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Electronic personal health records (PHRs) can support patient self-management of chronic conditions. Managing human immunodeficiency virus (HIV) viral load, through taking antiretroviral therapy (ART) is crucial to long term survival of persons with HIV. Many persons with HIV have difficulty adhering to their ART over long periods of time. PHRs contribute to chronic disease self-care and may help persons with HIV remain adherent to ART. Proportionally veterans with HIV are among the most active users of the US Department of Veterans Affairs (VA) PHR, called My HealtheVet. Little is known about whether the use of the PHR is associated with improved HIV outcomes in this population.
The objective of this study was to investigate whether there are associations between the use of PHR tools (electronic prescription refill and secure messaging [SM] with providers) and HIV viral load in US veterans.
We conducted a retrospective cohort study using data from the VA’s electronic health record (EHR) and the PHR. We identified veterans in VA care from 2009-2012 who had HIV and who used the PHR. We examined which ones had achieved the positive outcome of suppressed HIV viral load, and whether achievement of this outcome was associated with electronic prescription refill or SM. From 18,913 veterans with HIV, there were 3374 who both had a detectable viral load in 2009 and who had had a follow-up viral load test in 2012. To assess relationships between electronic prescription refill and viral control, and SM and viral control, we fit a series of multivariable generalized estimating equation models, accounting for clustering in VA facilities. We adjusted for patient demographic and clinical characteristics associated with portal use. In the initial models, the predictor variables were included in dichotomous format. Subsequently, to evaluate a potential dose-effect, the predictor variables were included as ordinal variables.
Among our sample of 3374 veterans with HIV who received VA care from 2009-2012, those who had transitioned from detectable HIV viral load in 2009 to undetectable viral load in 2012 tended to be older (
PHR use, specifically use of electronic prescription refill, was associated with greater control of HIV. Additional studies are needed to understand the mechanisms by which this may be occurring.
Electronic health records (EHRs) are increasingly being adopted by hospitals, health plans, and other health care providers to improve the efficiency and effectiveness of health care delivery, meet provisions of the Affordable Care Act, and to qualify for Meaningful Use financial incentives [
Controlling the amount of HIV virus in the bloodstream is crucial to persons with HIV, and combination ART is highly effective at reducing HIV viral load when taken as prescribed. But the management of HIV is complex. Patients must carefully adhere to their ART regimen both to control viremia and to reduce the likelihood of drug resistance. Lab work is needed regularly to monitor HIV virus levels and the status of the immune system through CD4 cell counts [
This study examines use of the My HealtheVet PHR Rx refill and SM features by persons with HIV in a large integrated health care system. We sought to examine whether use of these tools was associated with undetectable viral load. To this end, we identified a cohort of HIV-infected veterans receiving US Department of Veterans Affairs (VA) health care and examined their patterns of My HealtheVet PHR use along with their laboratory results for HIV viral load status in 2 time periods.
We conducted a retrospective cohort study, identifying veterans with HIV who used the My HealtheVet PHR and followed them to assess outcomes of suppression of viral load. The study was approved by the Bedford Massachusetts VA Medical Center Institutional Review Board.
We used data from the VA system of medical records available through the VA Corporate Data Warehouse (CDW). Variables included patient demographics and International Classification of Disease, 9th revision, clinical modification (ICD-9-CM) diagnosis codes associated with all VA inpatient and outpatient encounters from October 1, 2007, to March 31, 2012. These data were linked at the patient level with My HealtheVet registration, SM, and Rx refill data from April 2012.
The study population included all American veterans aged 18 years and older who had obtained care from the VA health care system between April 1, 2010, and March 31, 2012 (N=6,012,875). Obtaining care in the VA was defined as having at least two outpatient visits or 1 inpatient hospitalization for any cause during this period. The cohort of HIV-infected patients was identified by examining VA’s decision support system laboratory results contained in CDW. Inclusion criteria for the cohort were: (1) a veteran determined to be HIV positive based on 2 or more instances of ICD-9-CM codes for HIV in the CDW, (2) had a detectable viral load in 2009, and (3) had viral load test results (detectable or undetectable) in 2012. For these analyses, an undetectable viral load was considered less than 200 copies of the HIV virus per milliliter (mL) of blood (<200/mL); conversely, 200 copies or more of the HIV virus per mL of blood (>=200/mL) indicated a detectable viral load. We identified 18,913 veterans who were HIV-positive and had a viral load test result in 2009 (See
Creation of analytical database.
