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


Autoři: H. Manisha Yapa aff001;  Jan-Walter De Neve aff003;  Terusha Chetty aff004;  Carina Herbst aff002;  Frank A. Post aff005;  Awachana Jiamsakul aff001;  Pascal Geldsetzer aff003;  Guy Harling aff002;  Wendy Dhlomo-Mphatswe aff008;  Mosa Moshabela aff002;  Philippa Matthews aff002;  Osondu Ogbuoji aff011;  Frank Tanser aff002;  Dickman Gareta aff002;  Kobus Herbst aff002;  Deenan Pillay aff002;  Sally Wyke aff002;  Till Bärnighausen aff002
Působiště autorů: The Kirby Institute, University of New South Wales Sydney, NSW, Australia aff001;  Africa Health Research Institute (AHRI), KwaZulu-Natal, South Africa aff002;  Heidelberg Institute of Global Health (HIGH), Medical Faculty and University Hospital, Heidelberg University, Heidelberg, Germany aff003;  Health systems Research Unit, South African Medical Research Council, Durban, South Africa aff004;  King’s College Hospital NHS Foundation Trust, London, United Kingdom aff005;  Division of Primary Care and Population Health, Department of Medicine, Stanford University, Stanford, California, United States of America aff006;  Institute for Global Health, University College London, London, United Kingdom aff007;  School of Clinical Medicine, Discipline of Obstetrics and Gynaecology, University of KwaZulu-Natal, Durban, South Africa aff008;  School of Nursing and Public Health, University of KwaZulu-Natal, Durban, South Africa aff009;  Islington GP Federation, London, United Kingdom aff010;  Global Health Institute, Duke University, Durham, North Carolina, United States of America aff011;  Lincoln International Institute for Rural Health, University of Lincoln, Lincoln, United Kingdom aff012;  Centre for the AIDS Programme of Research in South Africa (CAPRISA), University of KwaZulu-Natal, Durban, South Africa aff013;  Division of Infection and Immunity, University College London, London, United Kingdom aff014;  Institute for Health & Wellbeing, University of Glasgow, Glasgow, United Kingdom aff015;  MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa aff016;  Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America aff017
Vyšlo v časopise: 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. PLoS Med 17(10): e32767. doi:10.1371/journal.pmed.1003150
Kategorie: Research Article
doi: 10.1371/journal.pmed.1003150

Souhrn

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 ≥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.

Klíčová slova:

Antenatal care – HIV – HIV diagnosis and management – Medical risk factors – Pregnancy – Primary care – South Africa – Virus testing


Zdroje

1. Cantiello J, Kitsantas P, Moncada S, Abdul S. The evolution of quality improvement in healthcare: patient-centered care and health information technology applications. J Hosp Admin. 2016;5(2):62–8. doi: 10.5430/jha.v5n2p62

2. Kelly DL, Johnson SP, Sollecito WA. Measurement, variation, and CQI tools. In: Sollecito WA, Johnson JK, editors. McLaughlin and Kaluzny's continuous quality improvement in health care. 4 ed: Jones & Bartlett Learning; 2011.

3. Laffel G, Blumenthal D. The case for using industrial quality management science in health care organizations. JAMA. 1989;262:2869–73. doi: 10.1001/jama.1989.03430200113036 2810623;

4. Luce JM, Bindman AB, Lee PR. A brief history of health care quality assessment and improvement in the United States. West J Med. 1994;160:263–8. 8191769;

5. Leatherman S, Ferris TG, Berwick D, Omaswa F, Crisp N. The role of quality improvement in strengthening health systems in developing countries. Int J Qual Health Care. 2010;22:237–43. doi: 10.1093/intqhc/mzq028 20543209;

6. Yapa HM, Bärnighausen T. Implementation science in resource-poor countries and communities. Impl Sci. 2018;13:154. doi: 10.1186/s13012-018-0847-1 30587195;

7. Mate KS, Ngubane G, Barker PM. A quality improvement model for the rapid scale-up of a program to prevent mother-to-child HIV transmission in South Africa. Int J Qual Health Care. 2013;25:373–80. doi: 10.1093/intqhc/mzt039 23710069;

8. Singh K, Brodish P, Speizer I, Barker P, Amenga-Etego I, Dasoberi I, et al. Can a quality improvement project impact maternal and child health outcomes at scale in northern Ghana? Health Res Policy Syst. 2016;14:45. doi: 10.1186/s12961-016-0115-2 27306769;

