Maternal health expert feedback on the attributes of a predictive analytics tool to improve pregnancy-related cardiovascular and mental health outcomes in the United States

Figures & data

Table 1. Demographic Characteristics of Interviewed Experts

#	Training	Specialty/Focus	Practice Type/Setting	Expertise
1	MPP	Patient advocacy	Nonprofit	Maternal health policy and advocacy
2	MPP	Patient advocacy	Nonprofit	Maternal mental health
3	MPH	Patient advocacy	Nonprofit	Epidemiology; health disparities
4	PhD	Researcher	Commercial	Mental health; racial disparities
5	PhD, MPH	Researcher	Academic	Women’s health disparities; maternal mental health
6	PhD	Research	Academic; Government	Maternal health quality improvement
7	PhD	Research	Government	Postpartum depression
8	DrPH, RN	Perinatal nursing	University hospital	Perinatal nursing; quality improvement
9	MSN	Women’s health nurse practice	Nonprofit	Women’s health integration; postpartum depression
10	DO	OB-GYN; maternal-fetal medicine	Tertiary care hospital	maternal-fetal medicine
11	MD, MPH	OB-GYN	Public hospital	Racial disparities
12	MD	Cardiology	Tertiary care hospital	Cardiovascular disease
13	DO, MS	Psychiatry	University hospital	Psychiatry; maternal mental health
14	MD	OB-GYN; maternal-fetal mental health	University hospital	Maternal-fetal mental health
15, 16^a	MBBS; MBA	Health care technology	Commercial	Digital technologies for maternal and cardiovascular health
17	MEng	Health care technology	Commercial	Health-related predictive analytics
18	MD	OB-GYN; health care technology	University hospital	Clinical decision guidance in health care settings

Abbreviations: OB/GYN, obstetrician-gynecologist.

^aIncludes 2 experts.

Figure 1. Expert opinion on the value of predictive analytics in pregnancy-related cardiovascular disease or perinatal depression.

Data Availability Statement

All data generated or analyzed during this study are represented in this published article.