metadata: authors: 0: author: Gopalan,Saji Saraswathy
1: author: Mohammed-Roberts,Rianna L.
2: author: Zanetti Matarazzo,Hellen Chrystine
count: Bangladesh
docna: 0: docna: Drivers of Utilization, Quality of Care, and
            RMNCH-N Services in Bangladesh : A Comparative Analysis of
            Demand and Supply-Side Determinants Using Machine Learning
            for Investment Decision-Making
docty: Policy Research Working Paper
subtopic: Health Care Services Industry,Nutrition,Educational Sciences,Pharmaceuticals Industry,Pharmaceuticals & Pharmacoeconomics
teratopic: Education,Industry,Health, Nutrition and Population
abstracts: cdata!: Amid noticeable improvements and
            achievements in the reproductive, maternal, neonatal, child
            health, and nutrition landscape in Bangladesh, existing
            evidence suggests that further accelerated progress hinges
            on strategic investment decision making. Addressing the top
            service utilization determinants that are both context- and
            time-specific is one cost-effective way of improving the
            unmet reproductive, maternal, neonatal, child health, and
            nutrition outcomes in a short timeframe. Against this
            backdrop, using machine learning analysis, the overall aim
            of this study was to help Bangladesh identify priority
            investment areas that could accelerate reproductive,
            maternal, neonatal, child health, and nutrition utilization,
            quality, and outcomes over the short run, by comparing the
            relative importance of demand- and-supply-side determinants
            of key reproductive, maternal, neonatal, child health, and
            nutrition indicators over the past decade (across two time
            points). Two rounds of the Bangladesh Health Facility Survey
            and the Demographic and Health Survey (2014 and 2017) were
            analyzed. The findings indicate that the relative importance
            of the demand-side determinants (except wealth and education
            status) have recently declined. Conversely, investments in
            key supply-side determinants (for example, availability of
            skilled staff, readiness for care, and quality of care)
            could provide a thrust toward further increases in
            utilization. Immediate attention is needed to address the
            regressive role of wealth status on utilization through, for
            example, demand-side financing that goes beyond user fee
            exemptions. Further, developing strategies to improve the
            engagement of community health workers in reproductive,
            maternal, neonatal, child health, and nutrition utilization
            and tapping into the potential of mobile health technology
            to support community health workers’ performance and women’s
            awareness could help to boost utilization patterns.
geo_reg_key: 517198,517212,517191
repnme: repnme: Drivers of Utilization, Quality of Care,
            and RMNCH-N Services in Bangladesh : A Comparative Analysis
            of Demand and Supply-Side Determinants Using Machine
            Learning for Investment Decision-Making
display_title: Drivers of Utilization, Quality of
            Care, and RMNCH-N Services in Bangladesh : A Comparative
            Analysis of Demand and Supply-Side Determinants Using
            Machine Learning for Investment Decision-Making
listing_relative_url: /research/2021/09/33440165/drivers-utilization-quality-care-rmnch-n-services-bangladesh-comparative-analysis-demand-supply-side-determinants-using-machine-learning-investment-decision-making
topicv3: Nutrition m1326779 644,Education m1327048 470,Sexual Reproductive, Maternal and Child
            Health m1327262 639,Pharmaceuticals m1327740 1350,Health m1504661 3480
publishtoextweb_dt: 2021-09-24T00:00:00Z
dois: 10.1596/1813-9450-9783
historic_topic: Education,Industry,Health, Nutrition and Population
origu: Health Nutri & Population SAR 2 (HSAHP)
no_of_pages: 34
author_keys: 0: author_key: 1225061
1: author_key: 915919
2: author_key: 1629325
model_extractions: Policy Research Working Paper 9783 Drivers of Utilization, Quality of Care, and RMNCH-N Services in Bangladesh A Comparative Analysis of Demand and Supply-Side Determinants Using Machine Learning for Investment Decision-Making _Saji Gopalan Rianna Mohammed-Roberts Hellen Chrystine Zanetti Matarazzo_ Health, Nutrition and Population Global Practice September 2021
Policy Research Working Paper 9783

# **Abstract**

Amid noticeable improvements and achievements in the reproductive, maternal, neonatal, child health, and nutrition landscape in Bangladesh, existing evidence suggests that further accelerated progress hinges on strategic investment decision making. Addressing the top service utilization determinants that are both context- and time-specific is one cost-effective way of improving the unmet reproductive, maternal, neonatal, child health, and nutrition outcomes in a short timeframe. Against this backdrop, using machine learning analysis, the overall aim of this study was to help Bangladesh identify priority investment areas that could accelerate reproductive, maternal, neonatal, child health, and nutrition utilization, quality, and outcomes over the short run, by comparing the relative importance of demand- and-supply-side determinants of key reproductive, maternal, neonatal, child health, and nutrition indicators over the past decade (across two time points). Two rounds of the Bangladesh Health Facility Survey and the Demographic and Health Survey (2014 and 2017) were analyzed. The findings indicate that the relative importance of the demand-side determinants (except wealth and education status) have recently declined. Conversely, investments in key supply-side determinants (for example, availability of skilled staff, readiness for care, and quality of care) could provide a thrust toward further increases in utilization. Immediate attention is needed to address the regressive role of wealth status on utilization through, for example, demand-side financing that goes beyond user fee exemptions. Further, developing strategies to improve the engagement of community health workers in reproductive, maternal, neonatal, child health, and nutrition utilization and tapping into the potential of mobile health technology to support community health workers’ performance and women’s awareness could help to boost utilization patterns.

This paper is a product of the Health, Nutrition and Population Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at sajisaraswathyg@gmail.com, rmohammed@worldbank.org, and hzmatarazarro@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
Drivers of Utilization, Quality of Care, and RMNCH-N Services in Bangladesh A comparative analysis of demand and supply-side determinants using machine learning for investment decision-making _Saji Gopalan Rianna Mohammed-Roberts Hellen Chrystine Zanetti Matarazzo_

**JEL:** I10, I12, I14, I19

**Keywords:** maternal and child health, family planning, nutrition, utilization determinants, investment decision-making, machine learning, Bangladesh

# **Acknowledgments**

This paper was prepared by a World Bank team led by Rianna Mohammed-Roberts (Senior Health Specialist), Saji Gopalan (Senior Economist Consultant), and Hellen Chrystine Zanetti Matarazzo (Data Scientist Consultant), under the overall supervision of E. Gail Richardson (Practice Manager). Insightful comments, suggestions and guidance are gratefully acknowledged from <mark>Mersedeh Tariverdi</mark> (Senior Data Scientist), Manuela Villar Uribe (Health Specialist) and Asib Nasim (Senior Health Specialist Consultant). Any errors or omissions are entirely the responsibility of the authors.
# **1. Introduction**

## **1.1    Why is investing in priority determinants important for RMNCH-N utilization and outcomes in low- and middle-income countries?**

Globally, the performance trajectory of countries in improving reproductive, maternal, neonatal, child health, and nutrition (RMNCH-N) outcomes over the last few decades highlights a number of exemplary pathways.<sup>1–5</sup> First, global evidence shows that timely and appropriate RMNCH-N service utilization is the foremost key to improving the RMNCH-N outcomes.<sup>5</sup> Specifically, countries that invested in enhancing utilization have achieved further improvements in RMNCH-N outcomes. A second pivotal step in improving RMNCH-N service utilization is by addressing its determinants. Third, both the demand- and supply-side determinants are equally relevant in boosting RMNCH-N service utilization in a timely manner. The relative importance of the various determinants, however, changes at different phases of the progress trajectory. Fourth, the determinants of RMNCH-N service utilization and outcomes are context-specific (i.e., country or region-specific) and time-specific.<sup>1</sup> For instance, certain demand-side determinants (e.g., cultural factors) are more dominant in the early stages of progress and sometimes, new determinants may arise (e.g., mass media influence). However, it is difficult to predict the role and magnitude of such determinants unless they are regularly assessed. Fifth, global evidence shows that countries can make more rapid progress when they make specific investments in priority determinants of RMNCH-N service utilization, rather than relying on generic strategies and interventions. For example, a recent global assessment has shown that interventions specifically addressing the priority (i.e., context and time-specific) RMNCH-N service determinants could reduce the fertility rate to 2.5 in certain Asian settings compared to generic interventions.<sup>1</sup> Another <mark>study of diarrhea and pneumonia interventions observed that 15 highly costeffective interventions addressing the top RMNCH-N service utilization determinants – if implemented at scale – would prevent 95 percent of deaths from diarrhea and 67 percent of deaths from pneumonia in under-5 children by 2025.</mark><sup>6</sup> <mark>S</mark> uch specific interventions addressing priority utilization determinants are also proven to be cost effective in improving the RMNCH-N outcomes in a short timeframe. In summary, the existing evidence shows that regular tracking, coupled with prioritized investments in context-specific utilization determinants, can improve RMNCH-N service utilization.

