Assessing Factors Affecting Readiness for Reproductive, Maternal, Newborn, and Child Health Services, Ethiopia SPA Survey 2021-22

Utilizing 2021-22 Ethiopia Service Provision Assessment data and principal component analysis, this study reveals significant regional and facility-level disparities in reproductive, maternal, newborn, and child health service readiness, highlighting critical gaps in resources, staffing, and infrastructure that necessitate targeted investments to ensure equitable access to quality care.

The Gist

Imagine Ethiopia's healthcare system as a massive, bustling network of restaurants trying to feed a hungry population. Some are tiny street stalls (Health Posts), some are neighborhood diners (Health Centers), and some are grand, five-star hotels (Hospitals).

The goal of this paper is to answer a simple question: "Are these restaurants actually ready to cook the meals they claim to serve?"

The authors (Rachael Church and her team) went into the kitchen of 1,158 of these "restaurants" using a giant checklist called the ESPA Survey (2021-22). They didn't just ask the chefs, "Do you have a stove?" They went in, looked at the stove, checked if it was plugged in, saw if there was gas, and checked if the chef knew how to use it.

Here is the story of what they found, explained simply:

1. The Big Surprise: The "Five-Star" Hotels are Often Empty

You would expect the big, fancy hospitals (the "five-star hotels") to be the best equipped. After all, they have the most money and the most doctors, right?

• The Reality: The study found that many of these big hospitals were actually less ready to provide basic care than the tiny street stalls.
• The Analogy: Imagine a five-star hotel that claims to serve breakfast but has no coffee maker, no eggs, and the chef has never been trained on how to make an omelet. Meanwhile, the small street stall next door has a working stove, fresh eggs, and a chef who knows the recipe perfectly.
• Why? The big hospitals are often overwhelmed, under-resourced, or have their supplies stuck in a warehouse far away. The small stalls are simpler and sometimes better stocked for the basics.

2. The "Recipe Book" Problem

To cook a good meal, you need three things:

1. Ingredients (Medicine and vaccines).
2. Tools (Stethoscopes, blood pressure machines, refrigerators).
3. The Recipe (Training and guidelines).

The study used a special math tool called PCA (Principal Component Analysis). Think of this as a smart detective that looks at all the ingredients, tools, and recipes in a kitchen and figures out which one matters most for a successful meal.

• For Family Planning: The detective found that the ingredients (birth control pills, condoms, implants) were the most important factor. If you don't have the pills, you can't serve the meal, no matter how good the chef is.
• For Child Vaccines: The detective found that the fridge (infrastructure) was the hero. If you don't have electricity to keep vaccines cold, they spoil. It doesn't matter how many vaccines you bought if they are melted in the sun.
• For Emergency Care (Mothers & Babies): The detective found that having the right tools (suction machines, oxygen) and trained chefs (doctors who know emergency procedures) was the key.

3. The Neighborhood Gap (Regional Disparities)

Ethiopia is huge, and the "restaurants" in different neighborhoods are in very different shapes.

• The Rich Neighborhoods: Some regions (like Sidama) had many restaurants that were well-stocked and ready.
• The Struggling Neighborhoods: Other regions (like Afar or Gambella) had very few restaurants, and the ones that existed were often missing half their ingredients.
• The Analogy: It's like one neighborhood having a fully stocked supermarket, while the next town over has a store with empty shelves and a broken freezer. The people in the second town are going hungry, not because they don't want food, but because the supply chain broke down.

4. The "Urban vs. Rural" Twist

Usually, we think big cities have better hospitals. But for some services (like C-Sections), the study found that urban facilities were actually less ready than rural ones.

• The Analogy: Imagine a city hospital that is so crowded with patients that the doctors are too busy to restock the medicine cabinet. Meanwhile, a small rural clinic has fewer patients, so they can keep their shelves perfectly organized. The city is "too big to fail," but it's failing because it's overwhelmed.

What Should We Do? (The Recommendations)

The authors suggest a few simple fixes to get the "restaurants" back on track:

1. Fix the Supply Chain: Make sure the "ingredients" (medicine, vaccines) actually get to the kitchen. No more empty shelves.
2. Train the Chefs: Keep teaching the doctors and nurses new recipes and emergency techniques.
3. Fix the Infrastructure: Ensure every kitchen has electricity (for the fridge) and running water.
4. Follow the Recipe: Make sure everyone is actually using the official guidelines, not just guessing.
5. Help the Struggling Neighborhoods: Send extra money and resources to the regions that are currently empty-handed.

The Bottom Line

Ethiopia has made great progress in the last 20 years, but there is still a long way to go to reach the global goals for saving mothers and children. The problem isn't just that there aren't enough hospitals; it's that many hospitals aren't actually ready to work.

By fixing the supply chains, training the staff, and ensuring the "kitchens" have the right tools, Ethiopia can turn those empty shelves into full meals for its people.

Technical Summary

1. Problem Statement

Despite significant progress in Reproductive, Maternal, Newborn, and Child Health (RMNCH) outcomes in Ethiopia over the last two decades, the country has not yet met the Sustainable Development Goals (SDGs) for maternal and child mortality. A critical gap exists between policy goals and the actual capacity of health facilities to deliver essential services. While previous assessments have tracked mortality rates, there is a need for a granular, facility-level analysis of service readiness—defined as the availability of trained personnel, essential medicines, equipment, infrastructure (WASH, electricity), and guidelines.

The study addresses the lack of comprehensive data on which specific factors (e.g., supply chain vs. human resources) drive readiness disparities across different facility types (hospitals vs. health posts) and regions, particularly in the context of the 2021-22 Ethiopia Service Provision Assessment (ESPA).

