Predictive Model uses EMR Records to Estimate Changes in Pregnancy and Birth Rates during COVID-19 Successfully

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With the help of EHR optimization, a predictive model predicted an initial decline in births during the COVID-19 pandemic successfully. 

The study published in JAMA Network looked at all pregnancy episodes within the Electronic Health Records from 2017 retrospectively and to 2021 prospectively. EDD management modeling techniques were used in the analysis to project anticipated delivery volumes after the COVID-19 pandemic.

It projected an initial decline in births starting in November of 2020 until spring of 2021. Researchers have found the prediction to be accurate. Following March 15, 2020, there has been a decline in pregnancy episodes by 14%.

The model also suggests that a surge in birth rate can be anticipated for the summer of 2021. Based on annual trajectories derived from the prior five years of institutional data, the anticipated births may even exceed the anticipated birth volume. 

The researchers involved in the study also analyzed factors that may have contributed to lower birth rates. Decrease in reproductive endocrinology services during the mandated shutdown and increase in preterm births were found to be the major reasons behind the dip in birth rates during the pandemic.

Why are predictive models of pregnancy important for healthcare executives?

Anticipatory planning for births is very crucial for health care systems to anticipate increasing or decreasing patient volumes and staffing needs. With the help of such predictions, healthcare executives can better prepare for periods of high and low delivery volume. They are also able to anticipate maternal and obstetric care needs, as well as neonatal intensive care and pediatric subspecialty volumes. This allows for the overall improvement of service delivery to patients, helping to ensure the best patient care possible.

Population dynamics are also important for governments, policymakers, economists, and businesses because fluctuations in populations are critical variables in their ability to plan appropriately to make investments, ensure social well-being, and anticipate economic patterns.

Similar to the findings, other centers in the US also reported decreased preterm birth rates after the onset of the pandemic. The study is a breakthrough in how it has used novel modeling techniques to project birth rate volumes with relative certainty, and its success will encourage predictive analysis in other healthcare areas as well.

There are some limitations also that have been outlined in the study. To get access to the complete study, you can visit thisĀ link.