Washington State Institute for Public Policy
Nurse Family Partnership
Public Health & Prevention: Home- or Family-based
Benefit-cost estimates updated May 2017.  Literature review updated June 2017.
The Nurse Family Partnership program provides intensive visitation by nurses during a woman’s pregnancy and the first two years after birth. The program is designed to serve low-income, at-risk pregnant women expecting their first child. The goal is to promote the child's development and provide support and instructive parenting skills to parents. Among programs included in the meta-analysis, participants received 25–35 home visits on average, spread over approximately two years.
BENEFIT-COST
META-ANALYSIS
CITATIONS
The estimates shown are present value, life cycle benefits and costs. All dollars are expressed in the base year chosen for this analysis (2016). The chance the benefits exceed the costs are derived from a Monte Carlo risk analysis. The details on this, as well as the economic discount rates and other relevant parameters are described in our Technical Documentation.
Benefit-Cost Summary Statistics Per Participant
Benefits to:
Taxpayers $5,221 Benefits minus costs $4,990
Participants $6,001 Benefit to cost ratio $1.42
Others $3,051 Chance the program will produce
Indirect $2,535 benefits greater than the costs 55 %
Total benefits $16,808
Net program cost ($11,818)
Benefits minus cost $4,990
1In addition to the outcomes measured in the meta-analysis table, WSIPP measures benefits and costs estimated from other outcomes associated with those reported in the evaluation literature. For example, empirical research demonstrates that high school graduation leads to reduced crime. These associated measures provide a more complete picture of the detailed costs and benefits of the program.

2“Others” includes benefits to people other than taxpayers and participants. Depending on the program, it could include reductions in crime victimization, the economic benefits from a more educated workforce, and the benefits from employer-paid health insurance.

3“Indirect benefits” includes estimates of the net changes in the value of a statistical life and net changes in the deadweight costs of taxation.
Detailed Monetary Benefit Estimates Per Participant
Benefits from changes to:1 Benefits to:
Taxpayers Participants Others2 Indirect3 Total
Crime $187 $0 $307 $93 $587
Labor market earnings associated with employment $528 $1,164 $0 $0 $1,692
Public assistance $747 ($317) $0 $371 $801
Food assistance $413 ($373) $0 $205 $245
Health care associated with preterm births ($10) $0 $0 ($5) ($15)
Health care associated with very low birthweight births $6 $0 $0 $3 $8
Subtotals $1,870 $473 $307 $667 $3,318
From secondary participant
Crime $1,861 $0 $3,888 $927 $6,676
Labor market earnings associated with high school graduation ($1,652) ($3,638) ($1,628) $0 ($6,918)
Child abuse and neglect $445 $1,547 $0 $222 $2,214
K-12 grade repetition ($47) $0 $0 ($24) ($71)
K-12 special education ($204) $0 $0 ($102) ($306)
Property loss associated with alcohol abuse or dependence $0 $1 $1 $0 $1
Public assistance ($232) $99 $0 ($117) ($251)
Health care associated with educational attainment ($390) $106 $424 ($196) ($56)
Labor market earnings associated with child abuse & neglect $3,278 $7,219 $0 $0 $10,498
Food assistance ($16) $14 $0 ($9) ($10)
Costs of higher education $212 $180 $59 $107 $557
Infant mortality $0 $0 $0 $6,904 $6,904
Health care associated with very low birthweight births $95 $0 $0 $47 $142
Subtotals $3,351 $5,528 $2,744 $7,759 $19,381
Adjustment for deadweight cost of program $0 $0 $0 ($5,891) ($5,891)
Totals $5,221 $6,001 $3,051 $2,535 $16,808
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $5,944 2015 Present value of net program costs (in 2016 dollars) ($11,818)
Comparison costs $0 2015 Cost range (+ or -) 10 %
Treatment cost estimates for this program reflect costs beyond treatment as usual. The annual per-participant cost estimate is based on average total cost per family in Washington State, provided by Siobhan Mahorter at the Nurse Family Partnership National Service Office, January 2017.
The figures shown are estimates of the costs to implement programs in Washington. The comparison group costs reflect either no treatment or treatment as usual, depending on how effect sizes were calculated in the meta-analysis. The cost range reported above reflects potential variation or uncertainty in the cost estimate; more detail can be found in our Technical Documentation.
Estimated Cumulative Net Benefits Over Time (Non-Discounted Dollars)
The graph above illustrates the estimated cumulative net benefits per-participant for the first fifty years beyond the initial investment in the program. We present these cash flows in non-discounted dollars to simplify the “break-even” point from a budgeting perspective. If the dollars are negative (bars below $0 line), the cumulative benefits do not outweigh the cost of the program up to that point in time. The program breaks even when the dollars reach $0. At this point, the total benefits to participants, taxpayers, and others, are equal to the cost of the program. If the dollars are above $0, the benefits of the program exceed the initial investment.

