The impact of continuous quality improvement on coverage of antenatal HIV care tests in rural South Africa: Results of a stepped-wedge cluster-randomised controlled implementation trial
Evidence for the effectiveness of continuous quality improvement (CQI) in resource-poor settings is very limited. We aimed to establish the effects of CQI on quality of antenatal HIV care in primary care clinics in rural South Africa. We conducted a stepped-wedge cluster-randomised controlled trial...
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| Published in | PLoS medicine Vol. 17; no. 10; p. e1003150 |
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| Main Authors | , , , , , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Public Library of Science
07.10.2020
Public Library of Science (PLoS) |
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| Abstract | Evidence for the effectiveness of continuous quality improvement (CQI) in resource-poor settings is very limited. We aimed to establish the effects of CQI on quality of antenatal HIV care in primary care clinics in rural South Africa.
We conducted a stepped-wedge cluster-randomised controlled trial (RCT) comparing CQI to usual standard of antenatal care (ANC) in 7 nurse-led, public-sector primary care clinics-combined into 6 clusters-over 8 steps and 19 months. Clusters randomly switched from comparator to intervention on pre-specified dates until all had rolled over to the CQI intervention. Investigators and clusters were blinded to randomisation until 2 weeks prior to each step. The intervention was delivered by trained CQI mentors and included standard CQI tools (process maps, fishbone diagrams, run charts, Plan-Do-Study-Act [PDSA] cycles, and action learning sessions). CQI mentors worked with health workers, including nurses and HIV lay counsellors. The mentors used the standard CQI tools flexibly, tailored to local clinic needs. Health workers were the direct recipients of the intervention, whereas the ultimate beneficiaries were pregnant women attending ANC. Our 2 registered primary endpoints were viral load (VL) monitoring (which is critical for elimination of mother-to-child transmission of HIV [eMTCT] and the health of pregnant women living with HIV) and repeat HIV testing (which is necessary to identify and treat women who seroconvert during pregnancy). All pregnant women who attended their first antenatal visit at one of the 7 study clinics and were ≥18 years old at delivery were eligible for endpoint assessment. We performed intention-to-treat (ITT) analyses using modified Poisson generalised linear mixed effects models. We estimated effect sizes with time-step fixed effects and clinic random effects (Model 1). In separate models, we added a nested random clinic-time step interaction term (Model 2) or individual random effects (Model 3). Between 15 July 2015 and 30 January 2017, 2,160 participants with 13,212 ANC visits (intervention n = 6,877, control n = 6,335) were eligible for ITT analysis. No adverse events were reported. Median age at first booking was 25 years (interquartile range [IQR] 21 to 30), and median parity was 1 (IQR 0 to 2). HIV prevalence was 47% (95% CI 42% to 53%). In Model 1, CQI significantly increased VL monitoring (relative risk [RR] 1.38, 95% CI 1.21 to 1.57, p < 0.001) but did not improve repeat HIV testing (RR 1.00, 95% CI 0.88 to 1.13, p = 0.958). These results remained essentially the same in both Model 2 and Model 3. Limitations of our study include that we did not establish impact beyond the duration of the relatively short study period of 19 months, and that transition steps may have been too short to achieve the full potential impact of the CQI intervention.
We found that CQI can be effective at increasing quality of primary care in rural Africa. Policy makers should consider CQI as a routine intervention to boost quality of primary care in rural African communities. Implementation research should accompany future CQI use to elucidate mechanisms of action and to identify factors supporting long-term success.
