Transfer of Information from Personal Health Records: A Survey of Veterans Using My HealtheVet

Abstract Objective: Personal health records provide patients with ownership of their health information and allow them to share information with multiple healthcare providers. However, the usefulness of these records relies on patients understanding and using their records appropriately. My HealtheVet is a Web-based patient portal containing a personal health record administered by the Veterans Health Administration. The goal of this study was to explore veterans' interest and use of My HealtheVet to transfer and share information as well as to identify opportunities to increase veteran use of the My HealtheVet functions. Materials and Methods: Two waves of data were collected in 2010 through an American Customer Satisfaction Index Web-based survey. A random sample of veterans using My HealtheVet was invited to participate in the survey conducted on the My HealtheVet portal through a Web-based pop-up browser window. Results: Wave One results (n=25,898) found that 41% of veterans reported printing information, 21% reported saving information electronically, and only 4% ever sent information from My HealtheVet to another person. In Wave Two (n=18,471), 30% reported self-entering medication information, with 18% sharing this information with their Veterans Affairs (VA) provider and 9.6% sharing with their non-VA provider. Conclusion: Although veterans are transferring important medical information from their personal health records, increased education and awareness are needed to increase use. Personal health records have the potential to improve continuity of care. However, more research is needed on both the barriers to adoption as well as the actual impact on patient health outcomes and well-being.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98490/1/tmj%2E2011%2E0109.pd

Development of a supported self-management intervention for adults with type 2 diabetes and a learning disability

Background: Although supported self-management is a well-recognised part of chronic disease management, it has not been routinely used as part of healthcare for adults with a learning disability. We developed an intervention for adults with a mild or moderate learning disability and type 2 diabetes, building on the principles of supported self-management with reasonable adjustments made for the target population. Methods: In five steps, we: 1. Clarified the principles of supported self-management as reported in the published literature 2. Identified the barriers to effective self-management of type 2 diabetes in adults with a learning disability 3. Reviewed existing materials that aim to support self-management of diabetes for people with a learning disability 4. Synthesised the outputs from the first three phases and identified elements of supported self-management that were (a) most relevant to the needs of our target population and (b) most likely to be acceptable and useful to them 5. Implemented and field tested the intervention Results: The final intervention had four standardised components: (1) establishing the participant’s daily routines and lifestyle, (2) identifying supporters and their roles, (3) using this information to inform setting realistic goals and providing materials to the patient and supporter to help them be achieved and (4) monitoring progress against goals. Of 41 people randomised in a feasibility RCT, thirty five (85%) completed the intervention sessions, with over three quarters of all participants (78%) attending at least three sessions. Twenty-three out of 40 (58%) participants were deemed to be very engaged with the sessions and 12/40 (30%) with the materials; 30 (73%) participants had another person present with them during at least one of their sessions; 15/41 (37%) were reported to have a very engaged main supporter, and 18/41 (44%) had a different person who was not their main supporter but who was engaged in the intervention implementation. Conclusions: The intervention was feasible to deliver and, as judged by participation and engagement, acceptable to participants and those who supported them. Trial registration: Current Controlled Trials ISRCTN41897033 (registered 21/01/2013)

Anticipating VA/non-VA care coordination demand for Veterans at high risk for hospitalization

AbstractU.S. Veterans Affairs (VA) patients' multi-system use can create challenges for VA clinicians who are responsible for coordinating Veterans' use of non-VA care, including VA-purchased care ("Community Care") and Medicare.To examine the relationship between drive distance and time-key eligibility criteria for Community Care-and VA reliance (proportion of care received in VA versus Medicare and Community Care) among Veterans at high risk for hospitalization. We used prepolicy data to anticipate the impact of the 2014 Choice Act and 2018 Maintaining Internal Systems and Strengthening Integrated Outside Networks Act (MISSION Act), which expanded access to Community Care.Cross-sectional analysis using fractional logistic regressions to examine the relationship between a Veteran's reliance on VA for outpatient primary, mental health, and other specialty care and their drive distance/time to a VA facility.Thirteen thousand seven hundred three Veterans over the age of 65 years enrolled in VA and fee-for-service Medicare in federal fiscal year 2014 who were in the top 10th percentile for hospitalization risk.Key explanatory variables were patients' drive distance to VA > 40 miles (Choice Act criteria) and drive time to VA ≥ 30 minutes for primary and mental health care and ≥60 minutes for specialty care (MISSION Act criteria).Veterans at high risk for hospitalization with drive distance eligibility had increased odds of an outpatient specialty care visit taking place in VA when compared to Veterans who did not meet Choice Act eligibility criteria (odds ratio = 1.10, 95% confidence interval 1.05-1.15). However, drive time eligibility (MISSION Act criteria) was associated with significantly lower odds of an outpatient specialty care visit taking place in VA (odds ratio = 0.69, 95% confidence interval 0.67, 0.71). Neither drive distance nor drive time were associated with reliance for outpatient primary care or mental health care.VA patients who are at high risk for hospitalization may continue to rely on VA for outpatient primary care and mental health care despite access to outside services, but may increase use of outpatient specialty care in the community in the MISSION era, increasing demand for multi-system care coordination