Feasibility of social network analysis to study outcomes of children with medical complexity

Author:

Coller Ryan J.1ORCID,Green Harold D.2,Kaminski Patrick C.3,Howell Kristina1,Alfaro Elena1,Nelson Cassandra1,Warner Gemma1,Werner Nicole E.2

Affiliation:

1. School of Medicine and Public Health University of Wisconsin‐Madison Madison Wisconsin USA

2. School of Public Health‐Bloomington Indiana University Bloomington Indiana USA

3. Luddy School of Informatics, Computing, and Engineering Indiana University Bloomington Indiana USA

Abstract

AbstractSince most care for children with medical complexity (CMC) is delivered daily in communities by multiple caregiving individuals, that is, caregiving networks, tools to assess and intervene across these networks are needed. This study evaluated the feasibility of applying social network analysis (SNA) to describe caregiving networks. Because hospitalization is among the most frequently used outcomes for CMC, exploratory correlations between network characteristics and CMC hospital use were evaluated. Within 3 weeks, the goal network enrollment was achieved, and all feasibility measures were favorable. Network characteristics correlated with hospital use, that is, smaller, denser networks, with more closed‐loop communication correlated with fewer hospital days. Networks with more professional caregivers also correlated with fewer hospital days. SNA is a feasible tool to study CMC caregiving networks. Preliminary data support rigorous hypothesis testing using SNA methods. Network‐based interventions to improve CMC health may be an important future direction.

Funder

National Center for Advancing Translational Sciences

Publisher

Wiley

Subject

Assessment and Diagnosis,Care Planning,Health Policy,Fundamentals and skills,General Medicine,Leadership and Management

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