This trial is registered at ClinicalTrials.gov under registration number NCT02626351. |
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| AbstractList | BACKGROUNDEvidence for the effectiveness of continuous quality improvement (CQI) in resource-poor settings is very limited. We aimed to establish the effects of CQI on quality of antenatal HIV care in primary care clinics in rural South Africa. METHODS AND FINDINGSWe conducted a stepped-wedge cluster-randomised controlled trial (RCT) comparing CQI to usual standard of antenatal care (ANC) in 7 nurse-led, public-sector primary care clinics-combined into 6 clusters-over 8 steps and 19 months. Clusters randomly switched from comparator to intervention on pre-specified dates until all had rolled over to the CQI intervention. Investigators and clusters were blinded to randomisation until 2 weeks prior to each step. The intervention was delivered by trained CQI mentors and included standard CQI tools (process maps, fishbone diagrams, run charts, Plan-Do-Study-Act [PDSA] cycles, and action learning sessions). CQI mentors worked with health workers, including nurses and HIV lay counsellors. The mentors used the standard CQI tools flexibly, tailored to local clinic needs. Health workers were the direct recipients of the intervention, whereas the ultimate beneficiaries were pregnant women attending ANC. Our 2 registered primary endpoints were viral load (VL) monitoring (which is critical for elimination of mother-to-child transmission of HIV [eMTCT] and the health of pregnant women living with HIV) and repeat HIV testing (which is necessary to identify and treat women who seroconvert during pregnancy). All pregnant women who attended their first antenatal visit at one of the 7 study clinics and were ≥18 years old at delivery were eligible for endpoint assessment. We performed intention-to-treat (ITT) analyses using modified Poisson generalised linear mixed effects models. We estimated effect sizes with time-step fixed effects and clinic random effects (Model 1). In separate models, we added a nested random clinic-time step interaction term (Model 2) or individual random effects (Model 3). Between 15 July 2015 and 30 January 2017, 2,160 participants with 13,212 ANC visits (intervention n = 6,877, control n = 6,335) were eligible for ITT analysis. No adverse events were reported. Median age at first booking was 25 years (interquartile range [IQR] 21 to 30), and median parity was 1 (IQR 0 to 2). HIV prevalence was 47% (95% CI 42% to 53%). In Model 1, CQI significantly increased VL monitoring (relative risk [RR] 1.38, 95% CI 1.21 to 1.57, p < 0.001) but did not improve repeat HIV testing (RR 1.00, 95% CI 0.88 to 1.13, p = 0.958). These results remained essentially the same in both Model 2 and Model 3. Limitations of our study include that we did not establish impact beyond the duration of the relatively short study period of 19 months, and that transition steps may have been too short to achieve the full potential impact of the CQI intervention. CONCLUSIONSWe found that CQI can be effective at increasing quality of primary care in rural Africa. Policy makers should consider CQI as a routine intervention to boost quality of primary care in rural African communities. Implementation research should accompany future CQI use to elucidate mechanisms of action and to identify factors supporting long-term success. TRIAL REGISTRATIONThis trial is registered at ClinicalTrials.gov under registration number NCT02626351. Evidence for the effectiveness of continuous quality improvement (CQI) in resource-poor settings is very limited. We aimed to establish the effects of CQI on quality of antenatal HIV care in primary care clinics in rural South Africa. We conducted a stepped-wedge cluster-randomised controlled trial (RCT) comparing CQI to usual standard of antenatal care (ANC) in 7 nurse-led, public-sector primary care clinics-combined into 6 clusters-over 8 steps and 19 months. Clusters randomly switched from comparator to intervention on pre-specified dates until all had rolled over to the CQI intervention. Investigators and clusters were blinded to randomisation until 2 weeks prior to each step. The intervention was delivered by trained CQI mentors and included standard CQI tools (process maps, fishbone diagrams, run charts, Plan-Do-Study-Act [PDSA] cycles, and action learning sessions). CQI mentors worked with health workers, including nurses and HIV lay counsellors. The mentors used the standard CQI tools flexibly, tailored to local clinic needs. Health workers were the direct recipients of the intervention, whereas the ultimate beneficiaries were pregnant women attending ANC. Our 2 registered primary endpoints were viral load (VL) monitoring (which is critical for elimination of mother-to-child transmission of HIV [eMTCT] and the health of pregnant women living with HIV) and repeat HIV