## **1.2 Reproductive, maternal, child health, and nutrition landscape in Bangladesh**

Bangladesh has witnessed significant improvements across key maternal, child health and nutrition indicators over the last few years, with multi-faceted and sector-wide approaches to improving the health of pregnant women and under-five children.<sup>7</sup> Changing fertility behavior, and increased access to and utilization of health services, for example, have been major contributors to the consistent decline in underfive and maternal mortalities.<sup>8</sup> Notwithstanding progress, however, Bangladesh is still far away from reaching a key Sustainable Development Goal (SDG) – “maternal mortality ratio target is 70 deaths per 100,000 live births” (currently at 165).<sup>8</sup> The uptake of certain key maternal and child health (MCH) services has been consistently sub-optimal. For instance, institutional deliveries are only 50% and skilled birth attendance is at 53%.<sup>9</sup> <mark>As per verbal autopsies and household surveys, two-thirds of total maternal deaths occur during the postpartum period, but postnatal care visits are still low at 65%.</mark><sup>10</sup> <mark>There are also</mark> persistent inequities in service utilization and health status among different socio-economic groups. Health indicators and service utilization, for example, are relatively better among the rich, urban and educated groups compared to their counterparts.<sup>11</sup> For 1
instance, under-5 mortality was 55 (out of 1,000 live births) among the lowest quintile compared to 36 among the highest, and perinatal mortality was 52 and 39 respectively <mark>in 2017.</mark> Women in urban areas were more likely to receive quality ANC services than those in rural areas (27% versus 14%) in 2017, and more women with a secondary-level education or higher (33%) reported receiving quality ANC services compared to less-educated women (6%). Only 7% of women from the lowest wealth quintile received quality ANC, compared to 37% from the highest wealth quintile. Similarly, only 21.4% of rural women received quality ANC compared to urban counterparts (34.6%). The status of key RMNCH-N indicators are summarized in Table 1.

**Table 1: Key reproductive, maternal, child and nutrition indicators**

|**Indicators**|**Value**|
|---|---|
|Maternal mortality ratio per 100,000 live births (2017)|173|
|Neonatal Mortality Rate per 1,000 live births (2019)|15|
|Infant Mortality Rate per 1,000 live births (2019)|34|
|Under-five Mortality Rate per 1,000 live births (2019)|40|
|Under-five stunting prevalence moderate & severe (2019)|31|
|Under-five underweight prevalence moderate & severe (2019)|22.6|
|Under-five wasting prevalence moderate & severe (2019)|9.8|
|Under-five overweight prevalence moderate & severe (2019)|2.4|
|Early initiation of breastfeeding (2019)|46.6%|
|Exclusive breastfeeding up to six months (2019)|62.6%|
|Children weighed at birth (2019)|51.9%|
|Delayed bathing (>24 hours after birth) (2019)|80%|
|Under-five received all vaccination (2017)|86%|
|Care-seeking for fever (2019)|55.6%|
|Contraceptive prevalence rate (2019)|70.3%|
|4+antenatal care visits by any provider (2019)|36.9%|
|Institutional deliveries (2019)|53%|
|Skilled birth attendance (2019)|59%|
|Postnatal health check for the mother at least one (2019)|65%|
|Contraceptive prevalence rate among 15-49 age women|62%|

**Sources:** DHS2017<sup>12</sup> ; MICS 2019<sup>9</sup> ; The World Bank 2017<sup>13</sup>

# **1.3 Context for the study**

With considerable investments and noticeable improvements, Bangladesh currently stands at a crucial phase in its RMNCH-N landscape. In order to accelerate achievement of improved RMNCH-N outcomes, global evidence suggests the need for smart and strategic health sector investments and interventions.<sup>1</sup> Further, global evidence also shows that the path to achieving the top RMNCH-N milestones (e.g. SDGs) is more complex and difficult for countries, compared to the earlier milestones (e.g. millennium development goals).<sup>1</sup> Consequently, for Bangladesh, strategic decision-making and investments are necessary.<sup>14</sup> It is already known that investments targeting appropriate RMNCH-N utilization would lead to improved RMNCH-N outcomes.<sup>15,16</sup> However, the success of such investments largely depends on how efficiently and timely (i.e. immediate to short-term) the service utilization determinants are addressed.<sup>14</sup> While there could be several determinants of RMNCH-N utilization, for example, addressing the key ones could be one of the most strategic approaches to ensuring timely progress in the short-term. For instance, while it is known that the quality of maternal, neonatal and child health is low in many countries, it is also known that improving the quality of care would reduce maternal and neonatal deaths. Current global evidence, however, does not establish that improving the quality of care alone would necessarily motivate women to 2
seek timely care. This is because RMNCH-N care-seeking also depends on certain demand-side factors, and utilization patterns are largely context- and time-specific. This situation necessitates that the determinants of RMNCH-N utilization be identified and addressed to ensure prioritized investment decision-making.

In Bangladesh, the evidence-base is inconclusive on the demand- and supply-side determinants that should be addressed urgently for improving RMNCH-N utilization. While the prevailing evidence largely points to socio-economic, cultural and regional factors as the key drivers of RMNCH-N utilization,<sup>8</sup> little is known about the role of service delivery status and quality of care in RMNCH-N uptake. Similarly, the relative significance of supply-side determinants over the demand-side determinants is not clear. For instance, if quality of care is the key determinant of service uptake, improving quality versus sizably investing in addressing certain demand-side determinants (e.g., cultural barriers) would be an immediate priority. While most existing studies have used DHS data and demand-side determinants alone to examine the patterns of RMNCH-N utilization, assessments which combine both demand- and supply-side determinants of RMNCH-N utilization, are limited.

It is against this backdrop that the World Bank, in collaboration with the Ministry of Health and Family Welfare (MoHFW), carried out this technical assistance study to ascertain the most important determinants that need to be addressed, on a priority basis, to improve RMNCH-N outcomes further. A comparative assessment of the drivers of RMNCH-N performance across time periods (2014 and 2017 surveys) reflects the success, as well as gaps, in the government strategies and interventions for further policy navigation. Study findings would also be influential to RMNCH-N policy making in the post-COVID-19 context.

## **1.4 Aim**

The overall aim of this study was to inform strategic RMNCH-N investment decision-making, through a three-pronged approach that involved:

1. Identifying the top ten determinants that need to be addressed on a priority basis to improve RMNCH-N utilization, quality of care and outcomes nationally and for divisions (or states)

2. Comparing the relative importance of demand- and-supply-side determinants on key RMNCH-N indicators in the last decade (across two time points) in Bangladesh 3. Proposing key strategic steps for improving the RMNCH-N utilization and quality in the country.

This study used machine learning analysis as the selected data sources (given below) were high-dimensional and large.

# **2.Methodology**

## **2.1 Data sources**

Two sources of secondary data were used in this study: the Bangladesh Health facility Survey (BHFS) and the Demographic and Health Survey (DHS). Two rounds (2014 and 2017) of BHFS and DHS survey data were used. Data sources and timelines were selected considering the need for a comparative analysis across two time points using multiple rounds of household and facility surveys. Both DHS and BHFS cover similar timeframes, enabling such a comparison. Averages of BFHS indicators by district and location (urbanrural) were merged with the DHS data.

