| Indicator ID | H1 |
|---|---|
| Indicator full statement | % of births assisted by skilled birth attendants. |
Purpose
| Importance | This indicator assesses the extent of women's utilization of skilled birth care services, whether delivered at the health facility or community level where Tdh is conducting related activities. This indicator aims to assess maternal health care coverage and identify gaps in access to qualified care. It is often used for comparisons over time and between regions. Timely and skilled attendance during childbirth is critical to reducing maternal and neonatal mortality. Given the challenges in accurately measuring maternal mortality in real-time, this indicator serves as a proxy for evaluating maternal health service coverage and quality, aligning with global health goals such as the Sustainable Development Goal (SDG) 3.1 to reduce maternal mortality. This indicator combined with other appropriate measurement may contribute to capture the impact of interventions aimed at improving maternal health coverage. |
|---|---|
| ToC pathway | This indicator directly refers to the Tdh’s Theory of Change (ToC) as it aims to contribute to the three inter-related pathways of change, namely 1) local health system, 2) communities, and 3) mothers, children, and their families. |
| Related services | It is used depending on the service provided by Tdh. This indicator can be linked to the use of Tdh’s SIMSONE project and IeDA maternity. |
Definition
The proportion of live births attended by skilled health personnel [within a specified period, irrespective of delivery location (facility or home)]:
The proportion of live births attended by skilled birth attendants (midwives, doctors, or nurses with midwifery skills) during a specified period is the ratio of the number of births attended by skilled personnel to the total number of births among Tdh’s target population.
Skilled health personnel, as defined by the WHO, possess the training and proficiency to manage uncomplicated pregnancies, childbirth and the immediate postnatal period; and recognize complications requiring referral or intervention.
Definitions of skilled health personnel vary between countries. Therefore, each delegation should use the current definition as per Ministry of health. This definition usually excludes traditional birth attendants (TBAs), dai, matrons, even if trained.
Live birth is the birth of a foetus after 22 weeks’ gestation or weighting 500 g or more that shows signs of life -breathing, cord pulsation or with audible heartbeat. This cut-off point refers to when the perinatal period commences and aims at confining the definition for pragmatic purposes.
How to collect & analyse the data
| What do we count? | Births |
|---|---|
| How to calculate the indicator's value | Household Survey Method: Number of births attended by skilled health personnel ×100 in a defined period / Total number of live births in the same geographic area and reference period. Facility-based Data Method: Number of births attended by skilled health personnel in a defined period ×100 / Expected live births (or expected deliveries) based on target population estimates or crude birth rate in the same geographic area and reference period. Note on Live and crude birth rate: Evaluators generally count all births, but usually use only live births to calculate this indicator because of the difficulty in obtaining information about non-live births. Where data on the number of live births are unavailable, rough approximations can be made using census data for the total population and crude birth rates in a specified area as follows: Total expected births = population x crude birth rate. In settings where the crude birth rate is unknown: Total expected births = female of reproductive age x general fertility rate The two indicators (population-level and facility-level) are not comparable. |
| Data sources | Secondary data (Health statistics) or mothers |
| Data collection methods and tools | Population based (household) survey such as the Demographic Health Surveys (DHS), or the Multiple Indicator Cluster Surveys (MICS) as primary data sources due to their robustness in low-resource settings: This indicator is best calculated from a survey, since vital registration systems are lacking in Tdh priorities countries. Population based survey: a cross-sectional household survey of mothers 15 to 49 years old who had a live birth in a given time period preceding the survey. A multi-stage, stratified sampling design will be used to select mothers from eligible women. Sampling of households will be based on probability proportional to size (PPS) thus ensuring villages with bigger populations had more sampled households. A structured questionnaire (adaptation of demographic health survey questionnaire) will be used to collect data from respondent. Routine facility information systems are another possible data source where health information systems are more or less comprehensive, administrative estimates are also possible based on expected births for the denominator. |
| Example of survey questions | |
| Disaggregation | Data should be stratified by age, place of delivery (home or facility), where appropriate depending on the data source. |
| Important considerations | Frequency and timing: Population based surveys: project baseline then biennial (every 2 years). More frequent surveys are probably not desirable because the survey periods may overlap, and sampling error makes it difficult to assess changes. Routine data sources: monthly, quarterly, and annual monitoring at delegation level. |
Limitations and precautions
The indicator for measuring skilled birth attendance is important for assessing maternal and newborn care during childbirth, but it may not fully reflect access to high-quality care, especially in cases of complications. To reduce maternal mortality, skilled health personnel must be both present and properly equipped with tools and referral options.
A challenge is the variation in the definition of "skilled health personnel" across countries due to differences in training, scope of practice, and resources. Even with comparable rates of skilled attendant deliveries, disparities in provider competencies and resources can affect care quality, especially in emergencies. The ability to manage complications depends on the working environment, including access to necessary equipment and infrastructure.
