Context

The ICRMP was launched in 2015 in a phased approach across all 52 districts in South Africa. The programme aimed to scale up all (approx. 3500) public health clinics (PHCs) to an “ideal clinic” status, ready to deliver on the national health insurance (NHI) mandate. The first phase of the programme involved the roll-out of the ICRMP in approximately 1,000 facilities. Enrolled facilities were supported by the provincial and national departments of health to improve quality standards and achieve a minimum score (ideal clinic status) required for accreditation as an NHI facility.

Research Question

Our study assesses the impact of the ICRMP on facility-level indicators that capture performance and quality of health care services. In order to achieve this, we take advantage of the phased implementation of the ICRMP to identify the programme effect.

Methods

The study pools data from difference sources, including administrative data from the District Health Information System (DHIS) and applies a difference-in-difference estimation approach to identify the impact of the ICRMP.

Intended outcomes and Impact

The two outcome measures of interest are programme outcomes (ideal clinic scores/status) and health facility indicators. Programme outcome measures provide insights into the extent to which the ICRMP was successful in improving scores of enrolled PHC facilities. The second outcome measures include health facility indicators that capture the performance of PHC facilities. These include antenatal care coverage and fully immunised infants. Preliminary findings suggest that the ICRMP was successful in improving programme outcomes. However, the extent to which improvements in programme outcomes translates to improvements in quality indicators remain unclear.

In addition to providing insights into the effectiveness of the ICRMP, our impact evaluation study provides an opportunity to test the usefulness of applying quasi-experimental methods to administrative data in settings where large-scale population survey data are often not readily available. Successful completion of this study could also be used to promote consideration of the rollout of interventions that allows for similar evaluations, as well as promote the use of these methods in other low-and middle-income country settings with similar health system data infrastructure.