3
## **<mark>BHFS</mark>**

<mark>BHFS is a nationally representative survey of r</mark> egistered health facilities; it includes public facilities, NGO static clinics/hospitals, and private for-profit hospitals. The BHFS 2014 included 1,596 facilities,<sup>17</sup> while the <mark>BHFS 2017 included 1,600 f</mark> acilities.<sup>18</sup> The <mark>BHFS p</mark> rovides information on the availability of basic and essential health care services, and the readiness of health facilities for care provision. It uses standardized questionnaires from the service provision assessment (SPA) component of the Demographic and Health Surveys (DHS) Program. Specifically, it provides information on child health, maternal and newborn care and family planning. For each of these services, BHFS assesses whether necessary elements are present and functioning.

## **DHS**

DHS is a nationally-representative survey of households and ever-married women aged 15-49 years.<sup>12</sup> The DHS 2014 covered 17,300 households and 17,863 women,<sup>17</sup> while the 2017 survey covered 19,457 households and 20,127 women.<sup>12</sup> DHS collects information on health and living conditions of women and children, household assets and wealth status, socio-economic and demographic characteristics, maternal and child health status, nutrition, fertility, family planning, mortality and care seeking for maternal and child health. This study only considered the RMNCH-N care-seeking, perceptions and health outcomes for the most-recent childbirth and child health episode from each DHS survey.

# **2.2 Variables**

Nineteen outcome variables (Table 2) related to service utilization, quality of care and nutrition status were selected from the DHS survey. Demand-side explanatory variables (or potential determinants) selected from the DHS were socio-economic and demographic characteristics and location of service seekers (Table 3). Supply-side explanatory variables chosen from the BFHS and the DHS include – type of provider, quality of care, availability of services (infrastructure, drugs, equipment and skilled staff) and readiness for care provision (Table 4). For the BFHS data, where possible, similar variables were combined and aggregated to create indices (e.g., medical equipment index and drug availability index) to reduce the variance of similar variables based on the categorization or criteria of indexing provided by the BFHS survey (more details can be found in BFHS reports). For utilization of reproductive and maternal care and quality of ANC, the unit of analysis was an individual woman. The unit of analysis for child related indicators was a child under-5. All study variables were selected based on the contextual literature and compatibility for a comparative analysis across time points.<sup>16,19–22</sup>

**Table 2:  Outcome variables**

|**Domain**|**Indicator**|
|---|---|
|Utilization|**Antenatal care (ANC)**<br>•<br>4+ ANC visits<br>•<br>ANC from medically trained provider<br>•<br>ANC in public sector|
||**Delivery**<br>•<br>Skilled birth attendance (i.e., delivery assisted by skilled staff such as doctor, nurse or<br>midwife)<br>•<br>Delivery in public sector|
||**Postnatal care (PNC)**<br>•<br>Availed atleast onePNC (for mother) within 42days|

4
||•<br>PNC for mother received from a medically trained provider|
|---|---|
||**Family Planning (FP)**<br>•<br>Use of any FP methods among married women (15- 49 years)<br>•<br>Use of Modern FP methods among married women (15-49 years)|
||**Vaccination coverage**<br>•<br>12–23 months old children receiving all basic vaccinations (i.e., BCG, three doses of<br>pentavalent (DPT-HepB-Hib), three doses of oral polio vaccine, and one dose of<br>measles vaccine)|
||**Care-seeking for sick under-5 children**<br>•<br>Children with diarrhea treated at a facility<br>•<br>Children with Acute Respiratory Infection (ARI) treated at a facility<br>•<br>Children with fever treated at a facility|
|Quality of care<sup>1</sup>|**Adequate ANC quality**(adequate quality indicates – a woman reported of receiving all given<br>below services in one visit)<br>•<br>Weight measured during ANC<br>•<br>BP measured during ANC<br>•<br>Urine sample taken for ANC<br>•<br>Blood sample taken during ANC<br>•<br>Ultra-sonogram conducted during ANC<br>•<br>Informed of signs of pregnancy complications during ANC|
||**Adequate quality for newborn PNC (**adequate quality indicates – a woman reported of her baby<br>receiving all given below services in one visit).<br>•<br>Examined the cord<br>•<br>Counselled on danger signs<br>•<br>Assessed temperature<br>•<br>Counselled mother on feeding<br>•<br>Observed feeding<br>•<br>Assessed weight|
||**Adequate essential newborn care at birth (**adequacy indicates – a woman reported of her baby<br>receiving all given below services at birth).<br>•<br>use of a safe delivery kit/ bag or boiled blade<br>•<br>nothing applied to the cord or only chlorhexidine applied<br>•<br>after the cord is cut and tied, cord dried within 5 minutes after birth<br>•<br>bathing delayed 72 hours or more<br>•<br>immediate breastfeeding|
|Health/nutrition<br>outcomes|<br>**Under-five Child nutrition**<br>•<br>Stunting (i.e., more than 2 standard deviations below the median for height-for-age)<br>•<br>Wasting (i.e., more than 2 standard deviations below the median for weight-for-height)<br>•<br>Underweight (i.e., less than 2 standard deviations below the median for weight-for-age)<br>**Source**: DHS|

**Table 3: Demand-side determinants***

|**Variables**|
|---|
|Household access toimproved sanitation facilities|
|Household access to improved drinking water|
|Household access to hand washing|
|Household wealth status in quintile|
|Age of mother at childbirth|
|Age at marriage|
|Education status|
|Employment status|

1 Quality of care indices consisted of equally weighted averages of their component variables.

5
|Marital status|
|---|
|Mass media access (_access to at least one media once a week out of radio, television and newspaper)_|
|Women empowerment in health index<br>(i.e.,_earning woman able to spend money as they wish, and able to participate in the decision-making_<br>_for the health care of herself and child)_|
|Residence (rural/urban)|
|Division|
|Women aware of community clinic nearby residence|
|Gender of sick child|
|Birth order|
|Exclusive breast feeding up to six months|
|Initiation of breastfeeding within 1 hour of birth|
|Child’s weight at birth|
|Under-5 received curative care at a facility for diarrhea or fever or acute respiratory infection|

**Source: DHS;** *represents mothers who delivered in the last five years preceding the survey

**Table 4: Supply-side determinants**

|**Variables**|**Definition**|
|---|---|
|Basic amenities index|Proportion of amenities available out of - national electricity grid, regular<br>electricity, improved water source, visual and auditory privacy,<br>functioning improved client latrine, computer with internet, emergency<br>transport, and functional communication equipment in a facility.|
|Basic equipment index|Proportion of equipment available out of - child scale, adult scale, infant<br>scale, thermometer, blood pressure apparatus, stethoscope and light source<br>in a facility.|
|Diagnostic laboratory capacity index|Proportion of lab tests available out of - tests for hemoglobin, blood<br>glucose, urine protein, urine glucose, stool microscopy, urine pregnancy<br>test and functional microscope in a facility.|
|Standard precautions for infection<br>control index<sup>2</sup>|Proportion of amenities available out of - necessary guidelines, equipment<br>and supplies for infection control in a facility.|
|Diagnostic capacity for antenatal<br>care services index|Proportion of diagnostic services available out of -diagnostic capacity for<br>hemoglobin, urine protein,urine glucose, blood grouping and Rhesus<br>factor and syphilis in a facility.|
|Medicines for routine antenatal care<br>index|Proportion of medicines available out of - iron tablets, folic acid tablets,<br>combined iron and folic acid and iron or folic acid tablets.|
|Essential medicines and commodities<br>for normal delivery index<sup>3</sup>|Proportion of medicines and commodities available out of - essential and<br>priority medicines and commodities for normal deliveryin a facility.|
|Essential Medicines for newborn<br>care index|Proportion of medicines available out of - essential medicines for newborn<br>care in a facility.|
|Essential and priority medicines and<br>commodities for childcare index|Proportion of medicines and commodities available out of - essential and<br>priority medicines and commodities for childcare in a facility.|
|Family planning commodities index|Proportion of commodities available out of - oral pills, injectable, intra<br>uterinecontraceptive device and condoms in a facility.|

2 Standard infection control measures include- sterilization equipment; equipment for high level disinfection and safe final disposal of sharps waste and infectious waste; appropriate storage of sharps waste and infectious waste; disinfectant, syringes, and needles; soap, running water, alcohol-based hand disinfectant, latex gloves, medical masks, gowns, eye protection and guidelines for standard precautions.

