Background The Academic Model Providing Access To Healthcare (AMPATH) program provides comprehensive HIV care and treatment services. Approximately 30% of patients have become lost to follow-up (LTFU). We sought to actively trace and identify outcomes for a sample of these patients. Methods LTFU was defined as missing a scheduled visit by ≥ 3 months. A randomly selected sample of 17% of patients identified as LTFU between January 2009 and June 2011 was generated, with sample stratification on age, antiretroviral therapy (ART) status at last visit, and facility. Chart reviews were conducted followed by active tracing. Tracing was completed by trained HIV-positive outreach workers July 2011 to February 2012. Outcomes were compared between adults and children and by ART status. Results Of 14,811 LTFU patients, 2,540 were randomly selected for tracing (2,179 adults, 1,071 on ART). The chart reviews indicated that 326 (12.8%) patients were not actually LTFU. Outcomes for 71% of sampled patients were determined including 85% of those physically traced. Of those with known outcomes, 21% had died while 29% had disengaged from care for various reasons. The remaining patients had moved away (n=458, 25%) or were still receiving HIV care (n=443 total, 25%). Conclusions Our findings demonstrate the feasibility of a large scale sampling-based approach. A significant proportion of patients were found not to be LTFU and further, high numbers of patients who were LTFU could not be located. Over a quarter of patients disengaged from care for various reasons including access challenges and familial influences.

doi: medRxiv preprint NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice.

BackgroundThroughout most of sub-Saharan Africa (and, indeed, most resource-limited areas), lack of death registries prohibits linkage of cancer diagnoses and precludes the most expeditious approach to determining cancer survival. Instead, estimation of cancer survival often uses clinical records, which have some mortality data but are replete with patients who are lost to follow-up (LTFU), some of which may be caused by undocumented death. The end result is that accurate estimation of cancer survival is rarely performed. A prominent example of a common cancer in Africa for which survival data are needed but for which frequent LTFU has precluded accurate estimation is Kaposi sarcoma (KS).MethodsUsing electronic records, we identified all newly diagnosed KS among HIV-infected adults at 33 primary care clinics in Kenya, Uganda, Nigeria, and Malawi from 2009 to 2012. We determined those patients who were apparently LTFU, defined as absent from clinic for ≥90 days at database closure and unknown to be dead or transferred. Using standardized protocols which included manual chart review, telephone calls, and physical tracking in the community, we attempted to update vital status amongst patients who were LTFU.ResultsWe identified 1222 patients with KS, of whom 440 were LTFU according to electronic records. Manual chart review revealed that 18 (4.1%) were classified as LFTU due to clerical error, leaving 422 as truly LTFU. Of these 422, we updated vital status in 78%; manual chart review was responsible for updating in 5.7%, telephone calls in 26%, and physical tracking in 46%. Among 378 patients who consented at clinic enrollment to be tracked if they became LTFU and who had sufficient geographic contact/locator information, we updated vital status in 88%. Duration of LTFU was not associated with success of tracking, but tracking success was better in Kenya than the other sites.ConclusionIt is feasible to update vital status in a large fraction of patients with HIV-associated KS in sub-Saharan Africa who have become LTFU from clinical care. This finding likely applies to other cancers as well. Updating vital status amongst lost patients paves the way towards accurate determination of cancer survival.

Purpose: To evaluate the use of the partograph as a critical tool in the management of labour in two hospitals in Kenya. Method: Midwives were observed administering partographs to a total of 234 women. This process was evaluated using a structured observation checklist. Results: Every one of the partographs evaluated was incomplete or incorrect in some respect. There was also minimal consideration of the recorded data in determining whether to intervene in the pregnancy. The alert line was crossed for 40 partographs (17.1%) with no intervention being instituted. In 6 cases (2.6%) there was a waiting time of 3–16 hours after crossing of the action line before interventions were carried out. Conclusion: Proper monitoring, recording, and interpretation are important in minimizing unnecessary interventions.