AIDS Behav DOI 10.1007/s10461-014-0761-8
ORIGINAL PAPER
Patient Outcomes in Lubumbashi, Democratic Republic of Congo After a Disruption in HIV Care Due to Decreased Global Fund Appropriations Anna Freeman • Modeste Kiumbu • Blaise Mwamba • Joseph Atibu • Henri Mukumbi • Louis Mwila • Christopher Cummiskey • Kristen Stolka Jennifer Hemingway-Foday • Jamie E. Newman
•
Ó Springer Science+Business Media New York 2014
Abstract This study examines care seeking behaviors, clinical outcomes, and satisfaction with care of HIV-positive adults in Lubumbashi, DRC, one year after a disruption in care due to decreased global fund appropriations. We describe outcomes before and after the disruption. We compared characteristics of those who completed the survey and those who did not using the Wald F test. Most patients sought care after the disruption and continued antiretroviral therapy (ART), though use of cotrimoxizole prophylaxis declined. Though there was little change in WHO clinical stage at the new site of care, the majority of participants lost weight, adherence decreased, support group participation dropped, and satisfaction with care worsened. Patients were more likely to participate in the study if they were taking ART. This study highlights the importance of provider-patient communication during a transfer and the vulnerability of pre-ART patients to becoming lost to follow-up. A. Freeman K. Stolka J. Hemingway-Foday J. E. Newman (&) Statistics and Epidemiology, RTI International, 3040 Cornwallis Road, Research Triangle Park, NC 27709-2194, USA e-mail: [email protected] M. Kiumbu J. Atibu Kinshasa School of Public Health, Kinshasa, Democratic Republic of the Congo
Resumen Este estudio analiza los comportamientos de bu´squeda de atencio´n, resultados clı´nicos y la satisfaccio´n de adultos con VIH respecto a la atencio´n recibida en Lubumbashi, RDC. El estudio se realizo´ un an˜o despue´s de la interrupcio´n en la atencio´n debido a la disminucio´n en la partida de recursos del Fondo Mundial. Se describen los resultados antes y despue´s de la interrupcio´n. Comparamos las caracterı´sticas de aquellos que completaron la encuesta con aquellos que no lo hicieron, usando la prueba F-Wald. La mayorı´a de los pacientes buscaron atencio´n despue´s de la interrupcio´n y continuaron con la terapia antirretroviral (TAR), aunque el uso de profilaxis con cotrimoxazol declino´. A pesar del pequen˜o cambio en el OMS estadio clı´nico, en el nuevo lugar de atencio´n, la mayorı´a de los participantes perdieron peso, la adherencia disminuyo´, la participacio´n en grupos de apoyo se redujo y la satisfaccio´n con la atencio´n empeoro´. Los pacientes fueron ma´s propensos a participar en el estudio si estaban tomando TAR. Este estudio resalta la importancia de la comunicacio´n proveedor-paciente durante una transferencia y el riesgo de perder el seguimiento en pacientes preTAR. Keywords HIV Africa Funds Delivery of health care Medication adherence
B. Mwamba L. Mwila AMO-Congo, Lubumbashi, Democratic Republic of the Congo
Introduction
H. Mukumbi AMO-Congo, Kinshasa, Democratic Republic of the Congo
Sub-Saharan Africa is the region of the world most affected by HIV/AIDS [1], and economic, political, and geographic constraints have added challenges to health care systems struggling to combat this epidemic. In 2002, the global fund to fight AIDS, tuberculosis, and malaria (global fund)
C. Cummiskey International Development Group, RTI International, Washington, DC, USA
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was created as an international financing institution to gather and dispense funds to prevent and treat these diseases [2]. In recent years, the global fund, which depends on donations from high-income countries, suffered a lack of contributions due to the worldwide economic downturn [3]. The amount of support that will be offered by global fund in coming years remains uncertain, and the implications of these changes in funding are potentially devastating to countries that depend on these funds for HIV/AIDS programming [4, 5]. The Democratic Republic of the Congo (DRC) has relied heavily on global fund contributions for its HIV/ AIDS prevention and treatment programs [6]. Historically, much of this funding has been allocated to AMO-Congo, a Congolese non-governmental organization that has provided HIV care and treatment services throughout the DRC since 1993 [7]. At its peak, AMO-Congo managed eleven clinics in six provinces and was the largest provider of antiretroviral therapy (ART) in the country. In Lubumbashi, the second largest city in the DRC, AMO-Congo operated two HIV care and treatment facilities, serving approximately 3,100 people living with HIV/AIDS. Services included counseling and testing, provision of ART and other medications, nutritional support, and psychosocial support services. In 2008 and 2009, the global fund reduced its assistance for HIV services to the DRC by one-third, and in subsequent years, the DRC was ineligible to receive funding from the global fund for HIV prevention and treatment [8]. As a consequence, AMO-Congo restricted services offered in some clinics, and in other areas, was forced to close treatment facilities. The two AMO-Congo clinics in Lubumbashi were closed in 2010 and the patients receiving care at these sites were transferred to government-run facilities. This study describes these patients one year after this disruption in care and examines care-seeking behaviors, clinical outcomes, medication use and adherence, and patient satisfaction.
