0
We're unable to sign you in at this time. Please try again in a few minutes.
Retry
We were able to sign you in, but your subscription(s) could not be found. Please try again in a few minutes.
Retry
There may be a problem with your account. Please contact the AMA Service Center to resolve this issue.
Contact the AMA Service Center:
Telephone: 1 (800) 262-2350 or 1 (312) 670-7827  *   Email: subscriptions@jamanetwork.com
Error Message ......
Research Letters |

Impact of Electronic Health Records on Racial and Ethnic Disparities in Blood Pressure Control at US Primary Care Visits FREE

Lipika Samal, MD, MPH; Stuart R. Lipsitz, ScD; LeRoi S. Hicks, MD, MPH
[+] Author Affiliations

Author Affiliations: Division of General Medicine and Primary Care, Brigham and Women's Hospital, Boston, Massachusetts (Drs Samal and Lipsitz); and Division of Hospital Medicine, University of Massachusetts Medical System, Worcester (Dr Hicks).


Arch Intern Med. 2012;172(1):75-76. doi:10.1001/archinternmed.2011.604.
Text Size: A A A
Published online

Prior literature suggests that practice level characteristics mediate racial/ethnic disparities in clinical outcomes.1 One such practice level characteristic, use of electronic health records (EHRs) with clinical decision support (CDS), has been associated with improved blood pressure (BP) control in a national study.2 However, we do not know whether these effects differ across racial/ethnic groups.3 We sought to determine whether physician use of EHRs with and without CDS is associated with a reduction in racial/ethnic disparities in BP control in a nationally representative sample.

We examined data from primary care visits in the 2007-2008 National Ambulatory Medical Care Survey (NAMCS), a nationally representative survey of nonhospital-based ambulatory visits administered by the National Center for Health Statistics (NCHS).4 In a recent article, we examined visits to NAMCS physicians who answered questions about EHRs and electronic guideline-based reminders.2 Primary care visits for patients older than 20 years with a recorded systolic and diastolic BP were included, regardless of whether hypertension was indicated as a diagnosis code, reason for visit, or chronic condition. We used the race/ethnicity categories and imputed values provided by the NCHS.4 In the prior analysis, we controlled for race/ethnicity but did not examine whether the effect of EHR and/or CDS on BP control differed across racial/ethnic groups.2

We report herein disparities in BP control as weighted percentages of visits with BP lower than 140/90 mm Hg. We stratified visits according to patient race/ethnicity and physician use of EHRs and/or CDS. We compared BP control rates for minority patients and white patients whose physicians were using similar technology. We fit a logistic regression within each strata, controlling for patient age, sex, diabetes, insurance type, and practice ownership. We conducted a secondary analysis for the one-third of patients with a known diagnosis of hypertension. Statistical analyses were performed using SAS-callable SUDAAN software (SAS version 9.2 [SAS Institute Inc] and SUDAAN version 10.0 [RTI International]).

We based our analyses on 17 016 visits, representing (weighted) 682 million visits nationally. Patients had a mean age of 51 years, 33% were male, 15% had diabetes, 34% had hypertension, 64% were non-Hispanic white, 14% were non-Hispanic black, and 15% were Hispanic. Overall, 71% of non-Hispanic black patients had BP control compared with 76% for both Hispanic and non-Hispanic white patients (P < .001) after controlling for patient characteristics and practice ownership. Adjusted analyses limited to the known hypertensive subgroup showed similar differences in rates of BP control between non-Hispanic black (53% of visits) and non-Hispanic white patients (60% of visits) (P = .004).

Fifteen percent of visits were made to physicians using only EHRs, 27% to physicians using both EHRs and CDS, and 48% to physicians using neither. In fully adjusted analyses stratified by EHR and CDS use, we found improved BP control for all racial/ethnic groups among patients receiving care from health care providers using both EHRs and CDS (Figure). Significant differences in rates of BP control between non-Hispanic black and non-Hispanic white patients persisted in only 1 category, the visits where physicians used neither EHRs nor CDS (69% vs 75%; P < .001). However, among patients receiving care from physicians using both EHRs and CDS, Hispanic patients were significantly more likely to have BP control (85%) compared with non-Hispanic whites (78%) (P = .001). In an analysis limited to patients with hypertension, these patterns persisted; however, the Hispanic vs non-Hispanic white difference was not statistically significant.

Place holder to copy figure label and caption
Graphic Jump Location

Figure. Predicted proportion with blood pressure lower than 140/90 mm Hg. Predicted proportion after adjusting for patient age, sex, diabetes, insurance, and practice ownership, and accounting for interactions between race and other covariates. AA indicates African American; CDS, clinical decision support; EHR, electronic health record; and NS, nonsignificant.

To our knowledge, this is the first nationally representative examination of how the effect of EHRs and/or CDS on BP control differs across racial/ethnic groups. We found that previously documented patterns of racial/ethnic disparities are present among patients whose physicians are not using EHRs or CDS. However, there is no disparity between white and black patients whose physicians use EHRs with CDS. Furthermore, we found that Hispanic patients had the greatest change in BP control rates when their physicians use EHRs with CDS.

