Evaluation of the National Adherence Guidelines for Chronic Diseases 2016
South Africa, 2016 - 2017
Matthew P.Fox, Sophie J. Pascoe, Amy N. Huber, Joshua Murphy, Mokgadi Phokojoe, Marelize Gorgens, Sydney Rosen, David Wilson, Yogan Pillay, Nicole Fraser-Hurt
Identification
IDNO
ZAF_2016_NAGCDIE_v01_M
Title
Evaluation of the National Adherence Guidelines for Chronic Diseases 2016
Subtitle
A Cluster-Randomised Evaluation
Countries
| Name | Code |
|---|---|
| South Africa | ZAF |
Study notes
This dataset was used in the preparation of the report: “Adherence Clubs and Decentralized Medication Delivery to Support Retention and Sustained Viral Suppression: Results from a Cluster Randomized Evaluation of Differentiated ART delivery models in South Africa” presenting the evaluation results of two interventions which were assessed in the context of an impact evaluation of five differentiated HIV care and adherence interventions in 24 South African facilities. The South African Government implemented Chronic Disease Adherence Guidelines, including adherence clubs (AC) and decentralized medication delivery (DMD). We compared those receiving AC/DMD at intervention sites to those eligible for AC/DMD at control sites. Outcomes were retention and sustained viral suppression (<400 copies/mL) 12 months after AC/DMD enrolment (or comparable time for controls). Twelve facilities were randomly allocated to intervention and 12 to control arms.
We saw comparable DMD outcomes vs. standard of care at facilities, an AC retention benefit and retention and sustained suppression benefits amongst men. This suggests the importance of alternative service delivery models for men and of community-based strategies to decongest primary healthcare facilities. As these strategies also reduce patient inconvenience and decongest clinics, comparable outcomes are a success.
We saw comparable DMD outcomes vs. standard of care at facilities, an AC retention benefit and retention and sustained suppression benefits amongst men. This suggests the importance of alternative service delivery models for men and of community-based strategies to decongest primary healthcare facilities. As these strategies also reduce patient inconvenience and decongest clinics, comparable outcomes are a success.
Coverage
Geographic coverage
It is taking place at 24 public sector clinics in four provinces in South Africa.
- Gauteng Province
- Limpopo Province
- North West Province
- KwaZulu Natal Province
- Gauteng Province
- Limpopo Province
- North West Province
- KwaZulu Natal Province
Producers and sponsors
Authoring entity
| Name | Affiliation |
|---|---|
| Matthew P.Fox | Boston University School of Public Health |
| Sophie J. Pascoe | University of the Witwatersrand |
| Amy N. Huber | University of the Witwatersrand |
| Joshua Murphy | University of the Witwatersrand |
| Mokgadi Phokojoe | National Department of Health, Pretoria, South Africa |
| Marelize Gorgens | The World Bank Group, Washington DC |
| Sydney Rosen | Boston University School of Public Health |
| David Wilson | The World Bank Group, Washington DC |
| Yogan Pillay | National Department of Health, Pretoria, South Africa |
| Nicole Fraser-Hurt | The World Bank Group, Washington DC |
Sampling
Sampling procedure
Selection and randomisation of study sites
The evaluation is being conducted at 24 PHCs in South Africa. All study sites follow the current guidelines for HIV care and treatment, dated December 2014. Six clinics were chosen from one district each in Gauteng, KwaZulu-Natal, Limpopo and North West Provinces.
These provinces were chosen in consultation with NDOH to represent high HIV burden regions with high-burden districts and high-volume clinics. The study team developed a list of all sites in each participating province that met these criteria and selected three matched pairs of clinics per province. Pairs were matched on ART patient volume (1000-1999, 2000-4999, or =5000 current ART
patients), setting (urban, informal settlement, or rural), location (pairs should be located relatively nearby one another) and HIV viral suppression rate (see table 2 of the report).
In each pair, one clinic was randomly assigned (using a computer-generated randomisation) to receive early implementation of the minimum package of interventions, while the other continued to provide standard of care. No blinding was used.
