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RRP 11-404 – HSR&D Study

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RRP 11-404
Identifying Opportunities for Targeted Interventions via My HealthVet
Cynthia A. Brandt MD MPH
VA Connecticut Healthcare System West Haven Campus, West Haven, CT
West Haven, CT
Funding Period: October 2011 - September 2012

BACKGROUND/RATIONALE:
My HealtheVet (MHV) is the VA's patient portal and personal health record (PHR). VA intends to utilize MHV as a platform to reach out to and engage Veterans and their caregivers as active participants in their care. However, rates of MHV adoption continue to be low and vary by specific patient characteristics such as age, gender, and educational attainment. For example, data from the 2008 VA Survey of Health Experiences of Patients (SHEP) has shown that a higher proportion of women use MHV in VA than men and that use declines with age but rises with education. Analysis of the same data showed that patients who were frequent users of MHV self-reported being less healthy than non-users. However, little else is known to characterize the comorbidities and medical complexity of Veterans using MHV. And nothing is known of how patient characteristics may differ between registrants (those simply registered for MHV) and in-person authenticated (IPA'd) users (with access to advanced MHV features). Proportionately, are more or less patients with mental illness authenticated for MHV? Are more or less Veterans with diabetes authenticated for MHV?
Patients may use MHV in different ways, with different intensities. A pilot study by McInnes and Rothendler found that patients on diabetes medications were more likely to use MHV to refill medications, compared with other diseases. Although detailed tracking of MHV use is not currently available, the VA system of records does contain information on medication refills through MHV and secure messaging use, both key functionalities of MHV. In this project we performed analyses to characterize how Veterans with different conditions use the MHV website for purposes such as medication refills, secure messaging, and self-care and education.

OBJECTIVE(S):
Aim 1: To create an eHealth QUERI database linking clinical data (e.g., ICD-9-CM codes) and key patient-level demographics for all Veterans who obtained care in VA in FY2010 to current, with data on MHV registration and In-Person Authentication (IPA), use of MHV for prescription refills, and use of MHV for secure messaging.
Aim 2: To characterize use of MHV across disease categories and patient demographics. We focused on the most prevalent or high priority diagnoses and conditions among Veterans. We specifically targeted conditions of interest to the nine disease-specific QUERI centers.
Aim 3: To use facility-level data to create graphic displays of variations in authentication and use in general and by condition that could be used by MHV coordinators and Patient Aligned Care Teams (PACTs) when planning marketing of MHV; and by QUERIs to determine ways to employ MHV in implementation of interventions.

METHODS:
This project was an observational retrospective database study. We merged data elements from existing VHA databases contained in the clinical data warehouse (CDW) to create an eHealth QUERI Database to evaluate current use of the My HealtheVet personal health record. This database was used to assess gaps in access to eHealth in VHA (such as gaps in MHV registration or IPA rates), and link them to important patient demographic or clinical characteristics, or local station or VISN efforts.

FINDINGS/RESULTS:
We have achieved our goals for Aims 1 and 2. Among the initial dataset of about 7 million Veterans, about 6% were women, 81% White, and a little more than 16% were African-American. Most lived in urban areas, with about 16% between 18-44 years of age, close to 37% 45-64 years, and about 47% over age 65. Of these veterans, about 16% were registered with MHV, with close to 9% authenticated to have access to all MHV features, and a little more than1% had actually used secure messaging. Almost 10% had refilled their prescriptions through the MHV.

Overall, patients with major depression, Post-Traumatic Stress Disorder and anxiety had the highest rates of authentication, were most likely using secure messaging and refilling prescriptions. Patients with schizophrenia and schizoaffective disorder had the lowest authentication rates and were less likely to use either feature. Medical conditions with high rates of adoption included HIV and diabetes. Authentication was lower among patients with other conditions such as stroke , coronary artery disease, and congestive heart failure.

IMPACT:
This was a detailed national description of MHV use. By identifying patient characteristics associated with a higher or lower likelihood of using the system, it will be possible to more effectively respond to the needs of those currently using the system as well as to implement targeted interventions to boost MHV use for those who are under-represented.

As expected, this RRP is generating new cross-QUERI collaborations. Based on our initial findings we have already started collaborating with other QUERI Centers on further analyses to identify how best to address the MHV-related needs of patients with varied clinical needs.

Findings from the study have been reported back to the MHV Program Office, and have also been included as supportive evidence for a report and presentation by the eConnected Task Force commissioned by Dr. Petzl.

PUBLICATIONS:

Journal Articles

  1. McInnes DK, Shimada SL, Midboe AM, Nazi KM, Zhao S, Wu J, Garvey CM, Houston TK. Patient Use of Electronic Prescription Refill and Secure Messaging and Its Association With Undetectable HIV Viral Load: A Retrospective Cohort Study. Journal of medical Internet research. 2017 Feb 15; 19(2):e34.
  2. Shimada SL, Brandt CA, Feng H, McInnes DK, Rao SR, Rothendler JA, Haggstrom DA, Abel EA, Cioffari LS, Houston TK. Personal health record reach in the Veterans Health Administration: a cross-sectional analysis. Journal of medical Internet research. 2014 Dec 12; 16(12):e272.
  3. Garla VN, Brandt C. Ontology-guided feature engineering for clinical text classification. Journal of Biomedical Informatics. 2012 Oct 1; 45(5):992-8.
Conference Presentations

  1. Abel EA, Shimada SL, Feng H, Skanderson M, Erdos JJ, Godleski L, Houston TK, Brandt CA. Complementary eHealth: Veterans Use of MyHealtheVet and Clinical Video Telehealth. Poster session presented at: Society of Behavioral Medicine Annual Meeting and Scientific Sessions; 2014 Apr 24; Philadelphia, PA.


DRA: Health Systems
DRE: Technology Development and Assessment
Keywords: QUERI Implementation
MeSH Terms: none