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 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.

An essential link in the cystic fibrosis (CF) newborn screening (NBS) process is communication of results. While this is described between NBS programs and primary care providers, data of this occurrence is limited with neonatologists. Neonatology providers represent a group caring for critically ill infants with conditions that can impact their ability to complete diagnostic testing after an abnormal NBS. Delays in testing can prolong time to diagnosis. We fielded a survey to assess neonatology provider knowledge and awareness of the Pennsylvania state CF NBS algorithm after an update occurred. Provider demographics, awareness of CF NBS update, and knowledge of the diagnostic testing process were measured. 86% of respondents were unaware of Pennsylvania CF NBS updates. Provider comfort with interpreting CF NBS results varied. 40% of providers identified the next diagnostic testing steps for a critically ill infant following an abnormal CF NBS. Our survey emphasizes the need for educating neonatology providers about CF NBS to improve knowledge and awareness of CF NBS algorithms to facilitate the early diagnosis of affected infants.