9. Magge H, Kiflie A, Mulissa Z, Abate M, Biadgo A, Bitewulign B, et al. Launching the Ethiopia health care quality initiative: interim results and initial lessons learned. BMJ Open Qual. 2017;6(Suppl 1):A1–A39. doi: 10.1136/bmjoq-2017-IHI.4

10. Mutanda P, Muange P, Lutta M, Kinyua K, Chebet L, Okaka B, et al. Improving prevention of mother to child transmission of HIV care: Experiences from implementing quality improvement in Kenya. Technical Report. USAID ASSIST Project. Chevy Chase, MD: University Research Co, LLC; 2017.

11. Bhardwaj S, Barron P, Pillay Y, Treger-Slavin L, Robinson P, Goga A, et al. Elimination of mother-to-child transmission of HIV in South Africa: Rapid scale-up using quality improvement. S Afr Med J. 2014;104:239–43. doi: 10.7196/samj.7605 24893500;

12. WHO and UNICEF. A vision for primary health care in the 21st century: towards universal health coverage and the Sustainable Development Goals. Geneva: World Health Organization and United Nations Children’s Fund, 2018.

13. Colbourn T, Nambiar B, Bondo A, Makwenda C, Tsetekani E, Makonda-Ridley A, et al. Effects of quality improvement in health facilities and community mobilization through women's groups on maternal, neonatal and perinatal mortality in three districts of Malawi: MaiKhanda, a cluster randomized controlled effectiveness trial. Int Health. 2013;5:180–95. doi: 10.1093/inthealth/iht011 24030269;

14. Oyeledun B, Phillips A, Oronsaye F, Alo OD, Shaffer N, Osibo B, et al. The effect of a continuous quality improvement intervention on retention-in-care at 6 months postpartum in a PMTCT program in northern Nigeria: results of a cluster randomized controlled study. J Acquir Immune Defic Syndr. 2017;75(Suppl 2):S156–S64. doi: 10.1097/QAI.0000000000001363 28498185;

15. Cawley C, McRobie E, Oti S, Njamwea B, Nyaguara A, Odhiambo F, et al. Identifying gaps in HIV policy and practice along the HIV care continuum: evidence from a national policy review and health facility surveys in urban and rural Kenya. Health Policy Plan. 2017;32:1316–26. doi: 10.1093/heapol/czx091 28981667;

16. Ezeanolue EE, Powell BJ, Patel D, Olutola A, Obiefune M, Dakum P, et al. Identifying and prioritizing implementation barriers, gaps, and strategies through the Nigeria Implementation Science Alliance: getting to zero in the prevention of mother-to-child transmission of HIV. J Acquir Immune Defic Syndr. 2016;72 Suppl 2:S161–6. doi: 10.1097/QAI.0000000000001066 27355504;

17. Proctor E, Silmere H, Raghavan R, Hovmand P, Aarons G, Bunger A, et al. Outcomes for implementation research: conceptual distinctions, measurement challenges, and research agenda. Adm Policy Ment Health. 2011;38:65–76. doi: 10.1007/s10488-010-0319-7 20957426;

18. Myer L, Dunning L, Lesosky M, Hsiao NY, Phillips T, Petro G, et al. Frequency of viremic episodes in HIV-infected women initiating antiretroviral therapy during pregnancy: a cohort study. Clin Infect Dis. 2017;64:422–7. doi: 10.1093/cid/ciw792 27927852;

19. Koss CA, Natureeba P, Kwarisiima D, Ogena M, Clark TD, Olwoch P, et al. Viral suppression and retention in care up to 5 years after initiation of lifelong ART during pregnancy (Option B+) in rural Uganda. J Acquir Immune Defic Syndr. 2017;74:279–84. doi: 10.1097/QAI.0000000000001228 27828878;

20. Myer L, Essajee S, Broyles LN, Watts DH, Lesosky M, El-Sadr WM, et al. Pregnant and breastfeeding women: A priority population for HIV viral load monitoring. PLoS Med. 2017;14:e1002375. doi: 10.1371/journal.pmed.1002375 28809929;

21. Warszawski J, Tubiana R, Le Chenadec J, Blanche S, Teglas JP, Dollfus C, et al. Mother-to-child HIV transmission despite antiretroviral therapy in the ANRS French Perinatal Cohort. AIDS. 2008;22:289–99. doi: 10.1097/QAD.0b013e3282f3d63c 18097232;

22. WHO. Mother-to-child transmission of HIV 2015. [cited 2019 Jul 9]. Available from: http://www.who.int/hiv/topics/mtct/about/en/.