Further, issues like staff overload or substandard practices can affect care quality within healthcare facilities. Comparisons between countries or regions may be misleading due to differences in training, skill levels, and resources.
Data quality is also a concern. Household surveys rely on respondents’ recall, which can lead to misclassification of attendants, introducing inaccuracies. Health facility data may be incomplete, as they often miss deliveries that occur outside formal healthcare settings. Accurate data requires proper recording, standardized definitions, and good data management practices.
Relying solely on the presence of skilled birth attendants oversimplifies maternal health. This measure overlooks important factors like emergency obstetric services, postpartum care, and stillbirths, limiting its scope. Additionally, rural, remote, and marginalized populations may lack access to skilled care or face financial barriers, which this indicator often fails to capture, masking inequalities in care access.
What further analysis are we interested in?
Cross-analyzing the utilization of services reflected by the skilled birth attendance indicator with the availability, accessibility, and acceptability of obstetric care offers a more complete view of maternal health in a region. This includes examining the number of health facilities, skilled personnel, and their distribution, as well as barriers like geographic distance, costs, cultural factors, and gender-sensitive service provisions.
Skilled birth attendance measures health care utilization, indicating the proportion of the population receiving care. When combined with indicators like Antenatal Care (ANC) coverage, it provides a fuller picture of service utilization and provision. Cross-analysing these with availability of emergency obstetric services (e.g., C-section rates) can expose gaps between potential and actual care. For instance, high rates of skilled attendance but low access to emergency services suggest that while basic care is available, critical services for complications are lacking.
Sociocultural norms and beliefs should also be considered, as they influence access to care. Qualitative research into cultural and gender-related health behaviours can help interpret the data more accurately.
Comparing skilled care coverage across regions or over time allows for trend and equity analysis. Additionally, systemic barriers such as weak governance or poor funding may further limit the health system's ability to train, retain, and support skilled health personnel.
Additional guidance
Resources: Under the technical assistance of HQ, Tdh M&E and operational teams in each delegation should work closely with health authorities to collect and interpret the data. Countries with limited resources to conduct household surveys, should consider using a consultant or facility-based estimates, though less reliable can provide interim insights.
Countries with limited health system infrastructure may consider partnerships with international organizations (e.g., WHO, UNICEF) and academic institutions to support capacity-building for data collection and maternal health service delivery.
Indicator global monitor and strategies:
Births attended by skilled health personnel. Available at: https://monitor.srhr.org/related-sheets/MonitorIndicatorsheetBirthsattendedbyskilledhealthpersonnel.pdf (Accessed: 11 September 2024).
Births attended by skilled health personnel (%) World Health Organization. Available at: https://www.who.int/data/gho/data/indicators/indicator-details/GHO/births-attended-by-skilled-health-personnel-(-) (Accessed: 10 September 2024).
Proportion of births delivered in a health facility (facility births) (%) World Health Organization. Available at: https://www.who.int/data/gho/data/indicators/indicator-details/GHO/institutional-births-(-) (Accessed: 10 September 2024).
Proportion of births delivered in a health facility (facility births) (%) World Health Organization. Available at: https://www.who.int/data/gho/data/indicators/indicator-details/GHO/institutional-births-(-) (Accessed: 10 September 2024).
Neonatal mortality rate (0 to 27 days) per 1000 live births) (SDG 3.2.2) World Health Organization. Available at: https://www.who.int/data/gho/data/indicators/indicator-details/GHO/neonatal-mortality-rate-(per-1000-live-births) (Accessed: 10 September 2024).
Ending preventable maternal mortality (EPMM): A renewed focus for improving maternal and newborn health and well-being World Health Organization. Available at: https://www.who.int/publications/i/item/9789240040519 (Accessed: 10 September 2024).
Strategies toward ending Preventable maternal mortality (EPMM) World Health Organization. Available at: https://www.who.int/publications/i/item/9789241508483 (Accessed: 10 September 2024).
Maternal mortality rates and statistics - UNICEF data. Available at: https://data.unicef.org/topic/maternal-health/maternal-mortality/ (Accessed: 10 September 2024).
Further readings:
The DHS program, The DHS Program - Available Datasets. Available at: https://dhsprogram.com/data/available-datasets.cfm (Accessed: 10 September 2024).
Berti, P.R. et al. (2021) Using DHS and MICS data to complement or replace NGO Baseline Health Data: An exploratory study, F1000Research. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8145218/ (Accessed: 10 September 2024).
Hancioglu, A. and Arnold, F., Measuring coverage in MNCH: Tracking progress in health for women and children using DHS and Mics household surveys, PLOS Medicine. Available at: https://journals.plos.org/plosmedicine/article?id=10.1371%2Fjournal.pmed.1001391 (Accessed: 10 September 2024).
Factors associated with skilled birth attendance in 37 low- ... Available at: https://www.thelancet.com/journals/langlo/article/PIIS2214-109X(24)00145-1/fulltext?rss=yes (Accessed: 10 September 2024).