testing (which is necessary to identify and treat women who seroconvert during pregnancy). All pregnant women who attended their first antenatal visit at one of the 7 study clinics and were [greater than or equal to]18 years old at delivery were eligible for endpoint assessment. We performed intention-to-treat (ITT) analyses using modified Poisson generalised linear mixed effects models. We estimated effect sizes with time-step fixed effects and clinic random effects (Model 1). In separate models, we added a nested random clinic-time step interaction term (Model 2) or individual random effects (Model 3). Between 15 July 2015 and 30 January 2017, 2,160 participants with 13,212 ANC visits (intervention n = 6,877, control n = 6,335) were eligible for ITT analysis. No adverse events were reported. Median age at first booking was 25 years (interquartile range [IQR] 21 to 30), and median parity was 1 (IQR 0 to 2). HIV prevalence was 47% (95% CI 42% to 53%). In Model 1, CQI significantly increased VL monitoring (relative risk [RR] 1.38, 95% CI 1.21 to 1.57, p < 0.001) but did not improve repeat HIV testing (RR 1.00, 95% CI 0.88 to 1.13, p = 0.958). These results remained essentially the same in both Model 2 and Model 3. Limitations of our study include that we did not establish impact beyond the duration of the relatively short study period of 19 months, and that transition steps may have been too short to achieve the full potential impact of the CQI intervention. We found that CQI can be effective at increasing quality of primary care in rural Africa. Policy makers should consider CQI as a routine intervention to boost quality of primary care in rural African communities. Implementation research should accompany future CQI use to elucidate mechanisms of action and to identify factors supporting long-term success. Background Evidence for the effectiveness of continuous quality improvement (CQI) in resource-poor settings is very limited. We aimed to establish the effects of CQI on quality of antenatal HIV care in primary care clinics in rural South Africa. Methods and findings We conducted a stepped-wedge cluster-randomised controlled trial (RCT) comparing CQI to usual standard of antenatal care (ANC) in 7 nurse-led, public-sector primary care clinics-combined into 6 clusters-over 8 steps and 19 months. Clusters randomly switched from comparator to intervention on pre-specified dates until all had rolled over to the CQI intervention. Investigators and clusters were blinded to randomisation until 2 weeks prior to each step. The intervention was delivered by trained CQI mentors and included standard CQI tools (process maps, fishbone diagrams, run charts, Plan-Do-Study-Act [PDSA] cycles, and action learning sessions). CQI mentors worked with health workers, including nurses and HIV lay counsellors. The mentors used the standard CQI tools flexibly, tailored to local clinic needs. Health workers were the direct recipients of the intervention, whereas the ultimate beneficiaries were pregnant women attending ANC. Our 2 registered primary endpoints were viral load (VL) monitoring (which is critical for elimination of mother-to-child transmission of HIV [eMTCT] and the health of pregnant women living with HIV) and repeat HIV testing (which is necessary to identify and treat women who seroconvert during pregnancy). All pregnant women who attended their first antenatal visit at one of the 7 study clinics and were [greater than or equal to]18 years old at delivery were eligible for endpoint assessment. We performed intention-to-treat (ITT) analyses using modified Poisson generalised linear mixed effects models. We estimated effect sizes with time-step fixed effects and clinic random effects (Model 1). In separate models, we added a nested random clinic-time step interaction term (Model 2) or individual random effects (Model 3). Between 15 July 2015 and 30 January 2017, 2,160 participants with 13,212 ANC visits (intervention n = 6,877, control n = 6,335) were eligible for ITT analysis. No adverse events were reported. Median age at first booking was 25 years (interquartile range [IQR] 21 to 30), and median parity was 1 (IQR 0 to 2). HIV prevalence was 47% (95% CI 42% to 53%). In Model 1, CQI significantly increased VL monitoring (relative risk [RR] 1.38, 95% CI 1.21 to 1.57, p < 0.001) but did not improve repeat HIV testing (RR 1.00, 95% CI 0.88 to 1.13, p = 0.958). These results remained essentially the same in both Model 2 and Model 3. Limitations of our study include that we did not establish impact beyond the duration of the relatively short study period of 19 months, and that transition steps may have been too short to achieve the full potential impact of the CQI intervention. Conclusions We found that CQI can be effective at increasing quality of primary care in rural Africa. Policy makers should consider CQI as a routine intervention to boost