23. National Department of Health South Africa. National consolidated guidelines for the prevention of mother-to-child transmission of HIV (PMTCT) and the management of HIV in children, adolescents and adults. Pretoria: National Department of Health, 2015.

24. Goga A, Chirinda W, Ngandu NK, Ngoma K, Bhardwaj S, Feucht U, et al. Closing the gaps to eliminate mother-to-child transmission of HIV (MTCT) in South Africa—understanding MTCT case rates, factors that hinder the monitoring and attainment of targets, and potential game changers. S Afr Med J. 2018;108(Suppl 1):S17–S24. doi: 10.7196/SAMJ.2018.v108i3.12817

25. Haas AD, Keiser O, Balestre E, Brown S, Bissagnene E, Chimbetete C, et al. Monitoring and switching of first-line antiretroviral therapy in adult treatment cohorts in sub-Saharan Africa: collaborative analysis. Lancet HIV. 2015;2:e271–e8. doi: 10.1016/s2352-3018(15)00087-9 26423252

26. Dinh TH, Delaney KP, Goga A, Jackson D, Lombard C, Woldesenbet S, et al. Impact of maternal HIV seroconversion during pregnancy on early mother to child transmission of HIV (MTCT) measured at 4–8 weeks postpartum in South Africa 2011–2012: a national population-based evaluation. PLoS ONE. 2015;10:e0125525. doi: 10.1371/journal.pone.0125525 25942423;

27. Drake AL, Wagner A, Richardson B, John-Stewart G. Incident HIV during pregnancy and postpartum and risk of mother-to-child HIV transmission: a systematic review and meta-analysis. PLoS Med. 2014;11:e1001608. doi: 10.1371/journal.pmed.1001608 24586123;

28. Maman D, Huerga H, Mukui I, Chilima B, Kirubi B, Van Cutsem G, et al. Most breastfeeding women with high viral load are still undiagnosed in sub-Saharan Africa. Conference on Retroviruses and Opportunistic Infections (CROI); 2015; Seattle, Washington: Abstract number 32.

29. Read PJ, Mandalia S, Khan P, Harrisson U, Naftalin C, Gilleece Y, et al. When should HAART be initiated in pregnancy to achieve an undetectable HIV viral load by delivery? AIDS. 2012;26:1095–103. doi: 10.1097/QAD.0b013e3283536a6c 22441248;

30. Chetty T, Yapa HMN, Herbst C, Geldsetzer P, Naidu KK, De Neve J-W, et al. The MONARCH intervention to enhance the quality of antenatal and postnatal primary health services in rural South Africa: protocol for a stepped-wedge cluster-randomised controlled trial. BMC Health Serv Res. 2018;18:625. doi: 10.1186/s12913-018-3404-3 30089485;

31. Tanser F, Hosegood V, Bärnighausen T, Herbst K, Nyirenda M, Muhwava W, et al. Cohort profile: Africa Centre Demographic Information System (ACDIS) and population-based HIV survey. Int J Epidemiol. 2008;37:956–62. doi: 10.1093/ije/dym211 17998242;

32. Massyn N, Day C, Peer N, Padarath A, Barron P, English M. District health barometer 2013/2014. Durban: Health Systems Trust; 2014.

33. Hemming K, Taljaard M, McKenzie JE, Hooper R, Copas A, Thompson JA, et al. Reporting of stepped wedge cluster randomised trials: extension of the CONSORT 2010 statement with explanation and elaboration. BMJ. 2018;363:k1614. doi: 10.1136/bmj.k1614 30413417;

34. Hoffmann TC, Glasziou PP, Boutron I, Milne R, Perera R, Moher D, et al. Better reporting of interventions: template for intervention description and replication (TIDieR) checklist and guide. BMJ. 2014;348:g1687. doi: 10.1136/bmj.g1687 24609605;

35. Institute for Healthcare Improvement (IHI). The breakthrough series: IHI’s collaborative model for achieving breakthrough improvement. IHI Innovation Series white paper. Boston: IHI; 2003.

