Personal Health record reach in the veterans health administration

A cross-sectional analysis

Stephanie Leah Shimada, Cynthia A. Brandt, Hua Feng, D. Keith McInnes, Sowmya R. Rao, James A. Rothendler, David Haggstrom, Erica A. Abel, Lisa S. Cioffari, Thomas K. Houston

Research output: Contribution to journalArticle

21 Citations (Scopus)

Abstract

Background: 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.

Objective: Our aim was to characterize the reach of the VA personal health record by clinical condition.

Methods: 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.

Results: 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.

Conclusions: 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.

Original languageEnglish
Article numbere272
JournalJournal of Medical Internet Research
Volume16
Issue number12
DOIs
StatePublished - Dec 1 2014

Fingerprint

Personal Health Records
Veterans Health
United States Department of Veterans Affairs
Cross-Sectional Studies
Veterans
Psychotic Disorders
Prescriptions
Schizophrenia
Logistic Models
Self Care
Hyperlipidemias
Spinal Cord Injuries
Alcoholism
Health Status
Substance-Related Disorders
Cluster Analysis
Comorbidity
Inpatients
Outpatients
Stroke

Keywords

  • Medical conditions
  • Patient characteristics
  • Personal health records
  • Veterans

ASJC Scopus subject areas

  • Health Informatics

Cite this

Shimada, S. L., Brandt, C. A., Feng, H., McInnes, D. K., Rao, S. R., Rothendler, J. A., ... Houston, T. K. (2014). Personal Health record reach in the veterans health administration: A cross-sectional analysis. Journal of Medical Internet Research, 16(12), [e272]. https://doi.org/10.2196/jmir.3751

Personal Health record reach in the veterans health administration : A cross-sectional analysis. / Shimada, Stephanie Leah; Brandt, Cynthia A.; Feng, Hua; McInnes, D. Keith; Rao, Sowmya R.; Rothendler, James A.; Haggstrom, David; Abel, Erica A.; Cioffari, Lisa S.; Houston, Thomas K.

In: Journal of Medical Internet Research, Vol. 16, No. 12, e272, 01.12.2014.

Research output: Contribution to journalArticle

Shimada, SL, Brandt, CA, Feng, H, McInnes, DK, Rao, SR, Rothendler, JA, Haggstrom, D, Abel, EA, Cioffari, LS & Houston, TK 2014, 'Personal Health record reach in the veterans health administration: A cross-sectional analysis', Journal of Medical Internet Research, vol. 16, no. 12, e272. https://doi.org/10.2196/jmir.3751
Shimada, Stephanie Leah ; Brandt, Cynthia A. ; Feng, Hua ; McInnes, D. Keith ; Rao, Sowmya R. ; Rothendler, James A. ; Haggstrom, David ; Abel, Erica A. ; Cioffari, Lisa S. ; Houston, Thomas K. / Personal Health record reach in the veterans health administration : A cross-sectional analysis. In: Journal of Medical Internet Research. 2014 ; Vol. 16, No. 12.
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abstract = "Background: 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.Objective: Our aim was to characterize the reach of the VA personal health record by clinical condition.Methods: 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.Results: 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.Conclusions: 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.",
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