quality of primary care in rural African communities. Implementation research should accompany future CQI use to elucidate mechanisms of action and to identify factors supporting long-term success. Trial registration This trial is registered at ClinicalTrials.gov under registration number NCT02626351. Manisha Yapa and co-workers study a quality improvement intervention for antenatal HIV care in South Africa. Originally developed to streamline production processes in the consumer industry [3], CQI was adopted in the 1990s by the healthcare sector to improve organisational systems to create better quality of care and health outcomes [4]. Implementation science, however, focuses on the improvement of processes whose intermediate outcomes, such as testing coverage, can be directly influenced by changes to health services and are known to be strong determinants of health outcomes [17]. To capture proximate effects of CQI relevant to the detection of HIV infection, we chose repeat HIV testing, because incident HIV infection in pregnancy increases risk of MTCT as VL peaks shortly after infection [26]. Study setting The Africa Health Research Institute (AHRI) at Somkhele (previously known as the Africa Centre for Population Health) is located in a rural community in northern KwaZulu-Natal, South Africa. Originally developed to streamline production processes in the consumer industry [3], CQI was adopted in the 1990s by the healthcare sector to improve organisational systems to create better quality of care and health outcomes [4]. Implementation science, however, focuses on the improvement of processes whose intermediate outcomes, such as testing coverage, can be directly influenced by changes to health services and are known to be strong determinants of health outcomes [17]. To capture proximate effects of CQI relevant to the detection of HIV infection, we chose repeat HIV testing, because incident HIV infection in pregnancy increases risk of MTCT as VL peaks shortly after infection [26]. Study setting The Africa Health Research Institute (AHRI) at Somkhele (previously known as the Africa Centre for Population Health) is located in a rural community in northern KwaZulu-Natal, South Africa. Evidence for the effectiveness of continuous quality improvement (CQI) in resource-poor settings is very limited. We aimed to establish the effects of CQI on quality of antenatal HIV care in primary care clinics in rural South Africa. We conducted a stepped-wedge cluster-randomised controlled trial (RCT) comparing CQI to usual standard of antenatal care (ANC) in 7 nurse-led, public-sector primary care clinics-combined into 6 clusters-over 8 steps and 19 months. Clusters randomly switched from comparator to intervention on pre-specified dates until all had rolled over to the CQI intervention. Investigators and clusters were blinded to randomisation until 2 weeks prior to each step. The intervention was delivered by trained CQI mentors and included standard CQI tools (process maps, fishbone diagrams, run charts, Plan-Do-Study-Act [PDSA] cycles, and action learning sessions). CQI mentors worked with health workers, including nurses and HIV lay counsellors. The mentors used the standard CQI tools flexibly, tailored to local clinic needs. Health workers were the direct recipients of the intervention, whereas the ultimate beneficiaries were pregnant women attending ANC. Our 2 registered primary endpoints were viral load (VL) monitoring (which is critical for elimination of mother-to-child transmission of HIV [eMTCT] and the health of pregnant women living with HIV) and repeat HIV testing (which is necessary to identify and treat women who seroconvert during pregnancy). All pregnant women who attended their first antenatal visit at one of the 7 study clinics and were ≥18 years old at delivery were eligible for endpoint assessment. We performed intention-to-treat (ITT) analyses using modified Poisson generalised linear mixed effects models. We estimated effect sizes with time-step fixed effects and clinic random effects (Model 1). In separate models, we added a nested random clinic-time step interaction term (Model 2) or individual random effects (Model 3). Between 15 July 2015 and 30 January 2017, 2,160 participants with 13,212 ANC visits (intervention n = 6,877, control n = 6,335) were eligible for ITT analysis. No adverse events were reported. Median age at first booking was 25 years (interquartile range [IQR] 21 to 30), and median parity was 1 (IQR 0 to 2). HIV prevalence was 47% (95% CI 42% to 53%). In Model 1, CQI significantly increased VL monitoring (relative risk [RR] 1.38, 95% CI 1.21 to 1.57, p < 0.001) but did not improve repeat HIV testing (RR 1.00, 95% CI 0.88 to 1.13, p = 0.958). These results remained essentially the same in both Model 2 and Model 3. Limitations of our study include that we did not establish impact beyond the duration of the relatively short study period of 19 months, and that transition steps may have been too short to achieve the full potential impact of the CQI intervention. We found that CQI can be effective at increasing quality of primary care in rural Africa. Policy makers should consider CQI as a routine intervention to boost quality of primary care in rural African communities. Implementation research should accompany future CQI use to elucidate mechanisms of action and to identify factors supporting long-term success. This trial is registered at ClinicalTrials.gov under registration number NCT02626351. |