36. Layton A, Moss F, Morgan G. Mapping out the patient’s journey—experiences of developing pathways of care. Qual Health Care. 1998;7(Suppl):S30–S6. 10339033;

37. Bonetti PO, Waeckerlin A, Schuepfer G, Frutiger A. Improving time-sensitive processes in the intensive care unit: the example of ‘door-to-needle time’ in acute myocardial infarction. Int J Qual Health Care. 2000;12:311–7. doi: 10.1093/intqhc/12.4.311 10985269;

38. Berwick D. Developing and testing changes in delivery of care. Ann Intern Med. 1998;128:651–6. doi: 10.7326/0003-4819-128-8-199804150-00009 9537939;

39. Perla RJ, Provost LP, Murray SK. The run chart: a simple analytical tool for learning from variation in healthcare processes. BMJ Qual Saf. 2011;20:46–51. doi: 10.1136/bmjqs.2009.037895 21228075;

40. Grol R, Wensing M. Implementation of Change in Healthcare: a Complex Problem. In: Grol R, Wensing M, Eccles M, Davis D, editors. Improving patient care: The implementation of change in health care. 2nd ed. West Sussex, UK: BMJ Books, Wiley Blackwell; 2013.

41. Moore GF, Audrey S, Barker M, Bond L, Bonell C, Hardeman W, et al. Process evaluation of complex interventions: Medical Research Council guidance. BMJ. 2015;350:h1258. doi: 10.1136/bmj.h1258 25791983;

42. Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42:377–81. doi: 10.1016/j.jbi.2008.08.010 18929686;

43. Barnhart D, Hertzmark E, Liu E, Mungure E, Muya AN, Sando D, et al. Intra-cluster correlation estimates for HIV-related outcomes from care and treatment clinics in Dar es Salaam, Tanzania. Contemp Clin Trials Commun. 2016;4:161–9. doi: 10.1016/j.conctc.2016.09.001 27766318;

44. Zou G. A modified Poisson regression approach to prospective studies with binary data. Am J Epidemiol. 2004;159:702–6. doi: 10.1093/aje/kwh090 15033648;

45. Zou GY, Donner A. Extension of the modified Poisson regression model to prospective studies with correlated binary data. Stat Methods Med Res. 2011;22:661–70. doi: 10.1177/0962280211427759 22072596;

46. Cummings P. The relative merits of risk ratios and odds ratios. Arch Pediatr Adolesc Med. 2009;163:438–45. doi: 10.1001/archpediatrics.2009.31 19414690;

47. Greenland S. Interpretation of choice of effect measures in epidemiologic analyses. Am J Epidemiol. 1987;125:761–8. doi: 10.1093/oxfordjournals.aje.a114593 3551588;

48. Hauck WW, Anderson S, Marcus SM. Should we adjust for covariates in nonlinear regression analyses of randomized trials? Control Clin Trials. 1998;19:249–56. doi: 10.1016/s0197-2456(97)00147-5 9620808;

49. Hernan MA, Clayton D, Keiding N. The Simpson's paradox unraveled. Int J Epidemiol. 2011;40:780–5. doi: 10.1093/ije/dyr041 21454324;

50. Yelland L, Salter A, Ryan P. Relative risk estimation in cluster randomized trials: a comparison of generalized estimating equation methods. Int J Biostat. 2011;7:1–26. doi: 10.2202/1557-4679.1323

51. Carter RE, Lipsitz SR, Tilley BC. Quasi-likelihood estimation for relative risk regression models. Biostatistics. 2005;6:39–44. doi: 10.1093/biostatistics/kxh016 15618526;

52. Williamson T, Eliasziw M, Fick GH. Log-binomial models: exploring failed convergence. Emerg Themes Epidemiol. 2013;10:14. doi: 10.1186/1742-7622-10-14 24330636;

53. Chen W, Qian L, Shi J, Franklin M. Comparing performance between log-binomial and robust Poisson regression models for estimating risk ratios under model misspecification. BMC Med Res Methodol. 2018;18:63. doi: 10.1186/s12874-018-0519-5 29929477;

54. Yelland LN, Salter AB, Ryan P. Performance of the modified Poisson regression approach for estimating relative risks from clustered prospective data. Am J Epidemiol. 2011;174:984–92. doi: 10.1093/aje/kwr183 21841157;

55. Zou GY. Assessment of risks by predicting counterfactuals. Stat Med. 2009;28:3761–81. doi: 10.1002/sim.3751 19856279;

