title: Examining clinic-based and public health approaches to ascertainment of HIV care status.
abstract: BACKGROUND
  Clinic-based tracing efforts and public health surveillance data can provide different information about HIV care status for the same patients. The relative yield and how best to use these sources to identify and reengage out-of-care patients is unknown.
  
  
  METHODS
  At a large public HIV clinic in San Francisco, we selected a 10% random sample of active patients who were at least 210 days "late" for an HIV primary care visit as of April 1, 2013, for clinic-based outreach. Patients were considered out of care if they did not have an HIV primary care visit in the 210 days before April 1, 2013. We then matched the sample with the San Francisco Department of Public Health HIV surveillance registry. Patients with a CD4 or viral load result in the 210-day period were classified as in care. We compared results from both sources and estimated the cumulative incidence of disengagement from care for the full cohort of clinic patients.
  
  
  RESULTS
  Of 940 patients lost to follow-up, 95 were sampled. Clinic tracing found 60 (63%) in care, 23 (24%) not located, 9 (10%) out of care, 2 (2%) incarcerated, and 1 (1%) had died. Of 42 individuals surveillance classified as out of care, tracing found 22 (52%) were in care. Of 52 patients found to be in care by surveillance, 12 (23%) were out of care by clinic tracing or unable to be located. The naive estimate of the cumulative incidence of disengagement from care at 3 years for the active clinic cohort was 41.1% [95% confidence interval (CI): 37.6 to 44.5]. The use of surveillance data reduced this estimate to 12.7% (95% CI: 18.2 to 25.4), and when further corrected using tracing outcomes, the estimate dropped to only 6.4% (95% CI: 3.4 to 9.4).
  
  
  CONCLUSIONS
  Clinic-based tracing and surveillance data together provide a better understanding of care status than either method alone. Using surveillance data to inform clinic-based outreach efforts may be an effective strategy, although tracing efforts are most likely to be successful if conducted in real time.
authors: *HIV/AIDS Division, San Francisco General Hospital, University of California, San Francisco, San Francisco, CA; †HIV Epidemiology Section, San Francisco Department of Public Health, San Francisco, CA; ‡Center for AIDS Prevention Studies, University of California, San Francisco, San Francisco, CA; and §Department of Family Medicine, University of California, Los Angeles, Los Angeles, CA.
authors: Katerina A
authors: KA
authors: Christopoulos
authors: Susan
authors: S
authors: Scheer
authors: Wayne T
authors: WT
authors: Steward
authors: Revery
authors: R
authors: Barnes
authors: Wendy
authors: W
authors: Hartogensis
authors: Edwin D
authors: ED
authors: Charlebois
authors: Stephen F
authors: SF
authors: Morin
authors: Hong-Ha M
authors: HM
authors: Truong
authors: Elvin H
authors: EH
authors: Geng
mesh_terms: D000328:Adult; D000554:Ambulatory Care Facilities; D018791:CD4 Lymphocyte Count; D015331:Cohort Studies; D003266:Continuity of Patient Care; D057286:Electronic Health Records; D005260:Female; D015658:HIV Infections / Q000453:epidemiology* / Q000517:prevention & control; D006801:Humans; D015994:Incidence; D059012:Lost to Follow-Up; D008297:Male; D008875:Middle Aged; D010342:Patient Acceptance of Health Care; D010355:Patient Identification Systems / Q000706:statistics & numerical data*; D011634:Public Health; D062486:Public Health Surveillance; D012042:Registries; D012495:San Francisco / Q000453:epidemiology; D019562:Viral Load