Primary healthcare seeking behaviour of low-income patients across the public and private health sectors in South Africa

The population for this study included all patients, aged 18 years and older (adults), who presented for PHC services at seven selected private PHC organisations (primarily providing services to the low-income predominantly uninsured patient population) and their matched public sector clinic counterpart in the same, or adjacent clinic catchment area. Inclusion criteria for the matched private sector site was based on: Patient volumes across the chosen subset of PHC services and proximity to a public sector clinic, as previously described [12]. Only patients able to communicate in English, willing to provide written informed consent, and be physically present for an interview during our site visit were eligible for inclusion in the final random study sample. In order to achieve a representative sample with a precise confidence interval (10%) at alpha of 0.05 and power of 80%, a minimum sample size of 86 is needed, or 43 in total per sector. Assuming a maximum of 15 private PHC service delivery organisations interviewed for key informant interviews [12], and a matched sample of public sector PHC clinics, as well as 11 patient interviews per site. Participants were randomly selected through a systematic random sampling technique. Both the sampling framework and sampling interval used in this study were informed by expected daily volumes, as obtained through a discussion with relevant facility personnel.

This study was approved by the Human Research Ethics Committee of the University of Witwatersrand (ref. no. M171082) and the Institutional Review Board of the Boston Medical Centre (ref. no. H-37230). The study design was cross-sectional with data collected during once-off patient interviews. Face-to-face interviews were conducted with enrolled participants and an interviewer administered a semi-structured questionnaire. Interviews were conducted in a private room within the clinic to ensure confidentiality. Study data were collected and managed using the Research Electronic Data Capture (REDCap) tool; REDCap is a secure, web-based software platform designed to support data capture for research studies [13]. Patient interviews took place between May 2018 and January 2019. The interview guide was informed by the Quality of Life Survey (QoL) which is conducted and published by the Gauteng City- Region Observatory (GCRO) and measures a wide range of variables relevant to the purpose of our study including socio-demographic variables, health-seeking behaviour and attitudes towards the health-care services [14]. Data was collected on demographic characteristics, socio-economic indicators, the associated costs of accessing PHC over the last 12 months, healthcare services utilised over the last year, specifics around any chronic (HIV, TB, diabetes and hypertension) and health care requirements over the last year. Details on patient satisfaction with the care received were only collected for repeat patients to a facility All data collection methods were performed in accordance with the relevant ethics guidelines and regulations.

The selection of demographic, socio-economic and health related variables for this analysis was informed by the behavioural model for health service utilisation [15]. This model describes health service utilization as being conditional on three sets of factors: predisposing (demographic and social) factors, enabling (economic) factors, and need (health outcome) factors [16]. The outcome variable for this analysis was the PHC at which the participant indicated usually accessing care (public PHC, private PHC or mix of public and private facilities). Descriptive statistics were used to provide a summary of the study population across the usual PHC options. A chi-squared test was used to provide a crude test of associations between the PHC facility where care was usually accessed and the demographic, socio-economic and health related categorical variables of our study population. A one-way ANOVA test was used to identify any significant differences between the PHC facility where care was usually accessed and the continuous variables age, as well as household size. Healthcare utilisation over 12 months was determined for each option indicating where care was usually accessed based on responses to a question regarding the patient’s average number of health care visits per year. Response categories included: (i) More than once a month (weighted as 12 or more visits a year for this analysis), (ii) Once a month (12 visits a year), (iii) Once every 2 months (six visits a year), (iv) Four visits a year, (v) Three visits a year, (vi) Two visits a year, (vii) Once a year or (viii) Never. The frequency of participants falling into each category was then multiplied by the associated weighting in terms of annual visits per year and divided by the N for each option of where care is usually accessed to obtain the final healthcare utilisation value over 12 months. The influence of socio-economic status (SES) on choice of usual PHC was examined through the creation of an SES index, constructed from household and individual level data using principal component analysis [17]. Patients were then stratified into 3 equal sized groups, according to their SES level (low, medium and high) to identify any association between where care was usually accessed and SES level. All statistical data analysis was performed using Stata Statistical Software (Release 15. College Station, TX: StataCorp LLC). Income and costs are reported in 2019 USD.

We enrolled and interviewed 153 participants across seven public and seven private PHC facilities – an average of 11 per study site. There was a shortfall of one participant at one study site. Table 1 shows the demographic, socio-economic and health related characteristics of our study sample. Two thirds (67%) of our study sample were female; the mean age was 40. The majority of our study population were economically active (63%), had no health insurance (91%) and earned up to $828 per month (71%). Almost two thirds (64%) reported having an educational level between Grade 8–12 (secondary/high school), 27% had completed their secondary/ high school education, while 3% had no formal education. The estimated mean household size was 4. The majority (58%) of our study participants indicated having either HIV, diabetes or hypertension or a combination of these diseases. Only 8% of participants indicated a willingness to switch the sector in which care (chronic or acute) was usually accessed.