3 Essential medicines and commodities for delivery care include - injectable uterotonic (oxytocin), injectable antibiotic, injectable magnesium sulphate, injectable diazepam, skin disinfectant, intravenous fluids with infusion set, sodium chloride injectable solution, injectable calcium gluconate, ampicillin powder for injection, injectable metronidazole, misoprostol capsules or tablets, azithromycin capsules or tablets or oral liquid, cefixime capsules or tablets, benzathine benzyl penicillin powder for injection, injectable bethamethasone/ dexamethasone, nifedipine capsules or tablets.

6
|Readiness for antenatal care services|Proportion of amenities available out of - ANC guidelines, staff trained in<br>ANC, equipment, hemoglobin and urine protein testing capacity, and<br>drugs in a facility.|
|---|---|
|Readiness for normal delivery<br>services|Proportion of amenities available out of - guidelines, staff trained in<br>delivery, equipment, and drugs in a facility.|
|Readiness for child curative care<br>services|Proportion of amenities available out of – integrated management of<br>childhood illness (IMCI) guidelines, IMCI staff, growth chart, equipment<br>and drugs in a facility.|
|Readiness for family planning<br>service|Proportion of amenities available out of - guidelines, staff trained in FP,<br>equipment and supplies in a facility.|
|Staff trained in ANC|Facilities with staff trained in ANC|
|Staff trained in delivery care|Facilities with staff trained in normal delivery|
|Staff trained in IMCI|Facilities with staff trained in IMCI|
|Staff trained in growth monitoring|Facilities with staff trained in growth monitoring|
||**Adequate quality for ANC**(adequate quality indicates - a woman reported<br>of receiving all given below services in one visit).<br>•<br>Weight measured during ANC<br>•<br>BP measured during ANC<br>•<br>Urine sample taken for ANC<br>•<br>Blood sample taken during ANC<br>•<br>Ultra-sonogram conducted during ANC<br>•<br>Informed of signs of pregnancy complications during ANC|
||**Adequate quality for newborn PNC (**adequate quality indicates - a<br>woman reported of her baby receiving all given below services in one visit).<br>•<br>Examined the cord|
||•<br>Counsel on danger signs|
|Quality of care*|•<br>Assessed temperature|
|(reported by recent mothers)|•<br>Counselled mother on feeding<br>•<br>Observed feeding<br>•<br>Assessed weight<br>•<br>Height for age<br>•<br>Weight for age|
||**Adequate quality for essential newborn care at birth** **(**adequacy indicates<br>- a woman reported of her baby receiving all given below services at birth).<br>•<br>Use of a safe delivery kit/ bag or boiled blade<br>•<br>Nothing applied to the cord or only chlorhexidine applied<br>•<br>After the cord is cut and tied, cord dried within 5 minutes after<br>birth|
||•<br>Bathing delayed 72 hours or more|
||•<br>Immediate breastfeeding|
|Type of provider (public, private for-<br>profit, NGO)*|<br>Providers of RMNCH-N care as reported by recent mothers|
|<br>ANC by medically trained provider*|Reported by recent mothers|
|<br>PNC for mothers by medically<br>trained provider*|<br>Reported by recent mothers|
|<br>ANC 4+*(completed at least 4 ANC<br>|Reported by recent mothers|
|visits)||
|Skilled birth attendance*|Reported by recent mothers|
|Institutional delivery*|<br>Reported by recent mothers|
|<br># Married woman aged 15-49 years<br>visited by NGO worker*|<br>NGO workers include paid and unpaid community health workers (CHW)<br>deployed by the NGOs|
|# Married woman aged 15-49 years<br>visited by government FP worker *|Government FP worker is a CHW and includes - Family Welfare<br>Assistants (FWA) deployed by the Directorate General of Family Planning<br>(DGFP)|

7
|# Married woman aged 15-49 years<br>visited by government health<br>worker*|Government health worker is a CHW and includes - Health Assistants<br>(HA) deployed by the Directorate General of Health Services (DGHS)|
|---|---|
|Availability of contraceptives|Availability of any modern contraceptive at facilities|

**Sources:** **<mark>BHFS & DHS;</mark>** <mark>* relevant only for a few outcome indicators; # represents community health workers (CHW)</mark>

## **2.3 Analysis**

### **_<mark>Why machine learning analysis?</mark>_**

This study applied the machine learning technique using R programming language.<sup>23</sup> <mark>Machine learning was found to be useful for this comparative analysis since it allowed large demand- and supply-side data sets to be combined. Machine learning was applied over conventional analysis due to the following specific advantages that it offers: 1) it helps to identify the trends and patterns in large data sets easily, and with minimal human biases; and 2) machine-learning algorithms continuously learn from data to help addressing the potential errors in the data. This increases the efficiency of the analysis and the accuracy and quality of predicted outcomes or trends.</mark><sup>24</sup> <mark>Machine learning consists of a group of artificial intelligence techniques, in which the algorithms learn the patterns in the data without being explicitly programmed to carry out specific applications.</mark><sup>24</sup> <mark>In this study, a gradient boosting algorithm was used to predict the outcomes based on the predictors listed in Tables 3 and 4. Gradient boosting combines shallow and successive decision trees.</mark><sup>25</sup> <mark>Decision trees consist of recursively partitioning (also known as splitting) predictors. The goal of each tree in our model was to maximize the accuracy of prediction. Each decision tree learns successively and improves upon the previous (learning rate). Eventually, predictions are based on a weighted combination of these trees.</mark><sup>26</sup> <mark>The preprocessed data (variable scaling and removal of highly correlated predictors) was split into training (80%) and test segments (20%) for all outcome variables. First, the algorithm was trained on the training segment and then validated on the test segment to determine predictions. The data was 10-fold cross-validated, with the data split into 80% training and 20% test observations randomly, ten times for all algorithms. The average of the cross-validations was taken as the final result. The relative influence of the predictors with the output was estimated using mean decrease Gini impurity coefficient (MDG) in the gradient boosting algorithm.</mark><sup>25</sup> <mark>MDG is the average across all trees of the decrease in Gini impurity for a predictor.</mark><sup>25</sup> <mark>The mean decrease in Gini coefficient is a measure of how each variable contributes to the homogeneity of the nodes and leaves in the resulting hierarchy of decision trees. A higher MDG value shows that the degree of impurity arising from a variable category could be reduced farthest by one variable, and therefore suggests an important associated factor.</mark><sup>25</sup> <mark>The ranking of the top 10 predictors was plotted based on the MDG. Predictors with a higher relative importance value are more likely to affect the outcomes than with the lower values. For instance, the predictor on the top of the relative importance chart (given in the results) has a relatively higher relative importance value and the highest influence on the outcome indicator among all predictors considered. Similarly, the predictor on the bottom of the relative importance chart (given in the results) has the least relative importance value and the least influence on the outcome among all predictors considered.</mark>

# **3. Results**

8
# **3.1 ANC** <mark>(ANC 4+visits, ANC by medically trained provider and ANC in the public sector)</mark>

<u>For all three ANC indicators – the level of utilization consistently across two time points (2014 and 2017)</u> was directly related to reported ANC quality among pregnant women, wealth status and media access (Figures 1- 3). These results indicate that the level of ANC utilization was higher for richer women, those having a higher media access, and those who reported that facilities provide a better quality of ANC. Compared to 2014, the relative role of education status was less in 2017 (except for 4+ANC). The chance of completing 4+ANC was higher among more educated women across years. However, women irrespective of their education level had a high chance of receiving ANC from medically trained staff. Meanwhile, the chance of availing ANC in public facilities was higher among relatively better educated women.