| Audience | Academic |
| Author | Jiamsakul, Awachana Dhlomo-Mphatswe, Wendy Yapa, H Manisha Ogbuoji, Osondu Moshabela, Mosa Tanser, Frank Harling, Guy Chetty, Terusha Bärnighausen, Till Post, Frank A De Neve, Jan-Walter Gareta, Dickman Pillay, Deenan Matthews, Philippa Herbst, Kobus Wyke, Sally Herbst, Carina Geldsetzer, Pascal |
| AuthorAffiliation | 1 The Kirby Institute, University of New South Wales Sydney, NSW, Australia University of California, San Francisco, UNITED STATES 8 School of Clinical Medicine, Discipline of Obstetrics and Gynaecology, University of KwaZulu-Natal, Durban, South Africa 3 Heidelberg Institute of Global Health (HIGH), Medical Faculty and University Hospital, Heidelberg University, Heidelberg, Germany 14 Division of Infection and Immunity, University College London, London, United Kingdom 9 School of Nursing and Public Health, University of KwaZulu-Natal, Durban, South Africa 13 Centre for the AIDS Programme of Research in South Africa (CAPRISA), University of KwaZulu-Natal, Durban, South Africa 5 King’s College Hospital NHS Foundation Trust, London, United Kingdom 15 Institute for Health & Wellbeing, University of Glasgow, Glasgow, United Kingdom 7 Institute for Global Health, University College London, London, United Kingdom 4 Health systems Research Unit, South African Medical Research Council, Durban, South Af |
| AuthorAffiliation_xml | – name: 17 Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America – name: 8 School of Clinical Medicine, Discipline of Obstetrics and Gynaecology, University of KwaZulu-Natal, Durban, South Africa – name: 10 Islington GP Federation, London, United Kingdom – name: 2 Africa Health Research Institute (AHRI), KwaZulu-Natal, South Africa – name: 9 School of Nursing and Public Health, University of KwaZulu-Natal, Durban, South Africa – name: 4 Health systems Research Unit, South African Medical Research Council, Durban, South Africa – name: 14 Division of Infection and Immunity, University College London, London, United Kingdom – name: University of California, San Francisco, UNITED STATES – name: 1 The Kirby Institute, University of New South Wales Sydney, NSW, Australia – name: 7 Institute for Global Health, University College London, London, United Kingdom – name: 5 King’s College Hospital NHS Foundation Trust, London, United Kingdom – name: 3 Heidelberg Institute of Global Health (HIGH), Medical Faculty and University Hospital, Heidelberg University, Heidelberg, Germany – name: 6 Division of Primary Care and Population Health, Department of Medicine, Stanford University, Stanford, California, United States of America – name: 11 Global Health Institute, Duke University, Durham, North Carolina, United States of America – name: 12 Lincoln International Institute for Rural Health, University of Lincoln, Lincoln, United Kingdom – name: 15 Institute for Health & Wellbeing, University of Glasgow, Glasgow, United Kingdom – name: 13 Centre for the AIDS Programme of Research in South Africa (CAPRISA), University of KwaZulu-Natal, Durban, South Africa – name: 16 MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa |
| Author_xml | – sequence: 1 givenname: H Manisha orcidid: 0000-0002-0100-4754 surname: Yapa fullname: Yapa, H Manisha organization: Africa Health Research Institute (AHRI), KwaZulu-Natal, South Africa – sequence: 2 givenname: Jan-Walter orcidid: 0000-0003-0090-8249 surname: De Neve fullname: De Neve, Jan-Walter organization: Heidelberg Institute of Global Health (HIGH), Medical Faculty and University Hospital, Heidelberg University, Heidelberg, Germany – sequence: 3 givenname: Terusha orcidid: 0000-0002-7554-2934 surname: Chetty fullname: Chetty, Terusha organization: Health systems Research Unit, South African Medical Research Council, Durban, South Africa – sequence: 4 givenname: Carina orcidid: 0000-0001-8759-8620 surname: Herbst fullname: Herbst, Carina organization: Africa Health Research Institute (AHRI), KwaZulu-Natal, South Africa – sequence: 5 givenname: Frank A surname: Post fullname: Post, Frank A organization: King's College Hospital NHS Foundation Trust, London, United Kingdom – sequence: 6 givenname: Awachana surname: Jiamsakul fullname: Jiamsakul, Awachana organization: The Kirby Institute, University of New South Wales Sydney, NSW, Australia – sequence: 7 givenname: Pascal orcidid: 0000-0002-8878-5505 surname: Geldsetzer fullname: Geldsetzer, Pascal organization: Division of Primary Care and Population Health, Department of Medicine, Stanford University, Stanford, California, United States of America – sequence: 8 givenname: Guy orcidid: 0000-0001-6604-491X surname: Harling fullname: Harling, Guy organization: Institute for Global Health, University College London, London, United Kingdom – sequence: 9 givenname: Wendy surname: Dhlomo-Mphatswe fullname: Dhlomo-Mphatswe, Wendy organization: School of Clinical Medicine, Discipline of Obstetrics and Gynaecology, University of KwaZulu-Natal, Durban, South Africa – sequence: 10 givenname: Mosa orcidid: 0000-0002-9438-7095 surname: Moshabela fullname: Moshabela, Mosa organization: School of Nursing and Public Health, University of KwaZulu-Natal, Durban, South Africa – sequence: 11 givenname: Philippa orcidid: 0000-0002-6157-9680 surname: Matthews fullname: Matthews, Philippa organization: Islington GP Federation, London, United Kingdom – sequence: 12 givenname: Osondu orcidid: 0000-0003-2472-6861 surname: Ogbuoji fullname: Ogbuoji, Osondu organization: Global Health Institute, Duke University, Durham, North Carolina, United States of America – sequence: 13 givenname: Frank orcidid: 0000-0001-9797-0000 surname: Tanser fullname: Tanser, Frank organization: Centre for the AIDS Programme of Research in South Africa (CAPRISA), University of KwaZulu-Natal, Durban, South Africa – sequence: 14 givenname: Dickman surname: Gareta fullname: Gareta, Dickman organization: Africa Health Research Institute (AHRI), KwaZulu-Natal, South Africa – sequence: 15 givenname: Kobus orcidid: 0000-0002-5436-9386 surname: Herbst fullname: Herbst, Kobus organization: Africa Health Research Institute (AHRI), KwaZulu-Natal, South Africa – sequence: 16 givenname: Deenan orcidid: 0000-0003-2431-244X surname: Pillay fullname: Pillay, Deenan organization: Division of Infection and Immunity, University College London, London, United Kingdom – sequence: 17 givenname: Sally orcidid: 0000-0002-7509-8247 surname: Wyke fullname: Wyke, Sally organization: Institute for Health & Wellbeing, University of Glasgow, Glasgow, United Kingdom – sequence: 18 givenname: Till orcidid: 0000-0002-4182-4212 surname: Bärnighausen fullname: Bärnighausen, Till organization: Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/33027246$$D View this record in MEDLINE/PubMed |
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| DOI | 10.1371/journal.pmed.1003150 |
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| Snippet | Evidence for the effectiveness of continuous quality improvement (CQI) in resource-poor settings is very limited. We aimed to establish the effects of CQI on... Background Evidence for the effectiveness of continuous quality improvement (CQI) in resource-poor settings is very limited. We aimed to establish the effects... Originally developed to streamline production processes in the consumer industry [3], CQI was adopted in the 1990s by the healthcare sector to improve... BACKGROUNDEvidence for the effectiveness of continuous quality improvement (CQI) in resource-poor settings is very limited. We aimed to establish the effects... Manisha Yapa and co-workers study a quality improvement intervention for antenatal HIV care in South Africa. BackgroundEvidence for the effectiveness of continuous quality improvement (CQI) in resource-poor settings is very limited. We aimed to establish the effects... |
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| SubjectTerms | Adult Advisors Anti-HIV Agents - therapeutic use Biology and Life Sciences Clinics Data collection Female Health aspects HIV HIV Infections - blood HIV Infections - diagnosis HIV Infections - drug therapy HIV Infections - prevention & control HIV Seropositivity - diagnosis HIV tests Human immunodeficiency virus Humans Implementation Science Infections Infectious Disease Transmission, Vertical - prevention & control Maternal health services Medical research Medical tests Medicine and Health Sciences Methods People and places Practice Patterns, Nurses Pregnancy Prenatal care Prenatal Care - standards Primary care Primary Health Care Process Assessment, Health Care Quality control Quality Improvement Quality Indicators, Health Care Quality management Research data management RNA, Viral - blood Rural areas Rural health services Rural Population Rural women South Africa Surveillance Total quality Total Quality Management Viral Load - statistics & numerical data Womens health Young Adult |
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| Title | The impact of continuous quality improvement on coverage of antenatal HIV care tests in rural South Africa: Results of a stepped-wedge cluster-randomised controlled implementation trial |
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