More details on our research

MP: Hey there, your research sounds motivating. Could you elaborate on the approach?

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Hi MP!

Thanks for your interest!  

The current mathematical model people use to predict baby weight is called the Johnson-Toshasch Formula, which is highly inaccurate and unable to predict low birth weight and macrosomia (too big) babies, especially in Asian population.  

To remedy this, we are planning to create a more precise and user-friendly formula, and develop clinical pathways for midwives and nurses in the community health centers. They will be able to immediately practice in a manner that improves outcome (refer high-risk pregnancies) and reduce cost (retain-low risk pregnancies). This will be beneficial for the mothers, babies, and the entire health system. 

We plan to work with secondary data. I currently have data from 350 pregnancies and deliveries in Indonesian primary care, and was able to develop more than 10 mathematical models that already work better than Johnson’s Formula.  

What we plan to do is to collect more than 2500 pregnancy data from medical record in hospitals and primary care centers in Indonesia, to have the statistical power to detect and separate high risk pregnancies. This data collection will also allow us to conduct model selection processes. This means we can pinpoint THE best model that yield the best outcome and highest cost savings – among all the mathematical models we generate. 

I start with Indonesia because I am familiar with the system and are able to quickly respond to any field problems in data collection. However, once the model is generated, it is very easy to adjust the model to reflect conditions in other countries by simply using data other people has published.  

I hope this clears out the confusion. If you need more information I’d be happy to share! 

Best regards  

Chris