^WSIPP’s benefit-cost model does not monetize this outcome.

^^WSIPP does not include this outcome when conducting benefit-cost analysis for this program.

***We report this outcome twice: once for mothers (designated as the primary participant) and once for infants (designated as the secondary participant). We do this because the outcome is associated with costs and benefits for both mothers and infants, and the amount of the cost or benefit is different for mothers than it is for infants.

Meta-analysis is a statistical method to combine the results from separate studies on a program, policy, or topic in order to estimate its effect on an outcome. WSIPP systematically evaluates all credible evaluations we can locate on each topic. The outcomes measured are the types of program impacts that were measured in the research literature (for example, crime or educational attainment). Treatment N represents the total number of individuals or units in the treatment group across the included studies.

An effect size (ES) is a standard metric that summarizes the degree to which a program or policy affects a measured outcome. If the effect size is positive, the outcome increases. If the effect size is negative, the outcome decreases.

Adjusted effect sizes are used to calculate the benefits from our benefit cost model. WSIPP may adjust effect sizes based on methodological characteristics of the study. For example, we may adjust effect sizes when a study has a weak research design or when the program developer is involved in the research. The magnitude of these adjustments varies depending on the topic area.

WSIPP may also adjust the second ES measurement. Research shows the magnitude of some effect sizes decrease over time. For those effect sizes, we estimate outcome-based adjustments which we apply between the first time ES is estimated and the second time ES is estimated. We also report the unadjusted effect size to show the effect sizes before any adjustments have been made. More details about these adjustments can be found in our Technical Documentation.

