SMART Start: Digitization in prenatal care

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In this interview, Dr. Constanza Pontones, M.D. and Dr. Hanna Hübner answered our questions about the project and current state of digitalization in prenatal care.

Dr. Hübner, how can smart helpers like wearables and sensors help simplify prenatal care and ease the burden on the healthcare system?

Dr. Hanna Hübner: Despite all available options, digitization in prenatal care is making slow progress compared to other areas of society. There is presently no established prenatal home care structure, even though it would be fairly easy, convenient, and inexpensive for the expectant mother to collect most of the screening parameters at home and given the shortages in medical specialties in many rural areas.

The project goal is to research how smart devices could find their place in standard prenatal care in the future. Considerations include aspects of feasibility, ethical and health economic concerns.

Being pregnant is a somewhat unique and exceptional situation in a woman’s life. Dr. Pontones, were there concerns about the smart helpers and digital data transmission or worries of inadequate prenatal care?

Dr. Constanza Pontones: Studies have shown a high acceptance rate of at-home digital technologies during pregnancy. The user group is predominantly made up of smartphone-savvy young women. That is why the project creates direct application options for the implementation of smart sensor technology, which facilitates optimized health care provision by doctors, but also puts pregnant women in control over metabolic optimization. In the short to medium term, the goal is to develop and establish pragmatic and innovative technical solutions to revolutionize prenatal care. The long-term objective aims to drastically reduce the stress on the existing maternal and obstetric care structure by integrating the problem-solving approaches created in this project for the implementation of requisite sensory and analytical prenatal care measurements into the home realm and into existing healthcare processes.

The initial studies that are being conducted at the Women's Hospital of the University Hospital Erlangen do not replace the standard and routine tests and exams. All digital aspects are applied and investigated on top of the existing prenatal care.

In theory, the electronic (digital) maternity passport has been a component of the electronic patient record since 2022. Did the project come across this subject in any way?

Hübner: Gematik's electronic maternity passport hasn't really made its way into routine check-ups yet. Since potential users still don’t make use of the ePA and the digital maternity passport comprehensively, we cannot draw any conclusions on this subject at this point. It requires more education and information provision to prepare pregnant women for this digital option in the future.

What important insights have been gained to date?

Pontones: Initial analysis pertaining to the project shows a high level of acceptance and willingness to use digital devices in prenatal care. Women who admit to being anxious about their pregnancy are especially interested in using digital devices and taking a more active approach in monitoring their condition.

Findings from the first part of the project studies are already available. Two additional sub-studies are in the process of recruitment. We expect to have the first results throughout 2023.

What role can machine learning and artificial intelligence (AI) play in continuous care improvement?

Hübner: AI is increasingly important in clinical decision-making and can support staff in many medical fields. Several pregnancy approaches are already AI-based. Thanks to self-monitoring efforts, expectant mothers collect data pertaining to activity, metabolism, cardiovascular health, and sleep patterns, which provides a great and sufficient foundation. Data collected at routine prenatal checkups and innovative parameters make it possible to develop a monitored, trained machine learning or AI system. This would allow specialists to detect abnormalities in repeated measurements, pave the way for recommended actions, allow risk predictions or even facilitate the discovery of under-researched/undiscovered scientific correlations.