Publication

Article

The American Journal of Managed Care

April 2013
Volume19
Issue 4

Use of Web-Based Shared Medical Records Among Patients With HIV

Use of online shared records was higher among HIV patients who had indicators of recent increases in healthcare needs and lower among several vulnerable populations.

Objectives: To compare use of 7 shared electronic medical record (SMR) features by adult HIV patients.

Study Design: Observational cohort study of adult HIV-positive patients in the first 36 months following implementation of the SMR at Group Health and Kaiser Permanente Northern California.

Methods: Automated data from the 36 months following SMR implementation were assessed in 2 integrated delivery systems. Cox proportional hazards analysis identified factors associated with any SMR use.

Results: Most (3888/7398) patients used the SMR at least once. Users were most likely to view medical test results (49%), use secure messaging (43%), or request appointments (31%) or medication refills (30%). Initial use was associated with new prescription for antiretroviral therapy (rate ratio [RR] 1.65, P <.001), recent change to a CD4+ count of fewer than 200 cells per microliter (RR = 1.34, P <.02), new HIV RNA of 75 or more copies per milliliter (RR = 1.63, P <.001), or recent increase in non-HIV comorbidity score (RR = 1.49, P = .0001). Users were less likely to be women (RR = 0.49, P = .0001), injection drug users (RR = 0.59, P = .0001), or from lower—socioeconomic status neighborhoods (RR = 0.68, P = .0001), and were less likely to be black (RR = 0.38, P = .0001), Hispanic (RR = 0.52, P = .0001) or Asian/Pacific Islander (RR = 0.59, P = .001).

Conclusions: SMR use was higher among HIVpatients who had indicators of recent increases in healthcare needs and lower among several vulnerable populations.

Am J Manag Care. 2013;19(4):e114-e124This observational cohort study compared use of 7 features of an online shared medical record by adult patients with HIV.

  • Use was higher among those with HIV who had indicators of recent increases in healthcare needs and lower among several vulnerable populations.

  • Healthcare providers and systems should support use of online shared medical records among patients with HIV as part of broader efforts to improve overall access to care.

Ongoing collaboration with providers is essential for care of patients with HIV. To reduce HIV-related morbidity and mortality, patients and providers monitor CD4+ T-cell counts and HIV viral loads, and initiate and adjust antiretroviral therapy. Patients on antiretroviral therapy must adhere tightly to the regimen for benefits, while managing the medications’ frequent side effects.1 Healthcare systems that enable good communication with providers and access to services such as laboratory monitoring and medication refills are critical for patients to manage HIV infection successfully.

Patient websites providing secure access to electronic medical records that are shared between patients and healthcare providers may help meet the ongoing care needs of many patients with HIV. Also known as integrated personal health records, these web-based shared electronic medical records (SMRs) can provide a constellation of services for patients, typically including exchanging secure electronic messages and scheduling appointments with healthcare providers, ordering medication refills, and viewing care plans, medical test results, and other portions of the electronic medical record.2-4 Proposed federal meaningful use criteria for electronic health records support patients’ use of the SMR, including secure messaging with providers.5 Many of these services may help patients with HIV, particularly during times of heightened need (eg, when starting new antiretroviral medications or when there is a significant CD4+ count decrease).

Despite the SMR’s potential, some groups of patients disproportionately affected by HIV may be less likely to use it. HIV is estimated to be 9 times more common in blacks and nearly 3 times more common in Hispanics6 than in whites; black and Hispanic populations are also less likely to receive highly active antiretroviral therapy7 and experimental treatments. Individuals with low socioeconomic status (SES) are twice as likely to have HIV8 and are more likely to die of HIV,9 and less likely to receive highly active antiretroviral therapy. Older patients with HIV have faster progression of disease, with treatment often complicated by coexisting chronic health conditions.10 All these sociodemographic groups are also less likely to use the Internet11 and patient websites.12-15 An initial study of personal health record use among patients with HIV receiving care at San Francisco General Hospital also found that users were more likely to be Caucasian and non-Hispanic.16 Further understanding of potential differences in SMR use by patients with HIV who belong to vulnerable populations is essential to ensure that healthcare is designed to meet the needs of all patients with HIV. These potential differences are particularly important if the SMR is being used to support care at critical times, such as initiation of antiretroviral medications or a drop in CD4+ cell count.

