Model Description:
A Bayesian model to predict the number of maternal deaths. This models takes into consideration the Janani Suraksha Yojana scheme and its benefits while predicting Maternal Deaths. It also considers other parameters like number of hospitals, ambulances, etc. Dependency relationships between the nodes are established from government reports and published literature.
Node / Attribute:
The above model is based on the following nodes. The color scheme used represents the type of node/attribute. (Purple – Independent node; Orange – Dependent node; Red – Target node)
| Node / Attribute | Description | Data Source |
| Estimated Total Pregnancies | Estimated number of pregnant women | KAG 2020-21 |
| Number of Beneficiaries Availed Janani Suraksha Yojana (JSY) | Number of women enrolled under the scheme | KAG 2020-21 |
| Number of Primary Health Centers compliant with Indian Public Health Standards | Number of Primary Health Centers compliant with Indian Public Health Standards | KAG 2020-21 |
| Number of pregnant women registered for antenatal care (ANC) | Number of pregnant women registered for antenatal care (ANC) | KAG 2020-21 |
| Number of women registered for ANC within 1st trimester | Number of women registered for ANC within 1st trimester | KAG 2020-21 |
| Number of Home Deliveries attended by Skilled Birth Attendants (SBA) | Number of Home Deliveries attended by Skilled Birth Attendants (SBA) | KAG 2020-21 |
| Number of Ayush Hospitals | Number of Ayush Hospitals | KAG 2020-21 |
| Number of Ambulances | Number of Ambulances | KAG 2020-21 |
| Number of institutional deliveries | No. of pregnant women delivering in a hospital | KAG 2020-21 |
| Number of deliveries at home | No. of pregnant women delivering at home | KAG 2020-21 |
| Number of Beneficiaries who received the Madilu kit | Number of Beneficiaries who received the Madilu kit | KAG 2020-21 |
| Maternal Mortality Rate (Target Variable) | Number of prenatal/postnatal deaths happened | KAG 2020-21 |
Intervention Modeling
It sets the network variables to specific levels, to track the changes in the target variable in the network. For instance: If we fix the value of the variable ‘Number of Beneficiaries availed Janani Suraksha Yojana_1338’ to ‘high’, then we would study the impact of this intervention on the target variable i.e., “Maternal Deaths” of the network across varieties of Taluks in Karnataka.
| Intervention Code | Intervening Node | Description | Ease of Intervention [1-most difficult, 5-easy] | Total Models Related | Related Models | Domains | Data Stories impacted upon intervention |
| I1 | Number of Beneficiaries availed Janani Suraksha Yojana | Promoting the JSY scheme in order to be able to give more medical care to Pregnant Women will reduce the number of maternal deaths. Beneficiaries can be increased by spending more resources on deploying more ASHA workers and spreading awareness amongst the general public. | 3 | 4 | 1. Child Malnutrition 2. Child Stunting 3. Child Wasting 4. Severe Anemia in Pregnant Women | Health | 1. Predicted Change In Maternal Deaths After Making Number Of Beneficiaries Under JSY to be high. 2. Maternal Mortality Rate story post intervention including Stress Modelling |
| I2 | Number of Primary Health Centers(PHC) compliant with Indian Public Health Standards | Increasing the number of PHCs to boost the reach of medical services to more women | 3 | 4 | 1. Child Malnutrition 2. Child Stunting 3. Child Wasting 4. Severe Anemia in Pregnant Women | Health | 1. Predicted Change In Maternal Deaths After Making number of PHC’s to be High |
| I3 | Number of ANC Health checkups undergone by Pregnant Women | Intervention to check if all pregnant women have undergone a maximum of 4 ANC checkups | 4 | Health | |||
| I4 | Number Of Aayush Hospitals | Increasing the number of Aayush hospitals will provide easier access to medical resources for pregnant women. Also as the number of hospitals increases, due to immediate medical attention available in case of any complication during pregnancy maternal deaths will go down. | 2 | 3 | 1. Child Stunting 2. Child Wasting 3. Severe Anemia in Pregnant Women | Health | |
| I5 | Number of Ambulances | With an increase in the number of ambulances, pregnant women’s transport to the nearest hospital/medical clinic is made easier. This facilitates immediate medical attention available in case of any complication during pregnancy and will help maternal deaths go down. | 4 | 2 | 1. Child Stunting 2. Child Wasting | Health | |
| I6 | Number of women registered for ANC within 1st trimester | As more and more women register for ANC in the first trimester, medical care and attention can be given from the beginning. With help of regular tests, any problems can be perceived in the earlier stages only and can be cured. | 4 | 1 | 1. Severe Anemia in Pregnant Women | Health | |
| I7 | No. of institutional deliveries_1350 | By promoting institutional deliveries through schemes and ads not limited to but including JSY we can aim at educating women on child nourishment and the care to be taken to ensure nourishment through counseling by doctors and professionals at the hospitals. | 4 | 4 | 1. Maternal Deaths 2. Child Malnutrition 3. Child Stunting 4. Child Wasting | Health |
Variable Correlation Matrix :
DISCLAIMER: AI predictive models are meant to support and augment expert decision-making, and not a replacement for the same. It is important for AI model predictions to be vetted by domain experts before committing to action