VA launched the My HealtheVet PHR in 2003 and enrollment has grown to approximately 3.5 million current registered users as of January 2016 [
Use of My HealtheVet Rx refill and SM features were the independent variables of interest. We examined whether each of these tools was used by each veteran in our sample in the 3-year follow-up period from 2010-2012, and whether use of the tool was associated with undetectable viral load. These 2 variables were dichotomous with 1 indicating use of Rx refill at least one time in the 2010-12 period, and 0 indicating no use of Rx refill during that time period. The SM variable was created in the same way, with 1 indicating at least one use in 2010-12 and 0 indicating no use during that time period. In separate analyses, we also explored whether there may be a dose-response such that sustained use of the tool (Rx refill or SM) was associated with an increased likelihood of having an undetectable viral load. For those analyses, each of the variables (Rx refill and SM) was coded as an ordinal variable with 0 indicating no use in 2010-12, 1 indicating use in only 1 of the 3 years, and 2 indicating use in 2 or more of the 3 years.
The outcome of interest was viral load status in 2012. It was coded 1 for viral load < 200 mL (undetectable) and 0 for viral load >=200 mL (detectable).
Following Shimada et al who examined electronic prescription refill and SM among 6 million veterans using VA health services, we included in our multivariable analyses the following demographic characteristics: age, gender, race or ethnicity, urban or rural residence based on home postal code, and economic need defined as eligibility for free care based on an annual VA means testing [
We began by examining bivariate relationships between HIV viral control and the independent variables using cross-tabulation and chi-square tests. To assess relationships between Rx refill and viral control, and SM and viral control, with the sample of 3289 patients, we fit a series of multivariable generalized estimating equation models, accounting for clustering in VA facilities. To understand how patient characteristics might bias the primary association of Rx refill (or SM) and viral control, our models controlled for socio-demographics (age, gender, race or ethnicity, economic need, marital status, rural or urban status) and health status (ie, Elixhauser comorbidity burden, as well as separate indicators of alcohol use, other substance use, depression, and psychoses). We ran models for Rx refill and SM separately. In initial models the predictor variables were included in dichotomous format. Subsequently, to evaluate a potential dose-effect, the predictor variables were included as ordinal, as described previously. This produced 4 different models. We considered statistical significance to be
Sociodemographic, health, and PHR use data are shown in
Participant characteristics, overall and by human immunodeficiency virus (HIV) viral control in 2012.
Variable | Overall, n (%) | Viral control | |||
Viral load undetectable, n (%) | Viral load detectable, n (%) | ||||
3374 (100) | 2247 (66.60) | 1127 (33.40) | |||
.003 | |||||
<45 | 637 (18.88) | 414 (18.42) | 223 (19.79) | ||
45-54 | 1190 (35.27) | 776 (34.53) | 414 (36.73) | ||
55-64 | 1226 (36.34) | 814 (36.23) | 412 (36.56) | ||
65+ | 321 (9.51) | 243 (10.81) | 78 (6.92) | ||
.05 | |||||
Female | 128 (3.79) | 75 (3.34) | 53 (4.70) | ||
Male | 3246 (96.21) | 2172 (96.66) | 1074 (95.30) | ||
<.001 | |||||
White | 1130 (33.49) | 826 (36.76) | 304 (26.97) | ||
Black | 2076 (61.53) | 1309 (58.26) | 767 (68.06) | ||
Hispanic | 28 (0.83) | 15 (0.67) | 13 (1.15) | ||
Native Hawaiian | 29 (0.86) | 24 (1.07) | 5 (0.44) | ||
American Indian | 14 (0.41) | 10 (0.45) | 4 (0.35) | ||
Asian | 11 (0.33) | 8 (0.36) | 3 (0.27) | ||
Unknown | 86 (2.55) | 55 (2.45) | 31 (2.75) | ||
.22 | |||||
Eligible for free care | 1554 (46.06) | 1018 (45.30) | 536 (47.56) | ||
Not eligible | 1820 (53.94) | 1229 (54.70) | 591 (52.44) | ||
.001 | |||||