METHODSStudy Design, Setting, and Participants

We performed a cohort study of adult HIV-positive patients in the first 36 months following implementation of the SMR at Group Health (GH) (August 1, 2003, to July 31, 2006) and Kaiser Permanente Northern California (KPNC) (November 1, 2005, to October 31, 2008). Group Health and KPNC are large, integrated healthcare delivery organizations providing multidisciplinary care, including HIV specialty care. The study population included enrollees 18 years or older in either institution’s HIV registry. Patients were followed from the date they met eligibility criteria (>18 years of age, HIV positive, enrolled in health plan) until the earliest of disenrollment, death, or the end of the study period.

Beginning in 2003 at GH and 2005 at KPNC, all patients could access an SMR (www.ghc.org or www.kp.org) with 7 features common to both sites: secure messaging with healthcare providers; requesting medication refills; requesting inperson appointments; and viewing after-visit summaries, allergies, immunizations, and test results (excluding CD4+ and HIV RNA results at KPNC). Detailed descriptions of the patient websites at GH3,17 and KPNC4 were previously reported. Patients verified their identity to GH or KPNC before using these features.17 We hypothesized that SMR use would be higher among those with a recent heightened need for care but lower among racial and ethnic minorities, older patients, and those from lower-SES groups.

Data Sources

The KPNC HIV registry18,19 includes all known cases since the early 1980s; the GH registry, since 1997. Registry data include sex; birth date; race/ethnicity; dates of known HIV infection and AIDS diagnoses; and at KPNC only, HIV transmission risk factors. There are also historical databases at KPNC and GH on member demographics, prescriptions, hospitalizations, outpatient visits, and laboratory tests, including CD4+ T-cell count and HIV RNA test results, health insurance status, and zip code. Date of death was identified from hospitalizations, membership files, California and Washington state death certificates,

and Social Security Administration data sets.

Measures

Use of the Shared Medical Record. The primary outcome of interest was any SMR use defined as using at least 1 of the 7 SMR features during the study period. Secondary outcome was continued SMR use (mean days of SMR use per month). Rates of use were measured as the number of days per month in which patients used any of the SMR features.

Variables Potentially Associated With Shared Medical Record Use. Primary predictors were recent increase in healthcare need, race/ethnicity, neighborhood SES, and age. We defined recent increase in healthcare need as 1 of the following clinical events occurring within the prior 3 months: start or restart of antiretroviral therapy; new CD4+ count of fewer than 200 cells per microliter; newly quantifiable HIV RNA of 75 or more copies per milliliter; or worsening comorbidity unrelated to HIV. Non-HIV morbidity was measured using a modified Charlson Comorbidity Index, excluding HIV/AIDS diagnoses.20 Neighborhood SES was categorized as low for a patient if at least 20% of 2000 Census block residents had an income below $20,000 or at least 25% of residents over age 25 years had not completed high school.14,21,22 Secondary predictors included sex, HIV risk factors, insurance status, time with health plan, and specific comorbid conditions (depression and hepatitis B and C). Predictor selection was based on prior studies of SMR use in other populations13,23,24 and prior studies of access to care in people with HIV.7 Depression was defined by outpatient diagnosis in prior 12 months. HIV transmission risk factors and history of hepatitis B and C were from the HIV and the hepatitis C virus/hepatitis B virus registries at each site.

Statistical Methods

We used Cox proportional hazards analysis to identify the factors associated with any use of the SMR. Outcome was time to first use; rate ratios (RRs; hazard ratios) compared the rate of initial use (percentage of patients per month who first used SMR) with that of a reference group. Separate Cox models were fit to each variable, first adjusting for site only, and then for site, sex, age, and non—HIV-related morbidity.

Race/ethnicity analyses adjusted for age, sex, and a modified Charlson Comorbidity Index (without HIV/AIDS)25; this allowed potential mediation of SMR use by racial/ethnic group through SES factors26 and is consistent with the Institute of Medicine recommendation for handling potential healthcare disparities (defined as any difference not due to clinical need or preferences) when comparing groups defined by race/ethnicity.25 Fixed and time-varying characteristics potentially associated with SMR use were identified before the analyses. We looked at baseline factors that did not change during follow-up and examined how the following time-varying factors (updated monthly) were related to use: non—HIV-related morbidity, antiretroviral use, CD4+ count, viral load, hepatitis B infection, hepatitis C infection, and depression diagnosis.

