Maternal Health Clinical Trial
Official title:
Increasing Equitable Access to Safe Deliveries in Zambia
Objectives: The primary objective of this evaluation is to determine if well-constructed and
well-resourced Maternity Waiting Homes are utilized by pregnant women living at distance from
the health facility and are associated with improved pregnancy outcomes, particularly for
women living farthest from health facilities. Findings from this evaluation will be provided
to policymakers formulating policy decisions affecting the implementation of the Maternity
Home Model and, if applicable, will be used as evidence for programmatic decisions made by
the Ministry in deciding to take this model to scale beyond the districts proposed for this
project.
Primary Impact Evaluation Question: Does the Minimum Core Maternity Home Model increase
access to high quality intrapartum care among mothers living more than 10 km from the
facilities compared to the standard of care?
Study Design: We propose a quasi-experimental pre-post design wherein one implementing
partner (BU/ZCAHRD) will use a cluster-randomized matched pair design and one implementing
partner (University of Michigan/Africare) will utilize a matched-pair, two-group comparison
design with no randomization.
Methods: Using mixed-methods, we will collect data from two main sources: 1) Household
Surveys and 2) In-depth Interviews. A quantitative household survey will be conducted among
2,400 randomly-selected households at both baseline (2015) and endline (2018) among recently
delivered women (delivered in the last 12 months) living more than 10 km from the
intervention and comparison facilities.
15% of the households enrolled in the study will be randomly selected to participate in an
In-Depth Interview (IDI). Content will include perceptions of labor and delivery practices,
barriers to accessing care, knowledge and awareness of MSs, perceptions of the quality of MS,
perceptions of respectful care at the facility, post-natal care, costs, and perceptions of MS
ownership.
BACKGROUND: Although Zambia's maternal mortality rate has decreased from 591 maternal deaths
per 100,000 live births since 2007 (2007 Zambia DHS), the maternal mortality rate in 2014 was
unacceptably high at 398 maternal deaths per 100,000 live births. The WHO strongly recommends
'skilled care at every birth' as a strategy to reduce maternal deaths. However, it remains
unanswered how to best deliver high-quality birth and postpartum care, particularly in rural
and remote areas where distance and poor transportation services severely restrict access to
care.
The Government of the Republic of Zambia (GRZ) is committed to improving maternal health and
has initiated a large cooperative effort that aims to do so through the Ministry of Health
(MOH), Ministry of Community Development, Mother and Child Health (MCDMCH), and several local
and international organizations. Within this context, MHs-temporary lodgings located near
health facilities with skilled care for pregnant mothers who are close to term-represent a
potentially useful strategy to improve access to skilled obstetric care, particularly for
those living farthest from the health facilities. MHs provide pregnant women with the option
of planning ahead and traveling to health facilities well before labor begins, and have
existed in various forms since the 1950s. However, there is insufficient evidence of the
effectiveness of MHs in improving access to delivery services and improving maternal
outcomes. While some evidence suggests MH utilization is correlated with improved maternal
health outcomes (Gaym, Lori), a Cochrane review found no randomized, quasi-randomized or
cluster-randomized trials assessing the effectiveness of MHs in low resource settings (van
Lonkhuijzen L). Rigorous evidence on the impacts of MHs on maternal and perinatal health
outcomes is needed.
The Maternity Homes Alliance (MHA) - a partnership between GRZ and implementing partners
working in collaboration with academic institutions, and evaluation advisor, - seek to help
women overcome the "distance problem" by implementing MHs, with the hypothesis that offering
women access to quality MHs will bring women closer to facility-based delivery and postpartum
care, ultimately improving health outcomes. If systematically implemented on a large scale
with optimal maintenance, management and community acceptability and utilization, MHs have
the potential to remove the distance barrier and increase access to safe delivery for women
living farthest from the health facilities.
INTERVENTION: This project will implement high quality MHs in Southern, Eastern and Luapula
Provinces in an effort to increase access to quality intrapartum care among the most
vulnerable women. Following a formative evaluation that found that MHs could be an acceptable
option to improve access to safe deliveries in rural Zambia, in-country partners, ZCAHRD and
Africare, will implement a Core Maternity Home Intervention Model in 10 sites each, totaling
20 intervention sites.
OBJECTIVES: The main objective of the evaluation is to understand if MHs can effectively
increase access to safe delivery, particularly for women living farthest from health
facilities. Findings from this evaluation will be used to inform program decisions regarding
implementation of the Maternity Home Model and, if applicable, to advocate for programmatic
improvements as the Maternity Home Model is taken to scale beyond the districts proposed for
this project.
Primary question:
1. Does the Minimum Core Maternity Home Model increase the number of facility deliveries
among mothers living more than 10 km from the facilities compared to facilities with no
improved maternity home services?
Secondary questions:
1. To what degree does the Minimum Core Maternity Home Model change maternal and neonatal
health outcomes among those living more than 10 km from the facility compared to the
standard of care?
2. How does the awareness and perceptions of MHs by communities located more than 10 km
from the health facility change over the period of this study?
3. How does awareness and perceptions of HF associated safe delivery and HF delivery
intention among pregnant women living in communities located more than 10 km from the
health facility change over time?
4. What is the financial impact that use of the MH has on the families of women who utilize
it compared to women who do not utilize it?
5. How does the perception of quality of care differ between intervention and comparison
sites?
