An Evaluation of the Impact of ARK’s Community Based Adherence Support Programme on ART Outcomes in selected sites in South Africa
JO Igumbor, E Scheepers, R Ebrahim, A Jason and A Grimwood
Absolute Return for Kids (ARK) South Africa
The success of antiretroviral therapy (ART) partly depends on patients’ level of adherence.
Unfortunately, adhering to any treatment is difficult. Adherence to ART, especially in SA, is critical to avoid virological resistance developing as there are very few treatment options for patients in the public sector. Treatment to resistant HIV is available in the private sector but virologic genotyping is essential to plan subsequent treatment regimens. This expensive investigation is only available in the private sector. Various adherence support paradigms with varying levels of success have been suggested. This evaluation hence assessed the impact of community based adherence support on the outcomes of patients on ART in the context of an ongoing programme. The evaluation was a retrospective study based on patient clinical records.
The key findings of the evaluation conclude that:

a significantly higher proportion of patients with a community based adherence supporter also known as a patient advocate (PA) had viral load of less than 400 copies/ml at six months of treatment (70%, p = 0.001);

a significantly higher proportion of patients with PAs (89%) attained a treatment pick up rate of over 95% (67%; χ 2 = 6.131; p = 0.021);

patients at health facilities with PA services maintained a suppressed viral load for a longer time when compared to patients at health facilities without PA services ( χ 2 = 143.46; p =
0.0000) and

patients at health facilities with PA services remained in care for a longer time ( χ 2 = 124.27; p = 0.0000).
This study concludes that integrated community based adherence support is important to ensure that patients remain in care, are virologically suppressed and regularly pick up their treatment from ART clinics. The study also underscores the importance of access to health services and the presence of an enabling environment in the treatment of AIDS.
Keywords: adherence, AIDS, antiretroviral therapy (ART), community based support, HIV.
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BACKGROUND
Antiretroviral therapy (ART) is a combination of drugs designed to inhibit the replication of the human immunodeficiency virus (HIV). Through this mechanism, ART combinations facilitate the reconstitution and maintenance of the immune system (Chesney, 2003). To achieve these goals patients are required to maintain an adherence rate of at least 95% (Battagolioli-DeNero et al.,2007; Chesney, 2003).This requirement constitutes an exceptional demand as the level of adherence to treatment among patients with chronic diseases has been documented to be as low as 20% and 80% at best (Icovics, 1997; Williams and Friedland, 1997; DiMatteo et al.,1993). A dherence (with regards to ART) is known to diminish over time, due to ‘pill or treatment fatigue’ (Ickovics et al., 2002). This phenomenon accentuates the need for sustained adherence support for persons on chronic treatment programmes (Ickovics et al., 2002)
The suboptimal use of ART has often been attributed to the plethora of complexities surrounding its use, such as the associated lifestyle adjustments, dietary restrictions, strict meal timing, pill load, drug toxicity, comorbidities and adverse drug reactions (Reiter et al.,2000).
These obstacles have resulted in sub-optimal adherence to treatment and as a consequence
‘hard-to-treat’ strains of the human immunodeficiency virus have emerged in globally
(Bangsberg et al.,2001; Paterson et al.,2000).
Ensuring adequate and consistent adherence to ART is hence a high priority for effective HIV management. This assertion is heightened by the knowledge that the odds of achieving a desired health outcome is three times higher among patients who are adherent to treatment
(DiMatteo et al.,2002). Similarly, the optimal use of ART has been shown to result in dramatic reductions in mortality and morbidity among persons living with HIV and AIDS (Palella et al.,
2003; Walmsely et al.,2002). It has also been suggested that poor adherence is a major predictor of progression to AIDS and death (Bangsberg et al., 2001; Garcia et al., 2002; Hogg et al., 2002). The stark levels of virologic failures (+50%) noted in ART programmes have also been attributed to suboptimal adherence to treatment (Lichtenstein, 2005; Chesney, 2003;
Knobel et al.,2001; Liu et al.,2001; Battagolioli-DeNero, 2007; Chesney, 2003).
On the basis of this evidence, a community based adherence support programme through patient advocates (PA) was designed to complement the clinic based ART services to ensure that patients are optimally adherent to treatment. The PA support service is provided by
Absolute Return for Kids South Africa (ARK SA). ARK SA is affiliated to ARK, which is an international charity, based in the United Kingdom, supporting, as part of its international charities, the South African government’s efforts to rapidly rollout antiretroviral treatment (ART).
