Identification of losses to follow-up in a community-based antiretroviral therapy clinic in South Africa using a computerized pharmacy tracking system

Antiretroviral therapy (ART) has become much more widely available in resource-limited countries with a high burden of HIV/AIDS. Four million people were estimated to be receiving ART in low- or middle- income countries by the end of 2008, of whom 2.9 million were in sub-Saharan Africa and 701,000 were in South Africa alone [1]. Success in scale-up, however, is being tempered by the fact that escalating case-loads of patients attending individual clinics present a major challenge to the effective retention of patients in care.

Low levels of retention particularly threaten to undermine ART programmes in sub-Saharan Africa. Here, 8%-26% of patients die in the first year of ART [2] and a further proportion may be lost to follow-up (LTFU), with combined attrition rates of approximately 40% at 2 years in many programmes [3]. Identifying and tracing patients who are potentially LTFU is essential to maintain programme quality. However, the human resources needed for this are very limited and development of information systems that permit the most effective deployment of these resources would be of great benefit.

Pharmacy-based records of collection of medication by patients can be used as a system for early identification of patients who are potentially LTFU [4]. iDART, for example, is a computerized software system that requires no licence and is freely available to download at URL http://www.cell-life.org/idart/download. This system allows clinic management teams to generate lists of patients who failed to pick up medication and who can then be traced in the community. However, it is not known what delay of pharmacy pick-ups optimally identifies true programme losses to follow-up.

We therefore conducted a study at a community-based ART clinic in Cape Town, South Africa, using pharmacy dispensing data recorded by the iDART system to examine the relationship between the duration of the delay in scheduled pharmacy pick-ups of medication and LTFU. We hypothesized a priori that too short a delay would be too non-specific and would inadvertently lead to the tracing of large numbers of patients who were not LTFU. Conversely, we hypothesized that too prolonged a delay would fail to identify a proportion of patients LTFU who did require tracing.

Practical solutions are urgently needed to address the challenge of low rates of patient retention in many ART programmes in sub-Saharan Africa [8]. A critical issue is the need to rapidly identify patients who have missed appointments so that patient tracing interventions can be deployed to re-engage patients as soon as possible in care. Using the iDART computerized pharmacy tracking system, we determined the optimal period of delay in pharmacy pick-ups that best identified true LTFU. A ≥6 weeks cut-off would result in the tracing of very large numbers of patients of whom only 15% (approximately 1 in 7) would be true LTFU. Use of cut-offs of ≥12, ≥18 and ≥24 weeks, however, would greatly reduce the numbers of patients who would require tracing, but the ≥12 weeks cut-off was found to be optimal with a sensitivity of 100.0% and a specificity of 95.6%.

Patients who are LTFU should ideally be re-engaged back in care as soon as possible and thus we included within this analysis an examination of a short delay in pharmacy pick-ups (≥6 weeks, typically representing 2 weeks since medication supply ran out) which had high sensitivity. However, one fifth of the cohort had failed to collect medication for ≥6 weeks and yet only a small minority was actually LTFU. Shorter delays than this period would be even more non-specific and the associated work-load associated with tracing all these patients would not be feasible in this service.

In keeping with most other literature from sub-Saharan Africa, we defined true LTFU as patients who had failed to attend for a period of ≥3 months [3]. However, we hypothesized that use of pharmacy delays longer than this period might identify smaller groups of patients with a high yield of LTFU, thereby minimizing the numbers of patients needing to be traced. Indeed, use of increasingly prolonged cut-offs of ≥12, ≥18 and ≥24 weeks was associated with sequential reductions in the numbers of patients that would require tracing. However, more prolonged delays of ≥18 and ≥24 weeks had substantially reduced sensitivity for LTFU despite higher specificity. Thus, on the basis of trade-off between sensitivity and specificity, we identified the ≥12 weeks delay as the optimal cut-off among the four periods assessed. This is entirely consistent with the optimal delay for identifying LTFU found in a study conducted in Zambia (56 days since medication ran out) [9].

We also ascertained outcomes of each of the same 4 groups of patients one year after the time of the cross-sectional study and compared them with the outcomes of patients for whom no pharmacy delay was detected. Approximately one quarter of patients with pharmacy delays of ≥6 weeks and one half of the patients with pharmacy delays of ≥12, ≥18 and ≥24 weeks were LTFU at this time-point compared to just 9.9% of those with no pharmacy delay. Moreover, higher proportions of those with pharmacy delays had died by one year follow-up. This indicates that the detection of pharmacy delays using the iDART system can be used to identify groups of patients who have poor long-term retention and increased mortality risk.

Computerised systems are used to track patients efficiently and are a potential solution for the rapid identification of patients potentially LTFU. However, the utility of these systems depends on user friendliness, affordability, sustainability, stability, security and data ownership. Sites across Africa employ a wide range of electronic information systems to identify patients to be potentially traced [10, 11]. The iDART system is non-commercial, user friendly, requires no license and is freely available to download at URL http://www.cell-life.org/idart/download. However, it requires an uninterrupted electricity supply and requires a computer, barcode printer, barcode reader and offsite back-up such a flash memory stick, cell phone, email or internet connection. This system has advantages over other known electronic information systems used in Haiti, Kenya, Malawi and Zambia in terms of its low cost, user friendliness, minimal staff training requirements and sustainability [11].

The strengths of this study include the fact that iDART is a relatively simple retention measure that could potentially be implemented in settings that are able to support the required infrastructure. In 2009, the system was being successfully used in over 35 sites, mainly in South Africa but also in other countries. The cohort studied is within the South African public sector system and is very well characterized with good quality data on patient outcomes. Limitations include the retrospective design of the study and that the impact of any existing interventions active within this clinic on one year outcomes is unknown. Although this initial cross-sectional study explores the association between LTFU and one key variable (i.e. delays in pharmacy pick-ups), multiple factors may be associated with LTFU and these factors may vary with duration of ART. The important findings of this initial cross-sectional study have been used to devise a long-term prospective study in which the complexities of predicting LTFU can be further refined. This may enable more sophisticated algorithms to identify patients who are potentially LTFU to be developed in due course. Outcomes may differ in clinics with different ART dispensing patterns. Although this study suggests that ≥12 weeks since last clinic attendance to pick-up medication is the optimal definition of LTFU, the choice of optimal delay in other settings may depend on the resources available.

In summary, the iDART electronic pharmacy system can best be used to identify patients potentially LTFU and with high risk of long-term LTFU or death by detecting those who have failed to collect medication for a period of ≥12 weeks. Approximately one half of such patients were true LTFU and use of this system may be used to trigger patient tracing. Use of this system should be evaluated prospectively in tandem with patient tracing interventions to assess the effects on both short-term and long-term outcomes.