Model Description:
A combination of H1.1 and H1.2 models with Maternal Deaths as the target variable. Restricted to 15 nodes on Netica.
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 |
| No. of pregnant women tested for Hemoglobin 4 or more times | Number of women tested four or more times for Hemoglobin | |
| Number of Pregnant women treated anemia (Hb<7) | Number of Pregnant women treated with anemia | 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 Hospitals | Number of 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 |
| Number of PW having severe anemia (Hb<7) | Number of Pregnant Women having severe anemia | |
| Maternal Deaths (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 Impacted | Models Impacted | Domains Impacted | Data Stories impacted upon intervention |
I1 | Number of Beneficiaries availed Janani Suraksha Yojana _1338 | Increasing the number of beneficiaries that avail the JSY scheme in order to assess its impact in reducing anemia amongst pregnant women. Beneficiaries can be increased by spending more resources on deploying more ASHA workers and spreading awareness amongst the general public. 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. Maternal Deaths 2. Child Malnutrition 3. Child Stunting 4. Child Wasting | Health | 1. Pregnant women & Lactating mothers – Anaemia |
| I2 | Number of pregnant women registered for antenatal care (ANC)_1342 | Increasing the number of pregnant women registering for ANC to determine how important of a factor it should play in the JSY scheme and how much this impacts in reducing severe Anemia. This can be implemented by making ANC registration the focal point of the JSY scheme. | 4 | 1 | 1. Maternal Deaths | Health | |
| I3 | Number of women registered for ANC within 1st trimester_1343 | Increasing the number of women registering for ANC within the 1st trimester to determine how important of a role registering for ANCs early plays in reducing severe Anemia and this too can be implemented via the JSY scheme and making early registration for ANCs a priority by the ASHA workers. | 4 | 1 | Maternal Deaths | Health | |
| I4 | Number of pregnant women who received 4 or more antenatal care check-ups_1344 | Increasing the number of women receiving at least 4 ANC checkups to determine the impact of frequent ANC checkups in reducing severe Anemia and this too can be implemented via the JSY scheme and strict vigilance by the ASHA workers on the women that have registered under the scheme. | 2 | 1 | Maternal Deaths | Health | |
| I5 | 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 increase, 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 Severe 3. Anemia in Pregnant Women | Health | |
| I6 | Number of Ambulances | With an increase in number of ambulances, pregnant women’s transport to 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 | |
| I7 | 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 | |
| I8 | 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 |
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