors.forename: Heather E
authors.initials: HE
authors.lastname: Smith
authors.forename: Kenneth A
authors.initials: KA
authors.lastname: Freedberg
authors.forename: A David
authors.initials: AD
authors.lastname: Paltiel
mesh_terms: D015492:AIDS Serodiagnosis / Q000191:economics / Q000706:statistics & numerical data*; D003198:Computer Simulation; D003266:Continuity of Patient Care / Q000706:statistics & numerical data*; D003362:Cost-Benefit Analysis; D003376:Counseling / Q000191:economics / Q000706:statistics & numerical data*; D003661:Decision Support Techniques; D015658:HIV Infections / Q000175:diagnosis* / Q000453:epidemiology / Q000628:therapy*; D006801:Humans; D007449:Investments / Q000706:statistics & numerical data; D008403:Mass Screening / Q000191:economics / Q000706:statistics & numerical data*; D015233:Models, Statistical; D010342:Patient Acceptance of Health Care / Q000706:statistics & numerical data*; D015995:Prevalence; D011336:Probability; D019057:Quality-Adjusted Life Years; D012017:Referral and Consultation / Q000191:economics / Q000706:statistics & numerical data*; D040841:Resource Allocation / Q000191:economics*; D012680:Sensitivity and Specificity; D014481:United States / Q000453:epidemiology