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Time and Money

The True Costs of Health Care Utilization for Patients Receiving “Free” HIV/Tuberculosis Care and Treatment in Rural KwaZulu-Natal

Chimbindi, Natsayi MSc*,†; Bor, Jacob ScD*,‡; Newell, Marie-Louise PhD†,§; Tanser, Frank PhD*; Baltussen, Rob PhD; Hontelez, Jan PhD*,‖,¶; de Vlas, Sake J. PhD; Lurie, Mark PhD#; Pillay, Deenan PhD*,**; Bärnighausen, Till MD, ScD*,†,††

JAIDS Journal of Acquired Immune Deficiency Syndromes: October 1, 2015 - Volume 70 - Issue 2 - p e52–e60
doi: 10.1097/QAI.0000000000000728
Implementation and Operational Research: Epidemiology and Prevention
Free

Background: HIV and tuberculosis (TB) services are provided free of charge in many sub-Saharan African countries, but patients still incur costs.

Methods: Patient-exit interviews were conducted in primary health care clinics in rural South Africa with representative samples of 200 HIV-infected patients enrolled in a pre-antiretroviral treatment (pre-ART) program, 300 patients receiving antiretroviral treatment (ART), and 300 patients receiving TB treatment. For each group, we calculated health expenditures across different spending categories, time spent traveling to and using services, and how patients financed their spending. Associations between patient group and costs were assessed in multivariate regression models.

Results: Total monthly health expenditures [1 USD = 7.3 South African Rand (ZAR)] were ZAR 171 [95% confidence interval (CI): 134 to 207] for pre-ART, ZAR 164 (95% CI: 141 to 187) for ART, and ZAR 122 (95% CI: 105 to 140) for TB patients (P = 0.01). Total monthly time costs (in hours) were 3.4 (95% CI: 3.3 to 3.5) for pre-ART, 5.0 (95% CI: 4.7 to 5.3) for ART, and 3.2 (95% CI: 2.9 to 3.4) for TB patients (P < 0.01). Although overall patient costs were similar across groups, pre-ART patients spent on average ZAR 29.2 more on traditional healers and ZAR 25.9 more on chemists and private doctors than ART patients, whereas ART patients spent ZAR 34.0 more than pre-ART patients on transport to clinics (P < 0.05 for all results). Thirty-one percent of pre-ART, 39% of ART, and 41% of TB patients borrowed money or sold assets to finance health care.

Conclusions: Patients receiving nominally free care for HIV/TB face large private costs, commonly leading to financial distress. Subsidized transport, fewer clinic visits, and drug pick-up points closer to home could reduce costs for ART patients, potentially improving retention and adherence. Large expenditure on alternative care among pre-ART patients suggests that transitioning patients to ART earlier, as under HIV treatment-as-prevention policies, may not substantially increase patients' financial burden.

*Wellcome Trust Africa Centre for Health and Population Studies, University of KwaZulu-Natal, South Africa;

School of Public Health, University of the Witwatersrand, Johannesburg, South Africa;

Department of Global Health, School of Public Health, Boston University, Boston, MA;

§Faculty of Medicine and Faculty of Human and Social Sciences, University of Southampton, Southampton, United Kingdom;

Nijmegen International Center for Health System Analysis and Education (NICHE), Department of Primary and Community Care, Radboud University Nijmegen Medical Centre, Nijmegen, the Netherlands;

Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands;

#Department of Epidemiology and International Health Institute, Brown University School of Public Health, Providence, RI;

**Department of Virology, University College London, London, United Kingdom; and

††Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA.

Correspondence to: Natsayi Chimbindi, MSc, Africa Centre for Health and Population Studies, P.O. Box 198, Mtubatuba, 3935 KwaZulu-Natal, South Africa (e-mail: nchimbindi@africacentre.ac.za).

Part of this work was carried out with support from the Global Health Research Initiative (GHRI), a collaborative research funding partnership of the Canadian Institutes of Health Research, the Canadian International Development Agency, Health Canada, the International Development Research Centre, and the Public Health Agency of Canada (T.B.). This work was carried out in part by the Impact of ART on HIV Epidemic Dynamics study which was funded by the US National Institutes of Health grant 1R01MH083539 (M.L.) and by the Understanding Causal Pathways of HIV Acquisition and Transmission study which was funded by the US National Institutes of Health grant 1R01-HD058482-01 from the National Institute of Child Health and Human Development, National Institutes of Health (T.B., F.T.); additional NIH support was received through 1K01MH105320-01A1 and US Agency for International Development (USAID) cooperative agreement AID 674-a-12-00029 (J.B.). The Africa Centre for Health and Population Studies, University of KwaZulu-Natal, South Africa, is supported by a Grant from the Wellcome Trust (082384/Z/07/Z). The Hlabisa HIV Treatment and Care program was funded by the generous support of the American people through the United States Agency for International Development (USAID) and the President's Emergency Plan (PEPFAR) under the terms of Award No. 674-A-00-08-0001-00.

Presented in part as an oral poster at the XIX International AIDS Conference (AIDS 2012), July 22–27, 2012, Washington, DC (Abstract MOPDE0201), and as a poster at the 20th International AIDS Conference (2014), July 20–25, 2014, Melbourne, Australia.