We tested for interactions between sites and each potential predictor of SMR use. To minimize the risk of false-positive interactions, interaction tests used a significance level of .01. We also tested for interactions between racial groups and HIV risk factor, sex, and overall HIV healthcare need in past 3 months (any start of antiretroviral therapy, new CD4+ count fewer than 200 cells per microliter, new HIV RNA of 75 or more copies per milliliter, or increase in Charlson Comorbidity Index score).

Cox models assessed the short-term effect of markers of increased healthcare need on the likelihood of initial SMR use. We defined short term as 3 months and assessed whether individuals were more likely to start using the SMR in the 3 months following 1 of these events: worsening non—HIVrelated morbidity, start of antiretroviral therapy, CD4+ count below 200 cells per microliter, or viral load exceeding 75 copies per milliliter.

We also examined which of these factors were correlated with more frequent use of the SMR among those who used the SMR at least once. We used negative binomial regression to compare rates of SMR use following initial use. To account for overdispersion typical of count data, we used robust standard errors. We fit 2 negative binomial regression models for each variable, first adjusting only for site and then for site, age, sex, and the non-HIV Charlson Comorbidity Index score.

Results

The study population consisted of 6644 KPNC and 754 GH patients (Table 1). Compared with GH patients, KPNC patients were more likely to be black (KPNC 17.7% vs 10.9% GH),Hispanic (KPNC 14.7% vs GH 5.4%), older (mean age KPNC 45.9 years vs GH 42.8 years), living in a low-SES neighborhood (KPNC 26.6% vs GH 18.1%), and HIV positive for longer (KPNC 9.3 years vs GH 3.5 years). Race/ethnicity was missing for 455 (6.6%) patients at KPNC and 67 (8.9%) patients at GH.

Overall Use of the Shared Medical Record by Health Plan

Over the 36-month study period, 3411 (51.3%) KPNC participants and 477 (63.6%) GH participants (P = .01 between sites) used the SMR. Among the SMR’s 7 available functions, the highest proportion of enrollees requested medication refills (27.9% KPNC, 58.9% GH); used secure messaging (41.1% KPNC, 57.6% GH); viewed medical test results (47.4% KPNC, 62.1% GH); and requested appointments (30.3% KPNC, 39.6% GH) (Table 2).

The Figure shows rates of use for SMR functions over the study period. In the final month of the study, the most frequently used features were viewing medical test results (16 unique users per 100 KPNC enrollees; 28 unique users per 100 GH enrollees), requesting medication refills (12 unique users per 100 KPNC enrollees; 34 unique users per 100 GH enrollees), and using secure messaging (14 unique users per 100 KPNC enrollees; 23 unique users per 100 GH enrollees).

Initial Shared Medical Record Use

We show results of analyses combining participants at KPNC and GH (Table 3). To see whether there was evidence that the factors associated with SMR use varied by site, we tested for interactions between each factor and site with SMR use as the outcome. None of the interactions were significant, so we report only the overall hazard ratio for each factor. Concordant with hypotheses, initial users were less likely to be black (ratio of sign-up rates [RR] = 0.35, P = .0001), Hispanic (RR = 0.54, P = .0001), Asian/Pacific Islander (RR = 0.62, P = .0001), or Native American (RR = 0.30, P = .04) than to be of non-Hispanic white. These differences persisted in analyses adjusting for age, sex, and non-HIV morbidity. The relationship between initial SMR use and race/ethnicity was similar across risk factors for HIV (P = .10 for interaction test) and across sex (P = .76). These racial differences were present whether or not someone had recently experienced 1 or more of the HIV-related clinical events listed in Table 4, such as starting on antiretroviral therapy or having their viral load rise above the detectable limit (P = .50 to test for race by event interaction). As shown in Table 3, SMR users were also less likely to live in lower-SES neighborhoods (RR = 0.66, P = .0001). Contrary to our hypothesis, SMR users were not more likely to be younger (RR = 1.18, P = .06 comparing those 50 years and older with those aged 18-29 years).