The relative importance of residence and divisions declined in 2017, indicating that inequalities in ANC utilization based on rural-urban status and divisions, have reduced in recent years. The demand-side determinants (e.g., handwashing access and age at marriage) had a higher influence on ANC usage than supply-side determinants in 2014. This shows that while women who had access to handwashing facilities in their households had a better chance of availing ANC earlier, this trend was reversed in 2017. The relative role of supply-side determinants (e.g., quality of care, availability of staff trained in ANC, amenities and equipment) became stronger in 2017, reflecting the emerging role of supply-side determinants in influencing improvements in ANC utilization in recent times.

<u>4+ANC visits -</u> the role of both public and NGO facilities became one of the top determinants of completing 4+ ANC in 2017 (Figure 1), indicating that women who availed ANC from these facilities had a higher chance of completing 4+ ANC visits. These results reflect the progressive influence of public and NGO facilities on 4+ ANC. Similarly, the role of supply-side determinants was stronger in 2017. For instance, the availability of staff trained in ANC became a top determinant (4<sup>th</sup> position) and readiness of facilities for ANC became the 7<sup>th</sup> most important determinant.

- <u>ANC by a medically trained provider</u> the role of demand-side determinants (e.g., education and age at marriage) decreased in 2017, while wealth remained a top determinant in both 2014 and 2017 (Figure 2). The role of supply-side determinants increased in 2017. For instance, the availability of staff trained in ANC and ANC medicines emerged as top determinants, indicating that they could both positively increase the chance of availing ANC from a medically trained staff. The role of CHWs (i.e., NGO worker and government health worker) also became a top determinant, reflecting their positive influence on encouraging women to seek ANC from medically trained staff.

<u>ANC in the public facilities - the importance of supply-side determinants increased in 2017 (Figure 3).</u> Findings show that women considered the availability of medically trained staff and quality in choosing the public sector. Women who were aware of the presence of community clinics in their locality had a higher chance of availing ANC from the public sector. The visits of CHWs (i.e., NGO worker and government health worker) were also the top determinants, positively influencing the use of the public facilities for ANC.

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<!-- Start of picture text --> 2014 2017<br>ancquality |Es ancquality |is<br>wealth | wealth | i’!<br>ancMedicallyTrained | Hi staff_anc7] Hii<br>equipment_basic 7 Hl equipment_basic 7 Hl<br>education 7 Hl education] Hl<br>mediaAcess 7 Hl mediaAcess 7 Hl<br>division 7 Hil readiness_anc+ Hi<br>medicines_anc 7 Hl ancNGO 4<br>ancPrivate 7 Hi ancPublic 7 fi<br>amenities_basic 7 Bf medicines_anc 7 ll<br>fe) 10 20 30 fe) 10 20 30 40 £50<br>Relative importance Relative importance<br><!-- End of picture text -->

<!-- Start of picture text --> 2014 2017<br>ancPrivate)] ancqualiy |]<br>ancquality) ancPublic |i!<br>ancPublic] ancPrivate | i’!<br>wealth] Hii” wealth 7 Hil<br>anc4plus7 Hi ancNGO +I<br>education] Hi visitedByNgo + I<br>equipment_basic 7 I visitedByGovHealthWorker 4 I<br>division 7 I medicines_anc 7 |<br>amenities_basic 7 | education 7 |<br>ageMarriage 7 | staff_anc 71<br>fe} 10 20 30 40 fe} 20 40<br>Relative importance Relative importance<br><!-- End of picture text -->
<!-- Start of picture text --> 2014 2017<br>medicines _anc] 7!Ei _ ancMedicallyTrained | Ei<br>Wealth] ssI wealth | iis<br>ancMedicallyTrained | ancquality | 7!<br>staff_anc 7] Ei anc4plus 7] Hi<br>diagnosis_anc |] i777! staff_anc] Hl<br>ancquality |]i medicines_anc7 Hl<br>handWashing 7 Hil awareComClinic 7<br>labtests 7 Hi employmentStatus 7 Hi<br>division 7 Hill labtests 7 Hl<br>amenities_basic7 Hl education 7 Hi<br>fe} 5 10 15 20 fe} 10 20 30<br>Relative importance Relative importance<br><!-- End of picture text -->
<!-- Start of picture text --> 2014 2017<br>ancqualiy |Ds ancquality |<br>Wealth |is wealth |<br>education |] Hl education |] i!<br>ancMedicallyTrained 7 Hill anc4plus 7 ii!<br>anc4plus 7 Hi ancMedicallyTrained |] Hl<br>amenities_basic |] Hl ancPrivate 7 Hi<br>mediaAcess 7 Hl mediaAcess 7 il<br>labtests 7 Hl amenities_basic 7 i<br>ageMarriage 7 ageMarriage 4 Il<br>division 7 Hi division 7 I<br>ie) 10 20 30 ie) 10 20 30<br>Relative importance Relative importance<br><!-- End of picture text -->

<!-- Start of picture text --> 2014 2017<br>ancPublic |is ancPublic 5<br>ancquality |] ancquality] i’<br>amenities_basic] Hi readiness_delivery 7] Hill<br>equipment_basic 7 Hil ancPrivate7 Hil<br>wealth | Hill division] Hill<br>ageMarriage 7 Hl equipment_basic 7 Hi<br>division] staff_delivery] Hl<br>labtests 7 Hl age<br>staff_delivery7 Hi education] Hl<br>visitedByNgo 7 Hf amenities_basic] Hl<br>fe} 10 20 30 40 fe) 10 20 30<br>Relative importance Relative importance<br><!-- End of picture text -->
|deliverylnstitutional ||2014<br>Ds<br>skiledBirth|2017<br>||
|---|---|---|
|skiledBith]|Es<br>deliveryinstitutional|| _<sup>=!</sup>|
|mediaAcess ||deliveryPublic 7|Hi|
|wealth ||anc4plus 7|i|
|amenities_basic ||equipment_basic 7||
|handWashing ||amenities_basic 7|fl|
|employmentStatus ||employmentStatus 7|If|
|improvedWater7|Hl<br>ready_del7|ll|
|anc4plus 7|Hill<br>labtests 4|Il|
|division]|Hi<br>age|I|
||fe)<br>5<br>10<br>15<br>20<br>Relative importance|0<br>10<br>20<br>30<br>40<br>50<br>Relative importance|
<!-- Start of picture text --> 2014 2017<br>skilledBirth |is skilledBirth |<br>deliverylnstitutional | wealth] Hi<br>wealth 7 fl deliveryPublic 7 Bf<br>deliveryPrivate 7 I division 7 Il<br>equipment_basic 7 | improvedSanitation 7 I<br>staff_del7 | amenities_basic 7 I<br>amenities_basic 7 | labtests 7 I<br>mediaAcess4 | staff_del7 |<br>education 4 | ready_del |<br>division + | awareComClinic 4 |<br>(e) 20 40 60 (e) 20 40 60<br>Relative importance Relative importance<br><!-- End of picture text -->
<!-- Start of picture text --> 2014 2017<br>age |Es age |<br>visitedByGovHealthWorker | i visitedByGovHealthWorker |<br>division] 7! visitedByGovFp |=’<br>visitedByGovFp | ii’ contracep_avibl7 Hill<br>amenities_basic 7 Hl division] i/<br>equipment_basic 7 Hi visitedByNgo 7 Hii<br>employmentStatus 7 | amenities_basic 7 Hl<br>labtests 7 | employmentStatus 7 Hl<br>ageMarriage 7 | equipment_basic 7 ff<br>wealth 7 | womempower 4 I<br>0 10 20 30 40 0 10 20 30<br>Relative importance Relative importance<br>2014 2017<br>age |Es age |]<br>visitedByGovHealthWorker | ii! visitedByGovHealthWorker |=<br>visitedByGovFp 7 Hii visitedByGovFp | =’<br>division] Hi visitedByNgo 7 Hl<br>amenities_basic 7 Hl division 7 Hi<br>equipment_basic 7 employmentStatus 7 Hi<br>contracep_avibl + I contracep_avibl7 Hl<br>ageMarriage 7 I amenities_basic 7<br>wealth 7 I womempower 7 ff<br>employmentStatus 7 | ageMarriage + |<br>Oo 10 20 30 40 50 fe) 10 20 30<br>Relative importance Relative importance<br><!-- End of picture text -->
||2014||2017|
|---|---|---|---|
|childAge|||chidAge ||is|
|Wealth |||mother_education ||iii’!|
|improvedSanitation 7|Hil|wealth 7|Hii|
|labtests ||]Hi|division]|Hil|
|curativecare_child<br>||]ill|improvedSanitation 7|Hl|
|equipment_basic 7|]Hl|labtests 7|Hl|
|staff_growthmonitoring ||]Hil|amenities_basic 7|Hl|
|medicines_child 7|Hil|awareComClinic 7|Hi|
|staff_imci]|Hl|medicines_child7|I|
|amenities_basic|7 Hl|staff_imci7|Hi|
||(e)<br>10<br>20<br>30<br>Relative importance||(e)<br>10<br>20<br>30<br>40<br>Relative importance|
<!-- Start of picture text --> 2014 2017<br>childAge ] iii a s: chldAge<br>wealth | wealth]<br>improvedSanitation 7] ii! mother_education] iii!<br>labtests |] Hi amenities_basic] Hii<br>amenities_basic 7 Hl handWashing 7 Mil<br>medicines_child | Hl labtests 7 Hi<br>visitedByGovFp 7 Hl childSex7 Hil<br>staff_growthmonitoring 7 Hl division] Hl<br>staff_imci7] mother_age7<br>improvedWater 7 staff_imci7] Hl<br>Oo 10 20 30 oO 10 20 30<br>Relative importance Relative importance<br><!-- End of picture text -->

