JOURNAL ARTICLE
RANDOMIZED CONTROLLED TRIAL
Add like
Add dislike
Add to saved papers

The Cost-effectiveness Analysis of Nurse-Family Partnership in the United States.

We evaluated whether Nurse-Family Partnership might serve as a cost-effective social policy for improving health. Using data from studies of randomized controlled trials as well as real-world data, we conducted a Monte Carlo simulation to estimate cost-effectiveness of Nurse-Family Partnership in a hypothetical cohort of first-born children in the United States. Analyses were conducted in 2015. Were all new mothers eligible for Nurse-Family Partnership, the program would produce 0.11 QALYs (95% confidence interval [CI]=0.06, 0.17) at an additional cost of $1,021 (95% CI=-$2,831, $4,414) per nurse-visited child's lifetime relative to the comparison-group children or $14,642 (95% CI = Savings, $71,877) per QALY gained. However, if applied to high-risk mothers, it would generate 0.19 QALYs (95% CI = 0.09, 0.44) and a net benefit of $2,764 (95% CI =-$1,210, $7,092) per nurse-visited child. Nurse-Family Partnership should be considered as a policy investment, particularly in an era of investments in the social determinants of health.

Full text links

We have located links that may give you full text access.
Can't access the paper?
Try logging in through your university/institutional subscription. For a smoother one-click institutional access experience, please use our mobile app.

For the best experience, use the Read mobile app

Mobile app image

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app

All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.

By using this service, you agree to our terms of use and privacy policy.

Your Privacy Choices Toggle icon

You can now claim free CME credits for this literature searchClaim now

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app