Data-driven quality improvement in low-and middle-income country health systems: Lessons from seven years of implementation experience across Mozambique, Rwanda, and Zambia

Bradley H. Wagenaar, Lisa R. Hirschhorn, Catherine Henley, Artur Gremu, Ntazana Sindano, Roma Chilengi, 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 KanlisiElizabeth F. Jackson, Mallory C. Sheff, Pearl Kyei, Patrick O. Asuming, Adriana Biney, Helen Ayles, Moses Mwanza, Cindy Chirwa, Jeffrey Stringer, Mary Mulenga, Dennis Musatwe, Masoso Chisala, Michael Lemba, Wilbroad Mutale, Peter Drobac, Felix Cyamatare Rwabukwisi, Agnes Binagwaho, Neil Gupta, Fulgence Nkikabahizi, Anatole Manzi, Jeanine Condo, Didi Bertrand Farmer, Bethany Hedt-Gauthier, Kenneth Sherr, Fatima Cuembelo, Catherine Michel, Sarah Gimbel, Marina Kariaganis, João Luis Manuel, Manuel Napua, Alusio Pio

Research output: Contribution to journalArticle

Abstract

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."

Original languageEnglish (US)
Article number830
JournalBMC Health Services Research
Volume17
DOIs
StatePublished - Dec 21 2017

Fingerprint

Rwanda
Mozambique
Zambia
Quality Improvement
Health
Interviews
Quality of Health Care
Social Adjustment
Data Accuracy
Ownership
Clinical Protocols
Decision Making
Research Personnel

Keywords

  • Data assessment
  • Decision making
  • Health systems research
  • Health systems strengthening
  • Low income
  • Maternal and child health
  • Mozambique
  • Quality improvement
  • Rwanda
  • Zambia

ASJC Scopus subject areas

  • Health Policy

Cite this

Data-driven quality improvement in low-and middle-income country health systems : Lessons from seven years of implementation experience across Mozambique, Rwanda, and Zambia. / Wagenaar, Bradley H.; Hirschhorn, Lisa R.; Henley, Catherine; Gremu, Artur; Sindano, Ntazana; Chilengi, Roma; Hingora, Ahmed; Mboya, Dominic; Exavery, Amon; Tani, Kassimu; Manzi, Fatuma; Pemba, Senga; Phillips, James; Kante, Almamy Malick; Ramsey, Kate; Baynes, Colin; Awoonor-Williams, John Koku; Bawah, Ayaga; Nimako, Belinda Afriyie; Kanlisi, Nicholas; Jackson, Elizabeth F.; Sheff, Mallory C.; Kyei, Pearl; Asuming, Patrick O.; Biney, Adriana; Ayles, Helen; Mwanza, Moses; Chirwa, Cindy; Stringer, Jeffrey; Mulenga, Mary; Musatwe, Dennis; Chisala, Masoso; Lemba, Michael; Mutale, Wilbroad; Drobac, Peter; Rwabukwisi, Felix Cyamatare; Binagwaho, Agnes; Gupta, Neil; Nkikabahizi, Fulgence; Manzi, Anatole; Condo, Jeanine; Farmer, Didi Bertrand; Hedt-Gauthier, Bethany; Sherr, Kenneth; Cuembelo, Fatima; Michel, Catherine; Gimbel, Sarah; Kariaganis, Marina; Manuel, João Luis; Napua, Manuel; Pio, Alusio.

In: BMC Health Services Research, Vol. 17, 830, 21.12.2017.

