TY - JOUR
T1 - Data-driven quality improvement in low-and middle-income country health systems
T2 - Lessons from seven years of implementation experience across Mozambique, Rwanda, and Zambia
AU - Wagenaar, Bradley H.
AU - Hirschhorn, Lisa R.
AU - Henley, Catherine
AU - Gremu, Artur
AU - Sindano, Ntazana
AU - Chilengi, Roma
AU - Hingora, Ahmed
AU - Mboya, Dominic
AU - Exavery, Amon
AU - Tani, Kassimu
AU - Manzi, Fatuma
AU - Pemba, Senga
AU - Phillips, James
AU - Kante, Almamy Malick
AU - Ramsey, Kate
AU - Baynes, Colin
AU - Awoonor-Williams, John Koku
AU - Bawah, Ayaga
AU - Nimako, Belinda Afriyie
AU - Kanlisi, Nicholas
AU - Jackson, Elizabeth F.
AU - Sheff, Mallory C.
AU - Kyei, Pearl
AU - Asuming, Patrick O.
AU - Biney, Adriana
AU - Ayles, Helen
AU - Mwanza, Moses
AU - Chirwa, Cindy
AU - Stringer, Jeffrey
AU - Mulenga, Mary
AU - Musatwe, Dennis
AU - Chisala, Masoso
AU - Lemba, Michael
AU - Mutale, Wilbroad
AU - Drobac, Peter
AU - Rwabukwisi, Felix Cyamatare
AU - Binagwaho, Agnes
AU - Gupta, Neil
AU - Nkikabahizi, Fulgence
AU - Manzi, Anatole
AU - Condo, Jeanine
AU - Farmer, Didi Bertrand
AU - Hedt-Gauthier, Bethany
AU - Sherr, Kenneth
AU - Cuembelo, Fatima
AU - Michel, Catherine
AU - Gimbel, Sarah
AU - Kariaganis, Marina
AU - Manuel, João Luis
AU - Napua, Manuel
AU - Pio, Alusio
N1 - Funding Information:
This work was supported by the African Health Initiative of the Doris Duke Charitable Foundation. We would also like to thank the members of the AHI PHIT Partnership Collaborative for their contributions to this manuscript. Members include: Ahmed Hingora, Dominic Mboya, Amon Exavery, Kassimu Tani, Fatuma Manzi, Senga Pemba, James Phillips, Almamy Malick Kante, Kate Ramsey, Colin Baynes, John Koku Awoonor-Williams, Ayaga Bawah, Belinda Afriyie Nimako, Nicholas Kanlisi, Elizabeth F. Jackson, Mallory C. Sheff, Pearl Kyei, Patrick O. Asuming, Adriana Biney, Roma Chilengi, Helen Ayles, Moses Mwanza, Cindy Chirwa, Jeffrey Stringer, Mary Mulenga, Dennis Musatwe, Masoso Chisala, Michael Lemba, Wilbroad Mutale, Peter Drobac, Felix Cyamatare Rwabukwisi, Lisa R. Hirschhorn, Agnes Binagwaho, Neil Gupta, Fulgence Nkikabahizi, Anatole Manzi, Jeanine Condo, Didi Bertrand Farmer, Bethany Hedt-Gauthier, Kenneth Sherr, Fatima Cuembelo, Catherine Michel, Sarah Gimbel, Bradley Wagenaar, Catherine Henley, Marina Kariaganis, João Luis Manuel, Manuel Napua, and Alusio Pio.
Funding Information:
The publication cost of this article was funded by the African Health Initiative of the Doris Duke Charitable Foundation.
Publisher Copyright:
© 2017 The Author(s).
