Indiana University SPEA Edward J. Bloustein School of Planning and Public Policy University of Pennsylvania AIR American University

Panel Paper: New Jersey's Data-Driven Scale up of Evidence-Based Home Visiting

Thursday, November 12, 2015 : 10:35 AM
Merrick I (Hyatt Regency Miami)

*Names in bold indicate Presenter

Anne K. Duggan, Johns Hopkins University
Introduction 

The Federal Home Visiting Program is taking evidence-based home visiting (HV) to scale.  However, it is not enough to adopt an evidence-based HV model.  Implementing agencies must reach and engage families most likely to benefit and tailor services to strengths, needs and interests. Organizations must assure that staff can motivate, enable and reinforce healthy family functioning and positive parenting.   

NJ’s HV infrastructure includes:  a statewide central intake system; network­ing of >60 local HV sites using 5 evidence-based models; performance standards; sophisticated  management information systems;  and on-going, statewide QI built on implementation science and theories of family and provider behavior.    

This session shows how we analyze MIS data with new primary data to improve performance in family engage­ment, visit content, referrals to community resources, and workforce devel­opment.  Our work aligns with and complements the Federal Home Visiting Program’s other major research initiatives, which are the subject of the other panel presentations.    

Objectives  Participants will understand:

  1. How NJ stakeholders use data to identify, explain and reduce unintended variation in HV services; and

  2. How other states and communities can use this approach and partner with us in shared learning.    

Presentation

Context:  This is an overview of how state agencies and community partners have expanded HV availability and implementation systems.        

Methods:  We use MIS data to measure service delivery and mixed methods such as in-depth interviews and web-based sur­veys to measure and test multi-level factors for service delivery.  Family engagement, visit content, and referrals reflect provider and family behavior.  We use multi-level modeling to test theo­ries of worker performance and parental behavior to explain unintended variation in service delivery and departures from standards.     

Results – Key Examples:  Family Level:  61% of enrolling families engage in HV (stay enrolled and receive ≥ half of expected visits in first 6 months.  Average visit time across content areas is:  50% parenting and child development, 16% health, 9% environmental needs, 11% family functioning, 12% administrative tasks, 2% unplanned.  Home visitors discuss mental health (MH) with 30% of mothers with identified, untreated poor MH at enrollment; they refer 9% to MH services.   Variation:  Service delivery varies greatly by site and home visitor.  For example, site-level family engagement rates are 24-81%, and sites devote 4-26% of visit time to health.  Home visitors discuss MH with 0-100% of enrolling mothers with poor MH in their caseloads; they refer 0-43% of these mothers.   Reasons for Variation:  Site-, visitor-, and family-level variation is concordant with theories of behav­ior and worker performance.  For example, home visitor perseverance in outreach and propensity to refer fam­ilies to community resources are positively associated with family engagement (both p<.001).  Home visitors’ personal qualities are predictive of how they address sensitive issues such as maternal mental health in ways that are concordant with theories of job performance.      

Action:  We will explain how we integrate implementation science with QI to improve actual practice via the state’s QI Committee and in-person meetings and webinars with local program leaders, supervisors and front line staff.