| Indicator ID | H8 |
|---|---|
| Indicator full statement | # of maternal, newborn and child health (MNCH) consultations performed with the use of an electronic clinical decision support system. |
Purpose
This indicator measures the adoption of electronic clinical decision support systems (CDSS) in maternal, newborn, and child health (MNCH) consultations where Tdh is conducting related activities. CDSS are digital platforms that offer healthcare providers evidence-based guidance for clinical decision-making, including diagnostic suggestions, treatment options, and patient management recommendations. Integrating CDSS into MNCH care aims to enhance the quality, consistency, and safety of care, particularly in resource-limited settings, by ensuring adherence to best practices and clinical guidelines.The indicator assesses the extent of CDSS usage in MNCH consultations and its potential impact on improving health outcomes for mothers, newborns, and children. See Indicator Digital MNCH consultations (% - outcome)
Definition
The total number of MNCH consultations (for maternal, newborn, and child health) in which healthcare providers utilized an electronic clinical decision support system (CDSS) supported by Tdh during a specified period. CDSS is defined as computerized system that provide real-time decision-making assistance during consultations by offering treatment protocols, and clinical actions guidance such as diagnosis, treatment plan and further management of the case in MNCH care based on internationally and/or nationally recognized protocols.
CDSS can be integrated into electronic health records (EHRs), or standalone digital tools used by healthcare providers during patient encounters.
How to collect & analyse the data
| What do we count? | Consultations |
|---|---|
| How to calculate the indicator's value | Sum of maternal, newborn, and child health (MNCH) consultations conducted with the use of an electronic clinical decision support system (CDSS) supported by Tdh during a specified period. |
| Data sources | Routine health facility data sources: Facility-based data capturing all consultations using CDSS tools, where available. Digital health platform records: Data from digital health platform that track the number of consultations conducted digitally using CDSS tools. Survey: In settings with limited means of communication, health worker surveys may be used to estimate the number of MNCH consultations where CDSS was used, based on the healthcare provider reporting. |
| Data collection methods and tools | Secondary data review (routine health facilities data, records) or survey |
| Disaggregation | Data should be disaggregated by type of health personnel (i.e., physician, nurse, midwife, community health worker), type of consultation (i.e., maternal, newborn, under-5 children), type of protocols (i.e., IMCI, PNC, ANC), type of health facility (i.e., community or primary health facility), and district, where appropriate depending on the data source. |
| Important considerations | Frequency and timing Monthly, quarterly, and annual reporting from health facilities, though this may only reflect facility-based care. Baseline, mid-term and endline studies through health facility assessment, REC. Survey: health worker surveys can be conducted every 1 to 2 years to supplement data where CDSS use is not routinely captured in the Health Information System (HIS). |
Limitations and precautions
This indicator serves as a proxy to assess the quality-of-care provision at the healthcare facility level, although it does not provide information on the availability of inputs like diagnostic testing or treatment. While it is assumed that consultations made through digital clinical decision support systems (CDSS) improve consultation quality and increase correct diagnosis rates, this indicator does not directly evaluate health outcomes or patient satisfaction from digital MNCH consultations.
The indicator measures only those consultations utilizing digital CDSS, excluding non-digital consultations, which are not necessarily of lower quality. This focus may overlook the quality and frequency of care provided in resource-constrained settings. Additionally, dual use of paper and digital records may lead to reporting inconsistencies. Some healthcare providers may underreport or fail to record CDSS usage due to time constraints or unfamiliarity with the technology, resulting in data gaps.
Disparities in access to digital infrastructure—such as unreliable internet, electricity, or functional digital devices—can influence this indicator, with rural areas often showing lower adoption rates. Effective use of digital tools requires healthcare workers to receive high-quality training, technical support, motivation, and acceptance. Solely analyzing this indicator may not reveal gaps in facility readiness and skills, which could ultimately affect quality of care. Follow-up assessments to gauge training retention and practical application are vital.
The effectiveness of CDSS in enhancing MNCH outcomes also depends on the system's capabilities and its integration into clinical workflows. While CDSS can improve decision-making, there is a risk of overreliance on digital tools, potentially diminishing providers' critical thinking skills. It is crucial that CDSS complements rather than replaces clinical expertise, with appropriate emphasis during training.
Comprehensive analysis of this indicator should include the motivation, restraint, and commitment of healthcare workers regarding digital tools. Furthermore, the availability of other health system resources—such as essential medicine stock, rapid test availability, and the number of qualified staff using the tool—should be factored in to assess the actual quality of care delivered.
Digital MNCH consultation tools may be concentrated in urban areas, potentially neglecting healthcare workers in rural or underserved regions. Disaggregation by geographical location and facility type is essential to ensure that digital health literacy initiatives reach all relevant healthcare workers in Tdh’s operational area. Health staff turnover and rotation across facilities should also be considered when analyzing the indicator's impact and planning further actions. Collaborating closely with technology providers, government ministries, and international organizations is advisable to scale up digital health initiatives, particularly in rural and underserved areas.
Note: Always consider the demographic context, as it may be affecting the denominator (i.e., IDPs, population movements, healthcare center attendance etc...).
What further analysis are we interested in?
This indicator allows to track the adoption and integration of CDSS digital tool into routine MNCH services, comparing usage and disparities rates across geographic areas and facility types (i.e., public or private clinic, community or primary health care level). It can reveal barriers to digital health tools utilization to be further investigated. More so, it can support the project manager decision-making regarding the expansion of digital health tools within the same health facility and/or district and/or state.
To understand the impact of the use of digital MNCH consultation tools on the service delivery and outcomes, we can cross-analyse with other health indicators (i.e., maternal and neonatal mortality rates, proportion of emergency referrals, and other child health indicators) compared to baseline and over time. To assess the improvement of childhood illnesses management and patient satisfaction, this indicator can be correlated with other indicator such as MNCH consultations attendance at the health facility level (i.e., ANC and PNC attendance rate, number of follow-up under-5 years old consultations).
Provider satisfaction and training needs should be evaluated with a standardized tool used during technical supervision and/or a qualitative study (i.e., survey, interview).
It might be interesting to cross-analyse this indicator with the total number of MNCH consultations conducted during the same specified period (i.e., from non-digital patients registers at the health facility level) to understand the proportion of MNCH consultations where a CDSS was used and enable the analyst to assess its impact.
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 deploy and integrate the digital tools, collect and interpret the data.
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 MNCH service delivery.
Global strategy on Digital Health 2020-2025. Available at: https://www.who.int/docs/default-source/documents/gs4dhdaa2a9f352b0445bafbc79ca799dce4d.pdf (Accessed: 11 September 2024).