The authors have no conflicts of interest to disclose.

The authors T.B., N.C., M.-L.N., R.B., M.L., F.T., S.d.V., and J.H. contributed to the conception of the study. T.B., N.C., M.-L.N., and J.B. contributed to the conception and design of the article, drafting the article, and revising it critically. N.C. and T.B. led the data collection, T.B., J.B., and N.C. did the analysis and interpretation of data. R.B., M.L., F.T., S.d.V., D.P., J.B., and J.H. critically reviewed the article. All authors have read and approved the final manuscript.

All the funding organizations had no role in the design and conduct of the study, in the collection, analysis, and interpretation of the data, or in the preparation, review or approval of the manuscript. The contents are the responsibility of the authors and do not necessarily reflect the views of any of the funders or the US government. Time and money: the true costs of health care utilization for patients receiving “free” HIV/TB care and treatment in rural KwaZulu-Natal.

Received January 03, 2015

Accepted April 30, 2015

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INTRODUCTION

South Africa has the largest number of people infected with HIV worldwide1 and the largest public antiretroviral therapy (ART) program in the world.2,3 Tuberculosis (TB) is among the leading causes of morbidity and mortality in South Africa and a common opportunistic infection in HIV patients.1,4

The South African Department of Health (DoH) has made both TB treatment and HIV care and treatment free of charge in public health care facilities to increase treatment accessibility.5,6 However, HIV and TB patients may still face financial hardships due to other health care–related expenditures, such as transport to and from the clinic, food and in some cases overnight accommodation near the clinic, expenditure on alternative sources of care including private doctors, pharmacies, and traditional healers, and income losses due to time spent seeking care.7,8 In this study, we aim to establish the true costs of health care utilization for patients receiving “free” HIV/TB care and treatment in rural KwaZulu-Natal.

Previous research suggests that patients bear costs—in both time and money—not captured in clinic fees. Routine surveillance data collected annually in the study area shows that the median time taken to travel to the nearest clinic is 81 minutes and the common mode of transport for most patients is by minibus taxis.9,10 These expenditures can lead to financial distress for patients already living in poverty. People may forego essential consumption to pay for health care by borrowing money from relatives or friends or resort to selling of assets, contributing to longer-term impoverishment.11–15 For HIV care and treatment in particular, time losses and out-of-pocket payments could amount cumulatively to very large sums, as treatment is life long.13,14

A key contribution of this study is the ability to compare health expenditures across both pre-ART and ART patients. Research focused on the health expenditures of pre-ART patients is scarce, yet it is important because it can provide insight into the barriers to retention during the pre-ART stage3 and patients' willingness and ability to transition to ART initiation when eligible.7 If ART initiation is associated with higher patient costs, eg, due to the higher frequency of clinic visits, then this may discourage pre-ART patients from remaining in care and lead to later-than-optimal initiation of ART. However, if patients experience high out-of-pocket expenditures in pre-ART care, eg, due to treatment of opportunistic infections, then ART initiation could be a financially attractive option and demand for earlier initiation could be high.3,16 The relative costs to patients of pre-ART vs. ART have significant implications for the successful rollout of treatment-as-prevention programs.

To provide insight into the true costs of health care seeking for public-sector patients, we set out to measure the financial and time-related costs of health care utilization among patients receiving “free” pre-ART, ART, and TB services in primary health care (PHC) clinics in rural South Africa. We assessed costs associated both with accessing public-sector care and with complementary utilization of traditional healers and private providers. Finally, we assessed whether these expenditures led to financial distress, as indicated by borrowing money or selling assets to finance care.

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METHODS

Study Area and Health Systems Context

We performed the study within the public-sector ART program of Hlabisa subdistrict, situated in northern KwaZulu-Natal, South Africa. HIV prevalence among adults in the rural Hlabisa subdistrict of KwaZulu-Natal in 2010 was 29%17 with incidence remaining high despite recent reductions in mortality and HIV acquisition due to the scale-up of ART.18–22 TB prevalence was almost 25% among those initiated on ART in 2006, and the population TB notification rate was approximately 928 cases per 100,000 in 2009, with evidence of emerging drug resistance.23

Since 2004, the Hlabisa HIV Treatment and Care Program (ART program) has provided free HIV treatment and care in 17 (16 at the time of the study) PHC clinics in the subdistrict; the program works in partnership with the DoH-TB program to provide free TB treatment in the same PHC clinics.24 The subdistrict is predominantly rural, about 90% of the population of approximately 228,000 individuals live in rural areas, with pockets of urban and peri-urban areas. All PHC clinics within the ART program (www.africacentre.ac.za)24 operate in accordance with the current South African DoH guidelines on HIV and TB management.5,23–26

Both HIV and TB care and treatment require repeated clinic visits to diagnose and manage these infections; ART and TB treatment can be collected on the same visit for coinfected patients. All PHC clinics offer HIV counseling and testing.24,27,28 When a patient tests HIV-positive, blood samples are sent to the National Health Laboratory Services at Hlabisa district hospital for CD4 cell count measurement, and patients return to the clinic for their results within a week from sample collection. Individuals who are not yet eligible for ART are instructed to return to the clinic every 6 or 12 months, depending on CD4 count.29 ART eligible patients attend 3 adherence counseling sessions and then initiate therapy. Patients initiated on ART are instructed to visit the clinic monthly to refill medications and for clinical observation.