ARK’s ART programme in South Africa is hinged on three key components consisting of the rapid ART roll-out within a primary care model; service provision through private/public partnerships and the PA support service that falls under its community access adherence (CAA) component. Together, these components seek to enhance the quality of survival of HIV-infected persons by providing and promoting optimum and sustained use of ART and social support grants by people infected or affected by HIV and AIDS.
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ARK’s PAs are community based health care workers (CBHCWs) trained in the elements of promotion adherence, providing home and community-based psycho-social support and the community-follow up of patients receiving ART. In some cases, the Patient Advocates may be dedicated workers employed for this specific task, but often they will be home-based carers or other existing carers taking on additional responsibility for adherence support. They complement the clinic treatment program by providing adherence support in partnership with clinicians in ART sites.
With the above background, this evaluation sought to establish the extent of impact of PA support on patient retention in care, adherence to ART and clinical treatment outcomes.
Analysis was done at two levels. The first level was patient level analysis that compared the study variables among patients exposed and not exposed to PA services at ART sites. The second level was site level analysis that compared patient outcomes at sites with and without
PA services.
METHODOLOGY
The study was retrospective based on patient record review and located at ARK supported health facilities. The study methodology is presented under two levels of analyses:
1. Patient level analysis
The study sites for the patient level analysis were selected based on patient enrolment rates,
PA coverage and quality of patient records. Sites with higher patient enrolment, better data quality and PA coverage (based on PA-patient ratio) were selected. With this, four study sites were selected from three provinces and this translated as one site in two provinces and two sites in the third province. The study targeted patients who were initiated on ART between July and September of 2007. The PA support database was implemented during the index period and hence the decision to target this cohort of patients on the basis that the spectrum of outcome indicators required for this evaluation will be available for this group of patients.
The spectrum of data elements extracted from the database included patients’ PA support status; ratio of clinical care workers (doctors / nurses) to total onsite-patients on ART; patient use of other adherence support measures like clinic based lay counsellors; history of missedclinic-appointments; treatment pick-up rate; patient retention status and viral load.
Spearman correlations were conducted to establish the associations between variables like
Doctor/Nurse-patient ratio, CD4 cell count, viral load and treatment-pick-up ratios. These variables were compared between patients with and without PA support. Chi-square test and the student-t test were used to compare rates of patient retention status (like remaining in care and being loss to follow-up), missed appointments and treatment-pick-up rates between the two groups of patients
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2. Site level analysis
The site level analysis used patient records from ART sites with (n=12) and without (n=14) PA services. Sites where ART services commenced before PA support was introduced were excluded given the longitudinal nature of the site level analysis. The analysis included all patient records where viral load (VL) test results were available. This means that each patient in the analysis can have multiple VL measurements over the duration of their treatment. This occurrence allowed for an assessment of how many patients maintained a suppressed viral load over time or the time it took to achieve a suppressed viral load. In the clinical outcomes analysis, treatment duration at any point was taken as the time difference between the respective clinical test and ART start dates.
In the analysis of the impact of PA services on patient retention, survival time was taken as the time difference between patients’ most recent pharmacy visit date for medication pick-up and the ART start date. The analysis compared the optimum time patients remained in care at sites with and without PA services
Unique patient records were used in this analysis. This cross sectional comparison is based on the fact that patients can only have a unique retention outcome which can be; “died”, “loss to follow up (LFT)” or “remaining in care (RIC)”. This is opposed to the viral load status which can vary from time to time, hence the inclusion of all patient records in the clinical outcome analysis performed at the beginning of this report. Patients who were discontinued and transferred-out of the respective sites were excluded from the remaining in care analysis.
The dignity of the study participants were respected and protected in this evaluation by maintaining confidentiality and anonymity. All the records used in this evaluation did not have any personal information (like participants’ names or addresses) linked to it. Permission was solicited from the respective Provincial Departments of Health and designated hospital authorities to access medical records. Ethical clearance for this evaluation was requested and granted by an ethical review board.
Limitations and opportunities
The major limitation of this evaluation was its reliance on data extracted from a routine programme monitoring database and not a database driven by a prospective research process.
The use of this approach largely explains the exclusion of many poor quality variables and hence the analytical limitations, as well as the missing values within variables. In the context of the data limitations and adaptations, exposure to PA was a dichotomous variables indicating whether a patient either had or did not have a PA. In other words patients who may have interacted with PA support only once were grouped with patients who have had repeated PA contacts. This level of measurement is however consistent with the requirements to answer the key evaluation question which was to indicate whether having a PA will result in optimum adherence to ART. Having said that, the database used represents a modest set of variables that will allow a technically feasible quantitative analysis of the impact of ARK’s community
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adherence support programme. However, the site analysis provides better discrimination of patients exposed and not exposed to PAs.