Methods This analysis was part of the National Institutes of Health (NIH)-funded Central Africa regional database of the International epidemiologic databases to evaluate AIDS (Phase I IeDEA Central Africa). Approval for this research was granted by the institutional review board at the Kinshasa school of public health in the DRC and RTI international. Patients were notified of the pending closure and transfers via telephone, signs posted at each clinic, and through word-of-mouth. Clinicians at AMO-Congo provided written transfers to one of three government facilities (based on patient address or per their request) for patients
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who came to the clinic during the period September to December 2010. Sample Selection For our sample, we randomly selected 1,000 patients from the Phase I IeDEA Central Africa database attending two AMO-Congo clinics in Lubumbashi. Inclusion criteria required patients to have a baseline data form in the IeDEA database (which was completed when patients originally enrolled into the IeDEA database) and at least one followup form during the time period between April 1 and September 30, 2010. As patients were asked to return to the clinic every three months (for those on ART) or every six months (for those pre-ART), this time frame was designed to capture all patients who were actively engaged in HIV care and treatment, and thus eliminated those who were lost to follow-up or deceased prior to the clinic closures. This sample was drawn using systematic random sampling stratified by the following variables of interest: ART status at follow up, WHO clinical stage at baseline, distance to clinic, age group (18–29, 30–39, 40–49, 50–59, and 60? years), and gender. Patients were contacted by telephone and home visit, or home visit only when no telephone number was available. Each patient received a total of five contact attempts before being declared lost to follow-up. Informed consent was obtained in French or Kiswahili, according to patient preference. Patients were reimbursed $5 USD for transport fees to the clinic. All surveys were conducted in face-to-face interviews between September and December 2011, approximately one year after this cohort of patients was transferred from AMO-Congo to government-run care facilities. Data Collection The survey included questions regarding care-seeking behaviors after disruption in care, services received at their new site of care, ART and other medication use, adherence, satisfaction with care at AMO-Congo and at the new site of care, and support group participation at AMO-Congo and the new site of care. Adherence was self-reported. Nonadherence was defined by missing any drug for two or more consecutive days within the past 30 days. Patient satisfaction questions were asked using a 5-point Likert scale (ranging from 1-not at all satisfied to 5-extremely satisfied) with open-ended follow-up. Outcomes related to death, relocation, and hospitalization were obtained from family members or neighbors, if the patient could not be reached. For pre-disruption indicators, we used data collected while the patients were receiving care at the AMO-Congo Lubumbashi clinics between 2007 and 2010 (Table 1). These data were collected as part of the Phase I IeDEA
AIDS Behav Table 1 Timepoints at which variables were measured Baseline (at enrollment into IeDEA database)
Last follow-up visit at AMO-Congo AND survey at one year after disruption of care
Survey at one year after disruption of care
Demographic information
ART and other medication use
Transfer information
Adherence
Services received at new site of care
Medical assessment Anthropometric measures WHO clinical stage
Care-seeking behaviors
Satisfaction with care (at AMO-Congo and new site of care) Support group participation (at AMO-Congo and new site of care)
Central Africa database and included information from the patient’s baseline visit and last follow up visit before the disruption in care. Data from these forms included demographics, information on ART and other medication use, and adherence. Adherence questions were worded identically on the post-disruption survey and the initial IeDEA forms: during the last month, has the patient missed taking medication more than 2 consecutive days? Statistical Analysis Epi-Info was used for on-site data-entry and cleaning. All data processing and analyses were conducted using SAS 9.1 for Windows (SAS Institute) and SUDAAN 10.0.1 (RTI International). We first analyzed the responses of the patients who participated in the survey (n = 373) to examine care seeking behaviors and patient outcomes after transfer. We examined baseline demographic, behavioral, and clinical characteristics of these patients using the IeDEA dataset to describe outcomes at baseline, or last documented follow-up visit, and at the time of the survey. Finally, we compared characteristics from baseline and last follow-up visit prior to disruption in care of the patients who completed the survey with those who were sampled but were deemed lost to follow-up. The Wald F test was used determine if distributions between these groups differed. Results Overview Information on sample selection and survey completion is detailed in Fig. 1. In total, 373 patients completed the
survey. Of those who did not participate, 427 were deemed lost to follow-up after five contact attempts were made. Twenty-seven patients were confirmed deceased. Ninetyone patients were contacted but were unable to participate in the study. Of these, one person was hospitalized, 84 had relocated, two were traveling during the time of the survey, and four were unavailable for unspecified reasons. An additional 82 people were not contacted due to time constraints. Transfers and Care-Seeking Behavior Of the 373 patients who completed the survey, 264 (70.8 %) were women, which is consistent with the proportion of women that attended the two Lubumbashi clinics as well as the Phase I IeDEA Central Africa database overall. Most (N = 304, 81.5 %) were aged 30–59 years, and the mean age was 44 years. Of these 373 patients, 319 (85.5 %) received a formal transfer notice from their AMO-Congo clinic in the form of a written or verbal transfer. Of the 373 patients surveyed, 289 (77.5 %) reported being transferred to an HIV care and treatment clinic in a government-run hospital and 16 (4.3 %) were transferred to other facilities at their request. Of the 289 patients who transferred to government-run facilities, 264 were referred to two civilian hospitals, and the remaining 25 were referred to a military hospital. In total, 284 patients (76.1 %) sought care at their site of transfer (SOT); that is, the government-run clinic to which they were referred by the clinicians at AMOCongo. Of the 35 patients who did not seek care at their SOT, 23 went to a different facility, one went to a clinic at their workplace, six abandoned treatment entirely, and five did not indicate their plans for seeking care. Reasons for not seeking care at their SOT that the 35 patients provided include: poor treatment or lack of confidence in the care at the SOT (N = 11), long travel time (N = 7), and stigmatization or concerns about patient confidentiality (N = 7). Of the 344 patients who sought care following the closure of the AMO-Congo clinics (though not necessarily at their SOT), 139 (40.4 %) first met with a physician, 131 (38.1 %) first met with a nurse, and 45 (13.1 %) first met with a pharmacist. In the one year since the disruption in care, 197 (57.3 %) patients saw a physician at some point. At their new site of care, 330 of the 344 patients (95.9 %) received a medical record file. Few (N = 75, 21.8 %) received adherence counseling, the consequences of which are discussed below. Fewer than half (N = 160, 46.5 %) had CD4 testing, and very few (N = 45, 13.1 %) had any other laboratory analyses, including viral load testing, performed.
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Fig. 1 Patient population sampled for this study
Medication Use and Adherence Of the 373 patients who participated in the survey, 313 (83.9 %) had been taking ART prior to the disruption in care. Of these 313 patients, 310 continued taking ART and only 3 reported discontinuing ART. Of the 310 patients who continued taking ART, 31 changed one or more of the drugs in their regimen. Of the 60 patients not taking ART prior to disruption in care, 38 started ART at their new site of care. Nearly all (97.9 %, N = 365) of the 373 patients surveyed were taking cotrimoxazole prophylaxis while receiving care at AMO-Congo though only 311 (83.4 %) were on cotrimoxazole at their new site of care. Three patients (0.8 %) started cotrimoxazole at their new site of care. At the time of the last follow-up visit at AMO-Congo, few (4.9 %) patients in this survey had self-reported nonadherence, defined by missing any drug for two or more consecutive days within the past 30 days. One year after the disruption in care, 91 (24.4 %) participants reported non-adherence. When asked about adherence to ART specifically, 36 (10.3 %) of the 348 participants who were taking ART reported non-adherence, due to stock-outs (N = 12), lack of healthcare worker to distribute the drugs at the clinic (N = 4), travel (N = 4), missed appointment by the patient (N = 3), or because the patient chose to stop taking ART (N = 5). When asked about adherence to cotrimoxazole one year after the disruption in care, 49
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(15.8 %) of the 311 participants who were taking this drug reported non-adherence, due to stock-outs (N = 25), forgetting to purchase it (N = 5), forgetting to take it (N = 4), lack of healthcare worker to distribute the drugs at the clinic (N = 5), travel, (N = 3), and lack of money to pay for the cotrimoxazole (N = 4). Clinical Outcomes A physician or nurse assessed the patient’s WHO clinical stage at the new site of care. Most of the 373 patients (N = 254, 68.1 %) were in Stage III, and 79 patients (21.2 %) were in Stage II. Few patients were in Stage I (N = 22, 5.9 %) or Stage IV (N = 18, 4.8 %). This represented very little change from the time of the last follow-up visit prior to disruption of care at AMO-Congo and the new site of care: 350 patients (93.8 %) had the same WHO clinical stage, 13 patients (3.5 %) had a worse clinical stage and 10 patients (2.7 %) had an improved clinical stage. Each patient was weighed at the new site of care, and these weights were compared to the recorded weight at the last follow-up visit prior to disruption in care at AMOCongo. Sixty patients (16.1 %) maintained the same body weight and 105 patients (28.2 %) gained weight (0.4-29 kg gained). However, 143 patients (38.3 %) lost up to 10 % of their body weight during the course of the year, and 65 (17.4 %) lost 10 % or more of their body weight. In total, 208 (55.8 %) study participants lost weight after disruption in care.