Sputum from patients with suspected TB is sent to the National Health Laboratory Services for acid-fast bacilli smear testing.25,26 All smear-positive patients are initiated onto first-line standard TB regimen, and patients with negative smear who remain symptomatic are referred to Hlabisa district hospital for further assessment. TB patients collect treatment monthly from the PHC clinic; multidrug (MDR) and extensively drug (XDR) resistant TB cases are hospitalized for 1-2 months with further follow-up at PHC clinics.

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Data Sources and Sampling

We measured the financial and time-related costs of health care utilization among patients using free pre-ART, ART, and TB services and other private health care services. Data were collected through exit interviews with 800 HIV and TB patients, with patients sampled to be representative of the patient population in the Hlabisa subdistrict public-sector health system. Data were collected on a wide range of health-related expenditures and time spent seeking clinical care. To assess whether these expenditures led to financial distress, we collected information on whether patients reported either borrowing money or selling assets to finance health care utilization.

We collected data in patient-exit interviews at the HIV and TB facilities from 2 cross-sectional surveys in the subdistrict. The first of these two surveys was the Hlabisa subdistrict component of a multisite study called Researching Equity in ACcess to Health care (REACH)15, which was conducted in 2009 and focused on patients using ART and TB services in PHC clinics. The ART and TB questionnaires for this survey were constructed using questions on access to health care that have been used, validated, and subjected to reliability analyses in multiple studies in sub-Saharan Africa (www.wits.ac.za/pdf/10500/10500_chp_10500_reach.pdf).15,30–32 We used the questions about patient affordability to establish the direct and indirect health care utilization expenditures in the study populations. The questionnaires were structured such that we started with simple and nonthreatening questions and ended with questions that were more sensitive or more difficult to answer.

Second, we extended the study to HIV-infected people not yet eligible for ART within the same PHC clinics in 2010 in Hlabisa subdistrict. We used a 2-stage cluster random sampling approach, first selecting a random sample of PHC clinics within the subdistrict drawn (with replacement) with probability proportional to size and then randomly sampling 60 patients in each facility in the second stage. The sample size for the final sampling unit (300 ART and 300 TB patients) was established through a formal power calculation to ensure a sufficiently large sample to detect significant differences in cost components while accounting for the expected clustering at the level of the PHC clinics where we approached patients for the interviews. Pre-ART patients (sample size 200) were randomly selected from the clinics included in the REACH study. To be included in the ART group, patients had to be on ART for at least 2 weeks; to be included in the TB group, patients had to have been on TB treatment for at least 2 months; pre-ART patients had to be ART naive. Four trained fieldworkers conducted the patient-exit interviews using the local language in the study area, isiZulu. The questionnaires were translated from English to Zulu and back-translated to English by certified translators to ensure that meaning and consistency were maintained in the translation. All 4 fieldworkers were native Zulu speakers, and all 4 had previously been trained and worked as fieldworkers in the population-based surveillance at the Africa Centre for Health and Population Studies. During the fieldwork, the study coordinator debriefed and discussed challenges with the fieldworkers. The study coordinator also continuously checked the interview forms for completeness and quality and provided feedback on interview issues to the fieldworkers once per week.

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Ethics Approval

We received ethical clearance for this study from the University of KwaZulu-Natal (BF072/09 and BE174/08). We obtained written informed consent from all participants. Interviews were performed within the clinic premises but in a separate space outside the health care facility to ensure privacy and confidentiality for all participants.

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Measures

Data were collected on different health-related financial expenditures, time spent traveling to and using clinical services, and indicators of financial distress due to health care expenditures.

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Financial Expenditures

We collected data on expenditures on 3 broad categories: costs of visits to the clinic, costs of other health care services, and costs associated with self care, each of which had a number of subcategories. Expenditures associated with clinic visits were assessed on a per-visit basis. Patients were asked: “In coming to receive treatment today, how much did you pay for: transport (one way), clinic/hospital fees, medicines, someone to take over your tasks while you are here including childcare, accommodation if you need to stay the night nearby, food during the visit, telephone, other, specify.” In addition patients were asked “Did you find it easy or difficult to incur these expenses?” Since most ART and TB patients had 1 visit per month, these single episode costs were taken to be monthly costs of seeking care at the clinic. To allow for the different visit schedules, we translated pre-ART patients' financial and time costs per clinic visit to monthly costs by dividing the financial and time costs by 3 (on average pre-ART patients are expected to make 4 clinic visits per year for CD4 count testing and clinical monitoring).5,29 Costs associated with other health care services and self care were assessed with reference to the past 4 weeks. With respect to other health care services, patients were asked about utilization and expenditure on “chemist/pharmacy, private doctor, traditional healer, other public or private hospital/clinics—inpatient stay or emergency/outpatient department.” To capture the costs of self care, we asked patients to report expenditure on “any other health care in the past month [eg, traditional medicines, spaza shops, special food, etc].” Spaza shops are informal convenience stores in South Africa, which sell a wide variety of food and health-related goods.33 The above health expenditures were aggregated to calculate “total expenditures in the last 4 weeks.” All expenditures were reported in South African Rand (USD 1 = ZAR 7.3, at the time of the study in 2010). We standardized the ART and TB patients' costs to 2010 for comparability with pre-ART patient costs taking into account inflation.34,35