Users of SMR were more likely to be men (RR 2.05, P = .0001) (Table 3). Compared with men with a history of sex with men, SMR use was lower among those with a history of injection drug use (RR = 0.60, P = .0001) and heterosexual activity (RR = 0.43, P = .0001). Users of SMR were more likely to be older than 18 to 29 years (RR = 1.34 and P = .001 for 30-39 years; RR = 1.18 and P = .05 for 40-49 years); have a lower non-HIV morbidity score (RR = 0.77, P = .0001 comparing high with low Charlson Comorbidity Index scores); be receiving antiretroviral therapy (RR = 1.30, P = .0001); have a CD4+ count of fewer than 200 cells per microliter (RR = 0.83, P = .002); have hepatitis C (RR = 0.76, P = .0002); have depression (RR = 1.24, P = .0001); have been with a health plan less than a year (RR = 1.53, P = .0001); and have Medicare (RR = 0.83, P = .001) or Medicaid (RR = 0.35, P = .0001) compared with commercial insurance. Those 50 years and older had a trend toward higher use compared with patients aged 18 to 29 years (RR = 1.18, P = .06). All tests of the proportional hazards assumption were nonsignificant, indicating the association of each variable with initial SMR use was similar in all 3 years.

Recent Healthcare Need and Initial Shared Medical Record Use

Concordant with our hypotheses, higher initial use of SMR was associated with a new prescription for antiretroviral therapy (RR = 1.69, P <.0001), a recent change to HIV RNA of 75 or more copies per milliliter (RR = 1.69, P <.0001), a recent change to a CD4+ count of fewer than 200 cells per microliter, and a recent change to a higher non-HIV morbidity score (Table 4).

Amount of Shared Medical Record Use

Among those who used the SMR at least once, black SMR users on average used the SMR 20% less frequently than did white SMR users (RR = 0.80, P = .0001) (Table 5). Hispanic and Asian/Pacific Islander SMR users used it about 15% less (P = .02 and P = .04, respectively). Adjustment for age, sex, site, and healthcare need minimally changed results. Using the SMR more often was associated with a recent change to detectable HIV RNA of 75 or more copies per milliliter (RR = 1.10, P <.03) (Table 6).

Discussion

In the first 3 years after implementation, a little more than half of all patients with HIV used at least 1 SMR feature. Patients were most likely to use the SMR to communicate electronically with providers, obtain medication refills, schedule appointments, and view medical test results. Compared with other SMR features, these 4 services support more frequent patient activities in managing HIV care. Patients with HIV used these 4 online features 2 to 5 times more often each month than the general enrollee population.3,4 In 2006, for example, the general population at GH had 4 unique users of secure messaging each month for every 100 enrollees3 compared with 23 unique users for every 100 patients with HIV. Use of an SMR was also more likely in patients with a recent decline in CD4+ count, a newly elevated HIV RNA level, and recent initiation of antiretroviral therapy. These events often mark a heightened need for care that may include communication with healthcare providers between office visits and medication adjustment or monitoring. To help meet these needs, providers have traditionally used phone calls between office visits; but for many patients, the SMR may now be more efficient and effective. Although no trials have reported using the SMR to improve care of individuals with HIV, trials using the SMR as part of planned care interventions in other chronic conditions have found improved clinical outcomes, including glycemic control in patients with type 2 diabetes,27 blood pressure control in patients with hypertension,28 and easing of depression in patients recently started on antidepressant medications.29 Our results suggest the online features of the SMR may help healthcare providers and systems better support many patients with HIV at key times of need.

SMR adoption, however, was not uniform. Major groups of patients disproportionately affected by HIV were less likely to use the SMR. Compared with the white population, blacks were two-thirds less likely, and Hispanics about half as likely, to use the SMR at all. Among those who had used the SMR at least once, blacks used the SMR 19% less often and Hispanics 11% less often than whites. Users of the SMR were also less likely to be from low-SES neighborhoods or have Medicaid insurance. Our results extend findings of other studies among patients with HIV, people with diabetes, and the general population that showed less use of patient websites among minority racial and ethnic groups12-16 and among people with lower-SES status.12,15,23 For race and ethnicity, 2 of these studies found less use among blacks regardless of education level,13,15 suggesting the reasons for the differences transcend SES clustering.13-15,30 For some patients who have experienced discrimination or have lower trust in healthcare providers, the additional social distance associated with the SMR may be a barrier to use. These minority groups have a higher prevalence of HIV and are less likely to receive combination antiretroviral therapy,6-9 raising concerns about the possibility of widening disparities in access associated with SMR implementations.