2. Methodology

The study utilizes a secondary data analysis of the 2021-22 Ethiopia Service Provision Assessment (ESPA) survey.

• Data Source: A nationally representative sample of 1,158 health facilities (excluding the Tigray region due to conflict). The dataset includes facility inventories, provider interviews, and client observations.
• Service Scope: The analysis focuses on six key RMNCH service areas:
  1. Family Planning (FP)
  2. Antenatal Care (ANC) and Prevention of Mother-to-Child Transmission (PMTCT)
  3. Basic Emergency Obstetric and Newborn Care (BEmONC)
  4. Comprehensive Emergency Obstetric Care (CEmOC)
  5. Child Vaccination
  6. Child Curative and Preventative Care
• Variable Construction: Tracer items were derived from WHO handbooks. Variables were coded as binary (available/functional) based on strict criteria:
  • Staff: Trained within the last 24 months or ever trained.
  • Guidelines: Reported available AND observed.
  • Equipment: Reported, observed, AND functioning.
  • Medicines: Reported available AND at least one unit valid (not expired).
• Analytical Approach:
  • Principal Component Analysis (PCA): Used to reduce dimensionality and identify underlying factors driving service readiness. PCA determined the weight of each tracer item based on the variance it explained, rather than using equal weighting.
  • Readiness Scoring: Facilities were assigned readiness scores based on PCA factor loadings and categorized into tertiles (Low, Medium, High).
  • Statistical Testing: Chi-squared tests were used to assess the significance of relationships between readiness levels and facility characteristics (type, ownership, location, region).

3. Key Contributions

• Methodological Rigor: The study moves beyond simple additive scoring by employing PCA, allowing for a data-driven identification of the most influential determinants of readiness for each specific service.
• Granular Disaggregation: It provides a detailed breakdown of readiness by facility type (e.g., Referral Hospitals vs. Health Posts) and ownership (Public vs. Private), revealing counter-intuitive findings (e.g., higher-level facilities often having lower readiness than lower-level ones).
• Regional Mapping: The analysis highlights specific regional disparities, identifying "hotspots" of low readiness (e.g., Afar, Gambella, Harari) versus regions with relatively better performance (e.g., Sidama, SNNP).
• Policy-Relevant Insights: By isolating specific drivers (e.g., supply chain for FP vs. human resources for ANC), the study offers targeted recommendations rather than generic calls for "system strengthening."

4. Key Results

A. Service Readiness Estimates

• Family Planning (FP): Significant disparity by facility type. General Hospitals, Primary Hospitals, and Health Centers showed very low readiness (74–87% low readiness), whereas Lower/Medium Clinics performed better. Private facilities had significantly higher readiness (56% high) compared to public facilities (30%).
• ANC & PMTCT: Only 166 out of 865 facilities offered both services, indicating a missed opportunity for integration. Sidama (60%) and SNNP (50%) had the highest proportions of high-readiness facilities. Private facilities again outperformed public ones.
• BEmONC: General Hospitals had the highest rate of low readiness (84%), while Medium Clinics had the lowest (3.3%). Public facilities were less ready (34% low) than private ones (18%). Amhara region showed high low-readiness (54%).
• CEmOC: Primary Hospitals (41% high readiness) outperformed General Hospitals (12% high readiness). Urban facilities had higher low-readiness (39%) than rural ones (12%), though the rural sample size was extremely small (n=4).
• Child Vaccination: Health Posts were the most ready (33% high readiness), while Health Centers and Hospitals were surprisingly less ready (65% and 57% low readiness, respectively).
• Child Curative Care: Health Centers had the lowest readiness (96% low), likely due to being overwhelmed by patient volume, whereas Health Posts were significantly more ready (14% low).

B. Principal Component Analysis (PCA) Findings

The PCA identified the primary drivers of variance for each service:

• Family Planning: Driven primarily by the availability of contraceptive commodities (pills, injectables, implants).
• ANC/PMTCT: Driven by trained personnel, adherence to clinical guidelines, and availability of diagnostic tests.
• BEmONC/CEmOC: Driven by the availability of essential drugs and emergency equipment (e.g., oxytocin, magnesium sulfate, incubators).
• Child Vaccination: Driven by infrastructure (cold chain, refrigeration) and vaccine availability.
• Child Curative Care: Driven by medications (antibiotics, antimalarials) and testing equipment.

5. Significance and Recommendations

The study concludes that Ethiopia's health system faces a "readiness paradox" where higher-level facilities (hospitals) often lack the basic readiness of lower-level facilities (health posts/clinics), likely due to resource misallocation, higher patient loads, and infrastructure deficits.

Strategic Recommendations:

1. Supply Chain Strengthening: Prioritize the continuous availability of essential commodities (contraceptives, emergency drugs, vaccines) to prevent stockouts.
2. Targeted Training: Focus on continuous professional development for staff, particularly in public facilities and underserved regions, with an emphasis on integrating ANC and PMTCT.
3. Infrastructure Investment: Upgrade facilities to ensure reliable electricity and water (WASH) to support cold chains and emergency care.
4. Regional Equity: Direct specific resources to low-performing regions (e.g., Afar, Gambella, Harari) to bridge the readiness gap.
5. Guideline Adherence: Enforce the use of standardized clinical protocols to improve care quality.

Limitations:
The study notes that the Tigray region was excluded due to conflict, limiting national generalizability. Additionally, the specific coding rules used (e.g., requiring equipment to be functioning and observed) differ from the official ESPA final report, which may affect direct comparability but increases the validity of the "functional readiness" metric.

In summary, this paper provides a critical evidence base for shifting Ethiopia's health strategy from broad coverage goals to targeted, facility-specific interventions that address the specific structural and resource barriers hindering RMNCH service delivery.