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Time Costs

Data were also collected on time-related costs associated with clinic visits. Data were collected on time (in hours) spent traveling to the clinic and time spent at the clinic, using the questions: “How much time did you spend at the clinic last time you came to collect your ARV or TB treatment?” and “How long did it take you to get here? (one way only i.e., time taken from leaving home to arriving at facility?)” Round-trip transit and utilization times were aggregated to calculate “total time costs” associated with clinic visits. As with financial costs, we divided pre-ART time costs by 3 to adjust for the different visit schedules.5,29

To enable comparisons between time and financial costs, we converted time spent in hours into equivalent monetary expenditure using an estimate of the opportunity cost of time. We calculated the rate of income per hour worked by dividing the Gross Domestic Product per capita for KwaZulu-Natal with the working hours per year and obtained an average hourly wage of ZAR 17.49.36,37 Evidence from the study setting finds 90% recovery of baseline employment levels among patients established on ART.38 To obtain time costs in Rand, we multiplied the monthly time spent during clinic visits and the travel times to the facility for pre-ART, ART, and TB patients by ZAR 17.49. We note that estimating the value of time in settings with very high unemployment is difficult, and therefore, we present time costs in hours as our main results.

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Financial Distress

Patients were asked how they paid for health care using the questions “In the last month, did you have to borrow money to pay for health care?” and “In the last month, did you have to sell personal or household items in order to pay for health care?” We constructed an indicator of “financial distress,” which took the value of 1 if individuals reported either borrowing money or selling personal or household items to pay for health care in the last month and 0 otherwise.13,15 We also elicited data on the disability grants that many ART and TB patients are eligible to receive to compensate for disease- and disability-related employment loss; most pre-ART patients are not eligible (and are not encouraged to apply) for the disability grants under the inability to work due to illness criteria unless they meet the criteria for reasons unrelated to their HIV infection. The question on disability grants was thus omitted for this group.39,40

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Analysis

The analysis proceeded in 3 steps. First, we used standard descriptive statistics to summarize the patient sociodemographic characteristics and time-related costs, financial costs, and financial distress indicators for pre-ART, ART, and TB patients. Second, to investigate whether patient type (pre-ART vs. ART vs. TB) was associated with differences in patient costs, we estimated multivariate regression models controlling for socioeconomic covariates and clustering standard errors at the clinic level. Third, we assessed the association between patient costs and financial distress in multivariate logistic regression models, controlling for sociodemographic characteristics and accounting for clustering at clinic level. We estimated separate logistic regression models for pre-ART, ART, and TB patients and a pooled model for all 3 groups, and we obtained predicted marginal effects after each model. When modeled as exposures, costs were expressed per ZAR 100. All analyses were performed using STATA version 11,41 and values of P < 0.05 were considered significant.

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RESULTS

Patients' Characteristics

Pre-ART patients were more likely to be female (79% pre-ART, 62% ART, and 53% TB) and were significantly younger than ART and TB patients (Table 1). ART patients had been on treatment for more than a year, on average 19 months [95% confidence interval (CI): 17.3 to 20.5], and the average most recent CD4 count was 347.9 cells per cubic millimeter (95% CI: 321 to 375). Most TB patients (75%) reported that it was their first episode of TB; 83% had pulmonary TB and 17% had extrapulmonary TB. Most households of ART patients (92%) and TB patients (89%) were receiving social grants from the government; households with ART patients received a significantly higher average grant amount than households with TB patients (Table 1).

TABLE 1

TABLE 1

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Patient Expenditures and Time Costs Associated With Clinic Visits

Financial Expenditures

For all groups, transport was the largest expense associated with clinic visits, with a monthly cost of pre-ART (ZAR 5; 95% CI: 4 to 6), ART (ZAR 37; 95% CI: 29 to 45), and TB patients (ZAR 24; 95% CI: 21 to 28) (Table 2). Sixty-three percent of ART and 57% of TB patients reported using public transportation to and from the clinic (mode of transport data were unavailable for pre-ART patients). Food costs during the clinic visit also contributed to monthly expenditures associated with clinic visits: pre-ART (ZAR 2; 95% CI: 2 to 3), ART (ZAR 9; 95% CI: 8 to 10), and TB patients (ZAR 6; 95% CI: 5 to 8). None of the patients paid for medicines, and small amounts were reported to have been spent on childcare, overnight accommodation, cell phone airtime, and on clinic/hospital fees. Total monthly costs of clinic visits (excluding time costs) were higher for ART patients (ZAR 46; 95% CI: 38 to 55) and TB patients (ZAR 33; 95% CI: 27 to 39) than for pre-ART (ZAR 8; 95% CI: 6 to 9), largely due to the frequency of visits (Table 2). Most patients indicated that it was difficult to bear these expenses [pre-ART: 135 (81%), ART: 203 (86%), and TB: 185 (92%) P = 0.01].

