Use of the internet and an online personal health record system by US veterans: Comparison of Veterans Affairs mental health service users and other veterans nationally

ArticleinJournal of the American Medical Informatics Association 19(6):1089-94 · July 2012with12 Reads
DOI: 10.1136/amiajnl-2012-000971 · Source: PubMed
The Department of Veterans Affairs (VA) operates one of the largest nationwide healthcare systems and is increasing use of internet technology, including development of an online personal health record system called My HealtheVet. This study examined internet use among veterans in general and particularly use of online health information among VA patients and specifically mental health service users. A nationally representative sample of 7215 veterans from the 2010 National Survey of Veterans was used. Logistic regression was employed to examine background characteristics associated with internet use and My HealtheVet. 71% of veterans reported using the internet and about a fifth reported using My HealtheVet. Veterans who were younger, more educated, white, married, and had higher incomes were more likely to use the internet. There was no association between background characteristics and use of My HealtheVet. Mental health service users were no less likely to use the internet or My HealtheVet than other veterans. Most veterans are willing to access VA information online, although many VA service users do not use My HealtheVet, suggesting more education and research is needed to reduce barriers to its use. Although adoption of My HealtheVet has been slow, the majority of veterans, including mental health service users, use the internet and indicate a willingness to receive and interact with health information online.
    • "Included studies employed a range of approaches for understanding barriers to PHR use (see Appendix A). Forty-five articles focused exclusively on patient work systems (McInnes et al., 2013; Tjora et al., 2005; Ancker et al., 2011; Burke et al., 2010; Day and Gu, 2012; Goel et al., 2011; Gu and Day, 2013; Guy et al., 2012; Hess et al., 2007; Kahn et al., 2010; Kim et al., 2009; Krist et al., 2011; Lau et al., 2013a Lau et al., , 2013b Lau et al., , 2013c Lober et al., 2006; Mayberry et al., 2011; Miller et al., 2007; Nagykaldi et al., 2012; Nielsen et al., 2012; Osborn et al., 2013; Sarkar et al., 2010 Sarkar et al., , 2011 Schnipper et al., 2008; Tsai et al., 2012; Tuil et al., 2006; Vodicka et al., 2013; Wade-Vuturo et al., 2013; Wagner et al., 2012 Wagner et al., , 2010 Wang et al., 2004; Weingart et al., 2006; Wen et al., 2010; Wiljer et al., 2010; Zickmund et al., 2008; Zulman et al., 2011; Emani et al., 2012; Nazi, 2010; Nazi et al., 2013; Wald et al., 2009; Tenforde et al., 2012; Denton, 2001; Goldner et al., 2013; Gordon et al., 2012; Lin et al., 2005), three exclusively on provider work systems (Crotty et al., 2013; Wynia et al., 2011; Fuji et al., 2008), two exclusively on caregiver work systems (Byczkowski et al., 2014; Britto et al., 2013), seven on patient and provider work systems (Nazi, 2013; Urowitz et al., 2012; Wald et al., 2010; Earnest et al., 2004; Jung et al., 2011; Do et al., 2011; Poon et al., 2007 ), two on patient and caregiver work systems (Tom et al., 2012; Weitzman et al., 2012), and one on patient, provider, and caregiver work systems (Woods et al., 2013). Sample sizes ranged from 10 to 100,617. "
    [Show abstract] [Hide abstract] ABSTRACT: Objectives: This review applied a human factors/ergonomics (HF/E) paradigm to assess individual, work system/unit, organization, and external environment factors generating barriers to patient, provider, and informal caregiver personal health record (PHR) use. Methods: The literature search was conducted using five electronic databases for the timeframe January 2000 to October 2013, resulting in 4865 citations. Two authors independently coded included articles (n = 60). Results: Fifty-five, ten and five articles reported barriers to patient, provider and caregiver PHR use, respectively. Barriers centered around 20 subfactors. The most frequently noted were needs, biases, beliefs, and mood (n = 35) and technology functions and features (n = 32). Conclusions: The HF/E paradigm was effective in framing the assessment of factors creating barriers to PHR use. Design efforts should address literacy, interoperability, access to health information, and secure messaging. A deeper understanding of the interactions between work systems and the role of organization and external environment factors is required.