Research output: Contribution to journalArticle

Wagenaar, BH, Hirschhorn, LR, Henley, C, Gremu, A, Sindano, N, Chilengi, R, Hingora, A, Mboya, D, Exavery, A, Tani, K, Manzi, F, Pemba, S, Phillips, J, Kante, AM, Ramsey, K, Baynes, C, Awoonor-Williams, JK, Bawah, A, Nimako, BA, Kanlisi, N, Jackson, EF, Sheff, MC, Kyei, P, Asuming, PO, Biney, A, Ayles, H, Mwanza, M, Chirwa, C, Stringer, J, Mulenga, M, Musatwe, D, Chisala, M, Lemba, M, Mutale, W, Drobac, P, Rwabukwisi, FC, Binagwaho, A, Gupta, N, Nkikabahizi, F, Manzi, A, Condo, J, Farmer, DB, Hedt-Gauthier, B, Sherr, K, Cuembelo, F, Michel, C, Gimbel, S, Kariaganis, M, Manuel, JL, Napua, M & Pio, A 2017, 'Data-driven quality improvement in low-and middle-income country health systems: Lessons from seven years of implementation experience across Mozambique, Rwanda, and Zambia', BMC Health Services Research, vol. 17, 830. https://doi.org/10.1186/s12913-017-2661-x
Wagenaar, Bradley H. ; Hirschhorn, Lisa R. ; Henley, Catherine ; Gremu, Artur ; Sindano, Ntazana ; Chilengi, Roma ; Hingora, Ahmed ; Mboya, Dominic ; Exavery, Amon ; Tani, Kassimu ; Manzi, Fatuma ; Pemba, Senga ; Phillips, James ; Kante, Almamy Malick ; Ramsey, Kate ; Baynes, Colin ; Awoonor-Williams, John Koku ; Bawah, Ayaga ; Nimako, Belinda Afriyie ; Kanlisi, Nicholas ; Jackson, Elizabeth F. ; Sheff, Mallory C. ; Kyei, Pearl ; Asuming, Patrick O. ; Biney, Adriana ; Ayles, Helen ; Mwanza, Moses ; Chirwa, Cindy ; Stringer, Jeffrey ; Mulenga, Mary ; Musatwe, Dennis ; Chisala, Masoso ; Lemba, Michael ; Mutale, Wilbroad ; Drobac, Peter ; Rwabukwisi, Felix Cyamatare ; Binagwaho, Agnes ; Gupta, Neil ; Nkikabahizi, Fulgence ; Manzi, Anatole ; Condo, Jeanine ; Farmer, Didi Bertrand ; Hedt-Gauthier, Bethany ; Sherr, Kenneth ; Cuembelo, Fatima ; Michel, Catherine ; Gimbel, Sarah ; Kariaganis, Marina ; Manuel, João Luis ; Napua, Manuel ; Pio, Alusio. / Data-driven quality improvement in low-and middle-income country health systems : Lessons from seven years of implementation experience across Mozambique, Rwanda, and Zambia. In: BMC Health Services Research. 2017 ; Vol. 17.
@article{3558226fd37940aaaa7891a597aa8e87,
title = "Data-driven quality improvement in low-and middle-income country health systems: Lessons from seven years of implementation experience across Mozambique, Rwanda, and Zambia",
abstract = "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.{"}",
keywords = "Data assessment, Decision making, Health systems research, Health systems strengthening, Low income, Maternal and child health, Mozambique, Quality improvement, Rwanda, Zambia",
author = "Wagenaar, {Bradley H.} and Hirschhorn, {Lisa R.} and Catherine Henley and Artur Gremu and Ntazana Sindano and Roma Chilengi and Ahmed Hingora and Dominic Mboya and Amon Exavery and Kassimu Tani and Fatuma Manzi and Senga Pemba and James Phillips and Kante, {Almamy Malick} and Kate Ramsey and Colin Baynes and Awoonor-Williams, {John Koku} and Ayaga Bawah and Nimako, {Belinda Afriyie} and Nicholas Kanlisi and Jackson, {Elizabeth F.} and Sheff, {Mallory C.} and Pearl Kyei and Asuming, {Patrick O.} and Adriana Biney and Helen Ayles and Moses Mwanza and Cindy Chirwa and Jeffrey Stringer and Mary Mulenga and Dennis Musatwe and Masoso Chisala and Michael Lemba and Wilbroad Mutale and Peter Drobac and Rwabukwisi, {Felix Cyamatare} and Agnes Binagwaho and Neil Gupta and Fulgence Nkikabahizi and Anatole Manzi and Jeanine Condo and Farmer, {Didi Bertrand} and Bethany Hedt-Gauthier and Kenneth Sherr and Fatima Cuembelo and Catherine Michel and Sarah Gimbel and Marina Kariaganis and Manuel, {Jo{\~a}o Luis} and Manuel Napua and Alusio Pio",
year = "2017",
month = "12",
day = "21",
doi = "10.1186/s12913-017-2661-x",
language = "English (US)",
volume = "17",
journal = "BMC Health Services Research",
issn = "1472-6963",
publisher = "BioMed Central",

}

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

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

UR - http://www.scopus.com/inward/record.url?scp=85039054013&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85039054013&partnerID=8YFLogxK

U2 - 10.1186/s12913-017-2661-x

DO - 10.1186/s12913-017-2661-x

M3 - Article

C2 - 29297319

AN - SCOPUS:85039054013

VL - 17

JO - BMC Health Services Research

JF - BMC Health Services Research

SN - 1472-6963

M1 - 830

ER -