<!-- Start of picture text --> 2014 2017<br>chidAge |Ds chidAge |<br>wealth | equipment_basic | Hii<br>staff_imci7 amenities_basic | il<br>improvedSanitation | Hii’ staff_growthmonitoring 7 Hii<br>mother_age |] Hi childSex 7 iil<br>visitedByGovFp 7 iil division 7 i!<br>amenities_basic7 Hl medicines_child 7 Hil<br>equipment_basic 7 Hl improvedSanitation 7 Hi<br>labtests 7 Hl staff_imci7] ll<br>awareComClinic 7 Hl labtests 7 Hl<br>0 10 20 0 10 20 30<br>Relative importance Relative importance<br><!-- End of picture text -->
<!-- Start of picture text --> 2014 2017<br>medicines_chid] mother_education 7=<br>mother_education |]is mother_age |=<br>staff_imci] wealth | i’<br>wealth | division |]7’<br>division] staff_imci7 i’<br>mediaAcess 7 staff_growthmonitoring 7 ii<br>mother_age | medicines_child | i<br>staff_growthmonitoring | equipment_basic 7 Hi<br>curativecare_child | I amenities_basic 7 Hl<br>equipment_basic 7 Hill visitedByGovHealthWorker 7 Hil<br>0 5 10 15 0 5 10 15 20<br>Relative importance Relative importance<br><!-- End of picture text -->
<!-- Start of picture text --> 2014 2017<br>Wealth |asiii ancMedicallyTrained |=<br>ancMedicallyTrained |]is anc4plus 4<br>anc4plus | wealth |=<br>ancPrivate 7 Hil education] Hl<br>education] Hl ancPrivate 7 Ml<br>ancNGO 4 ancPublic 4 I<br>division 7 medicines_anc 7 I<br>staff_anc 7 I equipment_basic 7 I<br>diagnosis_anc 7 | readiness_anc 7 |<br>employmentStatus 4 | staff_anc |<br>oO 10 20 30 Oo 10 20 30 40<br>Relative importance Relative importance<br><!-- End of picture text -->

<!-- Start of picture text --> 2014 2017<br>deliveryinstitutional] 7777sI skiledBith] Iii _ 7_ 7_<br>wealth |Zs deliveryPrivate 7 Hil<br>skilledBirth | anc4plus | Hii<br>amenities_basic | wealth 7 Hil<br>employmentStatus 7 Hill equipment_basic 7 Hill<br>deliveryPrivate 7] Hi division] Hl<br>ready_del7] Hl labtests 7 Hl<br>anc4plus 7 Hil deliveryinstitutional | Hi<br>labtests 7 Hi employmentStatus 7 Hi<br>staff_delj] Hi amenities_basic 7] Hi<br>Oo 10 20 30 Oo 10 20 30 40 50<br>Relative importance Relative importance<br><!-- End of picture text -->
<!-- Start of picture text --> 2014 2017<br>division |as division |<br>equipment_basic |] equipment_basic] ii!<br>ready_del] ready_del] Hii<br>wealth | staff_del] Hi<br>labtests | amenities_basic | Hl<br>staff_del] wealth 7 Hil<br>amenities_basic |] HE age]<br>education | labtests 7<br>age; Hi education] Hl<br>skilledBirth | Hil employmentStatus 7 Hl<br>fe) 10 20 fe) 10 20 30<br>Relative importance Relative importance<br><!-- End of picture text -->
<!-- Start of picture text --> 2014 2017<br>chidAge |is childAge |=<br>Wealth |is vealth |<br>mother_education | division] =!<br>curativecare_child7] Hl mother_education |i!<br>mediaAcess 7 Hl mediaAcess | Hi<br>improvedSanitation 7 Hl staff_growthmonitoring 7 Hl<br>staff_growthmonitoring 7 amenities_basic 7 Hi<br>division 7 Hi equipment_basic 7<br>labtests 7 fl medicines_child 7 i<br>mother_age 7 Il staff_imci7 I<br>ie} 10 20 30 (e) 10 20 30<br>Relative importance Relative importance<br><!-- End of picture text -->