AIDS Behav Table 2 Characteristics of 373 survey participants, one year after disruption in care Characteristic
N (%)
Gender
373
Characteristic
N (%)a
Missed doses of ART for two or more consecutive days at new site of care (among those on ART)
348
a
Male
109 (29.2)
Female
264 (70.8)
Age at survey
Table 2 continued
Yes Number of illness after transfer
36 (10.3) 373
346
0
222 (59.5)
18–29
21 (6.1)
1
147 (39.4)
30–39
97 (28.0)
2
4 (1.1)
40–49 50–59
135 (39.0) 72 (20.8)
New diagnoses of TB after transfer
60?
21 (6.1)
WHO clinical stage at new site of care
Received formal transfer notification Yes Intended site of transfer (SOT) Civilian government hospital
Yes I
22 (5.9)
319 (85.5)
II
79 (21.2)
305
III
254 (68.1)
264 (86.5)
IV
18 (4.8)
25 (8.2)
Other
16 (5.2)
Support group participation at new site of care Yes
373
a
Yes First contact at new site of care Nurse
131 (38.4)
Pharmacist
45 (13.2)
Other Don’t know
8 (2.3) 18 (5.3)
Services received at new site of care Medical record file
344 197 (57.3) 373 330 (88.5)
Adherence counseling
75 (20.1)
CD4 count
160 (42.9)
Other laboratory analysis
45 (12.1)
Satisfaction with care at AMO-Congo
353
Not at all
0 (0.0)
Slightly
2 (0.6)
Moderately
11 (3.1)
Very
257 (72.8)
Extremely
83 (23.5)
Satisfaction with care at new site of care
342
Not at all Slightly
107 (31.3) 84 (24.6)
Moderately
106 (31.0)
Very
45 (13.2)
Extremely
0 (0.0)
Taking cotrimoxazole at new site of care Yes Missed doses of any drug for two or more consecutive days at new site of care Yes
Percentages calculated among non-missing responses
341 139 (40.8)
Yes
373 82 (22.0)
284 (76.1)
Physician
Saw a physician at new site of care
373
373
Military government hospital Sought care at intended SOT
373 6 (1.6)
373 311 (83.4) 373 91 (24.4)
Support Services and Patient Satisfaction Prior to the disruption in care, the majority (N = 225, 60.3 %) of the study participants had been active in a support group at AMO-Congo. At the new site of care, the number of study participants that were in a support group dropped to 82 (22.0 %). When asked about satisfaction with care at AMO-Congo, only two people responded that they had been ‘‘not at all’’ or ‘‘slightly’’ satisfied with their care. The remaining 351 participants reported being ‘‘moderately,’’ ‘‘very,’’ or ‘‘extremely’’ satisfied with their care at AMO-Congo. When asked about satisfaction at their new site of care, more than half of the participants (N = 191, 51.2 %) reported being ‘‘not at all’’ or ‘‘slightly’’ satisfied with their care, and 151 (40.5 %) were either ‘‘moderately’’ or ‘‘very’’ satisfied. No participants reported being ‘‘extremely’’ satisfied with the care at their new site of care. Additional details regarding patient characteristics at the time of the survey are presented in Table 2. For details regarding patient outcomes at their last follow-up visit and outcomes one year after the disruption in care, please see Table 3. Comparison of Survey Participants with Those Considered Lost to Follow-Up or Otherwise Unavailable We compared characteristics from baseline and last followup visit prior to disruption in care among the patients who
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participated in the survey (n = 373) with those who were determined lost to follow-up or unavailable (n = 518) using the Wald F test. We found the following significant differences between the patients who participated in the study and those who did not. Participants who lived 1–2 h away from the clinic were less likely to have participated in the survey than those living within 30 min (OR = 0.6, 95 % CI 0.4–0.9, p \ 0.05) and those who lived more than two hours away were even less likely to participate than those who lived within 30 min (OR = 0.2, 95 % CI 0.1–0.3, p \ 0.001). Other baseline factors that increased odds of participation in the survey were having electricity at home (OR = 1.6, 95 % CI 1.3–2, p \ 0.001) and not being in a discordant partnership (OR = 1.3, 95 % CI 0.8–2, p \ 0.01). When we examined different variables at the follow-up visit prior to disruption in care, we found that taking ART was associated with participation in the study. Patients who had been taking or who started ART at their last follow-up visit had greater odds of participating in the survey (OR = 1.68, 95 % CI 1.3–2.2, p \ 0.001). Those who reported missing ARV doses for two or more consecutive days at their last follow-up visit at AMO-Congo had lesser odds of completing the survey than those who did not report missing ARV doses (OR = 0.36, 95 % CI 0.2–0.8, p \ 0.05), though this finding should be interpreted with caution given there were few who reported non-adherence. Only 6 patients who completed the survey reported ART non-adherence at their last follow-up visit at AMO-Congo as compared to 20 patients that did not complete the survey.
Discussion The results of this study illustrate the vulnerability of patients who experience a disruption in care, although not all outcomes were negative. Most of the patients who received a formal transfer from AMO-Congo did continue care at their SOT, which highlights the importance of provider-patient communication in the event of a disruption. Though there was little change in WHO clinical stage at the new site of care, more than half of the study participants lost weight after disruption in care, medication adherence decreased, cotrimoxizole prophylaxis use declined, support group participation dropped, and satisfaction with care worsened at the new site of care. The patients who continued seeking care were more likely to be taking ART than those who were deemed lost to follow-up. Many studies have shown higher rates of loss to care among patients who are pre-ART than those who are on therapy, in developed and developing countries [9– 15]. The data presented here further highlight the
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Table 3 Patient outcomes at last follow up visit and one year after disruption in care (n = 373) Outcome
N (%)a
WHO clinical stage
373
Worse status
13 (3.5)
Same status
350 (93.8)
Improved status
10 (2.7)
ART use
22 (5.9)
Was on ART at last follow-up; no longer on ART Was not on ART at last follow-up; started ART
3 (0.8) 38 (10.2)
Was on ART at last follow-up; still on ART Cotrimoxazole prophylaxis
310 (83.1) 368
Was on cotrixomazole at last follow-up; no longer on cotrimoxazole
58 (15.8)
Was not on cotrimoxazole at last follow-up; started cotrimoxazole
3 (0.8)
Was on cotrimoxazole at last follow-up; still on cotrimoxazole
307 (83.4)
Weight Lost 10 % or more of body weight
373 65 (17.4)
Lost \10 % of body weight
143 (38.3)
Maintained weight
60 (16.1)
Gained weight
105 (28.2)
Satisfaction with care
a
373
Never on ART
324
Worse satisfaction
282 (87.0)
Same satisfaction
38 (11.7)
Improved satisfaction
4 (1.2)
Percentages calculated among non-missing responses
vulnerability of these patients to be lost, particularly after a disruption in care. If Global Fund contributions remain uncertain, other providers may face the reality of closing or reducing services. Or, more optimistically, an increase in HIV/AIDS infrastructure or decentralization of services may allow patients to transfer to facilities that are closer and more convenient for them, which others have found to improve follow-up rates [16] and survival [17]. In the event of a planned disruption, efforts should be made to ensure that these patients are supported during the transfer to a different facility. In the event of any of these scenarios, providing structured transitions from one clinic to another can improve satisfaction and perceived health status [18]. Although little evidence exists on retention of patients after a formal clinic transfer, one study tracked a sample of patients considered lost to follow-up and found a corrected estimate of 86 % of patients to be retained in care after 2 years as compared to the naı¨ve estimate, which found only 69 % to be retained in care after 2 years [16]. This was, in part, due to patients transferring ‘‘silently’’ [16], pointing to the importance of our study in documenting the transfers and learning that the
