DISTRICT HEALTH SYSTEM

 

Ritshidze's community-led monitoring system as a source of information on health system responsiveness in South Africa

 

 

P Barron^I; B Honermann^II; K Vallabhjee^{III, IV}; K Govender^V; H Schneider^VI

^IFFCH (SA); School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
^IIJD; O'Neil Institute, Georgetown, Washington DC, USA
^IIIFFCH (SA); Clinton Health Access Initiative, South Africa
^IVFFCH (SA); Division: Health Policy and Systems, School of Public Health, Faculty of Health Sciences, University of Cape Town, South Africa
^VMSc (OT); School of Public Health and SAMRC Health Services to Systems Research Unit, University of the Western Cape, Cape Town, South Africa
^VIPhD; School of Public Health and SAMRC Health Services to Systems Research Unit, University of the Western Cape, Cape Town, South Africa

Correspondence

 

 

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ABSTRACT

Ritshidze is a large-scale community-led monitoring (CLM) system in South Africa, which has been conducting quarterly surveys of patient experiences at >400 primary healthcare facilities and community sites since 2019. This in-practice piece examines the data collected and publicly reported by Ritshidze, to highlight its role as an independent, complementary source of information on primary healthcare performance. It argues that CLM has significant potential to enhance health system responsiveness. We provide an overview of the data collection system, involving close to 500 data points organised into seven domains, and then focus on two sets of indicators that illustrate the utility of the monitoring and reporting system. The indicators selected are a set that assesses patient time spent at a facility (as a proxy for waiting times), illustrating both the depth and the breadth of the Ritshidze database; and the length of HIV prescriptions ('length of medicine refill'), as an indicator of the improvements in responsiveness of the health system to the needs of patients. Integrating CLM data into formal health system monitoring and evaluation frameworks could enhance the responsiveness of the health system to patients and communities, one of the key overall objectives of the district health system.

Keywords: community-led monitoring; district health systems information; information dashboards

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A recent introductory article in the District Health Systems (DHS) series outlined the Ritshidze model^[1] as a form of community participation through community-led monitoring (CLM) of selected clinics and community health centres. The monitoring focuses on those facilities with large numbers of patients living with HIV (PLHIV). Ritshidze surveys are conducted at >400 facilities, which collectively serve approximately half of all the PLHIV in South Africa (SA). These facilities are spread across 27 districts in eight provinces^[2] (excluding the Northern Cape Province, which has the smallest population and the lowest HIV prevalence).

CLM monitors are selected from the various civil society actors making up the Ritshidze coalition. The civil society actors are known as the 'PLHIV bodies' and include the Treatment Action Campaign (TAC) and National Association of People Living with HIV (NAPWA), among others. The monitors are well-placed to collect health systems data related to HIV, as they either have HIV themselves or are very conversant with how the facilities operate in relation to PLHIV.

Ritshidze, via TAC, has a memorandum of agreement with the National and Provincial Departments of Health for the collection and analysis of data. This is not considered formal research, but monitoring and evaluation (M and E), and the process has not required ethical clearance. As one spokesperson indicated, 'Ritshidze is not a research project. We are not testing hypotheses. CLM is more akin to independent M and E than research.' Regarding language, CLM monitors complete the forms (hard and soft copy) in English. CLM monitors are selected locally, and thus it stands to reason that they will use the local language if communication in English fails. When there are vacancies, Ritshidze recruits PLHIV sector members who use the facilities and speak the local language(s).

In their 2019 report 'Power to the People', the Joint United Nations Programme on HIV/AIDS (UNAIDS) defined community-led responses as 'actions and strategies that seek to improve the health and human rights of their constituencies, that are specifically informed and implemented by and for communities themselves and the organizations, groups, and networks that represent them. Community-led responses are determined by and respond to the needs and aspirations of their constituents. Community-led responses include advocacy, campaigning and holding decision-makers to account; monitoring of policies, practices, and service delivery.'^[3]

In an article on CLM in Malawi and SA, the principles of CLM are stated as 'prioritiz(ing) community leadership over mere community involvement. Communities lead in identifying pressing issues, defining indicators, managing data, conducting analysis (recommended in partnership with an advisory group, academic institution or other data expertise) and advocating for remedial action on identified gaps. If issues persist, communities engage in advocacy to hold duty-bearers accountable'.^[4] CLM of health service delivery was born historically out of healthcare advocacy led by PLHIV. The CLM cycle involves local community-led organizations and civil society leading a regular process of data collection, identifying issues, developing solutions, conducting advocacy and monitoring change to improve access and quality of services.^[5]

