Social Determinants of Health and E-Health Technology Use Among Adults with Type 2 Diabetes
Author(s)
Martin A1, Way N2, Jaffe D3, Maculaitis MC4
1Kantar, San Mateo, CA, USA, 2Kantar Health, San Mateo, CA, USA, 3Kantar, Tel Aviv, Israel, 4Kantar, New York, NY, USA
BACKGROUND: The use of electronic health technologies (eHealth) is fast becoming an important tool in the self-management of type 2 diabetes (T2DM). However, little is known about how eHealth use varies in this population based on social determinants of health (SDOH). OBJECTIVES: To examine the relationship between eHealth use and SDOH among adults with T2DM. METHODS: The 2019 US National Health and Wellness Survey was used to examine adults (≥18 years) with a self-reported physician diagnosis of T2DM. Patient-reported SDOH included age, income, marital status, education, insurance status, household size, family history of diabetes, and lifestyle behaviors (smoking, drinking, exercise). Respondents were categorized by level of eHealth use (0, 1, or ≥2 technologies). Chi-square tests were used to assess the relationship between eHealth use and SDOH variables. RESULTS: Analyses included N=5942 adults with T2DM (Mean±SD age=60.12±12.8 years, 51.6% male, 74% white). More eHealth use was associated with younger age (<65 years: 55.2% vs. 58.7% vs. 63.3%), racial/ethnic minorities (24.1% vs. 28.7% vs. 27.4%), married/living with a partner (58.3% vs. 62% vs. 65.5%), and ≥2 children living at home (6.6% vs. 9.9% vs. 15.3%) (all, p<0.05). More eHealth use was also related to higher socioeconomic status, indicated by a higher frequency of college graduates (36.5% vs. 49% vs. 59.1%), insured patients (93.7% vs. 97.4% vs. 98.4%), and household income >$75k (27.6% vs. 37.4% vs. 49.7%) (all, p<0.001). Additionally, more eHealth use was associated with a greater likelihood of having a family history of diabetes (64.6% vs. 68.4% vs. 69.7%), alcohol consumption (53.3% vs. 58.8% vs. 68.4%), and exercise (44.7% vs. 57.6% vs. 65.8%) (all, p<0.01). CONCLUSIONS: Results provide a summary profile of the SDOH of eHealth users and nonusers. By identifying factors associated with a patient's active involvement in their care, findings may help inform targeted strategies to optimize health outcomes.
Conference/Value in Health Info
2020-11, ISPOR Europe 2020, Milan, Italy
Value in Health, Volume 23, Issue S2 (December 2020)
Code
PDB80
Topic
Medical Technologies, Patient-Centered Research
Topic Subcategory
Digital Health, Patient Engagement, Patient-reported Outcomes & Quality of Life Outcomes
Disease
Diabetes/Endocrine/Metabolic Disorders