Table 4 of the report provided under Related Materials shows the sample size that is required to detect meaningful differences for objectives 1-5. Sample sizes were determined using PASS software for cluster-randomised designs. Each sample size was determined to measure our short-term outcome for the objective. All calculations assume a site-clustered design with the clinic as the cluster and 24 clusters evenly split between intervention and comparison groups.
We assumed power of 80% and an alpha of 0.05. Sample sizes accounted for the cluster-randomised design by assuming a coefficient of variation of 0.1. Each sample size was calculated assuming a baseline proportion of patients achieving the outcome in the absence of the intervention as determined from the literature or experience. Sample sizes were calculated based on being able to detect an absolute increase on outcomes deemed to be clinically meaningful, ranging from 15% to 20% as determined by consensus of the investigators. The total sample size was calculated to be 3456 including all of the five HIV cohorts.
The evaluation is being conducted at 24 PHCs in South Africa. All study sites follow the current guidelines for HIV care and treatment, dated December 2014. Six clinics were chosen from one district each in Gauteng, KwaZulu-Natal, Limpopo and North West Provinces.
These provinces were chosen in consultation with NDOH to represent high HIV burden regions with high-burden districts and high-volume clinics. The study team developed a list of all sites in each participating province that met these criteria and selected three matched pairs of clinics per province. Pairs were matched on ART patient volume (1000-1999, 2000-4999, or =5000 current ART
patients), setting (urban, informal settlement, or rural), location (pairs should be located relatively nearby one another) and HIV viral suppression rate (see table 2 of the report).
In each pair, one clinic was randomly assigned (using a computer-generated randomisation) to receive early implementation of the minimum package of interventions, while the other continued to provide standard of care. No blinding was used.
Table 4 of the report provided under Related Materials shows the sample size that is required to detect meaningful differences for objectives 1-5. Sample sizes were determined using PASS software for cluster-randomised designs. Each sample size was determined to measure our short-term outcome for the objective. All calculations assume a site-clustered design with the clinic as the cluster and 24 clusters evenly split between intervention and comparison groups.
We assumed power of 80% and an alpha of 0.05. Sample sizes accounted for the cluster-randomised design by assuming a coefficient of variation of 0.1. Each sample size was calculated assuming a baseline proportion of patients achieving the outcome in the absence of the intervention as determined from the literature or experience. Sample sizes were calculated based on being able to detect an absolute increase on outcomes deemed to be clinically meaningful, ranging from 15% to 20% as determined by consensus of the investigators. The total sample size was calculated to be 3456 including all of the five HIV cohorts.
Data Collection
Dates of collection
| Start | End |
|---|---|
| 2016 | 2017 |
Data sources
This study is relying on routinely collected data for study outcomes. Routine data sources will include TIER.Net, the National Health Laboratory Service (NHLS) database which contains all laboratory tests done in public sector clinics, and data sets created by entering information from clinic registers, adherence plans and patient clinic files into a database. Various degrees of
strengthening of existing data collection procedures were needed at the facilities in order to ensure complete entries into existing clinic registers or patient files, complete and accurate entry of source data onto electronic files and the use of a consistent clinic-level patient identifier to link patients between data sources (eg, a register containing a row for each visit and a patient file containing documents pertaining to that patient will each contribute to the evaluation record for that patient).
strengthening of existing data collection procedures were needed at the facilities in order to ensure complete entries into existing clinic registers or patient files, complete and accurate entry of source data onto electronic files and the use of a consistent clinic-level patient identifier to link patients between data sources (eg, a register containing a row for each visit and a patient file containing documents pertaining to that patient will each contribute to the evaluation record for that patient).
Mode of data collection
Other [oth]
Data access
Citation requirements
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
Disclaimer and copyrights
Disclaimer
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Metadata production
IDNo
DDI_ZAF_2016_NAGCDIE_v01_M_WB
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Economics Data Group | DECDG | The World Bank | Documentation of the DDI |
Production date
2019-06-25
Version
Version 01 (June 2019)