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Published on: May 31, 2024
A Conversational Agent Using Natural Language Processing for Postpartum Care for New Mothers: Development and
Kirstin Leitner1, Clare Cutri-French2, Abigail Mandel3
1Department of Obstetrics and Gynecology, University of Pennsylvania, 3701 Market Street, 3rd Floor, Philadelphia, PA, 19104, United States, 1 651-492-3856.
Background:
The "fourth trimester," or postpartum time period, remains a critical phase of pregnancy that significantly impacts parents and newborns. Care poses challenges due to complex individual needs as well as low attendance rates at routine appointments. A comprehensive technological solution could provide a holistic and equitable solution to meet care goals.
Objective:
This paper describes the development of patient engagement data with a novel postpartum conversational agent that uses natural language processing to support patients post partum.
Methods:
We report on the development of a postpartum conversational agent from concept to usable product as well as the patient engagement with this technology. Content for the program was developed using patient- and provider-based input and clinical algorithms. Our program offered 2-way communication to patients and details on physical recovery, lactation support, infant care, and warning signs for problems. This was iterated upon by our core clinical team and an external expert clinical panel before being tested on patients. Patients eligible for discharge around 24 hours after delivery who had delivered a singleton full-term infant vaginally were offered use of the program. Patient demographics, accuracy, and patient engagement were collected over the first 6 months of use.
Results:
A total of 290 patients used our conversational agent over the first 6 months, of which 112 (38.6%) were first time parents and 162 (56%) were Black. In total, 286 (98.6%) patients interacted with the platform at least once, 271 patients (93.4%) completed at least one survey, and 151 (52%) patients asked a question. First time parents and those breastfeeding their infants had higher rates of engagement overall. Black patients were more likely to promote the program than White patients (P=.047). The overall accuracy of the conversational agent during the first 6 months was 77%.
Conclusions:
It is possible to develop a comprehensive, automated postpartum conversational agent. The use of such a technology to support patients postdischarge appears to be acceptable with very high engagement and patient satisfaction.
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