    Article · May 2016
    • "Low education level and PTSD status were correlated with lower willingness to use e-mental health resources, even when controlling for other variables (age, education level, sex, and race or ethnicity). These correlations were relatively small but are consistent with recent research that has found that Veterans who have lower levels of education are less likely to use the Internet [65][66]and the VHA's personal electronic health record system (My HealtheVet) [66] . It may be that Veterans with low education have less familiarity and/or comfort with technology, which decreases their willingness to participate in e-mental health. "
    [Show abstract] [Hide abstract] ABSTRACT: Mental health care practices supported by electronic communication, referred to as e-mental health, offer ways to increase access to mental health resources. In recent years, e-mental health interventions using clinical video teleconferencing, Internet-based interventions, social networking sites, and telephones have emerged as viable, costeffective methods to augment traditional service delivery. Whereas some research evaluates attitudes about e-mental health, few studies have assessed interest in using these approaches in a contemporary sample of U.S. Veterans. This study sought to understand willingness to use e-mental health in a diverse group of Veterans residing in Hawaii. Mailed surveys were completed by 600 Operation Iraqi Freedom/Operation Enduring Freedom Veterans and National Guard members. Results suggest that overall willingness to use e-mental health ranged from 32.2% to 56.7% depending on modality type. Importantly, Veterans who screened positive for posttraumatic stress disorder (PTSD) were significantly less likely to report willingness to use each e-mental health modality than their peers without PTSD, despite their greater desire for mental health services. These results suggest that despite solutions to logistical barriers afforded via e-mental health services, certain barriers to mental health care may persist, especially among Veterans who screen positive for PTSD. © 2015, Rehabilitation Research and Development Service. All rights reserved.
    Full-text · Article · Nov 2015
    • "Reach of the PHR among patients with depression, anxiety, and PTSD was also relatively high in April 2012. Although a previous study did not detect a significant overall difference in use between veterans receiving care in the VA with and without mental health diagnoses [13], our larger sample size has enabled us to detect differences in actual adoption and use. While these differences are attenuated after adjusting for sociodemographic Shimada et al JOURNAL OF MEDICAL INTERNET RESEARCH "
    [Show abstract] [Hide abstract] ABSTRACT: My HealtheVet (MHV) is the personal health record and patient portal developed by the United States Veterans Health Administration (VA). While millions of American veterans have registered for MHV, little is known about how a patient's health status may affect adoption and use of the personal health record. Our aim was to characterize the reach of the VA personal health record by clinical condition. This was a cross-sectional analysis of all veterans nationwide with at least one inpatient admission or two outpatient visits between April 2010 and March 2012. We compared adoption (registration, authentication, opt-in to use secure messaging) and use (prescription refill and secure messaging) of MHV in April 2012 across 18 specific clinical conditions prevalent in and of high priority to the VA. We calculated predicted probabilities of adoption by condition using multivariable logistic regression models adjusting for sociodemographics, comorbidities, and clustering of patients within facilities. Among 6,012,875 veterans, 6.20% were women, 61.45% were Caucasian, and 26.31% resided in rural areas. The mean age was 63.3 years. Nationwide, 18.64% had registered for MHV, 11.06% refilled prescriptions via MHV, and 1.91% used secure messaging with their clinical providers. Results from the multivariable regression suggest that patients with HIV, hyperlipidemia, and spinal cord injury had the highest predicted probabilities of adoption, whereas those with schizophrenia/schizoaffective disorder, alcohol or drug abuse, and stroke had the lowest. Variation was observed across diagnoses in actual (unadjusted) adoption and use, with registration rates ranging from 29.19% of patients with traumatic brain injury to 14.18% of those with schizophrenia/schizoaffective disorder. Some of the variation in actual reach can be explained by facility-level differences in MHV adoption and by differences in patients' sociodemographic characteristics (eg, age, race, income) by diagnosis. In this phase of early adoption, opportunities are being missed for those with specific medical conditions that require intensive treatment and self-management, which could be greatly supported by functions of a tethered personal health record.
    Full-text · Article · Dec 2014
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