TABLE 2

TABLE 2

Patients in the 3 groups spent about the same amount of money per month on health care (clinic visit costs combined with expenditures on other health care services)—ZAR 171 (95% CI: 134 to 207) for pre-ART patients, ZAR 164 (95% CI: 140 to 187) for ART patients, and ZAR 122 (95% CI: 104 to 140) for TB patients (Table 2). However, the 3 patient groups differed widely in the composition of their financial expenditures: pre-ART patients spent more on traditional healers, chemists, and private doctors (Fig. 1; Table 2) compared with their counterparts; although they spent less on transport. All 3 groups reported large expenditures on self care (Table 2). These results held up in multivariate regression, after controlling for sociodemographic characteristics (Table 3). Pre-ART patients spent less on transport costs (−34.0; 95% CI: −57.0 to −11.0) than ART patients. However, pre-ART patients spent significantly more on traditional healers (29.2; 95% CI: 12.2 to 46.2) and private chemists/private doctors (25.9; 95% CI: 10.3 to 41.6) than ART patients, who spent very little on traditional, complementary, or alternative sources of care.

FIGURE 1

FIGURE 1

TABLE 3

TABLE 3

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Financing Patient Expenditures

For a single clinic visit, pre-ART patients reported spending significantly more hours at the clinic (3.5; 95% CI: 3.2 to 3.8) than both TB (1.1; 95% CI: 1.0 to 1.3) and ART patients (2.8; 95% CI: 2.5 to 3.0); ART patients spend significantly more time at clinics per month than either pre-ART or TB patients. There was no significant difference in average travel time across the groups (Table 2).

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Financial Distress

About one-third of patients borrowed money in the last month to pay for health care: 39% of TB patients, 29% of pre-ART patients, and 36% of ART patients. Fewer than one tenth of patients had sold personal or household items to finance health expenditures (Table 2). There was no difference in the average amount borrowed across all patient groups: pre-ART patients [ZAR 178; 95% CI: 128 to 229; median 100; interquartile range (IQR) 50–200], ART patients (ZAR 177; 95% CI: 97 to 256; median 104; IQR 42–209), and TB patients (ZAR 154; 95% CI: 108 to 201; median 94; IQR 31–209). Financial distress (as indicated by either borrowing money or selling assets) was high in all groups: TB patients (41%), pre-ART (31%), and ART (39%) (Table 2).

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Factors Associated With financial Distress Due to Using Healthcare

Being male or having an unemployed head of household among pre-ART patients was associated with more than twice the odds of being financially distressed (Table 4). Computing marginal effects, for each ZAR 100 in financial expenditure, the probability of reporting financial distress increased by 6.6% points (95% CI: 4.9 to 8.3). For every hour spent at the clinic using health care, the probability of reporting financial distress increased by 5.5% points (95% CI: 3.4 to 7.6).

TABLE 4

TABLE 4

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DISCUSSION

We show evidence of high health care–related financial expenditures and time costs among adults using public-sector HIV and TB services, although these services are provided free at point of service. Monthly private health expenditures were estimated at ZAR 171 for pre-ART patients, ZAR 164 for ART patients, and ZAR 122 for TB patients. From the patient perspective, these expenditures are very large, especially in a study area with high unemployment rates and dependency on social grants, representing over one third of median per capita income (ZAR 401) among Zulu-speaking South Africans.42 In this light, it is not surprising that 31%–41% of our samples reported that health expenditures led to financial distress, with many patients driven into debt by health expenditures. Furthermore, and contrary to popular perception, patients' private contributions are a significant component of total spending for public-sector health care. Including the public-sector contribution to ART treatment—estimated at $682 (ZAR 4979) per patient per year at the facility level43ART patients' private health expenditures represent over a quarter of the full cost of a patient being on ART. In addition to financial expenditures, patients face substantial time costs associated with care seeking, primarily due to the time required to travel to clinic visits. These patient costs are very likely large enough to influence ART and TB treatment uptake, adherence, and retention. Interventions to reduce the private costs of care could increase early treatment initiation and sustained viral suppression with benefits for patients and potentially large spillover effects in reducing onward transmission.

A critical gap in the HIV cascade of care has been the transition from pre-ART to ART, with high attrition from pre-ART care,3,44,45 and many patients are still initiating ART at low CD4 counts.3,45 One common explanation for this gap is the perception that the patient-borne costs of ART are significantly higher than the costs during pre-ART due to the burden of frequent and lengthy clinic visits to pick up medicines and that these costs discourage patients from initiating as early as they might. This theory is not supported by the data in this setting. Costs for ART patients were indeed large. However, expenditures were as high for pre-ART patients, who spent significant private resources on traditional healers, pharmacies, and private doctors. Use of alternative health care providers is common in South Africa and can result in hidden costs of illness that are not captured in facility-based costing studies.7,15,46,47 We find that HIV patients, if not yet eligible for ART, tend to seek alternative (and likely less efficacious) forms of therapy implying that the demand for treatment for HIV is high among HIV patients.47,48

Much has been made of the pattern in which HIV patients use both ART and traditional, complementary, and alternative medicines simultaneously.47 Interestingly, private expenditures on alternative sources of care all but disappeared for patients who had initiated ART, suggesting that in fact ART and alternative medicines may be substitutes rather than complements in this population.7,15,46,47 A likely explanation is that once patients initiated ART, they no longer had the symptoms for which they were seeking alternate sources of care. These findings have powerful implications for the rollout of HIV treatment-as-prevention programs, suggesting that demand for early ART may be higher than previously thought and that initiating ART may not impose large financial burdens on patients, but rather relieve them from other health expenditures on less efficacious therapies. Reports of financial distress, although common, did not differ significantly between pre-ART and ART patients, alleviating concerns that HIV treatment-as-prevention strategies may increase the financial burden of health care for patients and lead to low uptake.