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majority of the transferred patients were retained in care. Simple measures such as providing written transfer notes and ensuring that patients have an adequate drug supply during the gap between facilities may increase the likelihood of successful transfer. Use of ‘‘expert patients’’, those who attend appointments and take medications regularly, has been effective in HIV treatment [19], and may be beneficial in clinic transfers, as well. For example, expert patients could coordinate patient-run support groups to welcome newly transferred patients, and to facilitate uptake at new clinics. Poor adherence to ART leads to drug resistance and subsequent treatment failure [20, 21], particularly when interruption in therapy is sustained [21]. A systematic review of efforts to improve adherence to ART in subSaharan Africa found that several factors significantly improved adherence [22]. While some of these interventions, such as directly observed therapy (DOT) or providing food rations, would be difficult to maintain during a time of treatment disruption, others, such as continuous treatment supporters or cell phone reminders could be feasible during the transition time between clinics. Adherence among the patients surveyed in the current study decreased after the disruption in care, which is worrisome for potential resistance and treatment failure in this population. Studies conducted in Malawi and Kenya revealed that poor nutritional status contributed to attrition (due to loss to follow-up or mortality) from HIV care and treatment programs [23, 24], and food instability has been found to be a determinant of ART interruption [25]. Biadgilign et al. [26] found that, in Ethiopia, weight loss of greater than 10 % body weight at any point during disease progression was a predictor of mortality. More than one-third of the patients who participated in this study (N = 143, 38.3 %) lost up to 10 % of their body weight, and 65 patients (17.4 %) lost 10 % or more of their body weight after transferring, which may indicate food instability and certainly indicates a worse nutritional status after disruption in care. These figures are alarming considering both the health implications of weight loss in this patient population [26], and the increased risk for attrition from their SOT. In the current study, support group participation dropped from 60.3 % (N = 225) at AMO-Congo to 22.0 % (N = 82) at the new site of care. Others have found that HIV-infected patients who participated in a support group not only had improved mental health outcomes [27] and social support [28], but also lower rates of mortality and loss to follow-up, higher rates of retention, and higher rates of viral suppression [29]. Another study found better rates of ART adherence among women enrolled in a support group than those not enrolled [27]. These are compelling reasons to offer support groups as a component of
comprehensive HIV care and treatment, an area for improvement for the SOTs in this study. We assessed WHO clinical stage at the time of the survey and compared these results to those at the last follow-up visit prior to disruption in care. Although clinical stage remained the same for the vast majority of the patients in this survey, there may have been changes in immunologic status that were not apparent due to lack of CD4 counts throughout HIV care and treatment and at the time of the survey. Laboratory services are extremely limited in the DRC, and fewer than half of all patients receiving care at the Lubumbashi AMO-Congo clinics had documented CD4 counts at any point during their care and treatment. As such, we did not measure CD4 at the time of the survey, but one study from Canada found that patients who left and subsequently re-entered care were more likely to suffer from an AIDS defining event and to have a significant reduction in CD4 count than those who remained in care continuously [30]. Given we observed more nonadherence after the disruption than before the disruption, and that many of the sample patients who did not complete the survey were not taking ART at the time of disruption, it is likely that this population is at risk for accelerated disease progression. Limitations Time constraints during the study period, complicated by civil unrest in Lubumbashi during the 2011 presidential elections, limited our ability to contact all patients in our sample, which may have affected our results. Further, poor cell phone reception outside of Lubumbashi made it difficult to contact people living outside of town. This likely reduced participation in the survey of people who lived farther away from the clinics. The responses to the patient satisfaction questions were obtained at AMO-Congo by clinicians who were former AMO-Congo employees, which may have lead to social desirability bias. Adherence was assessed via self-report and may have also been affected by social desirability. However, Oyugi et al. [31] found that self-report is an accurate way to measure adherence in a resource-limited setting.
Conclusion The disruption in HIV care and treatment described here jeopardized patient retention, especially among those who were ART naı¨ve at the time of disruption. When possible, efforts should be made to facilitate patient transfers to new facilities in order to ensure uptake of services at the SOT. Adherence counseling should be provided throughout care
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and treatment, and especially during the transition to a new facility, which can compromise adherence. Clinicians should strive to offer continuity of care whenever possible, but in light of a planned disruption, vulnerable individuals, such as those pre-ART, should be identified and supported during the transfer process. Acknowledgments Research reported in this publication was supported by the National Institute of Allergy and Infectious Diseases (NIAID) of the National Institutes of Health under Award Number U01AI069927. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The International epidemiologic Databases to Evaluate AIDS (IeDEA) Central Africa region collaboration acknowledges the contribution of local staff and patients in this project, Dr. Robin Huebner of NIAID, and Ms. Jeniffer Iriondo-Perez at RTI International.
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IeDEA HIV clinics in DRC, Cameroon and Burundi. Poster session presented at the international AIDS conference, Washington DC, July 2012. Togun T, Peterson I, Jaffar S, et al. Pre-treatment mortality and loss-to-follow-up in HIV-1, HIV-2, and HIV-1/HIV-2 dually infected patients eligible for antiretroviral therapy in The Gambia, West Africa. AIDS Res Ther. 2011;8(1):24. Koole O, Kalenga L, Kiumbu M, et al. Retention in a NGO supported antiretroviral program in the Democratic Republic of Congo. PLoS ONE. 2012;7(7):e40971. doi:10.1371/journal.pone. 0040971. Geng EH, Glidden DV, Bwana MB, et al. Retention in care and connection to care among HIV-infected patients on antiretroviral therapy in Africa: estimation via a sampling-based approach. PLoS ONE. 2011;6(7):e21797. doi:10.1371/journal.pone.0021797. Geng EH, Bwana MB, Muyindike W, et al. Failure to initiate antiretroviral therapy, loss to follow-up and mortality among HIV-infected patients during the pre-ART period in Uganda. J Acquir Immune Defic Syndr. 2013;63(2):e64–71. Chaudhry SR, Keaton M, Nasr SZ. Evaluation of a cystic fibrosis transition program from pediatric to adult care. Pediatr Pulmonol. 2012;. doi:10.1002/ppul.22647. Tenthani L, Cataldo F, Chan AK, et al. Involving expert patients in antiretroviral treatment provision in a tertiary referral hospital HIV clinic in Malawi. BMC Health Serv Res. 2012;12(1):140. doi:10.1186/1472-6963-12-140. Oyugi JH, Byakika-Tusiime J, Ragland K, et al. Treatment interruptions predict resistance in HIV-positive individuals purchasing fixed-dose combination antiretroviral therapy in Kampala, Uganda. AIDS. 2007;21(8):965–71. Parienti J, Das-Douglas M, Massari V, et al. Not all missed doses are the same: sustained NNRTI treatment interruptions predict HIV rebound at low-to-moderate adherence levels. PLoS ONE. 2008;3(7):e2783. doi:10.1371/journal.pone.0002783. Barnighausen T, Chaiyachati K, Chimbindi N, Peoples A, Haberer J, Newell M. Interventions to increase antiretroviral adherence in sub-Saharan Africa: a systematic review of evaluation studies. Lancet Infect Dis. 2011;11(12):942–51. Zachariah R, Tayler-Smith K, Manzi M, et al. Retention and attrition during the preparation phase and after start of antiretroviral therapy in Thyolo, Malawi, and Kibera, Kenya: implications for programmes? Trans R Soc Trop Med Hyg. 2011; 105(8):421–30. Tayler-Smith K, Zachariah R, Manzi M, et al. Demographic characteristics and opportunistic diseases associated with attrition during preparation for antiretroviral therapy in primary health centres in Kibera, Kenya. Trop Med Int Health. 2011;16(5):579–84. Marcellin F, Boyer S, Protopopescu C, et al. Determinants of unplanned antiretroviral treatment interruptions among people living with HIV in Yaounde, Cameroon (EVAL survey, ANRS 12–116). Trop Med Int Health. 2008;13(12):1470–8. Biadgilign S, Reda AA, Digaffe T. Predictors of mortality among HIV infected patients taking antiretroviral therapy in Ethiopia: a retrospective cohort study. AIDS Res Ther. 2012;9(1):15. doi:10. 1186/1742-6405-9-15. Walstrom P, Operario D, Zlotnick C, Mutimura E, Benekigeri C, Cohen MH. ‘I think my future will be better than my past’: examining support group influence on the mental health of HIVinfected Rwandan women. Glob Public Health. 2013;8(1): 90–105. Smith Fawzi MC, Eustache E, Oswald C, et al. Psychological support intervention for HIV-affected families in Haiti: implications for programs and policies for orphans and vulnerable children. Soc Sci Med. 2012;74(10):1494–503. Fatti G, Meintjes G, Shea J, Eley B, Grimwood A. Improved survival and antiretroviral treatment outcomes in adults receiving
AIDS Behav community-based adherence support: five-year results from a multicentre cohort study in South Africa. J Acquir Immune Defic Syndr. 2012;61(4):e50–8. doi:10.1097/QAI.0b013e31826aee. 30. Krentz H, Worthington H, Gill JM. Adverse health effects for individuals who move between HIV care centers. J Acquir Immune Defic Syndr. 2011;1(57):51–4.