56. Marschner IC, Gillett AC. Relative risk regression: reliable and flexible methods for log-binomial models. Biostatistics. 2012;13:179–92. doi: 10.1093/biostatistics/kxr030 21914729;

57. Hussey MA, Hughes JP. Design and analysis of stepped wedge cluster randomized trials. Contemp ClinTrials. 2007;28:182–91. doi: 10.1016/j.cct.2006.05.007 16829207;

58. Hemming K, Taljaard M, Forbes A. Analysis of cluster randomised stepped wedge trials with repeated cross-sectional samples. Trials. 2017;18:101. doi: 10.1186/s13063-017-1833-7 28259174;

59. Greenland S, Rothman KJ. Measures of occurrence. In: Rothman KJ, Greenland S, editors. Modern epidemiology. Philadelphia: Lippincott Williams and Wilkins; 2008. p. 33–51.

60. WHO. WHO recommendations on antenatal care for a positive pregnancy experience. Geneva: World Health Organization, 2016.

61. Ukoumunne OC, Forbes AB, Carlin JB, Gulliford MC. Comparison of the risk difference, risk ratio and odds ratio scales for quantifying the unadjusted intervention effect in cluster randomized trials. Stat Med. 2008;27:5143–55. doi: 10.1002/sim.3359 18613226;

62. Médecins Sans Frontières (MSF). Getting to undetectable: usage of HIV viral load monitoring in five countries. Geneva: MSF; 2014.

63. Awungafac G, Amin ET, Fualefac A, Takah NF, Agyingi LA, Nwobegahay J, et al. Viral load testing and the use of test results for clinical decision making for HIV treatment in Cameroon: An insight into the clinic-laboratory interface. PLoS ONE. 2018;13:e0198686. doi: 10.1371/journal.pone.0198686 29889862;

64. Alemu YM, Ambaw F, Wilder-Smith A. Utilization of HIV testing services among pregnant mothers in low income primary care settings in northern Ethiopia: a cross sectional study. BMC Preg Childbirth. 2017;17:199. doi: 10.1186/s12884-017-1389-2 28646888;

65. Gebremedhin KB, Tian B, Tang C, Zhang X, Yisma E, Wang H. Factors associated with acceptance of provider-initiated HIV testing and counseling among pregnant women in Ethiopia. Patient Prefer Adherence. 2018;12:183–91. doi: 10.2147/PPA.S148687 29416320;

66. Hu J, Geldsetzer P, Steele SJ, Matthews P, Ortblad K, Solomon T, et al. The impact of lay counselors on HIV testing rates: quasi-experimental evidence from lay counselor redeployment in KwaZulu-Natal, South Africa. AIDS. 2018;32:2067–73. doi: 10.1097/QAD.0000000000001924 29912066;

67. Weaver MR, Burnett SM, Crozier I, Kinoti SN, Kirunda I, Mbonye MK, et al. Improving facility performance in infectious disease care in Uganda: a mixed design study with pre/post and cluster randomized trial components. PLoS ONE. 2014;9:e103017. doi: 10.1371/journal.pone.0103017 25133799;

68. Michel J, Chimbindi N, Mohlakoana N, Orgill M, Bärnighausen T, Obrist B, et al. How and why policy-practice gaps come about: a South African universal health coverage context. J Glob Health Reports. 2020;3:e2019069. doi: 10.29392/joghr.3.e2019069

69. Institute for Healthcare Improvement (IHI). IHI open school online courses 2020. [cited 2020 Feb 6]. Available from: http://www.ihi.org/education/IHIOpenSchool/Courses/Pages/OpenSchoolCertificates.aspx.

70. Institute for Healthcare Improvement (IHI). In-person training: Breakthrough series college 2020. [cited 2020 Feb 6]. Available from: http://www.ihi.org/education/InPersonTraining/breakthrough-series-college/Pages/default.aspx.


Článek vyšel v časopise

PLOS Medicine


2020 Číslo 10

Nejčtenější v tomto čísle

Tomuto tématu se dále věnují…


Přihlášení
Zapomenuté heslo

Nemáte účet?  Registrujte se

Zapomenuté heslo

Zadejte e-mailovou adresu se kterou jste vytvářel(a) účet, budou Vám na ni zaslány informace k nastavení nového hesla.

Přihlášení

Nemáte účet?  Registrujte se