Meta-Analysis of Program Effects
Outcomes measured Primary or secondary participant No. of effect sizes Treatment N Adjusted effect sizes (ES) and standard errors (SE) used in the benefit-cost analysis Unadjusted effect size (random effects model)
First time ES is estimated Second time ES is estimated
ES SE Age ES SE Age ES p-value
High school graduation Primary 2 401 0.035 0.086 21 0.035 0.086 21 0.096 0.271
Low birthweight births*** Primary 5 10020 0.022 0.022 19 0.000 0.000 20 0.026 0.243
Small for gestational age (SGA)*** Primary 1 455 0.000 0.081 19 0.000 0.000 20 0.000 1.000
Smoking during late pregnancy^ Primary 2 784 -0.079 0.078 19 n/a n/a n/a -0.079 0.315
Substance use^ Primary 2 266 -0.229 0.186 31 -0.031 0.279 33 -0.619 0.117
Very low birthweight birth (< 1500g)*** Primary 2 9162 -0.040 0.045 19 0.000 0.000 20 -0.040 0.373
Attention-deficit/hyperactivity disorder symptoms Secondary 1 166 -0.094 0.142 9 0.000 0.008 10 -0.260 0.068
NICU admission Secondary 1 564 -0.016 0.056 1 0.000 0.000 2 -0.016 0.781
Disruptive behavior disorder symptoms Secondary 1 191 -0.078 0.087 9 -0.037 0.048 12 -0.218 0.013
Emergency department visits Secondary 2 939 0.088 0.089 2 0.000 0.086 6 0.079 0.419
Externalizing behavior symptoms Secondary 1 138 -0.064 0.154 9 -0.030 0.080 12 -0.178 0.248
Hospitalization^^ Secondary 1 216 -0.051 0.109 2 0.000 0.000 3 -0.140 0.199
Illicit drug use in high school Secondary 1 91 -0.028 0.163 19 -0.028 0.163 29 -0.077 0.636
Internalizing symptoms Secondary 3 526 -0.083 0.079 9 -0.060 0.066 11 -0.229 0.005
Low birthweight births*** Secondary 5 10020 0.022 0.022 1 0.000 0.000 2 0.026 0.243
Preterm birth (< 37 weeks)*** Secondary 4 9783 0.028 0.020 1 0.000 0.000 2 0.022 0.397
Small for gestational age (SGA)*** Secondary 1 455 0.000 0.081 1 0.000 0.000 2 0.000 1.000
Test scores Secondary 3 368 0.021 0.067 11 0.015 0.073 17 0.052 0.516
Very preterm birth (< 30 weeks)***^ Secondary 1 8598 -0.135 0.079 1 n/a n/a n/a -0.135 0.087
Crime Primary 2 229 -0.106 0.080 32 -0.106 0.080 42 -0.463 0.092
Employment Primary 3 433 0.026 0.062 26 0.000 0.000 27 0.078 0.266
Food assistance Primary 3 433 -0.051 0.062 27 -0.051 0.062 27 -0.185 0.165
Preterm birth (< 37 weeks) Primary 4 9783 0.028 0.020 19 0.000 0.000 20 0.022 0.397
Public assistance Primary 3 433 -0.056 0.062 27 -0.056 0.062 27 -0.197 0.083
Very low birthweight birth (< 1500g) Primary 2 9162 -0.040 0.045 19 0.000 0.000 20 -0.040 0.373
Child abuse and neglect Secondary 2 206 -0.353 0.141 5 -0.353 0.141 17 -0.620 0.010
Crime Secondary 1 91 -0.230 0.194 19 -0.230 0.194 29 -0.639 0.005
Food assistance Secondary 1 91 0.004 0.179 19 0.004 0.179 19 0.012 0.945
High school graduation Secondary 1 91 -0.043 0.185 19 -0.043 0.185 19 -0.118 0.516
Infant mortality Secondary 2 8815 -0.130 0.118 1 0.000 0.000 2 -0.143 0.170
K-12 grade repetition Secondary 3 367 0.051 0.094 11 0.051 0.094 11 0.127 0.317
K-12 special education Secondary 3 367 0.031 0.111 11 0.031 0.111 17 0.046 0.820
Public assistance Secondary 1 91 0.029 0.179 19 0.029 0.179 19 0.081 0.653
Very low birthweight birth (< 1500g) Secondary 2 9162 -0.040 0.045 1 0.000 0.000 2 -0.040 0.373
Citations Used in the Meta-Analysis

Carabin, H., Cowan, L.D., Beebe, L.A., Skaggs, V.J., Thompson, D., & Agbangla, C. (2005). Does participation in a nurse visitation programme reduce the frequency of adverse perinatal outcomes in first-time mothers? Paediatric and Perinatal Epidemiology, 19(3), 194-205.

Eckenrode, J., Henderson, C.R., Jr., Powers, J., Campa, M., Lucky, D.W., Olds, D., . . . Sidora-Arcoleo, K. (2010). Long-term effects of prenatal and infancy nurse home visitation on the life course of youths: 19-year follow-up of a randomized trial. Archives of Pediatrics and Adolescent Medicine, 164(1), 9-15.

Holmes & Rutledge (2016). Evaluation of the Nurse Family Partnership in North Carolina. UNC Gillings School of Global Public Health.

Kitzman, H., Olds, D.L., Henderson Jr, C.R., Hanks, C., Cole, R., Tatelbaum, R., et al. (1997). Effect of prenatal and infancy home visitation by nurses on pregnancy outcomes, childhood injuries, and repeated childbearing: A randomized controlled trial. JAMA, 278(8), 644-652.

Kitzman, H.J., Olds, D.L., Cole, R.E., Hanks, C.A., Anson, E.A., Arcoleo, K.J., . . . Holmberg, J.R. (2010). Enduring effects of prenatal and infancy home visiting by nurses on children: Follow-up of a randomized trial among children at age 12 years. Archives of Pediatrics & Adolescent Medicine, 164(5), 412-418.

Mejdoubi, J., van, . H. S. C. C. M., van, L. F. J. M., Crone, M., Crijnen, A., HiraSing, R. A., & Special Sections: Focus on Infant Feeding and Postnatal Health and Well-being. (2014). Effects of nurse home visitation on cigarette smoking, pregnancy outcomes and breastfeeding: A randomized controlled trial. Midwifery, 30(6), 688-695.