Use of the SMR differed by a few other important patient factors. In contrast to studies in the general population24,31 and patients with diabetes15,23 that showed lower use in the older population, older age was associated with a trend toward higher adoption of the SMR. This may be because there are relatively few individuals over the age of 65 years in the HIV populations studied or because of unmeasured patient characteristics attenuating the effect of age in this population. Among SMR users, those 50 years and older also used the SMR more than those aged 18 to 29 years, suggesting that older individuals may be using the SMR to support their overall higher need for care. Patients with depression were more likely to use the SMR, which is in agreement with a study showing that mental health and substance abuse conditions were not barriers to engagement in personal health record use.32 Compared with men, women were about half as likely to use the SMR, which is also consistent with a prior study of personal health record use among patients with HIV.16 Women have worse HIV-related health outcomes,33 less use of combination antiretroviral therapy,7,34 and greater likelihood of discontinuing antiretroviral therapy.33-35 Use of the SMR was also less likely among those with a history of intravenous drug use or heterosexual exposure; both of these populations are also less likely to receive antiretroviral therapy compared with the population of men who have sex with men.7 Further research is needed to identify the causes behind these differences in SMR use and to alleviate potential disparities in access to care. For those individuals from lower- income populations, including many intravenous drug users,36 text messaging or mobile health applications may enable further reach of some SMR features. We did not find differences in patient demographic characteristics to account for the site differences in overall rate of initial use.

The study has several limitations. We evaluated use of the SMR among patients with HIV receiving care in 2 integrated healthcare delivery systems using advanced electronic medical record systems. Although use of SMRs and advanced electronic medical records is increasing, the generalizability of these results is currently limited. We could not measure participants’ individual-level education or income, both of which are associated with the digital divide.37 Patients at KPNC were not able to view CD4 or HIV RNA results in the SMR. We also could not measure patient preferences or abilities for communicating with healthcare providers. We did not account for potential provider factors38 and did not have complete information on different marketing efforts by the healthcare organizations that may have played a role in patients’ SMR use. Examining the relationship between SMR use and other healthcare utilization, including phone and inperson visits, was also beyond the scope of this analysis. Finally, we examined the first 3 years of use of the SMR. Although the pattern of adoption by racial and ethnic minorities did not change over this time period, longer studies may show different patterns of adoption over time, especially as both organizations conduct specific outreach to minority groups.

We found higher use of the SMR among patients with a recent increase in need for healthcare and found lower use across 4 racial and ethnic minority groups, among women, and among patients with a history of injection drug use and lower SES. Healthcare systems should continue efforts to enable SMR use by all patients, while integrating SMR access into broader efforts to better meet patients’ needs and preferences for access to care, whether in person, online, or by phone. Patients and physicians must be able to communicate freely through the best means possible for each patient and healthcare need. Future studies should seek to better understand and address the needs and care preferences of vulnerable HIV populations with respect to the SMR.The authors thank Gwen Schweitzer for her help in manuscript preparation.

Author Affiliations: From Group Health Research Institute (JDR, LG, TR, CS, SC, SLC), Group Health Cooperative, Seattle, WA; Division of Research (MJS, WAL), Kaiser Permanente, Oakland, CA; Department of Research (MH), Mid-Atlantic Permanente Medical Group, Rockville, MD.

Funding Source: This research was supported by National Institutes of Health grant 5R01MH081750-03 (principal investigator, Sheryl L. Catz) and grant K01AI071725 (principal investigator, Michael Silverberg).

Author Disclosures: Dr Silverberg reports receiving grants from Pfizer and Merck. Dr Catz reports that she was the principal investigator for this research study. The other authors (JDR, LG, WAL, TR, CS, SC, MH) report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Authorship Information: Concept and design (JDR, LG, SC, MH, SLC); acquisition of data (JDR, MJS, LG, WAL, TR, SC, SLC); analysis and interpretation of data (JDR, MJS, LG, WAL, TR, CS, SC, MH, SLC); drafting of the manuscript (JDR, CS, SC, SLC); critical revision of the manuscript for important intellectual content (JDR, MJS, LG, SC, MH, SLC); statistical analysis (JDR, LG); provision of study materials or patients (SC); obtaining funding (JDR, SC, SLC); and administrative, technical, or logistic support (TR, SC).