Transport was the single largest cost component for all patients groups, similar to what has been reported elsewhere, and contributed to high expenditures among ART and TB patients who have frequent clinic visits.8,14,15,49 Many patients use public transport to visit the clinic,7,10 but road networks are poor in most rural areas making it costly to access some clinics.50 Three in five patients walked to the clinic, while two in five used public transport.9 Both TB and ART patients are instructed to make monthly clinic visits to collect their medicines, whereas those not yet eligible for ART are instructed to make about 4 clinic visits per year. Two of these 4 visits in pre-ART care are for physical examination and blood taking for CD4 counts; the other 2 are to receive the CD4 count results and to decide on treatment eligibility. Interventions to reduce transport costs, eg, a medicine delivery service, less frequent clinic visits for stable patients, or transport vouchers for poor households, could substantially improve patient welfare and lead to better treatment outcomes.51,52 Importantly, because ART patients have more frequent clinic visits than pre-ART patients, any reductions in transport costs associated with clinic visits will lower the relative cost of ART from the patient perspective and could lead to even greater demand for early ART.

Our study has several limitations. First, due to the nature of the clinic-based sampling strategy, we excluded people in need of health care who did not access health care, including those who did not access health care because they could not afford it. In previous research, we found that distance to the nearest clinic strongly predicts ART initiation, suggesting that transport costs may discourage some HIV patients from seeking care.53 The long run costs of forgoing care may be substantial but are excluded from this analysis. Second, it is possible that our cross-sectional comparisons across patient types—pre-ART, ART, and TB—were confounded by unobserved factors. We controlled for employment status of household head and basic demographics; furthermore, by design, all 3 groups are patients who have sought clinical care for HIV or TB. However, as in most observational studies, unmeasured factors could influence our effect estimates. Third, time costs associated with care seeking outside the clinic were not assessed in the survey and could not be included in the analysis. Given the higher utilization of alternative care among pre-ART patients, this omission would bias pre-ART patient costs downward, implying that one of our main conclusions—that patients do not pay more for ART than for pre-ART would still be valid in this case. Fourth, in this study, we have assessed the costs of health care utilization from the perspective of individual patients. An important additional perspective is the costs of patients' health care utilization to their households. Although our study focused on the individual, our findings that large proportions of patients reported that they had to borrow money or sell assets to pay for health care is likely to imply substantial household financial burdens due to patients' health care utilization for pre-ART, ART, and TB. In particular, assets, such as livestock, bicycles, tables or televisions, are commonly shared among household and even community members, and their sale thus likely affects people who are socially linked to the patients we have interviewed here. The spillover effects of health care utilization to household and community members are an important area for future research, including the broader impacts on household activities, time use, and economic status. Finally, we report data for only one rural district in South Africa. However, we note that the study setting has many characteristics common to rural areas in South Africa and neighboring countries: extensive use of traditional healers, a socioeconomic context of high cyclical migration and unemployment, and a very high HIV burden. Further research will be needed to demonstrate generalizability to other settings.

HIV and TB patients receiving nominally free care, nevertheless, face considerable costs due to health care expenditures and the time costs of seeking care. Interventions to reduce patient costs could improve progression through the HIV cascade of care.54,55 ART patients have much lower expenditures than pre-ART patients on traditional healers, private doctors, and pharmacies, suggesting that ART serves as a substitute for alternative treatments. These findings imply high demand for some form of HIV treatment among HIV patients and that initiating patients earlier onto ART could be cost saving for patients, in addition to yielding health benefits for patients56 and for society at large.22,57

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ACKNOWLEDGMENTS

The authors would like to acknowledge the fieldworkers from the Africa Centre for Health and Population studies who collected the data—Mlungisi Mthetwa, Sibongiseni Mthetwa, Nomusa Mkhabela, and Cynthia Ncube, the staff working at the clinics and patients attending the primary health care clinics for their support and participation in this study. The authors would like to acknowledge the principal investigators, team members and the collaborating sites for the Researching Equity in ACcess to Health care (REACH) multisite study, and the principal investigators and research team members of the Impact of ART on HIV epidemic dynamics study. Special mention goes to Lorna Benton for proofreading and editing an earlier version of the article.

