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Research ArticleOriginal Research

Use of Clinical Decision Support to Improve Primary Care Identification and Management of Chronic Kidney Disease (CKD)

Cara B. Litvin, J. Madison Hyer and Steven M. Ornstein
The Journal of the American Board of Family Medicine September 2016, 29 (5) 604-612; DOI: https://doi.org/10.3122/jabfm.2016.05.160020
Cara B. Litvin
the Division of General Internal Medicine and Geriatrics, Department of Medicine, Medical University of South Carolina, South Carolina (CBL); the Department of Public Health Sciences, Medical University of South Carolina (JMH); and the Department of Family Medicine, Medical University of South Carolina (SMO).
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J. Madison Hyer
the Division of General Internal Medicine and Geriatrics, Department of Medicine, Medical University of South Carolina, South Carolina (CBL); the Department of Public Health Sciences, Medical University of South Carolina (JMH); and the Department of Family Medicine, Medical University of South Carolina (SMO).
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Steven M. Ornstein
the Division of General Internal Medicine and Geriatrics, Department of Medicine, Medical University of South Carolina, South Carolina (CBL); the Department of Public Health Sciences, Medical University of South Carolina (JMH); and the Department of Family Medicine, Medical University of South Carolina (SMO).
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Abstract

Background: Early detection of chronic kidney disease (CKD) can lead to interventions to prevent renal failure and reduce risk for cardiovascular disease, yet adherence to treatment goals is suboptimal in the primary care setting. The purpose of this study was to assess whether clinical decision support (CDS) can be used to improve the identification and management of CKD.

Methods: This 2 year demonstration study was conducted in 11 primary care PPRNet practices. CDS included a risk assessment tool, health maintenance protocols, flow chart and a patient registry. Practices received performance reports and hosted annual half day on-site visits.

Results: There were statistically significant increases in screening for albuminuria (median 24 month change 30%, p < 0.0005) and monitoring albuminuria (median 24 month change 25%, p < 0.0005). An absolute 23.5% improvement in appropriate use of ACE-inhibitor or angiotensin receptor blocker and an absolute 7.0% improvement in hemoglobin measurement were not statistically significant. There were no clinical or statistically significant differences in other CKD CQMs. Facilitators to CDS use included practices' prioritization of improving CKD and staff use of standing orders. Barriers included incorporating use into existing workflow and variable use among providers.

Conclusions: Use of CDS to improve CKD identification and management in primary care practices shows promise. However, other barriers must be addressed to effectively achieve improvements in CKD outcomes.

  • Albuminuria
  • Angiotensin Receptor Antagonists
  • Angiotensin-Converting Enzyme Inhibitors
  • Chronic Kidney Disease
  • Clinical Decision Support Systems
  • Hemoglobins
  • Hypertension
  • Practice-based Research
  • Primary Health Care
  • Risk Assessment
  • Workflow
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The Journal of the American Board of Family     Medicine: 29 (5)
The Journal of the American Board of Family Medicine
Vol. 29, Issue 5
September-October 2016
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Use of Clinical Decision Support to Improve Primary Care Identification and Management of Chronic Kidney Disease (CKD)
Cara B. Litvin, J. Madison Hyer, Steven M. Ornstein
The Journal of the American Board of Family Medicine Sep 2016, 29 (5) 604-612; DOI: 10.3122/jabfm.2016.05.160020

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Use of Clinical Decision Support to Improve Primary Care Identification and Management of Chronic Kidney Disease (CKD)
Cara B. Litvin, J. Madison Hyer, Steven M. Ornstein
The Journal of the American Board of Family Medicine Sep 2016, 29 (5) 604-612; DOI: 10.3122/jabfm.2016.05.160020
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Keywords

  • Albuminuria
  • Angiotensin Receptor Antagonists
  • Angiotensin-Converting Enzyme Inhibitors
  • Chronic Kidney Disease
  • Clinical Decision Support Systems
  • Hemoglobins
  • Hypertension
  • Practice-Based Research
  • Primary Health Care
  • Risk Assessment
  • Workflow

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