Remote patient monitoring (RPM) has become important for caring for pregnant women, especially those with health risks like high blood pressure or diabetes during pregnancy. RPM collects health data from patients at home and sends it to doctors. This means fewer office visits and quicker medical help when needed.
One notable program in the US is Connected Maternity Online Monitoring (Connected MOM) by Ochsner Health in Louisiana and Mississippi. It gives women tools like wireless blood pressure cuffs and digital scales. These devices send data to electronic medical records through smartphone apps like iHealth MyVitals and MyOchsner. Doctors regularly check this data to watch blood pressure and weight. If readings go beyond safe limits, alerts prompt doctors to review or act quickly.
The Connected MOM program has shown good results. It lowered early births by 20% compared to normal care. Women with pregnancy-related high blood pressure were twice as likely to complete follow-up blood pressure checks after birth. Also, follow-up visits for babies almost doubled, showing better care for mothers and newborns after delivery.
These remote monitoring systems help clinics too. For every 1,000 patients in Connected MOM, a doctor’s clinic can see about 0.6 more full-time patients. This lets healthcare staff focus on more serious cases or expand services. The program also helps many Medicaid patients, supporting more equal care.
The United States spends more money per person on maternal healthcare than other countries but has more problems during pregnancy. Programs like Connected MOM may lower costs and improve care quality and access.
The Centers for Medicare & Medicaid Services (CMS) started the Transforming Maternal Health (TMaH) Model in January 2025. It works in 15 states like California, Illinois, and Wisconsin. This model looks at the whole health of pregnant women, including physical, mental, and social needs during and after pregnancy. It will run for 10 years.
A key part of TMaH is getting more midwives, doulas, and perinatal Community Health Workers (CHWs) to help. They support things like cesarean sections, labor length, and mental health after childbirth. The program uses patient safety bundles, which are guidelines for conditions like pregnancy-related high blood pressure and drug use problems. These help reduce risks and improve safety.
In TMaH, remote monitoring helps manage risks like diabetes and high blood pressure by allowing patients to be watched at home. This lowers how often they must visit clinics in person. It also cuts down problems like travel, childcare, and scheduling. Providers can act early if the data shows possible problems.
Mental health is also a focus. The model requires regular checks for depression and anxiety during and after pregnancy. It also screens for social needs like housing and food insecurity. Pregnant women get help from community groups and social services. This broad approach addresses many factors that affect pregnancy outcomes.
TMaH works to reduce differences in care for different racial and ethnic groups. States in the model must create Health Equity Plans and train healthcare providers in cultural understanding. The goal is respectful care for all women, improving results for groups who often get less help.
Artificial intelligence (AI) and automation play an increasing role in maternal healthcare. AI can analyze a lot of patient data from remote monitoring, medical records, and social factors. This helps find patients at higher risk and predict problems. It also suggests tailored care plans.
For instance, AI can use patterns in monitoring data to predict early labor or blood pressure problems. This way, doctors can focus on patients who need immediate care. AI also reduces work for providers by collecting routine data and only flagging important alerts.
Automated workflows make life easier for medical staff. Systems can manage appointment scheduling based on patient risk and monitoring data. This lets staff spend more time helping patients directly. Virtual assistants can remind patients about appointments, explain health information, and check symptoms. This keeps patients on track with their care plans.
In call centers and clinics, AI phone systems answer common questions about appointments, medicine, or device use. They work all day and night, letting staff focus on urgent or complex calls.
Linking remote monitoring data with electronic health records is key. Real-time syncing means doctors have all clinical, behavioral, and social information in one place. This helps teams make better decisions and improves patient care.
Invest in Remote Monitoring Infrastructure: Clinics need to buy trustworthy devices like wireless blood pressure cuffs and digital scales that work with patient smartphones. They should test how well these devices connect with electronic health record systems like Epic or Cerner for smooth information flow.
Ensure Training and Support: Doctors, staff, and patients must learn how to use devices, apps, and understand alerts. Support like help lines or in-person tech help spots can reduce difficulties for patients.
Leverage AI for Care Coordination: Use AI to watch patient data, find risks early, and help doctors make decisions. Automate routine tasks like scheduling and patient contact to lessen staff workload.
Address Equity and Access: Make plans to include Medicaid and low-income patients in digital care programs. Work with community groups and expand roles for doulas and community health workers to provide culturally appropriate care.
Monitor Program Outcomes: Track results like preterm birth rates, blood pressure problems, patient follow-up rates, and clinic efficiency. Regular checks help improve and grow programs.