Address correspondence to: James D. Ralston, MD, MPH, Group Health Research Institute, 1730 Minor Ave, Ste 1600, Seattle, WA 98101-1448. Email ralston.j@ghc.org.1. Hammer SM, Eron JJ Jr, Reiss P, et al; International AIDS Society-USA. Antiretroviral treatment of adult HIV infection: 2008 recommendations of the International AIDS Society-USA panel. JAMA. 2008;300(5): 555-570.

2. Tang PC, Lansky D. The missing link: bridging the patient-provider health information gap. Health Aff (Millwood). 2005;24(5):1290-1295.

3. Ralston JD, Coleman K, Reid RJ, Handley MR, Larson EB. Patient experience should be part of meaningful-use criteria. Health Aff (Millwood). 2010;29(4):607-613.

4. Silvestre AL, Sue VM, Allen JY. If you build it, will they come? the Kaiser Permanente model of online health care. Health Aff (Millwood). 2009;28(2):334-344.

5. HIT Policy Committee. Meaningful Use Workgroup Request forComments Regarding Meaningful Use Stage 2. http://www.healthit.gov/sites/default/files/mu-rfc.2-2011-01-12-final.pdf. Published 2011. Accessed February 22, 2013.

6. Centers for Disease Control and Prevention. Diagnoses of HIV infection and AIDS in the United States and dependent areas, 2009. HIV/AIDS Surveillance Report. Vol 21. http://www.cdc.gov/hiv/surveillance/resources/reports/2009report/. Last updated February 16, 2011. Accessed February 22, 2013.

7. Andersen R, Bozzette S, Shapiro M, et al. Access of vulnerable groups to antiretroviral therapy among persons in care for HIV disease in the United States. HCSUS Consortium. HIV Cost and Services Utilization Study. Health Serv Res. 2000;35(2):389-416.

8. Denning P, DiNenno E. Communities in crisis: is there a generalized HIV epidemic in impoverished urban areas of the United States. Paper presented at: XVIII International AIDS Conference; July 18-23, 2010; Vienna, Austria.

9. Cunningham WE, Hays RD, Duan N, et al. The effect of socioeconomic status on the survival of people receiving care for HIV infection in the United States. J Health Care Poor Underserved. 2005;16(4): 655-676.

10. Kirk JB, Goetz MB. Human immunodeficiency virus in an aging population, a complication of success. J Am Geriatr Soc. 2009;57(11): 2129-2138.

11. PEW Internet and American Life Project. Demographics of internet users. http://www.pewinternet.org/Static-Pages/Trend-Data/Whos-Online.aspx. Published 2010. Accessed May 17, 2011.

12. Yamin CK, Emani S, Williams DH, et al. The digital divide in adoption and use of a personal health record. Arch Intern Med. 2011;171(6): 568-574.

13. Roblin DW, Houston TK 2nd, Allison JJ, Joski PJ, Becker ER. Disparities in use of a personal health record in a managed care organization. J Am Med Inform Assoc. 2009;16(5):683-689.

14. Hsu J, Huang J, Kinsman J, et al. Use of e-Health services between 1999 and 2002: a growing digital divide. J Am Med Inform Assoc. 2005; 12(2):164-171.

15. Sarkar U, Karter AJ, Liu JY, et al. Social disparities in internet patient portal use in diabetes: evidence that the digital divide extends beyond access. J Am Med Inform Assoc. 2011;18(3):318-321.

16. Kahn JS, Hilton JF, Van Nunnery T, et al. Personal health records in a public hospital: experience at the HIV/AIDS clinic at San Francisco General Hospital. J Am Med Inform Assoc. 2010;17(2):224-228.

17. Ralston JD, Carrell D, Reid R, Anderson M, Moran M, Hereford J. Patient web services integrated with a shared medical record: patient use and satisfaction. J Am Med Inform Assoc. 2007;14(6):798-806.

18. Horberg MA, Hurley LB, Silverberg MJ, Kinsman CJ, Quesenberry CP. Effect of clinical pharmacists on utilization of and clinical response to antiretroviral therapy. J Acquir Immune Defic Syndr. 2007;44(5):531-539.