Married | 387 (11.47) | 259 (11.53) | 128 (11.36) | ||
Never married | 1567 (46.44) | 1040 (46.28) | 527 (46.76) | ||
Divorced | 1037 (30.74) | 700 (31.15) | 337 (29.90) | ||
Separated | 228 (6.76) | 154 (6.85) | 74 (6.57) | ||
Widowed | 120 (3.56) | 83 (3.69) | 37 (3.28) | ||
Others | 35 (1.04) | 11 (0.49) | 24 (2.13) | ||
.18 | |||||
Missing | 82 (2.43) | 51 (2.27) | 31 (2.75) | ||
Urban | 3002 (88.97) | 1990 (88.56) | 1012 (89.80) | ||
Rural | 290 (8.60) | 206 (9.17) | 84 (7.45) | ||
Depression (% yes) | 2024 (60.04) | 1325 (58.97) | 699 (62.19) | .07 | |
Substance use (% yes) | 1397 (41.44) | 894 (39.79) | 503 (44.75) | .006 | |
Problem alcohol use (% yes) | 1112 (32.99) | 713 (31.73) | 399 (35.50) | .03 | |
Psychoses (% yes) | 213 (6.32) | 123 (5.47) | 90 (8.01) | .004 | |
Elixhauser comorbidity score, mean (STD) | 2.69 (2.35) | 2.67 (2.38) | 2.72 (2.31) | .57 | |
Registered to use My HealtheVet as of 2012 | 1130 (33.49) | 785 (34.94) | 345 (30.61) | .01 | |
Use Rx refill (2010-2012) | 601 (17.81) | 435 (19.36)) | 166 (14.73) | <.001 | |
Use secure messaging (2010-2012) | 200 (5.93) | 147 (6.54) | 53 (4.70) | .03 |
There were differences between veterans with undetectable versus detectable viral load. Veterans with undetectable viral load were older (10.81% vs 6.92%, 65+ years), more likely to be male (96.66% vs 95.30%), white (36.76% vs 26.97%), and divorced (31.15% vs 29.90%). They were less likely than veterans with detectable viral load to have symptoms of depression (58.97% vs 62.19%), substance use disorder (39.79% vs 44.75%), problem alcohol use (31.73% vs 35.50%), or psychoses (5.47% vs 8.01%). Those with undetectable viral load were also more likely to be registered for My HealtheVet (34.94% vs 30.61%), to have used Rx refill (19.36% vs 14.73%), and to have used SM (6.54% vs 4.70%).
In our multivariable model examining use of Rx refill, there was a positive association between use of Rx refill and viral load control (
Multivariable analysis of the odds of undetectable viral load in 2012 in relation to Rx refill use (n=3289).
Variable | Estimate | Odds ratio | 95% CI | |
Use Rx refill 2010-2012 (dichotomous) | 0.3085 | 1.36 | 1.11-1.66 | .003 |
Age | 0.0132 | 1.01 | 1.00-1.02 | .004 |
Male | 0.2555 | 1.29 | 0.86-1.94 | .22 |
White race | 0.399 | 1.49 | 1.21-1.83 | <.001 |
Economic need (means test) | -0.101 | 0.90 | 0.78-1.05 | .19 |
Married | -0.053 | 0.95 | 0.78-1.16 | .61 |
Elixhauser score | -0.009 | 0.99 | 0.96-1.03 | .61 |
Problem alcohol use | -0.007 | 0.99 | 0.84-1.17 | .93 |
Substance use | -0.059 | 0.94 | 0.76-1.18 | .60 |
Depression | -0.067 | 0.94 | 0.79-1.11 | .44 |
Psychoses | -0.417 | 0.66 | 0.46-0.95 | .03 |
Rural | 0.1506 | 1.16 | 0.86-1.57 | .33 |
There were similar associations when viral load was modeled with SM as the predictor variable. However, SM did not achieve a statistically significant association with viral load status (
Multivariable analysis of the odds of undetectable human immunodeficiency virus (HIV) viral load in 2012 in relation to secure messaging (SM) use (n=3289).
Variable | Estimate | Odds ratio | 95% CI | |
Use secure messaging | 0.2462 | 1.279 | 0.89-1.85 | .19 |
Age | 0.0114 | 1.012 | 1.00-1.02 | .01 |
Male | 0.2748 | 1.316 | 0.87-1.99 | .19 |
White race | 0.4231 | 1.527 | 1.25-1.86 | <.001 |
Economic need (means test) | -0.107 | 0.898 | 0.78-1.04 | .15 |
Married | -0.063 | 0.939 | 0.77-1.15 | .53 |
Elixhauser score | -0.008 | 0.992 | 0.96-1.03 | .64 |
Problem alcohol use | -0.017 | 0.983 | 0.84-1.16 | .83 |
Substance use | -0.073 | 0.929 | 0.75-1.16 | .51 |
Depression | -0.057 | 0.944 | 0.80-1.12 | .51 |
Psychoses | -0.416 | 0.659 | 0.46-0.95 | .03 |
Rural | 0.1509 | 1.163 | 0.86-1.58 | .33 |
There was no evidence of a dose effect for either Rx refill or SM when treated as ordinal variables (
Multivariable analysis of the odds of undetectable human immunodeficiency virus (HIV) viral load in 2012 in relation to Rx refill use (Rx refill included as ordinal variable), for assessment of dose effect (n=3289).