Stay Compliant and Secure: Keep patient data private and follow HIPAA rules. IT teams need to protect information, especially when using remote monitoring and AI tools.
Ochsner Health’s Connected MOM program shows how digital tools can improve maternal care in hospitals that serve different groups of people. Patients get connected devices, and their health data goes through smartphone apps right into the Epic electronic medical record. This has cut down on frequent visits in Louisiana and Mississippi, where many mothers face higher health risks.
In 2022, more than 2,250 women joined Connected MOM, a 32% increase from the year before. The program watched patients who were 10 to 20 weeks pregnant. The continuous monitoring helped doctors find hidden high blood pressure early. These efforts led to fewer early births and better follow-up care after delivery.
Patients said the program reduced their stress and gave them confidence by monitoring their health closely. Doctors found their work easier because they had fewer routine visits and more time to help high-risk patients.
The program also depends on funding help from groups like the National Institutes of Health (NIH) and support from the Federal Communications Commission (FCC). This helps keep the program running and growing, especially in rural areas and for patients on Medicaid. Other hospitals and health systems can use this example to set up similar remote monitoring and connected care programs.
Digital tools like remote monitoring and connected care programs can help improve pregnancy health in many parts of the US. They let doctors watch patients’ health constantly and talk with them even if they are far away. This means fewer in-person visits, safer care, and better help for high-risk pregnancies.
The CMS Transforming Maternal Health model combines these tools with extra help from midwives and social services. It looks at the full health needs of pregnant women. AI and automation add to this by helping analyze data, keep patients involved, and make clinics run better. This lets medical practices manage resources well and improve care for mothers and babies.
For those managing medical clinics or IT systems, using these technologies and care programs offers ways to provide better, more affordable maternal care that fits national health goals and helps local communities.
Atrium Health’s AH-HaH program combines in-person and virtual consultations, remote patient monitoring kits, and seamless integration with electronic health records (EHR) to deliver hospital-level care at home. This approach improves patient outcomes, provides quality care, and reduces hospital costs by leveraging technology for continuous remote monitoring and coordinated care delivery.
Concert Health integrates virtual behavioral health services with primary care using the Collaborative Care Model (CoCM). This model facilitates evidence-based behavioral treatment access, improves clinical outcomes, and creates a transdisciplinary care experience for patients and physicians by virtual collaboration and data-driven care coordination.
Geisinger Health System uses augmented intelligence and predictive analytics to streamline care coordination, optimize physician resources, and enable early disease detection. This technology-driven approach advances value-based care by targeting key populations through predictive modeling to improve chronic disease management and resource utilization.
Hattiesburg Clinic employs data-driven decision making supported by technology to deliver highly coordinated quality care. Their adoption of digital tools enhances clinical outcomes, access to care, and patient experience, showcasing the power of analytics in supporting value-based care models in independent physician groups.
Ochsner Health’s Connected Maternity Online Monitoring (MOM) program remotely monitors pregnant patients using digital tools, which reduces the need for in-person visits. This program improves maternal health outcomes through continuous virtual monitoring and timely interventions powered by connected technologies.
Omada Health supplements chronic care management with data-powered human coaching, connected devices, and enhanced care coordination. The integration of AI-driven data analytics guides personalized interventions, while coaches provide continuous behavioral support, improving patient engagement and health outcomes.
Oshi Health combines digital symptom tracking, 24/7 messaging, and a multidisciplinary care team to collaboratively create and iterate care plans. This hybrid model supplements traditional GI care by providing high-frequency, high-touch virtual support between office visits, enhancing patient outcomes and reducing avoidable costs.
Both One Medical and Mayo Clinic implement digital care models that incorporate virtual care pillars such as remote monitoring, telehealth consultations, and integrated care coordination, which improve chronic care management. Their approaches focus on accessibility, patient experience, and continuous monitoring to optimize health outcomes.
RPM provides continuous health data collection from patients outside clinical settings, enabling early detection of issues, timely interventions, and enhanced care coordination. This technology empowers chronic care coaching by healthcare AI agents through data-driven insights and personalized guidance between visits.
The AMA ChangeMedEd® Artificial Intelligence in Health Care Series educates learners about AI’s strengths and limitations in healthcare. This knowledge helps providers understand how AI-powered tools can support chronic care coaching by enhancing decision-making, patient engagement, and care delivery efficiency, while identifying appropriate use cases and potential challenges.
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