Our findings are subject to type II error because we are interpreting the lack of a statistical difference between groups as evidence that there is no disparity in BP control at a population level. However, our analysis is based on thousands of sampled visits in each EHR use category. Second, our analysis was limited by an approximately 30% rate of imputed race/ethnicity data, but NCHS uses validated methods to address missing data.5 Third, though we controlled for practice ownership on the basis of association with both the exposure and outcome, unmeasured confounding by physician or practice characteristics is possible. Last, owing to the cross-sectional study design, we cannot ascertain whether EHRs with CDS decrease disparities or through which mechanism they have an effect (eg, intervening on physician barriers to guideline adherence).5 Prospective trials must be conducted to answer these important questions. Nonetheless, our findings suggest that primary care implementation of EHRs with CDS may mitigate BP control disparities between whites and blacks, which may in turn reduce racial/ethnic disparities in morbidity and mortality from cardiovascular disease.

Correspondence: Dr Samal, Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital, 1620 Tremont St, Ste OBC-03-02V, Boston, MA 02120 (lsamal@partners.org).

Author Contributions:Study concept and design: Samal and Hicks. Acquisition of data: Samal. Analysis and interpretation of data: Samal and Lipsitz. Drafting of the manuscript: Samal and Lipsitz. Critical revision of the manuscript for important intellectual content: Lipsitz and Hicks. Statistical analysis: Samal and Lipsitz. Study supervision: Hicks.

Financial Disclosure: Dr Hicks is a Board Member of Health Resources in Action and a scientific advisory board member to the Health Management Corporation.

Additional Contributions: Jeffrey A. Linder, MD, MPH, provided advice on NAMCS and Shimon Shaykevich, MS, assisted in data management.

This article was corrected for errors in the Figure on February 1, 2012.

Hicks LS, O’Malley AJ, Lieu TA,  et al.  Impact of health disparities collaboratives on racial/ethnic and insurance disparities in US community health centers.  Arch Intern Med. 2010;170(3):279-286
PubMed   |  Link to Article
Samal L, Linder JA, Lipsitz SR, Hicks LS. Electronic health records, clinical decision support, and blood pressure control.  Am J Manag Care. 2011;17(9):626-632
PubMed
Hicks LS, Sequist TD, Ayanian JZ,  et al.  Impact of computerized decision support on blood pressure management and control: a randomized controlled trial.  J Gen Intern Med. 2008;23(4):429-441
PubMed   |  Link to Article
National Center for Health Statistics.  Public Use Microdata File Documentation, National Ambulatory Medical Care Survey, 2007. Hyattsville, MD: National Technical Information Service; 2007
Cabana MD, Rand CS, Powe NR,  et al.  Why don't physicians follow clinical practice guidelines? a framework for improvement.  JAMA. 1999;282(15):1458-1465
PubMed   |  Link to Article

Figures

Place holder to copy figure label and caption
Graphic Jump Location

Figure. Predicted proportion with blood pressure lower than 140/90 mm Hg. Predicted proportion after adjusting for patient age, sex, diabetes, insurance, and practice ownership, and accounting for interactions between race and other covariates. AA indicates African American; CDS, clinical decision support; EHR, electronic health record; and NS, nonsignificant.

Tables

References

Hicks LS, O’Malley AJ, Lieu TA,  et al.  Impact of health disparities collaboratives on racial/ethnic and insurance disparities in US community health centers.  Arch Intern Med. 2010;170(3):279-286
PubMed   |  Link to Article
Samal L, Linder JA, Lipsitz SR, Hicks LS. Electronic health records, clinical decision support, and blood pressure control.  Am J Manag Care. 2011;17(9):626-632
PubMed
Hicks LS, Sequist TD, Ayanian JZ,  et al.  Impact of computerized decision support on blood pressure management and control: a randomized controlled trial.  J Gen Intern Med. 2008;23(4):429-441
PubMed   |  Link to Article
National Center for Health Statistics.  Public Use Microdata File Documentation, National Ambulatory Medical Care Survey, 2007. Hyattsville, MD: National Technical Information Service; 2007
Cabana MD, Rand CS, Powe NR,  et al.  Why don't physicians follow clinical practice guidelines? a framework for improvement.  JAMA. 1999;282(15):1458-1465
PubMed   |  Link to Article

Correspondence

CME
Meets CME requirements for:
Browse CME for all U.S. States
Accreditation Information
The American Medical Association is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians. The AMA designates this journal-based CME activity for a maximum of 1 AMA PRA Category 1 CreditTM per course. Physicians should claim only the credit commensurate with the extent of their participation in the activity. Physicians who complete the CME course and score at least 80% correct on the quiz are eligible for AMA PRA Category 1 CreditTM.
Note: You must get at least of the answers correct to pass this quiz.
You have not filled in all the answers to complete this quiz
The following questions were not answered:
Sorry, you have unsuccessfully completed this CME quiz with a score of
The following questions were not answered correctly:
Commitment to Change (optional):
Indicate what change(s) you will implement in your practice, if any, based on this CME course.
Your quiz results:
The filled radio buttons indicate your responses. The preferred responses are highlighted
For CME Course: A Proposed Model for Initial Assessment and Management of Acute Heart Failure Syndromes
Indicate what changes(s) you will implement in your practice, if any, based on this CME course.
Submit a Comment

Multimedia

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Articles Related By Topic
Related Collections
JAMAevidence.com