Background: Excessive weight gain and elevated blood pressure are significant risk factors for adverse pregnancy outcomes such as gestational diabetes, premature birth, and preeclampsia. More effective strategies to facilitate adherence to gestational weight gain goals and monitor blood pressure may have a positive health benefit for pregnant women and their babies. The impact of utilizing a remote patient monitoring system to monitor blood pressure and weight gain as a component of prenatal care has not been previously assessed.
Objective: The objective of this study is to determine the feasibility of monitoring patients remotely in prenatal care using a mobile phone app and connected digital devices.
Methods: In this prospective observational study, 8 women with low risk pregnancy in the first trimester were recruited at an urban academic medical center. Participants received a mobile phone app with a connected digital weight scale and blood pressure cuff for at-home data collection for the duration of pregnancy. At-home data was assessed for abnormal values of blood pressure or weight to generate clinical alerts to the patient and provider. As measures of the feasibility of the system, participants were studied for engagement with the app, accuracy of remote data, efficacy of alert system, and patient satisfaction.
Results: Patient engagement with the mobile app averaged 5.5 times per week over the 6-month study period. Weight data collection and blood pressure data collection averaged 1.5 times and 1.1 times per week, respectively. At-home measurements of weight and blood pressure were highly accurate compared to in-office measurements. Automatic clinical alerts identified two episodes of abnormal weight gain with no false triggers. Patients demonstrated high satisfaction with the system.
Conclusions: In this pilot study, we demonstrated that a system using a mobile phone app coupled to remote monitoring devices is feasible for prenatal care.
Keywords: mobile app; pregnancy; prenatal care; remote pateint monitoring.
©Kathryn I Marko, Jill M Krapf, Andrew C Meltzer, Julia Oh, Nihar Ganju, Anjali G Martinez, Sheetal G Sheth, Nancy D Gaba. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 18.11.2016.