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REFERENCES

1. UNAIDS. Report on the Global AIDS Epidemic. Geneva, Switzerland: UNAIDS; 2008.
2. WHO. Towards Universal Access: Scaling up Priority HIV/AIDS Interventions in the Health Sector: Progress Report 2010. Geneva, Switzerland: WHO; 2010.
3. Lessells RJ, Mutevedzi PC, Cooke GS, et al.. Retention in HIV care for individuals not yet eligible for antiretroviral therapy: rural KwaZulu-Natal, South Africa. J Acquir Immune Defic Syndr. 2011;56:e79–e86.
4. WHO. Global Tuberculosis Control: WHO Report. Geneva, Switzerland: WHO; 2010.
5. National Department of Health. Operational Plan for Comprehensive HIV and AIDS Care, Management, and Treatment for South Africa. Pretoria, South Africa: Department of Health; 2003.
6. National Department of Health. The South African National Tuberculosis Control Programme—Practical Guidelines. Pretoria, South Africa: National Department of Health; 2004.
7. Rosen S, Ketlhapile M, Sanne I, et al.. Cost to patients of obtaining treatment for HIV/AIDS in South Africa. S Afr Med J. 2007;97:524–529.
8. Onwujekwe OE, Uzochukwu BSC, Obikeze N, et al.. Investigating determinants of out- of-pocket spending and strategies for coping with payments for healthcare in southeast Nigeria. BMC Health Serv Res. 2010;10:67.
9. Tanser F, Gijsbertsen B, Herbst K. Modelling and understanding primary health care accessibility and utilization in rural South Africa: an exploration using a geographical information system. Soc Sci Med. 2006;63:691–705.
10. Chimbindi NZ, Bärnighausen T, Newell ML. An integrated approach to improving the availability and utilisation of tuberculosis healthcare in rural South Africa. S Afr Med J. 2013;103:237–240.
11. United Nations Economic Commission for Africa; Commission on HIV/AIDS and Governance in Africa. The Impacts of HIV/AIDS on Families and Communities in Africa. Addis Ababa, Ethiopia: Economic Commission for Africa; 2005.
12. Russell S. Ability to pay for health care: concepts and evidence. Health Policy Plan. 1996;11:219–237.
13. Leive A, Xu K. Coping with out-of-pocket health payments: empirical evidence from 15 African countries. Bull World Health Organ. 2008;86:849–856.
14. Kruk ME, Goldmann E, Galea S. Borrowing and selling to pay for health care in low- and middle-income countries. Health Aff (Millwood). 2009;28:1056–1066.
15. Cleary S, Birch S, Chimbindi N, et al.. Investigating the affordability of key health services in South Africa. Soc Sci Med. 2013;80:37–46.
16. Rosen S, Fox MP. Retention in HIV care between testing and treatment in sub-Saharan Africa: a systematic review. PLoS Med. 2011;8:e1001056.
17. Zaidi J, Grapsa E, Tanser F, et al.. Dramatic increase in HIV prevalence after scale-up of antiretroviral treatment. AIDS. 2013;27:2301–2305.
18. Bärnighausen TF, Gqwede Z, Mbizana C, et al.. High HIV incidence in a community with high HIV prevalence in rural South Africa: findings from a prospective population-based study. AIDS. 2008;22:139–144.
19. Bärnighausen T, Tanser F, Newell ML. Lack of a decline in HIV incidence in a rural community with high HIV prevalence in South Africa, 2003–2007. AIDS Res Hum Retroviruses. 2009;25:405–409.
20. Welz THV, Jaffar S, Batzing-Feigenbaum J, et al.. Continued very high prevalence of HIV infection in rural KwaZulu-Natal, South Africa: a population-based longitudinal study. AIDS. 2007;21:1467–1472.
21. Bor J, Herbst AJ, Newell ML, et al.. Increases in adult life expectancy in rural South Africa: valuing the scale-up of HIV treatment. Science. 2013;339:961–965.
22. Tanser F, Bärnighausen T, Grapsa E, et al.. High coverage of ART associated with decline in risk of HIV acquisition in rural KwaZulu-Natal, South Africa. Science. 2013;339:966–971.
23. National Department of Health. Tuberculosis strategic plan for South Africa, 2007–2011 Pretoria: National Department of Health. 2006.
24. Houlihan CF, Bland RM, Mutevedzi PC, et al.. Cohort profile: Hlabisa HIV treatment and care programme. Int J Epidemiol. 2011;40:318–326.
25. Wallrauch C, Heller T, Lessells R, et al.. High uptake of HIV testing for tuberculosis patients in an integrated primary health care HIV/TB programme in rural KwaZulu-Natal. S Afr Med J. 2010;100:146–147.
26. Houlihan CF, Mutevedzi PC, Lessells RJ, et al.. The tuberculosis challenge in a rural South African HIV programme. BMC Infect Dis. 2010;10:23.
27. Houlihan CF, Maheswaran H, Thulare H, et al.. Pilot of provider initiated testing and counselling in a rural primary health care clinic. Southern African AIDS Conference, Durban, South Africa, 2009.
28. WHO. Guidance on Provider-initiated HIV Testing and Counselling in Health Facilities. Geneva, Switzerland: WHO; 2007.
29. WHO. Antiretroviral Therapy for HIV Infection in Adults and Adolescents: Recommendations for a Public Health Approach—2010 Revision. Geneva, Switzerland: WHO; 2010.
30. Cleary SM, Birch S, Moshabela M, et al.. Unequal access to ART: exploratory results from rural and urban case studies of ART use. Sex Transm Infect. 2012;88:141–146.