The following steps were additionally taken to enhance the quality of data:
1. Purposive selection of sites. The potential sites for the quantitative evaluation were purposively selected based on the overall quality of their CAA data.
2. Definition of the sample to ensure an adequate number of study participants and followup time with reliable data on exposure to PA support, the evaluation focused on the cohort of patients initiated to ART in the third calendar quarter of 2007 (July to
September).
3. Active search for missing data and verification of existing data at site level by specially appointed external data capturers.
4. Data quality assessment. Only variables that were found to be reliable and with adequate number of patient records and distribution across its attributes were considered for the evaluation.
FINDINGS
1. Patient demographic information distribution by key variables
540 patient records were used for patient level analysis and the average treatment duration of the patients was about 9 months. 17%, 46% and 37% of the patient records were from the sites in three respective provinces that participated in this study. PA-patient distribution across the selected sites was noted to be significantly different (p=0.000). The majority of the patients were female (64%), persons aged between 25 and 39 years old (59%) persons supported by patient advocates (56%) and patients who lived within a 9 kilometre radius from the health facility
(58%). A higher proportion of the patients had been exposed to clinic based adherence counselling (66%) and in most cases more than two times (45%). HIV disclosure rate was high
(96%) and 47% of the patients had disclosed their HIV status to one only person; 18% disclosed to two people and about 32% have disclosed to more than 3 people. Notwithstanding this, 25%
(n = 125) of the study participants were neither being supported by a PA nor by a clinic based counsellor. A high majority of this study cohort remained in care (82%), when compared to the proportion of patients who were lost to follow up (12%), transferred out (4%) and died (3%).
2. Relationship between patient advocate exposure and key study variables
Tables 1 contain the distribution of study variables by exposure to PA. Patients who reside more than 40km from the health facilities were significantly less likely to have a PA (Table 1). As an indicator of economic standing, PAs were significantly more likely to be allocated to patients who lived in informal accommodations (75%) when compared to those who lived in formal
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accommodation (25%). Patients with PAs were more likely to disclose their HIV status (58%) when compared to the proportion of patients without PAs who disclosed their HIV status (42%; p
= 0.005). Patients with PAs were also significantly more likely to be receiving clinic based counselling. A significantly higher proportion of patients with PAs had viral loads of less than
400 copies/ml at six months (70%, p = 0.001). Patients with viral load greater than 400copies/ml at six months was slightly higher among patients with PAs (51%, p = 0.001). When comparing the frequency of viral suppression among patients with and without PAs respectively, the proportion of patients with unsuppressed viral loads at six months was higher among those without PAs (42%) when compared to the frequency of unsuppressed viral loads among patients with PAs (24%; p > 0.001).
Table 1: Cross-tabulation of exposure to patient advocates and patient characteristics
Sex Female (n = 346)
Male (n = 194)
Exposure to patient advocate
No Yes
44.8%
41.2%
55.2%
58.8%
Pearson chisquare
(p-value)
.641 (.469)
Age group
(N= 537)
Distance from home to health facility
(N = 514)
Type of accommodation
(N = 299)
Disclosure of HIV status
(N = 457)
Number of persons disclosed to (N = 452)
Exposure to clinic based counselling (N = 501)
Frequency of exposure to clinic based counselling
(N = 490)
Viral load at six months (N
= 319)
0 to 19 years (n = 34)
20 to 24 years (n = 27)
25 to 29 years (n = 90)
30 to 34 years (n = 118)
35 to 39 years (n = 108)
40 to 44 years (n = 77)
45 to 49 year (n = 39)
50 + years (n = 44)
0 to 9 km (n = 300)
10 to 19 km (n = 22)
20 to 29 km (n = 112)
30 to 39 km (n = 15)
40 + km (n = 65)
Informal (n = 79)
Formal (n = 220)
No (n = 20)
Yes (n = 437)
No person (n = 20)
1 or 2 persons (n = 289)
> 2 persons (n = 143)
No (n = 172)
Yes (n = 329)
Never (n = 172)
1 or 2 times (n = 97)
> 2 times (n = 221)
< 400 copies/ml (n = 221)
400 + copies/ml (n = 98)
75.0%
51.6%
22.4%
72.7%
33.1%
72.7%
62.9%
19.0%
29.9%
49.0%
26.0%
31.8%
71.4%
66.7%
83.1%
7.6%
24.1%
75.0%
42.1%
58.8%
37.0%
40.0%
43.2%
44.4%
45.5%
51.3%
31.8%
74.0%
68.2%
28.6%
33.3%
16.9%
92.4%
75.9%
25.0%
57.9%
41.2%
63.0%
60.0%
56.8%
55.6%
54.5%
48.7%
68.2%
25.0%
48.4%
77.6%
27.3%
66.9%
27.3%
37.1%
81.0%
70.1%
51.0%
7.781 (.358)
118.013 (.000)
9.987 (.001)
8.418 (.005)
41.694 (.000)
70.956 (.000)
124.986 (.000)
10.802 (.001)
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3. Relationship between treatment pick up rates and patient characteristics
The average treatment pick-up rate was 99.0% (sd = 10.3; median = 101.0; 95% CI = 96.4 –
101.0) and the average missed appointments was 11.4 days (sd = 22.2; 95% CI = 6.8 – 16.0).