31. Oyugi JH, Byakika-Tusiime J, Charlebois ED, et al. Multiple validated measures of adherence indicate high levels of adherence to generic HIV antiretroviral therapy in a resource-limited setting. J Acquir Immune Defic Syndr. 2004;36(5):1100–2.
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ORIGINAL PAPER
Patient Outcomes in Lubumbashi, Democratic Republic of Congo After a Disruption in HIV Care Due to Decreased Global Fund Appropriations Anna Freeman • Modeste Kiumbu • Blaise Mwamba • Joseph Atibu • Henri Mukumbi • Louis Mwila • Christopher Cummiskey • Kristen Stolka Jennifer Hemingway-Foday • Jamie E. Newman
•
Ó Springer Science+Business Media New York 2014
Abstract This study examines care seeking behaviors, clinical outcomes, and satisfaction with care of HIV-positive adults in Lubumbashi, DRC, one year after a disruption in care due to decreased global fund appropriations. We describe outcomes before and after the disruption. We compared characteristics of those who completed the survey and those who did not using the Wald F test. Most patients sought care after the disruption and continued antiretroviral therapy (ART), though use of cotrimoxizole prophylaxis declined. Though there was little change in WHO clinical stage at the new site of care, the majority of participants lost weight, adherence decreased, support group participation dropped, and satisfaction with care worsened. Patients were more likely to participate in the study if they were taking ART. This study highlights the importance of provider-patient communication during a transfer and the vulnerability of pre-ART patients to becoming lost to follow-up. A. Freeman K. Stolka J. Hemingway-Foday J. E. Newman (&) Statistics and Epidemiology, RTI International, 3040 Cornwallis Road, Research Triangle Park, NC 27709-2194, USA e-mail: [email protected] M. Kiumbu J. Atibu Kinshasa School of Public Health, Kinshasa, Democratic Republic of the Congo
Resumen Este estudio analiza los comportamientos de bu´squeda de atencio´n, resultados clı´nicos y la satisfaccio´n de adultos con VIH respecto a la atencio´n recibida en Lubumbashi, RDC. El estudio se realizo´ un an˜o despue´s de la interrupcio´n en la atencio´n debido a la disminucio´n en la partida de recursos del Fondo Mundial. Se describen los resultados antes y despue´s de la interrupcio´n. Comparamos las caracterı´sticas de aquellos que completaron la encuesta con aquellos que no lo hicieron, usando la prueba F-Wald. La mayorı´a de los pacientes buscaron atencio´n despue´s de la interrupcio´n y continuaron con la terapia antirretroviral (TAR), aunque el uso de profilaxis con cotrimoxazol declino´. A pesar del pequen˜o cambio en el OMS estadio clı´nico, en el nuevo lugar de atencio´n, la mayorı´a de los participantes perdieron peso, la adherencia disminuyo´, la participacio´n en grupos de apoyo se redujo y la satisfaccio´n con la atencio´n empeoro´. Los pacientes fueron ma´s propensos a participar en el estudio si estaban tomando TAR. Este estudio resalta la importancia de la comunicacio´n proveedor-paciente durante una transferencia y el riesgo de perder el seguimiento en pacientes preTAR. Keywords HIV Africa Funds Delivery of health care Medication adherence
B. Mwamba L. Mwila AMO-Congo, Lubumbashi, Democratic Republic of the Congo
Introduction
H. Mukumbi AMO-Congo, Kinshasa, Democratic Republic of the Congo
Sub-Saharan Africa is the region of the world most affected by HIV/AIDS [1], and economic, political, and geographic constraints have added challenges to health care systems struggling to combat this epidemic. In 2002, the global fund to fight AIDS, tuberculosis, and malaria (global fund)
C. Cummiskey International Development Group, RTI International, Washington, DC, USA
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was created as an international financing institution to gather and dispense funds to prevent and treat these diseases [2]. In recent years, the global fund, which depends on donations from high-income countries, suffered a lack of contributions due to the worldwide economic downturn [3]. The amount of support that will be offered by global fund in coming years remains uncertain, and the implications of these changes in funding are potentially devastating to countries that depend on these funds for HIV/AIDS programming [4, 5]. The Democratic Republic of the Congo (DRC) has relied heavily on global fund contributions for its HIV/ AIDS prevention and treatment programs [6]. Historically, much of this funding has been allocated to AMO-Congo, a Congolese non-governmental organization that has provided HIV care and treatment services throughout the DRC since 1993 [7]. At its peak, AMO-Congo managed eleven clinics in six provinces and was the largest provider of antiretroviral therapy (ART) in the country. In Lubumbashi, the second largest city in the DRC, AMO-Congo operated two HIV care and treatment facilities, serving approximately 3,100 people living with HIV/AIDS. Services included counseling and testing, provision of ART and other medications, nutritional support, and psychosocial support services. In 2008 and 2009, the global fund reduced its assistance for HIV services to the DRC by one-third, and in subsequent years, the DRC was ineligible to receive funding from the global fund for HIV prevention and treatment [8]. As a consequence, AMO-Congo restricted services offered in some clinics, and in other areas, was forced to close treatment facilities. The two AMO-Congo clinics in Lubumbashi were closed in 2010 and the patients receiving care at these sites were transferred to government-run facilities. This study describes these patients one year after this disruption in care and examines care-seeking behaviors, clinical outcomes, medication use and adherence, and patient satisfaction.