<!-- Start of picture text --> 2014 2017<br>childAge |ss chidAge |Ts<br>wealth | staff_growthmonitoring | iii!<br>mother_age | Hill childSex |] Hii<br>improvedWater | Hii medicines_child | Hil<br>division 7il equipment_basic 7 Hill<br>mother_education 7 Hl mother_age 7 Hl<br>labtests 7 Hl labtests 7 Hl<br>staff_growthmonitoring 7 Hl wealth 7 Hi<br>equipment_basic 7 amenities_basic 7 Hl<br>staff_imci7 staff_imci7 il<br>fe) 10 20 30 (e) 10 20 30<br>Relative importance Relative importance<br><!-- End of picture text -->
<!-- Start of picture text --> 2014 2017<br>wealth |is childAge |is<br>childAge | wealth |ay<br>mother_education 7 Hl mother_education |7!<br>mediaAcess | Hi division] =<br>improvedSanitation 7 Hil staff_growthmonitoring 7 Hil<br>staff_growthmonitoring 7 medicines_child 7 Hl<br>curativecare_child 7 equipment_basic 7 Hl<br>medicines_child 7 amenities_basic 7 li<br>labtests 7 Bf improvedSanitation 7<br>division + staff_imci7 li<br>(e) 10 20 30 (e) 10 20 30<br>Relative importance Relative importance<br><!-- End of picture text -->
Findings clearly indicate that, compared to 2014, the relative importance of individual (e.g., mother’s age, birth order) and household (sanitation and handwashing) determinants have declined considerably in 2017. Similarly, differences in utilization based on divisional location (except for nutrition status) and residence (rural-urban) also declined in 2017. The existing literature shows that Bangladesh has been successful in reducing inequalities in RMNCH-N service utilization based on location (i.e. division), residence and sociodemographic groups; the role of individual determinants (e.g., age and birth order) has less influential after 2015.<sup>27,28</sup> The persistent efforts of the government in integrating community needs into the <mark>safe motherhood programs, identifying local needs through community-based platforms and mainstreaming NGOs into community health, are worth acknowledging here as success factors.</mark><sup>27</sup> The study found two exceptions to the above findings. First, in the case of FP usage, age and birth order were found to be top determinants. This, however, was a positive observation, indicating that older women, and those with a greater number of children, had a higher chance of using FP methods. This is promising finding for maintaining the low fertility rate in Bangladesh, and reflects the success of FP strategies. A second exception was increased availability of improved sanitation and handwashing facilities, which has improved household care-seeking behavior for the under-5 age-group. Perhaps, households with such amenities were more aware of appropriate care-seeking and financially better-off to afford care. Further, it could be postulated that wealth status is the ultimate determinant here, as wealth status considerably increases the possibility of having sanitation and handwashing facilities in households.<sup>27</sup> Additionally, wealth and education status affected utilization across most RMNCH-N service indicators. For example, and as expected, wealth and education status of mothers were the top determinants of nutrition outcomes. Inequalities in utilization, based on wealth status, can adversely exacerbate rural-urban gaps in RMNCH-N service usage. A recent study reported noticeable inequalities in RMNCH-N service utilization, based on wealth, even within urban areas.<sup>28</sup> As such, prevailing user fees exemption (with only nominal charges) in public facilities may have limited scope in improving utilization by poor women for two major reasons: 1) functional readiness of public facilities is limited, causing women to seek care in the private for-profit sector and/ or purchase drugs and supplies outside of facilities, thereby incurring sizable out-ofpocket expenses; and 2) remote and less-developed regions have limited presence of public facilities. Resultingly, women must depend on private providers.<sup>29</sup> This study, however, also observed that a greater number of wealthier women used public facilities for PNC compared with their poorer counterparts. This is a common phenomenon in the South Asia region, where the wealthier have a better chance of availing public goods and social benefits.<sup>30</sup> This study did not assess the financial catastrophic spending (where outof-pocket spending exceeds a certain threshold of monthly household income or monthly total consumption) related to RMNCH-N care-seeking. Heavy reliance on the private for-profit sector, and the indirect costs of care (e.g. transportation), can contribute to severe financial catastrophies.<sup>31</sup> Results also showed that a better educated woman had a higher chance of completing 4+ ANC and SBA, and her under-5 child(ren) also had a relatively higher chance of accessing treatment. Education status also influenced the chance of child-care seeking and full vaccination. Access to mass media could be instrumental here. Although this study did not assess the impact of any specific health awareness strategies through mass media platforms, women having better access to mass media, also showed higher RMNCHN service utilization. Some pilot studies have shown that behavior change interventions through mobile technology are cost effective for maternal and neonatal health in Bangladesh.<sup>32,33</sup> Education and wealth status are also directly related and, perhaps, low RMNCH-N utilization among the less-educated could be due to both their inability to pay, and a lack of knowledge and awareness. In the South Asia context, poor 23
awareness has greater potential to reduce FP utilization, than maternal care usage.<sup>28</sup> This is because there is a greater prioritization of maternal care at the household-level, as childbirth is considered to be more of a household event.<sup>34</sup> However, this study observed a contrary scenario in which utilization was better for FP than that for maternal care.

# **2. Availability of skilled staff, amenities and equipment at facilities could positively influence RMNCH-N service utilization and outcomes.**

All RMNCH-N service utilization indicators were positively affected by the availability of skilled staff, amenities, drugs, and equipment in both public and private sectors. Availability of growth monitoring staff and childcare medicines positively influenced nutrition status, care-seeking and vaccination, with this positive influence perhaps could linked to their delivery of sensitization messages to mothers.<sup>35</sup> It is a welcome trend that most women are willing to seek care if facilities are functional with medically trained staff, and necessary equipment and amenities.

# **3. Quality of care could positively influence RMNCH-N service utilization.**

This study observed that the utilization rate was higher among those women who reported receiving better quality of ANC, PNC and essential newborn birth care practice. However, quality of care in the private forprofit sector had a relatively better influence on RMNCH-N service utilization. This scenario reflects suboptimal and less-satisfactory quality experienced by women in public facilities. Women reported receiving better quality care if they received ANC from a medically trained staff. This is likely linked to adherence to relevant treatment guidelines, by medically trained staff .<sup>31</sup> Similarly, women reported better quality care if basic equipment and amenities were available in facilities.

While this study did not assess the motivation and performance of health workers, reported quality was proportionately higher based on the availability of medically trained staff, equipment, and amenities. This could perhaps be interpreted as a scenario in which medically trained providers were motivated to perform their duties in the for-profit private sector. And given the low influence of quality in the public facilities on RMNCH-N service utilization, it could be interpreted that work motivation and performance is relatively lower for public facilities’ providers.<sup>28</sup> Existing studies in Bangladesh show that the quality of RMNCH-N care in Bangladesh is particularly poor in the public sector,<sup>36</sup> with some divisions and urban areas far betteroff in terms of quality of care.<sup>36</sup>

# **4. The role of public facilities is emerging strongly in influencing RMNCH-N service utilization, but poor quality of care is a constraint here.**

Women who availed ANC from the private for-profit sector had a better chance of completing 4+ ANC in 2014. This trend was reversed in 2017, with an emerging role for the public sector. This is a welcome trend, and reflects substantive improvements in the availability of services at public facilities and the performance of staff in motivating women to avail appropriate care. Perhaps the pivotal role of community clinics in linking the community with the primary health care system needs to be highlighted.<sup>28</sup>

# **5. The role of CHWs was obvious in driving FP utilization, but not maternal and childcare utilization.**

Although primary data collection was not conducted, the study findings show that CHWs had a limited role in influencing maternal and child service utilization unlike for FP. With regards to FP use, the motivation of CHWs (i.e., FP and health workers) were shown to have a greater influence than mass media. Not having 24
a qualitative study is a limitation in validating this finding. However, the existing literature does not provide substantial contradictory evidence to refute this finding. While studies do reflect the promising role of CHWs in FP utilization, there is limited evidence of influence on other utilization indicators.<sup>37</sup> Nonetheless, this limited role is not promising, especially when compared with other countries in the South Asia region that have shown the impressive role of CHWs in driving maternal and child service uptake. The Accredited Social Health Activist (ASHA) program in India, for example, has emerged as one of the largest and most effective CHW programs globally for RMNCH-N services.<sup>38</sup> It is worth noting that the Bangladesh National Community Health Worker Strategy 2019 also calls for reinforcing the scope of CHWs in community health through multi-faceted approaches.<sup>37</sup>

# **Study Limitations**

This study has certain limitations. First, the selection of determinants and outcome indicators was limited by both data availability and compatibility for a comparative analysis across two time points. Therefore, certain crucial health outcomes (e.g., maternal and under-five mortalities) and child feeding practices could not be included when considering the nutrition outcomes. Also, data for Mymensingh was not separately included in DHS 2014 and therefore this division was excluded from division-specific analyses. Second, this study inherits the data quality issues and biases of both DHS and BHFS. Utilization and quality of care data were self-reported without verification, with a chance of recall bias, information bias and social desirability bias. BHFS did not physically verify the availability of services in facilities, as it collected information from the facility records. Validation studies in LMICs, however, have found a <mark>moderate to high sensitivity, and a m</mark> oderate validity for self-reported coverage of RMNCH-N service utilization and quality of care in household surveys.<sup>39,40</sup> For quality of care, DHS uses objective questions on standardized medical procedures and thus, the typical subjectivity concerns for psychometric assessments may not be applicable here as shown by validating studies.<sup>39,40</sup> Also, while assessing the determinants of RMNCH-N service utilization, the service seekers’ experience is more meaningful than a facility-based empirical assessment of quality.<sup>40</sup> Third, this study did not have a primary data component, and, in particular, a qualitative component to triangulate why and how certain determinants influenced each outcome in a particular way. Therefore, drawing conclusions from the findings requires a cautionary approach. Fourth, the machine learning analysis provides the top determinants that influenced the study outcomes. But a careful approach (substantiated by literature) is needed while concluding the direction of association between a specific determinant and an outcome. This study used a vast contextual literature including the DHS reports for triangulation.

