Introduction In the era of Sustainable Development Goals, reducing maternal and neonatal mortality is a priority. With one of the highest maternal mortality ratios in the world, Malawi has a significant opportunity for improvement. One effort to improve maternal outcomes involves increasing access to high-quality health facilities for delivery. This study aimed to determine the role that quality plays in women’s choice of delivery facility.
Methods A revealed-preference latent class analysis was performed with data from 6625 facility births among women in Malawi from 2013 to 2014. Responses were weighted for national representativeness, and model structure and class number were selected using the Bayesian information criterion.
Results Two classes of preferences exist for pregnant women in Malawi. Most of the population 65.85% (95% CI 65.847% to 65.853%) prefer closer facilities that do not charge fees. The remaining third (34.15%, 95% CI 34.147% to 34.153%) prefers central hospitals, facilities with higher basic obstetric readiness scores and locations further from home. Women in this class are more likely to be older, literate, educated and wealthier than the majority of women.
Conclusion For only one-third of pregnant Malawian women, structural quality of care, as measured by basic obstetric readiness score, factored into their choice of facility for delivery. Most women instead prioritise closer care and care without fees. Interventions designed to increase access to high-quality care in Malawi will need to take education, distance, fees and facility type into account, as structural quality alone is not predictive of facility type selection in this population.
- health systems
- health services research
- maternal health
- public health
- latent class analysis
This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.
Statistics from Altmetric.com
RRY and KRI are joint first authors.
Handling editor Valery Ridde
Twitter Rachel Yorlets: @RachelYorlets
Hannah Leslie: @H2Leslie
Anna Gage: @agage93
Sanam Roder-DeWan: @SanamRoderDeWan
Humphreys Nsona: @hnsona1
Mark Shrime: @markshrime
Contributors RRY and KRI performed the literature search, cocreated the latent class model, analysed and interpreted the data, and cowrote methods and results. RRY wrote the discussion, created tables 1, 4 and 5, performed the sensitivity analyses, calculated entropy and cocreated appendix table 1 with HHL. KRI wrote the introduction, created figure 1, table 2 and table 3. HHL and ADG prepared the dataset for analysis. HHL, ADG and SR-D provided revisions on the manuscript. HHL and SR-D contributed to the literature search. HN provided the original dataset, contributed to the literature search, provided local context and revised the manuscript. SR-D and MGS contributed to the conception of the study and the study design. MGS cocreated the latent class model, created the random effects model, contributed to data analysis and interpretation, created appendix figure 1 and appendix table 2 and provided revisions on the manuscript. All authors reviewed and approved the final version of the manuscript.
Funding This study was funded in part by the Bill & Melinda Gates Foundation (Grant #OPP1161450).
Disclaimer The study of funding had no role in the study design, the collection, analysis, and interpretation of data, or in the writing of or decision to submit the manuscript for publication.
Competing interests MGS has grant funding from Mercy Ships and the Damon Runyon Cancer Research Foundation (Grant #CA91-17).
Patient consent for publication Not required.
Ethics approval Because this was an analysis on previously collected data, the Harvard T.H. Chan School of Public Health deemed this secondary analysis exempt from human subject review.
Provenance and peer review Not commissioned; externally peer reviewed.
Data sharing statement Data are publicly accessible from the Malawi Millennium Endline Survey and the Malawi Service Provision Assessment, both from 2013 to 2014.
If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.