Methods This analysis was part of the National Institutes of Health (NIH)-funded Central Africa regional database of the International epidemiologic databases to evaluate AIDS (Phase I IeDEA Central Africa). Approval for this research was granted by the institutional review board at the Kinshasa school of public health in the DRC and RTI international. Patients were notified of the pending closure and transfers via telephone, signs posted at each clinic, and through word-of-mouth. Clinicians at AMO-Congo provided written transfers to one of three government facilities (based on patient address or per their request) for patients
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who came to the clinic during the period September to December 2010. Sample Selection For our sample, we randomly selected 1,000 patients from the Phase I IeDEA Central Africa database attending two AMO-Congo clinics in Lubumbashi. Inclusion criteria required patients to have a baseline data form in the IeDEA database (which was completed when patients originally enrolled into the IeDEA database) and at least one followup form during the time period between April 1 and September 30, 2010. As patients were asked to return to the clinic every three months (for those on ART) or every six months (for those pre-ART), this time frame was designed to capture all patients who were actively engaged in HIV care and treatment, and thus eliminated those who were lost to follow-up or deceased prior to the clinic closures. This sample was drawn using systematic random sampling stratified by the following variables of interest: ART status at follow up, WHO clinical stage at baseline, distance to clinic, age group (18–29, 30–39, 40–49, 50–59, and 60? years), and gender. Patients were contacted by telephone and home visit, or home visit only when no telephone number was available. Each patient received a total of five contact attempts before being declared lost to follow-up. Informed consent was obtained in French or Kiswahili, according to patient preference. Patients were reimbursed $5 USD for transport fees to the clinic. All surveys were conducted in face-to-face interviews between September and December 2011, approximately one year after this cohort of patients was transferred from AMO-Congo to government-run care facilities. Data Collection The survey included questions regarding care-seeking behaviors after disruption in care, services received at their new site of care, ART and other medication use, adherence, satisfaction with care at AMO-Congo and at the new site of care, and support group participation at AMO-Congo and the new site of care. Adherence was self-reported. Nonadherence was defined by missing any drug for two or more consecutive days within the past 30 days. Patient satisfaction questions were asked using a 5-point Likert scale (ranging from 1-not at all satisfied to 5-extremely satisfied) with open-ended follow-up. Outcomes related to death, relocation, and hospitalization were obtained from family members or neighbors, if the patient could not be reached. For pre-disruption indicators, we used data collected while the patients were receiving care at the AMO-Congo Lubumbashi clinics between 2007 and 2010 (Table 1). These data were collected as part of the Phase I IeDEA
AIDS Behav Table 1 Timepoints at which variables were measured Baseline (at enrollment into IeDEA database)
Last follow-up visit at AMO-Congo AND survey at one year after disruption of care
Survey at one year after disruption of care
Demographic information
ART and other medication use
Transfer information
Adherence
Services received at new site of care
Medical assessment Anthropometric measures WHO clinical stage
Care-seeking behaviors
Satisfaction with care (at AMO-Congo and new site of care) Support group participation (at AMO-Congo and new site of care)
Central Africa database and included information from the patient’s baseline visit and last follow up visit before the disruption in care. Data from these forms included demographics, information on ART and other medication use, and adherence. Adherence questions were worded identically on the post-disruption survey and the initial IeDEA forms: during the last month, has the patient missed taking medication more than 2 consecutive days? Statistical Analysis Epi-Info was used for on-site data-entry and cleaning. All data processing and analyses were conducted using SAS 9.1 for Windows (SAS Institute) and SUDAAN 10.0.1 (RTI International). We first analyzed the responses of the patients who participated in the survey (n = 373) to examine care seeking behaviors and patient outcomes after transfer. We examined baseline demographic, behavioral, and clinical characteristics of these patients using the IeDEA dataset to describe outcomes at baseline, or last documented follow-up visit, and at the time of the survey. Finally, we compared characteristics from baseline and last follow-up visit prior to disruption in care of the patients who completed the survey with those who were sampled but were deemed lost to follow-up. The Wald F test was used determine if distributions between these groups differed. Results Overview Information on sample selection and survey completion is detailed in Fig. 1. In total, 373 patients completed the
survey. Of those who did not participate, 427 were deemed lost to follow-up after five contact attempts were made. Twenty-seven patients were confirmed deceased. Ninetyone patients were contacted but were unable to participate in the study. Of these, one person was hospitalized, 84 had relocated, two were traveling during the time of the survey, and four were unavailable for unspecified reasons. An additional 82 people were not contacted due to time constraints. Transfers and Care-Seeking Behavior Of the 373 patients who completed the survey, 264 (70.8 %) were women, which is consistent with the proportion of women that attended the two Lubumbashi clinics as well as the Phase I IeDEA Central Africa database overall. Most (N = 304, 81.5 %) were aged 30–59 years, and the mean age was 44 years. Of these 373 patients, 319 (85.5 %) received a formal transfer notice from their AMO-Congo clinic in the form of a written or verbal transfer. Of the 373 patients surveyed, 289 (77.5 %) reported being transferred to an HIV care and treatment clinic in a government-run hospital and 16 (4.3 %) were transferred to other facilities at their request. Of the 289 patients who transferred to government-run facilities, 264 were referred to two civilian hospitals, and the remaining 25 were referred to a military hospital. In total, 284 patients (76.1 %) sought care at their site of transfer (SOT); that is, the government-run clinic to which they were referred by the clinicians at AMOCongo. Of the 35 patients who did not seek care at their SOT, 23 went to a different facility, one went to a clinic at their workplace, six abandoned treatment entirely, and five did not indicate their plans for seeking care. Reasons for not seeking care at their SOT that the 35 patients provided include: poor treatment or lack of confidence in the care at the SOT (N = 11), long travel time (N = 7), and stigmatization or concerns about patient confidentiality (N = 7). Of the 344 patients who sought care following the closure of the AMO-Congo clinics (though not necessarily at their SOT), 139 (40.4 %) first met with a physician, 131 (38.1 %) first met with a nurse, and 45 (13.1 %) first met with a pharmacist. In the one year since the disruption in care, 197 (57.3 %) patients saw a physician at some point. At their new site of care, 330 of the 344 patients (95.9 %) received a medical record file. Few (N = 75, 21.8 %) received adherence counseling, the consequences of which are discussed below. Fewer than half (N = 160, 46.5 %) had CD4 testing, and very few (N = 45, 13.1 %) had any other laboratory analyses, including viral load testing, performed.
