Social Networks of Self-care and Perceived Treatment Burden Among Patients on In-Center Hemodialysis

• Authors: Mi-Kyung Song, Emory University; Sudeshna Paul, Emory University; Laura Plantinga, Emory University; Carrie Henry, Woodruff Health Sciences Center; Linda Turberville-Trujillo, Emory University
• Journal Title: Kidney Medicine
• Volume: Volume 1, Number 3
• Publisher: Elsevier | 2019-05-01, Pages 97-103
• Type of Work: Article | Final Publisher PDF
• Publisher DOI: http://doi.org/10.1016/j.xkme.2019.04.001
• Subjects: Health Sciences, Medicine and Surgery; Sociology, Public and Social Welfare; Health Sciences, Health Care Management
• Keywords: Chronic illness management; care coordination; dialysis; kidney failure; social network

Abstract

Background: Dialysis patients manage not only the demand of dialysis but also other complex chronic conditions. These individuals may draw upon personal and social resources to cope with the demands of self-management and care coordination. This study was designed to describe social networks for self-management and care coordination among hemodialysis patients and explore the association between network characteristics and perceived treatment burden. Study Design: A cross-sectional study using social network analysis. Setting & Participants: 20 patients from an outpatient dialysis center. Factors: Social network characteristics (eg, size and connectivity) and perceived treatment burden. Measurements/Outcomes: Participants completed a battery of questionnaires, including the Patient Experience With Treatment and Self-management Questionnaire (measuring perceived treatment burden) and a social network survey asking the respondent to name up to 5 people to whom he or she turned for help with self-care and care coordination tasks and their characteristics and relationships. Results: Participants were aged 53.4 years on average, half were women, and 18 were African Americans. On average, network size was 3.1 members, most of whom were women and family members. 7 patient networks included at least 1 health care provider. The clustering coefficient (the overall connection between members) was 0.54, suggesting that not all members within the patient's network were connected with each other. Multimorbidity was not associated with treatment burden domain scores, but greater network connectivity was associated with lower treatment-related financial burden (r = −0.61). Limitations: The small sample was racially homogeneous and precluded controlling for potential confounding factors. Conclusions: Dialysis patients used networks of people to manage self-care and coordination tasks, but interconnectedness between members of individual patients’ networks was limited, which might negatively affect their perceived treatment burden. The social context of dialysis patients could play an important role in their illness management and treatment burden and calls for future research.