CLM has been implemented in a number of middle- and low-income countries. One example of CLM is community treatment observatories (CTOs), which involve the systematic and regular collection of quantitative data across the HIV prevention, care and treatment cascade. This model has been implemented in 11 countries across West Africa. Within 18 months of the CTO implementation, there was an improvement in a range of HIV indicators, such as decrease in antiretroviral therapy (ART) and laboratory reagent stockouts, as well as improvements in HIV testing rates.^[6]

One of the aims of CLM is to improve health systems responsiveness, which itself is an important measure of the overall performance of a health system.^[7] The key elements of health systems responsiveness are dignity, autonomy, confidentiality, prompt attention, quality of basic amenities, choice of care provider and access to social support networks.^[8] This is still a nascent field, and CLM is an area that lends itself to further research to demonstrate its relationship with health system responsiveness.^[9]

With a view to highlighting the role and value of information generated by Ritshidze for practitioners and managers, in this article we take a deeper dive into the data collected, and illustrate this through two sets of indicators assessed by Ritshidze: time spent by healthcare clients at facilities (called 'waiting times' by Ritshidze), and multi-month dispensing (MMD) of antiretroviral medicines. A study in Malawi and Zambia showed that there was no difference in HIV outcomes between patients who received their ART as part of a 6-month prescription (6 MMD) and those who received 3 MMD or monthly.^[10]

Both of these indicators are key components of health system responsiveness to the needs of patients. We analyse and comment on these indicators, show how they are communicated in dashboards and reflect on the possible ways in which Ritshidze indicators and metrics can augment the monitoring and evaluation of the overall district health system in SA.^[11]

 

Overview of data collection, analysis and reporting

Ritshidze collects data at both facility and community levels through tools covering a combination of general and disease-specific domains relating to facility staffing, clinic conditions, services for HIV, tuberculosis (TB) and key populations, access to medicines and accountability processes (e.g. capturing what the facility manager promises to fix and then monitoring to see this is done). Key populations are those with increased vulnerability to HIV, including, for example, sex workers and people in prison and other closed settings.^[12] A community-led monitoring activist guideline details the facilities where data will be collected and the various steps to be followed in collecting, collating, entering and analysing the data.^[2]

Information is collected on the following key aspects:

• facility functionality (observation survey of space, condition and cleanliness - the monitor observes various aspects of the clinic, and records these observations, such as the condition of the toilet and filing system)

• patient experiences of waiting times, staffing, staff attitudes, stockouts, TB infection control, antiretroviral (ARV) refill length, service quality, privacy and confidentiality, and viral load understanding (patient survey)

• facility managers' perspectives on staffing levels, infrastructure, HIV linkage and retention, TB services and programmes that target key populations, youth and men (facility manager survey)

• a medicines survey, which assesses the frequency and type of stockouts and shortages of medicines and vaccines at the clinic (the monitor asks to see particular HIV and TB drugs to see availability on the day of survey, but also asks about stock-outs over the period of the survey).

The community-based tools capture the insights and experiences of both users and non-users of public clinics, providing feedback about what is and is not working at facilities.^[13]

Ritshidze data are available in public-facing dashboards on their website (https://ritshidze.org.za/). Reports, tables, and graphs can be extracted at facility, district and provincial levels for any of the reporting periods since data were first collected in 2019.^[14] Drawing on the 25 quarterly surveys that were conducted between October 2019 and September 2024, the dashboards contain individual facility data covering close to 500 data points from questions in the specific surveys, as well as tables and graphs. Examples of the kind of reports available include staffing and waiting times, clinic conditions, HIV services and access by specific key populations.

Based on analyses of these data, Ritshidze has produced a number of provincial reports since 2020, including four for Gauteng,^[15-18] Eastern Cape,^[19-22] Free State,^[23-26] Mpumalanga,^[27-30] North West,^[31-34] three from KwaZulu-Natal,^[35-37] and two from Limpopo.^[38,39] These provincial reports contain similar information to the dashboards, but the emphasis is on more granular detail down to facility level. Each report, although written as if for a particular year, is based on data collected for a particular quarter in that year. Ritshidze has also produced three reviews of the state of healthcare for key populations, the first in January 2022,^[40] a second edition in February 2023^[41] and a third in February 2024.^[42] There is also a state of health report for South Africa published in December 2023.^[43]

In SA, as in other African countries, long queues at facilities, distance to facilities, stigma and lack of money for transportation are common barriers to continuity in HIV treatment. In addition, high volumes of clients with inadequate staffing result in long wait times, overworked staff, poor client satisfaction and high rates of interruptions in treatment. Also, clients often have to make frequent visits to health facilities for clinical consultations and ART refills, which further burdens clients and contributes to poor clinical outcomes.^[44]

To deal with these issues, the health system needs to be responsive to the feedback and needs of patients. In order to illustrate the degree of responsiveness, we chose two indicators that are measured by the Ritshidze data to illustrate how this can be measured and tracked. Both times spent waiting at the facility for clinical care, and how often a patient must attend a facility to get their ART drugs, are factors that will determine how favourably a patient views the health system.