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Fig. 1 Patient population sampled for this study
Medication Use and Adherence Of the 373 patients who participated in the survey, 313 (83.9 %) had been taking ART prior to the disruption in care. Of these 313 patients, 310 continued taking ART and only 3 reported discontinuing ART. Of the 310 patients who continued taking ART, 31 changed one or more of the drugs in their regimen. Of the 60 patients not taking ART prior to disruption in care, 38 started ART at their new site of care. Nearly all (97.9 %, N = 365) of the 373 patients surveyed were taking cotrimoxazole prophylaxis while receiving care at AMO-Congo though only 311 (83.4 %) were on cotrimoxazole at their new site of care. Three patients (0.8 %) started cotrimoxazole at their new site of care. At the time of the last follow-up visit at AMO-Congo, few (4.9 %) patients in this survey had self-reported nonadherence, defined by missing any drug for two or more consecutive days within the past 30 days. One year after the disruption in care, 91 (24.4 %) participants reported non-adherence. When asked about adherence to ART specifically, 36 (10.3 %) of the 348 participants who were taking ART reported non-adherence, due to stock-outs (N = 12), lack of healthcare worker to distribute the drugs at the clinic (N = 4), travel (N = 4), missed appointment by the patient (N = 3), or because the patient chose to stop taking ART (N = 5). When asked about adherence to cotrimoxazole one year after the disruption in care, 49
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(15.8 %) of the 311 participants who were taking this drug reported non-adherence, due to stock-outs (N = 25), forgetting to purchase it (N = 5), forgetting to take it (N = 4), lack of healthcare worker to distribute the drugs at the clinic (N = 5), travel, (N = 3), and lack of money to pay for the cotrimoxazole (N = 4). Clinical Outcomes A physician or nurse assessed the patient’s WHO clinical stage at the new site of care. Most of the 373 patients (N = 254, 68.1 %) were in Stage III, and 79 patients (21.2 %) were in Stage II. Few patients were in Stage I (N = 22, 5.9 %) or Stage IV (N = 18, 4.8 %). This represented very little change from the time of the last follow-up visit prior to disruption of care at AMO-Congo and the new site of care: 350 patients (93.8 %) had the same WHO clinical stage, 13 patients (3.5 %) had a worse clinical stage and 10 patients (2.7 %) had an improved clinical stage. Each patient was weighed at the new site of care, and these weights were compared to the recorded weight at the last follow-up visit prior to disruption in care at AMOCongo. Sixty patients (16.1 %) maintained the same body weight and 105 patients (28.2 %) gained weight (0.4-29 kg gained). However, 143 patients (38.3 %) lost up to 10 % of their body weight during the course of the year, and 65 (17.4 %) lost 10 % or more of their body weight. In total, 208 (55.8 %) study participants lost weight after disruption in care.
AIDS Behav Table 2 Characteristics of 373 survey participants, one year after disruption in care Characteristic
N (%)
Gender
373
Characteristic
N (%)a
Missed doses of ART for two or more consecutive days at new site of care (among those on ART)
348
a
Male
109 (29.2)
Female
264 (70.8)
Age at survey
Table 2 continued
Yes Number of illness after transfer
36 (10.3) 373
346
0
222 (59.5)
18–29
21 (6.1)
1
147 (39.4)
30–39
97 (28.0)
2
4 (1.1)
40–49 50–59
135 (39.0) 72 (20.8)
New diagnoses of TB after transfer
60?
21 (6.1)
WHO clinical stage at new site of care
Received formal transfer notification Yes Intended site of transfer (SOT) Civilian government hospital
Yes I
22 (5.9)
319 (85.5)
II
79 (21.2)
305
III
254 (68.1)
264 (86.5)
IV
18 (4.8)
25 (8.2)
Other
16 (5.2)
Support group participation at new site of care Yes
373
a
Yes First contact at new site of care Nurse
131 (38.4)
Pharmacist
45 (13.2)
Other Don’t know
8 (2.3) 18 (5.3)
Services received at new site of care Medical record file
344 197 (57.3) 373 330 (88.5)
Adherence counseling
75 (20.1)
CD4 count
160 (42.9)
Other laboratory analysis
45 (12.1)
Satisfaction with care at AMO-Congo
353
Not at all
0 (0.0)
Slightly
2 (0.6)
Moderately
11 (3.1)
Very
257 (72.8)
Extremely
83 (23.5)
Satisfaction with care at new site of care
342
Not at all Slightly
107 (31.3) 84 (24.6)
Moderately
106 (31.0)
Very
45 (13.2)
Extremely
0 (0.0)
Taking cotrimoxazole at new site of care Yes Missed doses of any drug for two or more consecutive days at new site of care Yes
Percentages calculated among non-missing responses
341 139 (40.8)
Yes
373 82 (22.0)
284 (76.1)
Physician
Saw a physician at new site of care
373
373
Military government hospital Sought care at intended SOT
373 6 (1.6)
373 311 (83.4) 373 91 (24.4)
Support Services and Patient Satisfaction Prior to the disruption in care, the majority (N = 225, 60.3 %) of the study participants had been active in a support group at AMO-Congo. At the new site of care, the number of study participants that were in a support group dropped to 82 (22.0 %). When asked about satisfaction with care at AMO-Congo, only two people responded that they had been ‘‘not at all’’ or ‘‘slightly’’ satisfied with their care. The remaining 351 participants reported being ‘‘moderately,’’ ‘‘very,’’ or ‘‘extremely’’ satisfied with their care at AMO-Congo. When asked about satisfaction at their new site of care, more than half of the participants (N = 191, 51.2 %) reported being ‘‘not at all’’ or ‘‘slightly’’ satisfied with their care, and 151 (40.5 %) were either ‘‘moderately’’ or ‘‘very’’ satisfied. No participants reported being ‘‘extremely’’ satisfied with the care at their new site of care. Additional details regarding patient characteristics at the time of the survey are presented in Table 2. For details regarding patient outcomes at their last follow-up visit and outcomes one year after the disruption in care, please see Table 3. Comparison of Survey Participants with Those Considered Lost to Follow-Up or Otherwise Unavailable We compared characteristics from baseline and last followup visit prior to disruption in care among the patients who
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participated in the survey (n = 373) with those who were determined lost to follow-up or unavailable (n = 518) using the Wald F test. We found the following significant differences between the patients who participated in the study and those who did not. Participants who lived 1–2 h away from the clinic were less likely to have participated in the survey than those living within 30 min (OR = 0.6, 95 % CI 0.4–0.9, p \ 0.05) and those who lived more than two hours away were even less likely to participate than those who lived within 30 min (OR = 0.2, 95 % CI 0.1–0.3, p \ 0.001). Other baseline factors that increased odds of participation in the survey were having electricity at home (OR = 1.6, 95 % CI 1.3–2, p \ 0.001) and not being in a discordant partnership (OR = 1.3, 95 % CI 0.8–2, p \ 0.01). When we examined different variables at the follow-up visit prior to disruption in care, we found that taking ART was associated with participation in the study. Patients who had been taking or who started ART at their last follow-up visit had greater odds of participating in the survey (OR = 1.68, 95 % CI 1.3–2.2, p \ 0.001). Those who reported missing ARV doses for two or more consecutive days at their last follow-up visit at AMO-Congo had lesser odds of completing the survey than those who did not report missing ARV doses (OR = 0.36, 95 % CI 0.2–0.8, p \ 0.05), though this finding should be interpreted with caution given there were few who reported non-adherence. Only 6 patients who completed the survey reported ART non-adherence at their last follow-up visit at AMO-Congo as compared to 20 patients that did not complete the survey.