Variable | Estimate | Odds ratio | 95% CI | |
Use Rx refill 0 years (ref) | - | - | - | - |
Use Rx refill 1 year | 0.3194 | 1.376 | 1.02-1.87 | .04 |
Use Rx refill 2-3 years | 0.3016 | 1.352 | 1.07-1.71 | .01 |
Age | 0.0132 | 1.013 | 1.00-1.02 | .004 |
Male | 0.2556 | 1.291 | 0.86-1.94 | .22 |
White race | 0.3995 | 1.491 | 1.21-1.83 | <.001 |
Economic need (means test) | -0.101 | 0.904 | 0.78-1.05 | .19 |
Married | -0.052 | 0.949 | 0.78-1.16 | .61 |
Elixhauser score | -0.009 | 0.991 | 0.96-1.03 | .61 |
Problem alcohol use | -0.007 | 0.993 | 0.84-1.17 | .93 |
Substance use | -0.059 | 0.943 | 0.76-1.17 | .60 |
Depression | -0.067 | 0.935 | 0.79-1.11 | .44 |
Psychoses | -0.417 | 0.659 | 0.46-0.95 | .03 |
Rural | 0.1501 | 1.162 | 0.86-1.57 | .33 |
The findings for SM also indicated no evidence of dose effect. The odds ratio for SM use in 1 year was 1.37 (95% CI 0.88-2.13) and for SM use in 2+ years was 1.02 (95% CI 0.51-2.01) though neither was statistically significant (
Multivariable analysis of the odds of undetectable human immunodeficiency virus (HIV) viral load in 2012 in relation to secure messaging (SM) use (as ordinal variable), for assessment of dose effect (n=3289).
Variable | Estimate | Odds ratio | 95% CI | |
Secure messaging 0 years (reference) | - | - | - | - |
Secure messaging 1 year | 0.3157 | 1.371 | 0.88-2.13 | .16 |
Secure messaging 2-3 years | 0.0149 | 1.015 | 0.51-2.01 | .97 |
Age | 0.0114 | 1.012 | 1.00-1.02 | .01 |
Male | 0.2759 | 1.318 | 0.87-1.99 | .19 |
White race | 0.4252 | 1.53 | 1.25-1.87 | <.001 |
Economic need (means test) | -0.106 | 0.9 | 0.77-1.04 | .16 |
Married | -0.064 | 0.938 | 0.77-1.14 | .53 |
Elixhauser score | -0.008 | 0.992 | 0.96-1.03 | .62 |
Problem alcohol use | -0.017 | 0.983 | 0.84-1.16 | .84 |
Substance use | -0.073 | 0.929 | 0.75-1.16 | .51 |
Depression | -0.056 | 0.945 | 0.80-1.12 | .51 |
Psychoses | -0.421 | 0.657 | 0.45-0.95 | .03 |
Rural | 0.1501 | 1.162 | 0.86-1.58 | .34 |
Our sensitivity analyses, in which the regression models were reestimated using the restricted sample of the 1130 registered patients, did not yield any substantively different results than those presented in
We found that among veterans with HIV, there was a positive association between My HealtheVet PHR use and undetectable viral load. Specifically, veterans who had detectable viral loads in 2009, and who used the Rx refill function between 2010 and 2012, had 1.36 times the likelihood of undetectable viral load in 2012 compared with veterans who did not use Rx refill. There was no evidence of dose effect of either of Rx refill or SM on the likelihood of undetectable viral load. No observational study can prove causality, but we had features that support a causal argument—we identified a longitudinal relationship, but not a clear dose-response. Thus it is possible that PHR use is a marker for some unmeasured covariates, such as engagement with the health care system.