When asked about the health sector where they usually accessed care, 73 (48%) indicated usually visiting a public health facility, 49 (32%) usually chose a private health facility and 31 (20%) frequently utilised a mix of both facility types (Table 2). Education, health insurance being economically active and SES were significantly associated with usual PHC choice (p ≤ 0.05).

The majority of participants interviewed at both public and private facilities (84 and 82%, respectively) reported having accessed primary healthcare at that facility prior to enrolment. When asked to indicate the PHC clinic at which they usually access care, participants revealed a tendency to cycle between sectors. The proportion of participants using a mix of facility types was three times larger in the private sector than in the public sector (30% versus 10% respectively, Fig. 1).

Healthcare utilisation over 12 months was similar across sectors, with a weighted average number of annual visits of 6.25 for those usually accessing care in the public sector (N = 73), 5.83 for those usually accessing care in the private sector (N = 49), and 5.81 for those using a mix of facilities (N = 31). An analysis of the utilisation distribution did however reveal a difference across the “Usual PHC” options (Fig. 2). The data showed higher visit frequency (defined as consulting a healthcare provider six or more times a year for this analysis) amongst those usually accessing care in the public sector (58% in comparison to 45% amongst those usually choosing to visit the private sector). The majority (80%) of participants with a higher visit frequency in our study sample had been diagnosed with one or more of the chronic conditions of interest in this research (i.e. HIV, diabetes or hypertension). Lower visit frequency (defined as consulting a healthcare provider three or fewer times a year for this analysis) was associated with usually accessing care in the private sector (38% in comparison to 29% in the public sector). These participants were also less likely to have been diagnosed with one or more of the chronic conditions of interest (38% reported being diagnosed with either HIV, diabetes, hypertension of a combination of these diseases).

Whilst we interviewed an equal number of patients currently accessing private and public facilities, the type of facility where patients were diagnosed and treated for HIV, TB, diabetes and hypertension differed across sector (Fig. 3).

Equal numbers were diagnosed and treated for hypertension across sectors (50 and 45%), whereas more patients are diagnosed (75%) and treated (75%) for diabetes in the public sector. Despite the greater expense and specialised care required for TB and HIV, a relatively high proportion of TB and HIV patients are treated in the private sector (75 and 42% respectively). More patients were diagnosed (71%) and treated (75%) for TB in the private sector, but this is probably driven by the low numbers (5/7) were diagnosed with TB in the private sector and 3/4 were treated for TB in the private sector) and the inclusion of a PHC clinic with certain specialised TB services in the private sector sample.

Patients were asked to list the different healthcare services that they had accessed over the last 12 months and where they access them. They could choose more than one service, e.g. chronic services (related to diabetes, hypertension, HIV, TB, asthma, cancer etc.) and/or acute services (including minor ailments), and/or ‘other’ services including maternal and child health, sexual and reproductive health services, and support services (eye, oral, palliative etc.) (Table 3). An analysis of all services and facilities accessed by patients over the last 12 months revealed that acute services and chronic care services were the most commonly accessed services (46 and 43%). The majority of public hospital and private clinic visits were for acute services (64 and 57%), whilst the majority of public PHC clinics and private GP visitswere for chronic care services (44 and 52%). Our sample of patients only accessed private hospitals twice in the preceding 12 months: one for acute services and one for maternal and child health services. Public clinics provide the majority of maternal and child health care services (included in the ‘Other’ category).

Answers to multiple response questions indicated that affordability (67%) and a convenient location (60%) were the main reasons for usually accessing care at a public health facility. Those participants who usually accessed care in the private sector specified convenience of location (71%) and quality of the care received (59%) as their main reasons behind facility choice. Finally, participants usually utilising a mix of facilities indicated similar key reasons for visiting each sector type, a convenient location (48%) and affordability (39%) were the main drivers of public sector access while quality of care (71%) and location convenience (42%) emerged as key drivers of private sector access for this segment of the study population. Refer to Table 4 for more detail.

All repeat patients to the facility of interview were asked to describe their level of satisfaction with the care received at that clinic: 97% of private sector clients were either very satisfied or satisfied with the service they received as compared to 74% in the public sector. The public sector had a higher proportion of patients who were either dissatisfied or indifferent (neither satisfied/ dissatisfied). This was reflected in the open-ended comments patients were asked to provide on their experience of care: 73% of negative comments (i.e. slow or long waiting times, staff shortages, inadequate opening hours or cramped facilities etc.) were by patients who attended a public sector clinic, whilst 63% of positive comments on the experience of care (friendly and good staff etc.) were by patients attending a private sector clinic (Table 5).