Discussion The results of this study illustrate the vulnerability of patients who experience a disruption in care, although not all outcomes were negative. Most of the patients who received a formal transfer from AMO-Congo did continue care at their SOT, which highlights the importance of provider-patient communication in the event of a disruption. Though there was little change in WHO clinical stage at the new site of care, more than half of the study participants lost weight after disruption in care, medication adherence decreased, cotrimoxizole prophylaxis use declined, support group participation dropped, and satisfaction with care worsened at the new site of care. The patients who continued seeking care were more likely to be taking ART than those who were deemed lost to follow-up. Many studies have shown higher rates of loss to care among patients who are pre-ART than those who are on therapy, in developed and developing countries [9– 15]. The data presented here further highlight the
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Table 3 Patient outcomes at last follow up visit and one year after disruption in care (n = 373) Outcome
N (%)a
WHO clinical stage
373
Worse status
13 (3.5)
Same status
350 (93.8)
Improved status
10 (2.7)
ART use
22 (5.9)
Was on ART at last follow-up; no longer on ART Was not on ART at last follow-up; started ART
3 (0.8) 38 (10.2)
Was on ART at last follow-up; still on ART Cotrimoxazole prophylaxis
310 (83.1) 368
Was on cotrixomazole at last follow-up; no longer on cotrimoxazole
58 (15.8)
Was not on cotrimoxazole at last follow-up; started cotrimoxazole
3 (0.8)
Was on cotrimoxazole at last follow-up; still on cotrimoxazole
307 (83.4)
Weight Lost 10 % or more of body weight
373 65 (17.4)
Lost \10 % of body weight
143 (38.3)
Maintained weight
60 (16.1)
Gained weight
105 (28.2)
Satisfaction with care
a
373
Never on ART
324
Worse satisfaction
282 (87.0)
Same satisfaction
38 (11.7)
Improved satisfaction
4 (1.2)
Percentages calculated among non-missing responses
vulnerability of these patients to be lost, particularly after a disruption in care. If Global Fund contributions remain uncertain, other providers may face the reality of closing or reducing services. Or, more optimistically, an increase in HIV/AIDS infrastructure or decentralization of services may allow patients to transfer to facilities that are closer and more convenient for them, which others have found to improve follow-up rates [16] and survival [17]. In the event of a planned disruption, efforts should be made to ensure that these patients are supported during the transfer to a different facility. In the event of any of these scenarios, providing structured transitions from one clinic to another can improve satisfaction and perceived health status [18]. Although little evidence exists on retention of patients after a formal clinic transfer, one study tracked a sample of patients considered lost to follow-up and found a corrected estimate of 86 % of patients to be retained in care after 2 years as compared to the naı¨ve estimate, which found only 69 % to be retained in care after 2 years [16]. This was, in part, due to patients transferring ‘‘silently’’ [16], pointing to the importance of our study in documenting the transfers and learning that the
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majority of the transferred patients were retained in care. Simple measures such as providing written transfer notes and ensuring that patients have an adequate drug supply during the gap between facilities may increase the likelihood of successful transfer. Use of ‘‘expert patients’’, those who attend appointments and take medications regularly, has been effective in HIV treatment [19], and may be beneficial in clinic transfers, as well. For example, expert patients could coordinate patient-run support groups to welcome newly transferred patients, and to facilitate uptake at new clinics. Poor adherence to ART leads to drug resistance and subsequent treatment failure [20, 21], particularly when interruption in therapy is sustained [21]. A systematic review of efforts to improve adherence to ART in subSaharan Africa found that several factors significantly improved adherence [22]. While some of these interventions, such as directly observed therapy (DOT) or providing food rations, would be difficult to maintain during a time of treatment disruption, others, such as continuous treatment supporters or cell phone reminders could be feasible during the transition time between clinics. Adherence among the patients surveyed in the current study decreased after the disruption in care, which is worrisome for potential resistance and treatment failure in this population. Studies conducted in Malawi and Kenya revealed that poor nutritional status contributed to attrition (due to loss to follow-up or mortality) from HIV care and treatment programs [23, 24], and food instability has been found to be a determinant of ART interruption [25]. Biadgilign et al. [26] found that, in Ethiopia, weight loss of greater than 10 % body weight at any point during disease progression was a predictor of mortality. More than one-third of the patients who participated in this study (N = 143, 38.3 %) lost up to 10 % of their body weight, and 65 patients (17.4 %) lost 10 % or more of their body weight after transferring, which may indicate food instability and certainly indicates a worse nutritional status after disruption in care. These figures are alarming considering both the health implications of weight loss in this patient population [26], and the increased risk for attrition from their SOT. In the current study, support group participation dropped from 60.3 % (N = 225) at AMO-Congo to 22.0 % (N = 82) at the new site of care. Others have found that HIV-infected patients who participated in a support group not only had improved mental health outcomes [27] and social support [28], but also lower rates of mortality and loss to follow-up, higher rates of retention, and higher rates of viral suppression [29]. Another study found better rates of ART adherence among women enrolled in a support group than those not enrolled [27]. These are compelling reasons to offer support groups as a component of
comprehensive HIV care and treatment, an area for improvement for the SOTs in this study. We assessed WHO clinical stage at the time of the survey and compared these results to those at the last follow-up visit prior to disruption in care. Although clinical stage remained the same for the vast majority of the patients in this survey, there may have been changes in immunologic status that were not apparent due to lack of CD4 counts throughout HIV care and treatment and at the time of the survey. Laboratory services are extremely limited in the DRC, and fewer than half of all patients receiving care at the Lubumbashi AMO-Congo clinics had documented CD4 counts at any point during their care and treatment. As such, we did not measure CD4 at the time of the survey, but one study from Canada found that patients who left and subsequently re-entered care were more likely to suffer from an AIDS defining event and to have a significant reduction in CD4 count than those who remained in care continuously [30]. Given we observed more nonadherence after the disruption than before the disruption, and that many of the sample patients who did not complete the survey were not taking ART at the time of disruption, it is likely that this population is at risk for accelerated disease progression. Limitations Time constraints during the study period, complicated by civil unrest in Lubumbashi during the 2011 presidential elections, limited our ability to contact all patients in our sample, which may have affected our results. Further, poor cell phone reception outside of Lubumbashi made it difficult to contact people living outside of town. This likely reduced participation in the survey of people who lived farther away from the clinics. The responses to the patient satisfaction questions were obtained at AMO-Congo by clinicians who were former AMO-Congo employees, which may have lead to social desirability bias. Adherence was assessed via self-report and may have also been affected by social desirability. However, Oyugi et al. [31] found that self-report is an accurate way to measure adherence in a resource-limited setting.
Conclusion The disruption in HIV care and treatment described here jeopardized patient retention, especially among those who were ART naı¨ve at the time of disruption. When possible, efforts should be made to facilitate patient transfers to new facilities in order to ensure uptake of services at the SOT. Adherence counseling should be provided throughout care
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and treatment, and especially during the transition to a new facility, which can compromise adherence. Clinicians should strive to offer continuity of care whenever possible, but in light of a planned disruption, vulnerable individuals, such as those pre-ART, should be identified and supported during the transfer process. Acknowledgments Research reported in this publication was supported by the National Institute of Allergy and Infectious Diseases (NIAID) of the National Institutes of Health under Award Number U01AI069927. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The International epidemiologic Databases to Evaluate AIDS (IeDEA) Central Africa region collaboration acknowledges the contribution of local staff and patients in this project, Dr. Robin Huebner of NIAID, and Ms. Jeniffer Iriondo-Perez at RTI International.
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![[Study of anemia in HIV positive children naive to antiretroviral treatment in Lubumbashi, Democratic Republic of Congo].](/assets/img/hold.png)