The treatment pick-up rate was significantly higher among patients with viral loads less than 400 copies/ml (100.3%) when compared to patients with viral loads equal to or greater than 400 copies/ml (91%; p = 0.000). The number of days between scheduled medicine pick-up date and actual medicine pick up date was significantly more among patients with unsuppressed viral load (30.1 days) when compared to the number of missed days among patients with suppressed viral load (16.0 days; p = 0.001). The treatment pick up rate showed that 78% of the participants attained a 95% pick-up rate while 22% did not. The 95% benchmark is in line with global requirement for optimum adherence to ART. Furthermore, about half of those who did not attain the 95% treatment pick up rate experienced virologic failure, while 17% of those who achieved the 95% treatment pick up rate experienced virologic failure (χ 2 = 6.558; p = 0.010).
Despite these figures, a significantly higher proportion of patients with PAs (89%) attained a treatment pick up rate of over 95% when compared to the proportion of patients without PAs who achieved the 95% pick up rate (67%; χ 2 = 6.131; p = 0.021).
4. Impact of PA services on the rate of virologic failure
The median time in which patients at sites with PA services maintained a suppressed viral load was 235 days while the median time in which patients at sites without PA services maintained a suppressed viral load was 199 days ( χ 2 = 143.46; p = 0.0000).
Table 2: Risk of virologic failure among patients at Sites with and without PA services (N
= 3,097)
PA status
Incidence rate of unsuppressed viral load
Hazard ratio 95% CI Sig.
Sites without PA (n = 1,958)
Sites with PA (n = 1,139)
0.0030758
0.0019787
0.6366499
0.5852183 -
0.6926017
0.000
The hazard ratio of not having a suppressed viral load was less than 1 (0.6363047). This means that the negative event, which is an unsuppressed viral load, is less likely to occur among patients at sites with PA services when compared to its occurrence at sites without PA services
(Table 2).
5. Impact of PA services on patient retention
The median retention in care time for patients at sites with PA services was 561 days while the median retention in care time for patients at sites without PA services was 455 days ( χ 2 =
124.27; p = 0.0000). This finding shows that more patients at sites with PA services remained in
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care for a longer time when compared to the median patient retention time at sites without PA services.
Table 3: Risk of non retention in care (Dying and LTF) among patients at Sites with and without PA services (N = 2,431)
PA status
Incidence rate of Death or
LTF
Hazard ratio 95% CI Sig.
Sites without PA (n = 1,544) 0. 0019032
0. 0014310
0.6205410
0 .620541 -
0 .6757964
0.000
Sites with PA (n = 887)
LFT= loss to follow up
The Hazard Ratio was less than 1 (0.6205410) and this implies that the negative event which is non-retention in care (dying or LTF) is less likely to occur at sites with PA services when compared to its occurrence at sites without PA services (Table 3).
DISCUSSION
Adherence in this study was measured using the patient treatment pickup rate as a process indicator. The treatment pickup rate is analogous to the pharmacy refill data, which is defined as
(pills dispensed/pills prescribed per day)/days between refills) X 100% (Grosberg et al., 2004).
This measure has been widely validated and used as a proxy measure of adherence to
ART(Grossberg and Gross, 2007; Grossberg et al., 2004; Wood et al., 2003 ) . Similar to other studies, this study noted that treatment pickup rate was significantly higher among persons with suppressed viral load while missed appointment rate was lower among persons with unsuppressed viral load. Studies that have linked treatment pickup rate and adherence have described it as simple, inexpensive and a valid proxy measure of adherence to ART (Grossberg and Gross, 2007).
