Maternal and Child Health Journal

, Volume 23, Issue 10, pp 1327–1338 | Cite as

Integrating Community Health Worker Roles to Improve Facility Delivery Utilization in Tanzania: Evidence from an Interrupted Time Series Analysis

  • Katharine D. ShelleyEmail author
  • Rose Mpembeni
  • Gasto Frumence
  • Elizabeth A. Stuart
  • Japhet Killewo
  • Abdullah H. Baqui
  • David H. Peters



Despite renewed interest in expansion of multi-tasked community health workers (CHWs) there is limited research on HIV and maternal health integration at the community-level. This study assessed the impact of integrating CHW roles for HIV and maternal health promotion on facility delivery utilization in rural Tanzania.


A 36-month time series data set (2014–2016) of reported facility deliveries from 68 health facilities in two districts of Tanzania was constructed. Interrupted time series analyses evaluated population-averaged longitudinal trends in facility delivery at intervention and comparison facilities. Analyses were stratified by district, controlling for secular trends, seasonality, and type of facility.


There was no significant change from baseline in the average number of facility deliveries observed at intervention health centers/dispensaries relative to comparison sites. However, there was a significant 16% increase (p < 0.001) in average monthly deliveries in hospitals, from an average of 202–234 in Iringa Rural and from 167 to 194 in Kilolo. While total facility deliveries were relatively stable over time at the district-level, during intervention the relative change in the proportion of hospital deliveries out of total facility deliveries increased by 17.2% in Iringa Rural (p < 0.001) and 14.7% in Kilolo (p < 0.001).

Conclusions for Practice

Results suggest community-delivered outreach by dual role CHWs was successful at mobilizing pregnant women to deliver at facilities and may be effective at reaching previously under-served pregnant women. More research is necessary to understand the effect of dual role CHWs on patterns of service utilization, including decisions to use referral level facilities for obstetric care.


Bypassing Community health worker Interrupted time series Facility delivery Maternal child health services Segmented regression Tanzania 



This work was funded by the United States Agency for International Development (USAID) through the Health Research Challenge for Impact (HRCI) Cooperative Agreement [#GHS-A-00-09-00004-00] with the Johns Hopkins Bloomberg School of Public Health (JHSPH). The contents are the responsibility of the authors and do not necessarily reflect the views of USAID or the United States Government. The Community Health Worker Learning Agenda Project (CHW-LAP) was a multiyear implementation research partnership between JHSPH in the USA and Muhimbili University of Health and Allied Sciences (MUHAS) in Tanzania, within which we embedded the present research. Our thanks and remembrance to the late Helen Semu, Assistant Director of Health Promotion in the Ministry of Health, Community Development, Gender, Elderly and Children (MoHCDGEC) for her guidance and support throughout CHW-LAP. Thanks to the Iringa Regional Medical Office and the Iringa Rural and Kilolo District Health Management Teams for facilitation of our data collection plans and overall interest in the research. Collaboration with Deloitte Limited Consulting and Christian Social Services Commission, implementers of TUNAJALI II, was instrumental to this research—they provided numerous insights on their program design and approach, in addition to access to their local civil society organization partners who were essential to facilitating the data collection. Our special thanks for the work of our data collection team: Ismail Amiri, Bernadetha Hubert, Emmanuel Maawe, Christina Maluli, Debora Mlambo, Hereswida Monyiechi, Maurus Mpunga, Annobeatrice Mville, and Zaina Sheweji. We also thank several CHW-LAP staff, including Juliana Joachim who helped coordinate the initial round of data collection, Patrick Kazonda who oversaw survey data entry, and Aisha Omary and Mary Glory Emmanuel who provided administrative support. Special thanks also to Priscia Wanjiro of MoHCDGEC for serving as our government liaison during data collection in Iringa. Thank you also to Dr. Asha George for mentorship and guidance throughout the project; Dr. Kadia Petricca for early input on the study design; and Dr. Ashley Sheffel for design of an electronic interface for tablet data entry.

Authors’ Contribution

AB and JK are the Principal Investigators of the overarching evaluation within which we designed and collected data for this study. As part of her PhD dissertation, KS designed the protocol and developed data collection instruments with inputs from all authors. KS, GF and RM coordinated and oversaw data collection and management. KS conducted quantitative analyses, with guidance from DP, ES, and AB on interpretation and presentation of results. KS wrote the first draft of the paper, with revision and inputs from all authors. All authors read and approved the final manuscript.

Compliance with Ethical Standards

Ethical Approval

The study was jointly approved for ethical clearance by the Institutional Review Boards of Johns Hopkins School of Public Health in Baltimore, Maryland (IRB No. 00005497) and Muhimbili University of Health and Allied Sciences in Dar es Salaam, Tanzania (Ref. No. 2015-12-18/AEC/Vol. X/94).

Supplementary material

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Supplementary material 1 (PDF 1408 kb)


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of International HealthJohns Hopkins Bloomberg School of Public HealthBaltimoreUSA
  2. 2.Department of Epidemiology and Biostatistics, School of Public Health and Social SciencesMuhimbili University of Health and Allied SciencesDar Es SalaamTanzania
  3. 3.Department of Development Studies, School of Public Health and Social SciencesMuhimbili University of Health and Allied SciencesDar Es SalaamTanzania
  4. 4.Department of Mental Health, Department of Biostatistics, Department of Health Policy and ManagementJohns Hopkins Bloomberg School of Public HealthBaltimoreUSA

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