Mejdoubi, J., van, . H. S. C. C. M., van, L. F. J. M., Heymans, M. W., Crijnen, A., Hirasing, R. A., & Carlo, W. A. (2015). The Effect of VoorZorg, the Dutch Nurse-Family Partnership, on Child Maltreatment and Development: A Randomized Controlled Trial. Plos One, 10(4).

Olds, D.L., C.R. Henderson Jr, R. Tatelbaum, and R. Chamberlin. (1986). Improving the delivery of prenatal care and outcomes of pregnancy: A randomized trial of nurse home visitation. Pediatrics, 77(1), 16-28.

Olds, D.L., Eckenrode, J., Henderson, C.R., Jr., Kitzman, H., Powers, J., Cole, R., . . . Luckey, D. (1997). Long-term effects of home visitation on maternal life course and child abuse and neglect: Fifteen-year follow-up of a randomized trial. JAMA, 278(8), 637-643.

Olds, D.L., Holmberg, J.R., Donelan-McCall, N., Luckey, D.W., Knudtson, M.D., & Robinson, J. (2014). Effects of home visits by paraprofessionals and by nurses on children: follow-up of a randomized trial at ages 6 and 9 years. JAMA Pediatrics, 168(2), 114-21.

Olds, D.L., Kitzman, H., Cole, R., Robinson, J., Sidora, K., Luckey, D.W., . . . Holmberg, J. (2004). Effects of nurse home- visiting on maternal life course and child development: Age 6 follow-up results of a randomized trial. Pediatrics, 114(6), 1550-1559.

Olds, D.L., Kitzman, H., Hanks, C., Cole, R., Anson, E., Sidora-Arcoleo, K., . . . Bondy, J. (2007). Effects of nurse home visiting on maternal and child functioning: Age-9 follow-up of a randomized trial. Pediatrics, 120(4), 832-845.

Olds, D.L., Kitzman, H., Knudtson, M.D., Anson, E., Smith, J.A., & Cole, R. (2014). Effect of home visiting by nurses on maternal and child mortality: results of a 2-decade follow-up of a randomized clinical trial. JAMA Pediatrics, 168(9), 800-806.

Olds, D L., Kitzman, H.J., Cole, R.E., Hanks, C.A., Arcoleo, K.J., Anson, E.A., . . . Stevenson, A. (2010). Enduring effects of prenatal and infancy home visiting by nurses on maternal life course and government spending: Follow-up of a randomized trial among children at age 12 years. Archives of Pediatrics & Adolescent Medicine, 164(5), 419-424.

Olds, D.L., Robinson, J., O'Brien, R., Luckey, D.W., Pettitt, L.M., Henderson, C.R., Jr., . . . Talmi, A. (2002). Home visiting by paraprofessionals and by nurses: A randomized, controlled trial. Pediatrics, 110(3), 486-496.

Olds, D.L., Robinson, J., Pettitt, L., Luckey, D. W., Holmberg, J., Ng, R.K., . . . Henderson, C.R., Jr. (2004). Effects of home visits by paraprofessionals and by nurses: Age 4 follow-up results of a randomized trial. Pediatrics, 114(6), 1560-1568.

Robling, M., Bekkers, M.J., Bell, K., Butler, C.C., Cannings-John, R., Channon, S., . . . Kenkre, J. (2016). Effectiveness of a nurse-led intensive home-visitation programme for first-time teenage mothers (Building Blocks): a pragmatic randomised controlled trial. The Lancet, 387(10014), 146-155.

Rubin, D.M., O'Reilly, A.L., Luan, X., Dai, D., Localio, A.R., & Christian, C.W. (2011). Variation in pregnancy outcomes following statewide implementation of a prenatal home visitation program. Archives of Pediatrics & Adolescent Medicine, 165,(3), 198-204.

Sidora-Arcoleo, K., Anson, E., Lorber, M., Cole, R., Olds, D., & Kitzman, H. (2010). Differential effects of a nurse home- visiting intervention on physically aggressive behavior in children. Journal of Pediatric Nursing, 25(1), 35-45.

For more information on the methods
used please see our Technical Documentation.
360.664.9800
institute@wsipp.wa.gov