Fifth, this study exclusively focused on the pre-pandemic (COVID-19) phase and used one of the most recent household and facility surveys data. Findings may not be appropriate for any decision making during the pandemic but would certainly be relevant for the post-COVID phase. The existing evidence indicates that the determinants of RMNCH-N service utilization would remain largely the same in the post-pandemic phase. Nonetheless, low service provision, poor quality and financial constraints of service seekers perhaps would be multiplied and remain as the top determinants in the post-pandemic phase.<sup>41</sup> This study, however, also shows that service availability, quality and household wealth status are the top determinants even in the pre-pandemic phase. Lastly, this study did not assess the impact of any ongoing policy interventions. Thus, findings are not robust enough to make a conclusion on the ultimate impact of any initiatives. However, findings certainly reflect the key determinants that could be addressed further, on a priority basis. Findings can also indicate the need, as well as the direction, for mainstreaming some of the current policy strategies and interventions.

25
# **5. Policy Implications**

The findings clearly indicate that demand-side awareness has improved substantially, with women more influenced by service availability, and quality, than by cultural barriers. This shift could be considered progressive, as women choose to seek care depending on the quality of services available at facilities. A caution here is that the readiness of facilities for RMNCH-N care and quality of services need to be improved further, especially in public facilities to keep up the current momentum of care-seeking. Otherwise, either this momentum may not persist, or the care-seeking behaviors of pregnant women and mothers may not translate into proportionate improvements in MCH status and reduction in mortality. Improved health facility readiness and quality of care, however, does not exclude the need to significantly increase the financial access of poor women, and further increase awareness among less-educated women. Unless targeted and specific strategies are implemented for these two groups (poor and less educated), the country’s remarkable progress in improving RMNCH-N outcomes may be limited.<sup>42</sup> Similarly, study findings also show that some divisions will require additional focused attention.

Overall RMNCH-N achievements in the country over the last two decades, and some obvious improvements in the determinants of RMNCH-N (as shown in the study) point to the need to deepen and mainstream: a) targeted population-specific interventions to enhance affordability and awareness; b) community-based approaches; and c) specific management strategies to improve facility performance and quality of care. A few strategies that can be considered are outlined below:

1. **Improving funding, functional readiness and management capacities of facilities** – public facilities in remote and some rural areas require constant funding, supportive supervision, and governance support. A recent study in Bangladesh showed that public facilities cannot improve their efficiency further without additional investments on specific inputs (e.g. staff performance).<sup>43</sup> In this regard, a specific health sector intervention involving results-based financing or pay-for-performance, which could potentially improve the capacity and performance of facilities in remote areas, could be piloted.<sup>42</sup> Results-based financing has shown to improve functional readiness of health facilities in several lowand middle-income countries (LMIC).<sup>42</sup>

2. **Improving clinical quality of care** – improving the clinical quality further would be a requirement, particularly for the rural areas in all divisions. The prevailing evidence shows that measures such as _continuous capacity building needs assessment_ of staff could help to improve the clinical quality of care.<sup>44</sup> Some countries have also experienced improvements in quality through pay-for-performance inventives.<sup>45</sup> 3. **Strengthening the use of mass media or mobile technology in RMNCH-N service provision**

- a. **_Targeted behavior change interventions using mass media platforms_** – targeted interventions using mass media have proven to be more effective for behavior change than regular awareness strategies.<sup>46</sup> Behavior-change strategies targeting specific groups (e.g. less educated women) have also been shown to remove cultural barriers in MCH care.<sup>46</sup> This platform could potentially help in elevating the consistently low PNC usage from the current 50% and 4+ ANC among less educated women.<sup>46</sup>

- b. **_Mobile technology for improving the capacity and performance of health and FP workers in rural and urban areas–_** mobile applications could help in the identification of maternal and neonatal danger signs; sending of reminders about ANC, PNC and vaccination timeline; spreading awareness on nutrition; and growth monitoring of children.

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4. **Mainstreaming the scope, capacity, and influence of CHWs (health, FP and NGO workers)** **_–_** improving the scope, capacity, and performance of CHWs could be a wise strategy for improving RMNCH-N service utilization, particularly PNC. Existing evidence shows that a regular _capacity building needs assessment of CHWs_ would help to identify the gaps in skills relative to local RMNCHN service needs. Introducing measures to improve CHWs’ work motivation and performance could be relevant here. Studies show that motivation of CHWs is pivotal to their satisfactory performance. In addition, challenges such as transportation and non-acceptance from the community, which are shown to affect performance, should also be addressed.<sup>38</sup> Findings also encourage a full-fledged implementation of the Bangladesh National CHW Strategy as a means of enhancing CHW performance.

5. **Deepening the public-private (i.e. NGO) engagement at the community-level** **_–_** mainstreaming the role of CHWs in RMNCH-N service delivery. First, NGOs could be deployed to train CHWs. Evidence from some of the pilot interventions in Bangladesh have shown successes with this approach. For instance, a public-private partnership pilot was effective <mark>in early identification of maternal danger signs, and community mobilization efforts, by training</mark> the <mark>community skilled birth attendants (CSBA) in 10 sub-districts and 50 unions of Sunamganj.</mark><sup>47</sup> <mark>Second, NGOs could be involved in the supportivesupervision of CHWs in rural and remote areas. Evidence from the South Asia region shows promising results from the provision of supportive supervision to CHWs, by NGOs.</mark><sup>48</sup> 6. **Improving affordability for poor women** **_–_** as mentioned earlier, user fees exemption in public facilities will have limited impact on poor women, given their dependence on private providers (due to limited public facilities in remote areas and their low functional readiness). In this context, _demandside vouchers (cashless system) and cash incentives_ could be potential options explored, with the possibility of national scalability. Vouchers have been shown to be effective in improving RMNCH-N service utilization across several LMICs and in addressing the indirect costs of care.<sup>49</sup> Similarly, cash incentives are known to positively impact a wide range of RMNCH-N behaviors including dietary behaviors in LMICS.<sup>49</sup> 7. **Additional explorations through analytic studies** **_–_** given findings that less educated women had better FP utilization and less MCH utilization, there is a need to explore: (i) the role of affordability and awareness in driving MCH utilization through a qualitative study; (ii) the household financial catastrophic spending from RMNCH-N care; (iii) a benefit-incidence analysis to understand equity in public health spending for RMNCH-N services; and (iv) the positive role of community-based mechanisms (e.g., community clinics, CHWs and NGOs) in improving FP usage, in order to replicate such exemplary strategies for MCH care.

# **6. Conclusions**

Overall, this study found that the health system of Bangladesh stands at a positive juncture currently, where increasing the functional readiness of facilities and quality of care would increase RMNCH-N service utilization, compared to earlier times, given the reduced dominance of demand-side determinants (e.g., age, birth order, education status) in recent years. Findings clearly indicate that demand-side awareness has improved substantially, with women, on the whole, being more influenced by service availability, and quality, than cultural barriers. This shift could be considered progressive, since women choose to seek care if quality services are perceived to be available at health facilities. However, quality of care was better in urban areas across almost all divisions. A caution is that the readiness of facilities for RMNCH-N care provision, and quality services, needs to be improved further, especially in the public facilities to keep up 27
with the current momentum of care-seeking, as the influence of the public facilities was relatively lower (except for PNC). Otherwise, either this momentum may not persist, or the sincere care-seeking of pregnant women and mothers may not result in proportionate improvements in RMNCH-N status and reductions in mortality.

Supply-side improvements, however, do not preclude the significant need to increase the affordability of poor women and further improve awareness among less-educated women. Wealth status, being a top determinant across years, indicates that perhaps the prevailing user fees exemption alone is not adequate to improve RMNCH-N service uptake. Additionally, given low service delivery status in the public sector, and the heavy reliance on the private for-profit sector for RMNCH-N care, it would be pertinent to consider addressing the direct and indirect costs of care through demand-side financial incentives. Although this study did not assess the direct impact of any awareness strategies through mass media, women having mass media access had a better chance of utilizing RMNCH-N services. This suggests the need for specific targeted interventions using mobile technology to augment awareness and utilization among vulnerable groups (e.g., less educated). The low influence of CHWs in maternal and childcare utilization (unlike FP) also further suggests the need to leverage the potential of mobile technology to improve CHW capacity and connectivity with the communities. If needed, NGOs can be involved in providing supportive supervision of CHWs. Finally, additional analytical studies are suggested to generate further evidence on improving both the financial access of poor women and the role of CHWs in the provision of MCH care.

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