The reported average treatment pick-up rate of 99% represents an unusually high level of adherence considering that 50% of the patients (with treatment pick-up data) were not being support by a PA. This assertion is predicated on the fact that similar studies have reported such high levels of adherence only among patients receiving active adherence support interventions.
For instance, Tuldra et al (2000) found that over 94% of patients in the adherence support intervention group maintained an adherence rate of >=95% as against the 64% of the control group that attained the >=95% adherence rate. The high treatment pick up rate noted in one of evaluation sites may be attributable to the fact that almost all the patients in this site (95%) and especially the patients without PAs (97%) had repeatedly seen a clinic based adherence counsellor. It is however important to note that PAs often serve as clinic based adherence counsellors due to a shortage or absence of such skills in the clinics. In all, this finding is in consonance with similar studies that have noted the effect of such interventions in ensuring optimum adherence to ART (Golin et al., 2006).
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It remains however a concern that access to PAs or clinic based adherence counsellors was widely uneven across the evaluation sites. In addition, approximately 25% of all the participants from the four sites were not being supported by a PA or clinic based adherence counsellor. The concern with this gap is based on the notably higher virologic failures reported at sites with lesser PA coverage. This assertion is on the basis that the health facilities with significantly higher proportions of patients without any form of adherence support were also significantly more likely to have patients with unsuppressed viral loads. Furthermore, a significantly high majority (70%) of patients with suppressed viral load were patients who were supported by a PA and the chance of attaining a treatment pick up rate of >=95% was higher among PA supported patients. These findings support the need for adherence support as critical in HIV management.
The potential effects of patients’ proximity to health facilities were noted in this evaluation.
Patients who lived closer to a health facility were significantly more likely to have a PA.
Similarly, patients who lived closer to a health facility were more likely to have a suppressed viral load. The suggested relationship between the likelihood of being supported by a PA and proximity to health facility is attributable to the fact that the PA support service is located in the same geographical area as the health facility. In the same manner, the health facilities are designed to cater for people in its immediate catchment area. This is not always the case as some HIV infected patients prefer to access related services at health facilities that are far from where they live due to fear of disclosing their HIV status and the associated stigma. This phenomenon makes it increasingly challenging to provide community based adherence support to patients who live far from the health facility. It however remains a concern that patients who live far from the health facility may not be receiving adherence support despite its importance to
ART outcome (Rathbun et al, 2004; Pradier et al., 2003).
Another key objective of this study was to establish if exposure to PA support contributed to whether patients were lost to follow up or remained in care. In this regard, the data from the patient level analysis showed no significant difference between patients who were supported by a PA and those who were not. This finding should however be taken with caution on the basis that having or not having a PA as measured in this evaluation is not enough to establish the impact PA support on the likelihood of remaining in care. The reliance on this level of categorization was due to the limited information on frequency of patient exposure to PA support at the time of the study. This categorization undermines the potential effect of the frequency of exposure to PA services on patient retention. In the context of this argument, this study showed that patients who had repeatedly seen a clinic based adherence counsellor were significantly more likely to remain in care. The site level analysis in this study provides a more credible comparison of the likelihood of patient retention in care and viral suppression between sites with and without PA services, with a marked significant difference between sites favouring sites with PA services. In summary the two strands of analyses support the growing evidence that adherence support is relevant in promoting adherence to ART (Simoni et al, 2003;
Holzemer et al, 2006).
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CONCLUSIONS AND RECOMMENDATIONS
The evaluation strongly underscores the importance of having an integrated community adherence support strategy as part of the package of HIV management at the primary level of care. Thus, it is essential that all patients on ART should be provided with an adherence support service that is responsive to unique patient socio-economic status (SES) and clinical situations.
Similarly, adherence support should be intensified particularly in health facilities with low adherence support coverage. This recommendation is in view of the possible interactions between the extent of adherence support coverage and the proportion of virologic failures at the health facilities.
There is a need to identify the unique needs of and obstacles encountered by patients who live far from the health facilities. This will facilitate the planning of health services provided to them to ensure optimum treatment outcome including appropriate referral processes.
In addition, patients who live far from health facilities should be considered as high priority for health facility based adherence support given their high likelihood of not benefiting from the PA adherence support programme. Alternatively, efficient and creative home visit opportunities need to be explored for such patients.
To ensure further rigour, future evaluations will require data that are reflective of a continuous scale rather than the largely categorical level of measurements that was used in this evaluation.
The future evaluation variable list should at least include: frequency of contact between the patient and the PA; background information on the PA; more socio-economic patient data; linking of PAs with patients; viral load measurement on a continuous scale; patient treatment regimen and alternative adherence support methods used by patients.
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