19. Silverberg MJ, Leyden W, Horberg MA, DeLorenze GN, Klein D, Quesenberry CP Jr. Older age and the response to and tolerability of antiretroviral therapy. Arch Intern Med. 2007;167(7):684-691.

20. Hartzell JD, Spooner K, Howard R, Wegner S, Wortmann G. Race and mental health diagnosis are risk factors for highly active antiretroviral therapy failure in a military cohort despite equal access to care. J Acquir Immune Defic Syndr. 2007;44(4):411-416.

21. Braveman PA, Cubbin C, Egerter S, et al. Socioeconomic status in health research: one size does not fit all. JAMA. 2005;294(22): 2879-2888.

22. Krieger N. Overcoming the absence of socioeconomic data in medical records: validation and application of a census-based methodology. Am J Public Health. 1992;82(5):703-710.

23. Weppner WG, Ralston JD, Koepsell TD, et al. Use of a shared medical record with secure messaging by older patients with diabetes. Diabetes Care. 2010;33(11):2314-2319.

24. Ralston JD, Rutter CM, Carrell D, Hecht J, Rubanowice D, Simon GE. Patient use of secure electronic messaging within a shared medical record: a cross-sectional study. J Gen Intern Med. 2009;24(3): 349-355.

25. Smedley BD, Stith AY, Nelson AR, eds; Committee on Understanding and Eliminating Racial and Ethnic Disparities in Health Care, Board on Health Sciences Policy, Institute of Medicine. Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care. Washington, DC: National Academies Press; 2003

.

26. Lê Cook B, McGuire TG, Zuvekas SH. Measuring trends in racial/ethnic health care disparities. Med Care Res Rev. 2009;66(1):23-48.

27. Ralston JD, Hirsch IB, Hoath J, Mullen M, Cheadle A, Goldberg HI. Web-based collaborative care for type 2 diabetes: a pilot randomized trial. Diabetes Care. 2009;32(2):234-239.

28. Green BB, Cook AJ, Ralston JD, et al. Effectiveness of home blood pressure monitoring, Web communication, and pharmacist care on hypertension control: a randomized controlled trial. JAMA. 2008;299(24): 2857-2867.

29. Simon GE, Ralston JD, Savarino J, Pabiniak C, Wentzel C, Operskalski BH. Randomized trial of depression follow-up care by online messaging. J Gen Intern Med. 2011;26(7):698-704.

30. Kalichman SC, Weinhardt L, Benotsch E, DiFonzo K, Luke W, Austin J. Internet access and Internet use for health information among people living with HIV-AIDS. Patient Educ Couns. 2002;46(2):109-116.

31. Weingart SN, Rind D, Tofias Z, Sands DZ. Who uses the patient internet portal? the PatientSite experience. J Am Med Inform Assoc. 2006;13(1):91-95.

32. Hilton JF, Barkoff L, Chang O, et al. A cross-sectional study of barriers to personal health record use among patients attending a safetynet clinic. PLoS One. 2012;7(2):e31888.

33. Losina E, Schackman BR, Sadownik SN, et al. Racial and sex disparities in life expectancy losses among HIV-infected persons in the United States: impact of risk behavior, late initiation, and early discontinuation of antiretroviral therapy. Clin Infect Dis. 2009;49(10): 1570-1578.

34. Wood E, Montaner JS, Tyndall MW, Schechter MT, O’Shaughnessy MV, Hogg RS. Prevalence and correlates of untreated human immunodeficiency virus type 1 infection among persons who have died in the era of modern antiretroviral therapy. J Infect Dis. 2003;188(8): 1164-1170.

35. Gebo KA, Fleishman JA, Conviser R, et al; HIV Research Network. Racial and gender disparities in receipt of highly active antiretroviral therapy persist in a multistate sample of HIV patients in 2001. J Acquir Immune Defic Syndr. 2005;38(1):96-103.

36. Schrager L, Friedland G, Feiner C, Kahl P. Demographic characteristics, drug use, and sexual behavior of i.v. drug user with AIDS in Bronx, New York. Public Health Rep. 1991;106(1):78-84.

37. Mehra B, Merkel C, Bishop AP. The internet for empowerment of minority and marginalized users. New Media & Society. 2004;6(6): 781-802.

38. Wald JS. Variations in patient portal adoption in four primary care practices. AMIA Annu Symp Proc. 2010:837-841.

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