 

Data on time spent at facilities and ART prescribing intervals as illustrative examples

Time spent at facilities

Waiting times are a key element of health system responsiveness, and a source of frequent public complaint. Illustrating the depth and range of Ritshidze's monitoring system, a total of 20 questions in patient and observation surveys relate to waiting times.

Table 1 shows the information sources for data on time spent at facilities, where each indicator comes from different surveys and/or tools.

 

 

Fig. 1 ^[5] is an example of one of the dashboards that reports cross-sectional findings on the first of these indicators - the duration of time spent at individual facilities in one district (Buffalo City) in one quarter (January - March 2022). These clinic-level metrics can also be aggregated in overall district, provincial and national level reports.

Another way of presenting data on time spent at facilities is shown in Fig. 2, reporting on patient opinions and experiences of waiting periods. Here again, the cross-sectional results for one specific district (Buffalo City, in the Eastern Cape Province) are shown for one quarter in 2023. As with duration of time spent at facilities, these figures are also available for district and provincial levels.

One of the Ritshidze dashboards is also able to generate longitudinal data for all the recorded quarters to date. A simple click of a mouse on the quarter generates the metrics for the facility, district or province (in this case, the metric is average time spent at facilities for a particular quarter). An example of this is Fig. 3, for the Eastern Cape districts.

From these data, it is possible to show that the average time spent at facilities across all four districts in the Eastern Cape declined steadily from 5.15 hours in the fourth quarter of 2020 to 3.25 hours in the third quarter of 2023 (the quarters are linked to the US financial year). After that - for the next five quarters - the average time spent at facilities across all four districts plateaued, and has been fairly static at around 3.5 hours.

Using the dashboard data, it is also possible to construct comparisons between districts. For example, in two provinces, KwaZulu-Natal and Eastern Cape, a district comparison was created in Table 2, showing the average time spent at facilities in the monitored districts. There are wide differences in how long patients spend at the facilities among the different districts. These differences run both internally in provinces and between the two provinces, as well as longitudinally over time. For example, in KwaZulu-Natal, the average time in facilities decreased by 30%, but Zululand had a 60% decrease, illustrating the variation in district improvement. Further investigation may lead to lessons being shared from Zululand.

Reduced waiting times must be one of the most compelling ways in which a health system can respond to the needs of patients and increase their satisfaction.^[45] In addition to reducing personal frustration, there are also reduced opportunity costs and economic costs associated with shorter facility visits, as well as overall better patient compliance.

Length of HIV medicine refill

In this section, we focus on the length of time (in months) for which a patient's drugs are prescribed. The length of prescribing intervals for ART is another indicator that measures the responsiveness of the health system. Ideally, in terms of the National Department of Health's 2023 ART Clinical Guidelines, stable patients on ART should be given 6 months' prescriptions, with 3 months dispensed immediately so that the frequency of their visits to the clinics is reduced.^[46] MMD has massive benefits in terms of convenience and cost to the patient, as well as to the primary care system in terms of reducing the workload of staff. The longer the length of the prescription, the fewer visits the patient must make to the facility to see the clinician. A randomised trial in Lesotho showed no difference in viral load suppression (VLS) and patient retention in stable HIV patients receiving 6 MMD compared with 3 MMD or monthly dispensing,^[47] thus confirming the benefits to the patient and health system.

Table 3 gives the average number of months, obtained in patient surveys, for which HIV ARV medicines were prescribed in the third quarter of successive years, by province. This indicator is referred to as 'length of HIV medicines refill'. The provincial average, which summarises all the surveys done at all the Ritshidze-monitored facilities in the seven provinces, shows an overall increase from 1.77 months in the quarter April - June 2020 to 2.67 months in the quarter April - June 2024. As there were also changes in the official guidelines regarding the dispensing of ART during this time, it is difficult to ascribe the improvements directly to Ritshidze without doing additional research.

However, the data show that length of HIV medicine refill indicator was widely variable among the provinces. More detailed reports identify that in 2023 in the Free State, only 3% of patients received a 3 - 6-month ART refill prescription, while in Mpumalanga, nearly two-thirds (64%) received such a refill. Outside of SA, the US government's Presidential Program for AIDS Relief (PEPFAR)-supported countries report that 80% of patients get such a refill, and that large HIV programmes have successfully scaled up MMD to patients, while sustaining and increasing VLS rates in real-world settings, supporting data from clinical trials.^[48]

A review of client perceptions of MMD in Ethiopia in 2019 found that benefits included time and cost savings, fewer work disruptions, reduced stigma due to fewer clinic visits, better medication adherence and improved overall health. Perceived health system-level benefits included improved quality of care, decongested facilities, reduced provider workloads and improved record-keeping.^[49] The World Health Organization recommends that people who are established on ART should be offered refills lasting 3 - 6 months, preferably 6 months where feasible,^[50] and MMD is now frequently offered as a component of differentiated service delivery models.