31. Goudge J, Gumede T, Gilson L, et al.. Coping with the cost burdens of illness: combining qualitative and quantitative methods in longitudinal, household research. Scand J Public Health Suppl. 2007;69:181–185.
32. McIntyre D, Mills A. Research to support universal coverage reforms in Africa: the SHIELD project. Health Policy Plan. 2012;27(suppl 1):i1–i3.
33. Wikipedia. Spaza shop. 2012. Available at: http://en.wikipedia.org/wiki/Spaza_shop. Accessed April 11, 2012.
34. CDC. Cost analysis: CDC economics evaluation tutorials (E). Available at: http://www.cdc.gov/owcd/eet/Cost/fixed/4.html. Accessed June 14, 2012.
35. Health Economics Resource Centre. Resources. Available at: http://www.herc.research.va.gov/resources/faq_a03.asp. Accessed June 14, 2012.
36. Statistics South Africa. Gross Domestic Product: Annual Estimates 2002—2010. Regional Estimates 2002—2010. Third Quarter 2011. Pretoria, South Africa: Statistics South Africa; 2011.
37. Wikipedia free encyclopedia. List of South African provinces by gross domestic product per capita. Available at: http://en.wikipedia.org/wiki/List_of_South_African_provinces_by_gross_domestic_product_per_capita. Accessed July 01, 2014.
38. Bor J, Tanser F, Newell ML, et al.. In a study of a population cohort in South Africa, HIV patients on antiretrovirals had nearly full recovery of employment. Health Aff (Millwood). 2012;31:1459–1469.
39. South African Social Security Agency. Social grants: disability grants. Available at: http://www.sassa.gov.za/index.php/social-grants/disability-grant. Accessed March 16, 2015.
40. Rosen S, Larson B, Rohr J, et al.. Effect of antiretroviral therapy on patients' economic well being: five-year follow-up. AIDS. 2014;28:417–424.
41. StataCorp. Stata Statistical Software Release version 11. College Station, Texas, United States: StataCorp; 2009.
42. Gradin C. Poverty and Ethnicity Among Black South Africans (WIDER Working Paper 2014/113). Helsinki Finland: UNU-WIDER; 2014.
43. Elya T, Sundaram M, Condliffe K, et al.. Multi-country Analysis of Treatment Costs for HIV/AIDS (MATCH): Unit Costing at 161 Representative Facilities in Ethiopia, Malawi, Rwanda, South Africa and Zambia. New York, NY: Clinton Health Access Initiative; 2012.
44. Lamb MR, Fayorsey R, Nuwagaba-Biribonwoha H, et al.. High attrition before and after ART initiation among youth (15–24 years of age) enrolled in HIV care. AIDS. 2014;28:559–568.
45. Mulissa Z, Jerene D, Lindtjorn B. Patients present earlier and survival has improved, but pre-ART attrition is high in a six-year HIV cohort data from Ethiopia. PLoS One. 2010;5:e13268.
46. Russell S. The economic burden of illness for households in developing countries: a review of studies focusing on malaria, tuberculosis, and human immunodeficiency virus/acquired immunodeficiency syndrome. Am J Trop Med Hyg. 2004;71(suppl 2):147–155.
47. Moshabela M, Pronyk P, Williams N, et al.. Patterns and implications of medical pluralism among HIV/AIDS patients in rural South Africa. AIDS Behav. 2011;15:823–831.
48. Peltzer K, Preez NF, Ramlagan S, et al.. Use of traditional complementary and alternative medicine for HIV patients in KwaZulu-Natal, South Africa. BMC Public Health. 2008;8:255.
49. Goudge J, Gilson L, Russell S, et al.. The household costs of health care in rural South Africa with free public primary care and hospital exemptions for the poor. Trop Med Int Health. 2009;14:458–467.
50. Hardon AP, Akurut D, Comoro C, et al.. Hunger, waiting time and transport costs: time to confront challenges to ART adherence in Africa. AIDS Care. 2007;19:658–665.
51. Harries AD, Zachariah R, Lawn SD, et al.. Strategies to improve patient retention on antiretroviral therapy in sub-Saharan Africa. Trop Med Int Health. 2010;15(suppl 1):70–75.
52. Wilkinson LS. ART adherence clubs: a long-term retention strategy for clinically stable patients receiving antiretroviral therapy. S Afr J HIV Med. 2013;14:48–50.
53. Cooke GS, Tanser FC, Bärnighausen TW, et al.. Population uptake of antiretroviral treatment through primary care in rural South Africa. BMC Public Health. 2010;10.
54. Haber N, Chimbindi N, Herbst K, et al.. Longitudinal HIV treatment cascade in KwaZulu-Natal, South Africa. 20th International AIDS Conference, Melbourne, Australia, 2014.
55. Mutevedzi PC, Lessells RJ, Newell ML. Disengagement from care in a decentralised primary healthcare antiretroviral treatment programme: cohort study in rural South Africa. Trop Med Int Health. 2013;18:934–941.
56. Bor J, Moscoe E, Mutevedzi P, et al.. Regression discontinuity designs in epidemiology: causal inference without randomized trials. Epidemiology. 2014;25:729–737.
57. Cohen MS, Chen YQ, McCauley M, et al.. Prevention of HIV-1 infection with early antiretroviral therapy. N Engl J Med. 2011;365:493–505.
Keywords:

borrowing; selling assets; financial distress; health care costs; HIV; TB; out-of-pocket; health expenditure; time use; South Africa; ART; pre-ART; retention; costs

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