Due to the study limitations, we cannot rule out that there may be other explanations for our main finding of an association between use of Rx refill and undetectable viral load. The most salient limitation is that as an observational study there is potential for confounding by indication, in that patients who are already activated to improve their health may also be more likely to try new tools, such as PHRs. It is possible that more empowered and self-efficacious patients decide to use a PHR, whereas patients who are less motivated and more challenged with self-management tasks do not. Self-efficacy and empowerment may be driving forces behind achievement of undetectable viral load, and not actually PHR use alone. However, by limiting our analytic sample to the HIV positive veterans who had uncontrolled viral load in 2009, we sought to minimize variation in self-efficacy and empowerment. Another important variable, which was not available in our dataset and thus not included in our models, is stigma. Data indicate that Web-based tools are seen as particularly valuable, and used more often, among persons with stigmatized health conditions than among persons with nonstigmatized conditions [
Additionally, the linkage between Web-based prescription refill and undetectable viral load is presumably mediated by proper medication taking and medication adherence. Our data did not permit us to evaluate medication adherence, or whether the PHR prescription refills were specifically for ART as compared with medications for other comorbid conditions (eg, for diabetes, hypertension). Additional studies are needed that address these limitations, for example by randomizing patients to PHR use, and by assessing ART adherence to see whether the trajectory from PHR use to undetectable viral load occurs though the expected taking of ART. Our sample was all veterans and mostly male, therefore our results may not be generalizable to nonveterans and to women. Another way that generalizability may be limited is that the VA is unlike many smaller health care systems in that it has succeeded in registering a large number of its patients for PHR use, approximately 3.5 million users as of 2016 [
Overall evidence on the effect of PHR use on care processes and outcomes for a variety of health conditions show mixed results [
In HIV, similarly, the evidence is mixed, with several studies suggesting that PHR use may assist with care processes and outcomes, but at least one study finding no association. A 6-site study by Shade et al [
Our findings also point to potential racial disparities in access to and use of HIV related care. In each of our multivariable analyses, white patients had greater odds of achieving viral control than other races (which were overwhelmingly black). This may be due to uncontrolled variables such as education level which may vary by race. Other research, including studies in the VA health care system, suggests various sources for racial disparities. Richardson et al recently examined racial differences in HIV care (and in comorbid care for HIV-infected patients) in VA and reported, “Despite the lack of insurance-related barriers to care in the equal-access VHA health care system, racial disparities in the care for veterans with HIV remain problematic and extend to comorbid conditions” [
The persistent finding, in each of our models, of a negative association between the presence of psychoses and uncontrolled viral load is noteworthy. This may indicate patients in this group have difficulty adhering to their HIV medications. Research into nonadherence (in general, not just for HIV) for persons with psychoses suggests that there are a number of potential barriers to adherence to medications. These include lack of social support, problems with therapeutic alliance, lack of daily routines, negative attitudes toward medications, and cognitive deficits [
More broadly, among persons with HIV, adoption and use of PHRs have been associated with a number of sociodemographic characteristics. A study of veterans with HIV found that PHR use is associated with younger age, less than excellent or very good health, white race, more education, lack of substance use disorder, and higher incomes [
PHRs provide patients with greater access to their providers and health information, and also provide tools that allow patients to undertake health self-management tasks more efficiently than through in-person or phone contact with their health care team [
Our examination of PHR use adds important information to the existing body of work. Our data come from a highly stigmatized and vulnerable population of veterans with HIV, many of whom have high economic need, are racial or ethnic minorities, have a mental health or substance use disorder, and may lack social support (only 11% married). Interestingly, this population has been shown to use VA’s My HealtheVet PHR more than other chronic disease groups [
Given our observational study design, however, further examination of the potential benefits of PHRs, and tools such as electronic prescription refill, are merited, especially if they can involve randomization. That a considerable proportion of this population is using PHR tools is encouraging—and yet about two-thirds do not. This suggests that continued efforts are needed to reach out to this population and to provide eHealth tools that are seen as easy to use and beneficial, regardless of the background or socio-economic and health status of the potential user.
antiretroviral therapy
Corporate Data Warehouse
electronic health record
Hemoglobin A1c
human immunodeficiency virus
information technology
milliliter
odds ratio
personal health record
secure messaging
Department of Veterans Affairs
We thank Dr Allen Gifford and Dr Matthew Goetz for their advice on the interpretation of the corporate data warehouse viral load laboratory results and Dr Cynthia Brandt for consulting on methods for identifying HIV diagnoses in VA datasets. Dr McInnes was supported by a Career Development Award (CDA 09-016) from VA Health Services Research and Development Service, and 3 VA Quality Enhancement Research Initiatives: eHealth QUERI (EHQ 10-190), HIV/Hepatitis QUERI (HIV 98-001), and Bridging the Care Continuum QUERI (15-284). The contents do not represent the views of the US Department of Veterans Affairs or the US Government.
None declared.