Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

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.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12223682PMC
http://dx.doi.org/10.2196/58454DOI Listing

Publication Analysis

Top Keywords

conversational agent
24
patient engagement
12
postpartum conversational
12
patients
11
agent natural
8
natural language
8
language processing
8
support patients
8
agent months
8
time parents
8

Similar Publications

Large language models (LLMs) represent a transformative advance in artificial intelligence, with growing potential to impact chronic kidney disease (CKD) management. CKD is a complex, highly prevalent condition requiring multifaceted care and substantial patient engagement. Recent developments in LLMs-including conversational AI, multimodal integration, and autonomous agents-offer novel opportunities to enhance patient education, streamline clinical documentation, and support decision-making across nephrology practice.

View Article and Find Full Text PDF

The adolescent mental health crisis is compounded by a shortage of mental health services, which mobile health apps may alleviate. We assessed the feasibility and acceptability of the Wysa app (a commercially available app containing cognitive behavioral therapy-based digital modules and an artificial intelligence-based conversational agent) among 13- to 18-year-old adolescents recruited from a primary care clinic in New York City and online from March to June 2022. We assessed adolescent engagement in the Wysa app over a 3-week period.

View Article and Find Full Text PDF

Background: Young adults face emotional problems in their daily lives. Considering that youth are prevalent among mobile internet users, it would be helpful if functions that can intervene in young people's depression and anxiety can be designed based on short video apps. Large language model (LLM)-based AI conversational agents based on short video apps may play an important role in intervening in young adults' negative emotions.

View Article and Find Full Text PDF

The global population of older adults is growing. Older adults are more vulnerable to infectious diseases compared to younger adults. Vaccines are available to protect older adults against several infectious diseases, yet their uptake remains sub-optimal.

View Article and Find Full Text PDF

The RTK-RAS signaling cascade is a central axis in colorectal cancer (CRC) pathogenesis, governing cellular proliferation, survival, and therapeutic resistance. Somatic alterations in key pathway genes-including KRAS, NRAS, BRAF, and EGFR-are pivotal to clinical decision-making in precision oncology. However, the integration of these genomic events with clinical and demographic data remains hindered by fragmented resources and a lack of accessible analytical frameworks.

View Article and Find Full Text PDF