 

Discussion

The Ritshidze dashboards have a wide range of data and associated indicators on staffing and waiting times, clinic conditions, HIV and TB services, specific population (e.g. sex workers) programming, access to medicines and accountability. The Ritshidze system is functional in >10% of all public sector facilities in SA. Although only two examples (patient time spent at facilities, and length of ARV prescriptions) were used in the tables and graphics above to illustrate the depth of data, as well as the interactivity in the Ritshidze database and dashboard, there are many other metrics and indicators that could be similarly accessed, analysed and utilised.

The indicators complement and add value to indicators already monitored and evaluated on a regular basis by district, subdistrict and facility managers. Specifically, the Ritshidze indicators unpack one of the overarching impact goals of the district health system, namely responsiveness, which 'encompasses attributes of health system encounters valued by people and measured from the user's perspective in eight domains: dignity, autonomy, confidentiality, communication, prompt attention, social support, quality of basic amenities and choice'.^[51] Importantly, the CLM process provides the community with a transparent and factual account of the pathways by which poor-quality healthcare services are experienced by patients of the public healthcare system, and a means to identify community-driven responses to those issues. Social accountability approaches have been shown to improve efficiency and responsiveness of health services, although there is no common blueprint, and their success depends on, among other factors, context, capacity, information, independence from power agendas and leadership.^[52]

Whether the general improvement in the indicators measured by Ritshidze, of which the two shown in this article are but examples, was because of the monitoring by Ritshidze or a result of other factors in the health system (e.g. changes in clinical guidelines) cannot be categorically stated. The increase in the prescription length of 50.8% in 4 years, and the initial declines in waiting times, are impressive in public health intervention terms. However, the principle of accountability by health managers and the health system to the community that it serves is likely to influence the behaviour of leaders and individuals in the health system, and through them, ultimately to its performance.

The Ritshidze data and indicators appear at face value to be reliable, user-friendly and easily accessible, and provide high-quality and regular feedback on user and community experience. This system complements the internal audit of clinic performance (the so-called 'ideal clinic'),^[53] as well as that done by the Office of Health Standards Compliance that monitors and assesses the compliance of facilities against a range of norms and standards.^[54] In this regard, a national policy guideline on waiting times was published in December 2023, which defines the elements of waiting times, methods to measure them and factors to be addressed to improve waiting times. The aspirational target time spent at primary healthcare facilities in the guideline is 3 hours, and it calculates this from the official opening time of the clinic.^[55] Ritshidze calculates this from the time the patient arrives at the clinic, which could be significantly earlier than the clinic opens.

Ritshidze information seems underutilised at present. There may be challenges to incorporating and using data and indicators in a compliance-driven environment of information and reporting overloads.^[2] There may also be scepticism of the sustainability of a monitoring system generated by a third party outside of the formal health system, supported by non-governmental organisations and funded with external donor resources, in this instance, PEPFAR. Nevertheless, we believe there is great potential for CLM to augment the current DHS monitoring and evaluation systems, and to enhance the overall responsiveness of the health system to the needs of individual patients, as well as the community, through social accountability. District health councils and the willingness of managers to engage more with civil society may play important roles in enabling this. The health system could also better engage and integrate Ritshidze data and indicators into the district planning and review processes, and draw lessons from districts that have managed to do this. In short, successful implementation of CLM requires prioritising community ownership and leadership, donor commitment to sustainable and reliable funding and strengthened support of programmes across the data collection and advocacy lifecycle.^[56]

 

Conclusion

As was indicated in the introductory paper on Ritshidze, community-led monitoring of health services adds a great deal of value to the overall monitoring of the district health system.^[1] If incorporated into formal health system monitoring and evaluation, CLM could enhance the responsiveness of the health system to patients and communities, one of the key overall objectives of the district health system.

Data availability. The data used in this article are all available in the public domain (references supplied in the text).

Declaration. None.

Acknowledgements. We thank the Ritshidze Collective for giving permission to use their data dashboards to construct this article.

Author contributions. PB conceived the article and wrote the first draft. All other authors read various iterations of the paper and gave comments and feedback, which were incorporated into the final version.

Funding. This article was made possible with funding from the School of Public Health and SAMRC Health Services to Systems Research Unit, University of the Western Cape.

Conflicts of interest. None.

 

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Correspondence:
P Barron
pbarron@iafrica.com

Received 5 October 2024
Accepted 17 February 2025