Abstract: Associated Factors with Electronic Personal Health Records Use (ePHRs): An Application of Anderson's Behavioral Model of Health Services Use to Ehealth Services (Society for Social Work and Research 24th Annual Conference - Reducing Racial and Economic Inequality)

675P Associated Factors with Electronic Personal Health Records Use (ePHRs): An Application of Anderson's Behavioral Model of Health Services Use to Ehealth Services

Schedule:
Sunday, January 19, 2020
Marquis BR Salon 6 (ML 2) (Marriott Marquis Washington DC)
* noted as presenting author
Yan Luo, MSW, PhD student, University of Alabama, Tuscaloosa, AL
Leah Cheatham, JD, PhD, Assistant Professor, University of Alabama, AL
Krystal Dozier, MSW, Doctoral Student, University of Alabama, AL
Carin Ikenberg, LMSW, Ph.D. Student, University of Alabama, Tuscaloosa, AL
Background/ Purpose

As a growing population, older cancer survivors have a need for supportive care, which is not always met due to the change of healthcare system, distance to hospital, or frustrating referral to other care.  Electronic personal health records (ePHRs) are commonly viewed as potential tools to improve clinical outcomes through increasing patients’ ability to self-manage healthcare. Older cancer survivors could be benefited from using ePHRs for their supportive care.  By applying Anderson’s Behavioral Model of Health Services Use, this study aims to examine factors associated with ePHRs use among elderly cancer survivors.

Methods

This study utilized the Health Information National Trends Survey (HINTS5; Cycle 1 and 2, 2017 and 2018) collected by National Cancer Institutes. The present study includes only respondents ages 65 and older who were diagnosed with cancer and were offered using ePHRs (N=275). Participant descriptive information was examined, including univariate analyses and bivariate analyses of relationships between each variable and ePHRs use. Multiple linear regression was used to examine factors predictive of ePHRs use. Informed by Anderson’s Model, the regression model included predisposing factors (i.e., age, gender, marital status), enabling factors (i.e., educational attainment, primary healthcare provider, frequency of visiting health care providers, internet use), and need factors (i.e., medical conditions, Patient Health Questionnaire–4 [PHQ-4] score).

Results

The mean age of participants was 73.7 years old (SD=6.63). Around half participants were female (52.7%), married or living as married (53.8%). Less than half participants obtained a bachelor’s degree (42.2%). Most participants had a regular health care provider (91.6%) and used internet (84.7%). Only 3.6% of participants had not visited health care providers in past 12 months, while 20% visited 1-2 times, 40% of them visited 3-4 times, and 30.2% of them visited more than 5 times. Levels of medical conditions (M=2.01, SD=1.26, range 0-6) and PHQ-4 score (M=1.51, SD=2.48, range 0-12) among participants remained low, as well as the overall use of ePHRs among older cancer survivors (M=1.05, SD=1.25, range from 0 to 4). Bivariate analysis showed differences in gender, marital status, education, frequency of visiting health care providers, using Internet, and medical conditions (p<.05). According to regression analysis of predisposing factors, age (b=-.155) and gender (b=-.139) were associated with ePHRs use (p<.05). Interestingly, most enabling factors were predictive of ePHRs use (p<.05), including educational attainment (b=.135), frequency of visiting health care providers (b=.123), and use Internet (b=.164). Additionally, medical condition level was the only need factor that related to ePHRs (b=.260, p<0.05).

Conclusion and Implications

The analytical results showed that Anderson's Model of Health Services Use was effective in predicting ePHRs use in older cancer survivors. The low rates of ePHRs use suggests additional efforts to increase ePHRs utilization among older cancer survivors. Intervention of health education regarding ePHRs use should be implemented among this particular population, as well as increasing the access to internet. Additional studies are needed to include participants who are not offered using ePHRs and explore the associated factors with ePHRs use from the angle of healthcare providers.