Stella Talisuna-Alamo

Objectives: To understand reasons for lost-to-follow-up (LTFU) from a community-based antiretroviral therapy program in Uganda. Study Design: Retrospective cohort of patients LTFU between May 31, 2001, to May 31, 2010, was examined. A representative sample of 579 patients traced to ascertain their outcomes. Methods: Mixed methods were used. Using “stopped care” as the hazard and “self-transferred” as the comparator, we examined using Cox proportional multivariable model risk factors for stopping care. Results: Overall, 2933 of 3954 (74.0%) patients were LTFU. Of 579 of 2933 (19%) patients sampled for tracing, 32 (5.5%) were untraceable, 66(11.4 %) were dead, and 481 (83.0%) found alive. Of those found alive, 232 (40.0%) stopped care, 249 (43.0%) self-transferred, whereas 61 (12.7%) returned to care at Reach Out Mbuya HIV/AIDS Initiative. In adjusted hazards ratios, born-again religion, originating from outside Kampala, resident in Kampala for 1 year, having school-age children who were out of school, non-HIV disclosure, CD4 counts >250 cells per cubic millimeter and pre–antiretroviral therapy were associated with increased risk of stopping care. Qualitative interviews revealed return to a normal life as a key reason for LTFU. Of 61 patients who returned to care, their median CD4 count at LTFU was higher than on return into care (401/mm³ vs. 205/mm³, P < 0.0001). Conclusions: Many patients become LTFU during the course of years, necessitating the need for effective mechanisms to identify those in need of close monitoring. Efforts should be made to improve referrals and mechanisms to track patients who transfer to different facilities. Additionally, tracing of patients who become LTFU is required to convince them to return.

We address a critical aspect of antiretroviral therapy (ART) scale-up: poor clinic organization leading to long waiting times and reduced patient retention. Using a before and after study design, time and motion studies and qualitative methods we evaluated the impact of triage and longer clinic appointment intervals (triage) on clinic efficiency in a community-based program in Uganda. We compared time waiting to see and time spent with providers for various patient categories and examined patient and provider satisfaction with the triage. Overall, median time spent at the clinic reduced from 206 to 83 min. Total median time waiting to see providers for stable-ART patients reduced from 102 to 20 min while that for patients undergoing ART preparation reduced 88–37 min. Improved patient flow, patient and provider satisfaction and reduced waiting times allowed for service delivery to more patients using the same staff following the implementation of triage.

Objectives: We evaluated the benefit of socioeconomic support (S-E support), comprising various financial and nonfinancial services that are available based on assessment of need, in reducing mortality and lost to follow-up (LTFU) at Reach Out Mbuya, a community-based, antiretroviral therapy program in Uganda. Design: Retrospective observational cohort data from adult patients enrolled between May 31, 2001, and May 31, 2010, were examined. Methods: Patients were categorized into none, 1, and 2 or more S-E support based on the number of different S-E support services they received. Using Cox proportional hazards regression, we modeled the association between S-E support and mortality or LTFU. Kaplan–Meier curves were fitted to examine retention functions stratified by S-E support. Results: In total, 6654 patients were evaluated. After 10 years, 2700 (41%) were retained. Of the 3954 not retained, 2933 (74%) were LTFU and 1021 (26%) had died. After 1, 2, 5, and 10 years, the risks of LTFU or mortality in patients who received no S-E support were significantly higher than those who received some S-E support. In adjusted hazards ratios, patients who received no S-E support were 1.5-fold (1.39–1.64) and 6.7-fold (5.56–7.69) more likely to get LTFU compared with those who received 1 or ≥2 S-E support, respectively. Likewise, patients who received no S-E support were 1.5-fold (confidence interval: 1.16 to 1.89) and 4.3-fold (confidence interval: 2.94 to 6.25) more likely to die compared with those who received 1 or 2+ S-E support, respectively. Conclusions: Provision of S-E support reduced LTFU and mortality, suggesting the value of incorporating such strategies for promoting continuity of care.

Task shifting to community health workers (CHW) has received recognition. We examined the performance of community antiretroviral therapy and tuberculosis treatment supporters (CATTS) in scaling up antiretroviral therapy (ART) in Reach Out, a community-based ART program in Uganda. Retrospective data on home visits made by CATTS were analyzed to examine the CATTS ability to perform home visits to patients based on the model's standard procedures. Qualitative interviews conducted with 347 randomly selected patients and 47 CATTS explored their satisfaction with the model. The CATTS ability to follow-up with patients worsened from patients requiring daily, weekly, monthly, to three-monthly home visits. Only 26% and 15% of them correctly home visited patients with drug side effects and a missed clinic appointment, respectively. Additionally, 83% visited stable pre-ART and ART patients (96%) more frequently than required. Six hundred eighty of the 3650 (18%) patients were lost to follow-up (LTFU) during the study period. The mean number of patients LTFU per CATTS was 40.5. Male (p=0.005), worked for longer durations (p=0.02), and had lower education (p=0.005). An increased number of patients (p=0.01) were associated with increased LTFU. Ninety-two percent of the CATTS felt the model could be improved by reducing the workload. CATTS who were HIV positive, female, not residing in the same village as their patients, more educated, married, on ART, and spent less time with the patients were rated better by their patients. The Reach-Out CHW model is labor-intensive. Triaged home visits could improve performance and allow CATTS time to focus on patients requiring more intensive follow-up.

Patients who miss clinic appointments make unscheduled visits which compromise the ability to plan for and deliver quality care. We implemented Electronic Medical Records (EMR) and same day patient tracing to minimize missed appointments in a community-based HIV clinic in Kampala. Missed, early, on-schedule appointments and waiting times were evaluated before (pre-EMR) and 6 months after implementation of EMR and patient tracing (post-EMR). Reasons for missed appointments were documented pre and post-EMR. The mean daily number of missed appointments significantly reduced from 21 pre-EMR to 8 post-EMR. The main reason for missed appointments was forgetting (37%) but reduced significantly by 30% post-EMR. Loss to follow-up (LTFU) also significantly decreased from 10.9 to 4.8% The total median waiting time to see providers significantly decreased from 291 to 94 min. Our findings suggest that EMR and same day patient tracing can significantly reduce missed appointments, and LTFU and improve clinic efficiency.