STUDY DESIGN: This is a quasi-experimental pre-post design wherein one implementing partner
(BU/ZCAHRD) will use a cluster-randomized matched-pair design and one implementing partner
(University of Michigan/Africare) will utilize a non-randomized matched-pair, comparison
design. The framework of the study design is shown below:
Table 2: Quasi-experimental Study Design to Evaluate the Impact of MHs
BU/ZCAHRD UMich/Africare Overall R O1 X O2 NR O1 X O2 NR O1 X O2 R O1 _ O2 NR O1 _ O2 NR O1 _
O2 X = Minimum Core Maternity Home (see above) O = Observations at baseline (O1, in 2016) and
endline (O2, in 2018) at intervention (X) and comparison (_) sites. R = cluster randomized;
NR = not randomized.
Data will be pooled for analysis but sample sizes provide sufficient power to separately
analyze the BU/ZCAHRD and UMich/Africare sites.
DATA SOURCES: We will collect data from two main sources:
1. Household Surveys
2. In-depth Interviews
Household Survey (O1, O2): A quantitative household survey will be conducted at baseline
(2016) and endline (2018) among women who have delivered in the last 12 months) living more
than 10 km from the intervention and comparison facilities. This approach will capture the
experiences of those who utilized the facility in their catchment, other facilities, and
those did who not access a facility for delivery, allowing us to more accurately estimate the
impact of the MH intervention.
In-depth Interviews (IDI) (O1, O2): IDIs will be conducted among a sample of respondents
identified for the household survey to gain a deeper understanding of community perceptions.
Content will include perceptions of labor and delivery practices, barriers to accessing care,
knowledge and awareness of MHs, perceptions of the quality of maternity homes, perceptions of
respectful care at the facility, post-natal care, costs, and perceptions of MH ownership.
STUDY SITES: Selection and Randomization BU/ZCAHRD will select the 20 sites or 10 pairs
matched on transfer time to CEmONC and clinic delivery volume. Pairs were randomized into the
intervention group and control groups, yielding 10 intervention and 10 control sites.
UMich/Africare will purposively select 10 intervention sites and identify 10 comparison
sites, matched on transfer time to CEmONC and clinic volume. This totals 20 intervention and
20 comparison sites across the Alliance. The unit of randomization (for BU/ZCAHRD) and
matching (both partners) is the facility and its catchment area.
SAMPLING STRATEGY: We will employ multi-stage random sampling. First, we will randomly select
a sample of 10 clusters (villages within the catchment area more than 10k from facility) from
each study catchment area with probability proportionate to population size. Second, we will
list all households within the selected villages, randomly order them, visit each in that
order and screen for eligibility, continuing down the list until the nth eligible household
in each village is identified. Third, we will randomly select, if applicable, one eligible
woman from each household.
FOLLOW UP: At each observation point (O1 and O2) we will select a new cross-sectional sample
using the same methodology. Therefore, households will not be followed up over time.
DATA QUALITY CONTROL STRATEGY: For quality control, first, enumerators will participate in a
5-day training. Second, enumerators will be overseen by experienced supervisors. These
individuals will review surveys for quality nightly. Third, supervisors will randomly select
a 5% subsample of households for each of the enumerators they oversee and revisit these
households to re-conduct a subset of survey questions. Data collected by supervisors will be
compared to data originally collected by enumerators to check reliability. Fourth, data will
be uploaded and transferred nightly to the data analysis team in Boston (see Data Entry and
Storage section below) and the analysis team will review in real time for consistency and
quality.
DATA ENTRY AND STORAGE: Survey data will be captured on the tablets and saved to the tablets'
internal memory. Each evening, a supervisor will review and encrypt surveys, then upload the
surveys nightly to a secure server administered by SurveyCTO. The project team will download
the encrypted data using the SurveyCTO Client software, and decrypt the data using a
decryption key generated by the BU/ZCAHRD team themselves.
The project staff will oversee data entry, management, and storage for qualitative data. All
qualitative data will be translated into English and transcribed within 1 month of being
collected. Digital recorders and paper copies of qualitative notes will be kept in a locked
cabinet until they are fully translated and transcribed, at which point audio files will be
deleted and notes shredded. The electronic transcriptions will be kept in a
password-protected file. The qualitative transcriptions will not contain identifying
information, only a study id number. Only the study team will have access to identifiable
quantitative and qualitative data.
SAMPLE SIZE: We will recruit 2,400 women into the survey, 1,200 from each study group per
round for a study sample of 4,800 households plus 50 pilots at each round. After accounting
for the clustered sampling design (ICC estimated at 0.04 based on previous work), and
assuming an alpha of .05, this sample will provide us with 80% power to detect a minimum of
10 percentage point difference in the anticipated impact of the MH intervention on the
primary outcome of facility delivery.
For the IDIs, we estimate a sample of 360 at baseline and endline, but will stop if we reach
saturation or predictability before the full 360.
DATA ANALYSIS: All quantitative analyses will be conducted in SAS version 9.4 (SAS Institute,
Cary, NC). Our quantitative analytic plan is threefold, yielding descriptive, bivariate and
multivariate statistics. First, we will begin with a descriptive analysis of the sample for
the household level characteristics and respondent level demographics.
Second, we will also look for differences in outcomes within the matched pairs. Categorical
variables will be compared between intervention and control groups using the chi-squared test
if cell sizes are sufficient or Fisher's exact test if cell sizes are small; continuous
variables will be compared using t-tests if normally distributed or non-parametric Wilcoxon
rank sum tests if distribution is non-normal.
Third, we will calculate crude and adjusted logistic or linear regression models depending on
the outcome variable. We will calculate the relative risk or odds ratios comparing the
intervention to control arms, adjusting for any imbalanced covariates.
All qualitative data will be analyzed in Nvivo 10 © (Doncaster, Australia). We will conduct a
content analysis of the in-depth interview transcripts. Coding themes have been identified a
priori according to the outline of the interview guide. Additional themes will be included if
they emerge during analysis. We will triangulate findings with the quantitative data to
identify consistencies, inconsistencies or additional themes to be explored.
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