PY - 2017/12/21
Y1 - 2017/12/21
N2 - Background: Well-functioning health systems need to utilize data at all levels, from the provider, to local and national-level decision makers, in order to make evidence-based and needed adjustments to improve the quality of care provided. Over the last 7 years, the Doris Duke Charitable Foundation's African Health Initiative funded health systems strengthening projects at the facility, district, and/or provincial level to improve population health. Increasing data-driven decision making was a common strategy in Mozambique, Rwanda and Zambia. This paper describes the similar and divergent approaches to increase data-driven quality of care improvements (QI) and implementation challenge and opportunities encountered in these three countries. Methods: Eight semi-structured in-depth interviews (IDIs) were administered to program staff working in each country. IDIs for this paper included principal investigators of each project, key program implementers (medically-trained support staff, data managers and statisticians, and country directors), as well as Ministry of Health counterparts. IDI data were collected through field notes; interviews were not audio recorded. Data were analyzed using thematic analysis but no systematic coding was conducted. IDIs were supplemented through donor report abstractions, a structured questionnaire, one-on-one phone calls, and email exchanges with country program leaders to clarify and expand on key themes emerging from IDIs. Results: Project successes ranged from over 450 collaborative action-plans developed, implemented, and evaluated in Mozambique, to an increase from <10% to >80% of basic clinical protocols followed in intervention facilities in rural Zambia, and a shift from a lack of awareness of health data among health system staff to collaborative ownership of data and using data to drive change in Rwanda. Conclusion: Based on common successes across the country experiences, we recommend future data-driven QI interventions begin with data quality assessments to promote that rapid health system improvement is possible, ensure confidence in available data, serve as the first step in data-driven targeted improvements, and improve staff data analysis and visualization skills. Explicit Ministry of Health collaborative engagement can ensure performance review is collaborative and internally-driven rather than viewed as an external "audit."
AB - Background: Well-functioning health systems need to utilize data at all levels, from the provider, to local and national-level decision makers, in order to make evidence-based and needed adjustments to improve the quality of care provided. Over the last 7 years, the Doris Duke Charitable Foundation's African Health Initiative funded health systems strengthening projects at the facility, district, and/or provincial level to improve population health. Increasing data-driven decision making was a common strategy in Mozambique, Rwanda and Zambia. This paper describes the similar and divergent approaches to increase data-driven quality of care improvements (QI) and implementation challenge and opportunities encountered in these three countries. Methods: Eight semi-structured in-depth interviews (IDIs) were administered to program staff working in each country. IDIs for this paper included principal investigators of each project, key program implementers (medically-trained support staff, data managers and statisticians, and country directors), as well as Ministry of Health counterparts. IDI data were collected through field notes; interviews were not audio recorded. Data were analyzed using thematic analysis but no systematic coding was conducted. IDIs were supplemented through donor report abstractions, a structured questionnaire, one-on-one phone calls, and email exchanges with country program leaders to clarify and expand on key themes emerging from IDIs. Results: Project successes ranged from over 450 collaborative action-plans developed, implemented, and evaluated in Mozambique, to an increase from <10% to >80% of basic clinical protocols followed in intervention facilities in rural Zambia, and a shift from a lack of awareness of health data among health system staff to collaborative ownership of data and using data to drive change in Rwanda. Conclusion: Based on common successes across the country experiences, we recommend future data-driven QI interventions begin with data quality assessments to promote that rapid health system improvement is possible, ensure confidence in available data, serve as the first step in data-driven targeted improvements, and improve staff data analysis and visualization skills. Explicit Ministry of Health collaborative engagement can ensure performance review is collaborative and internally-driven rather than viewed as an external "audit."
KW - Data assessment
KW - Decision making
KW - Health systems research
KW - Health systems strengthening
KW - Low income
KW - Maternal and child health
KW - Mozambique
KW - Quality improvement
KW - Rwanda
KW - Zambia
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U2 - 10.1186/s12913-017-2661-x
DO - 10.1186/s12913-017-2661-x
M3 - Article
C2 - 29297319
AN - SCOPUS:85039054013
SN - 1472-6963
VL - 17
JO - BMC health services research
JF - BMC health services research
M1 - 830
ER -