Appl Clin Inform 2011; 02(03): 284-303
DOI: 10.4338/ACI-2011-02-RA-0012
Research Article
Schattauer GmbH

Comparison of Computer-based Clinical Decision Support Systems and Content for Diabetes Mellitus

M. Kantor
1  Partners Healthcare System, Boston, MA
2  Harvard Medical School, Boston, MA
,
A. Wright
1  Partners Healthcare System, Boston, MA
2  Harvard Medical School, Boston, MA
,
M. Burton
4  Indiana University School of Medicine, Indianapolis, IN
5  Regenstrief Institute, Inc., Indianapolis, IN
,
G. Fraser
6  Mid-Valley Independent Physicians Association, Salem, OR
7  Oregon Health & Science University, Portland, OR
,
M. Krall
8  Kaiser Permanente Northwest, Portland, OR
,
S. Maviglia
1  Partners Healthcare System, Boston, MA
2  Harvard Medical School, Boston, MA
3  Brigham and Women’s Hospital, Boston, MA
,
N. Mohammed-Rajput
5  Regenstrief Institute, Inc., Indianapolis, IN
9  Roudebush VA Medical Center, Indianapolis, IN
,
L. Simonaitis
4  Indiana University School of Medicine, Indianapolis, IN
,
F. Sonnenberg
10  UMDNJ Robert Wood Johnson Medical School, New Brunswick, NJ
,
B. Middleton
1  Partners Healthcare System, Boston, MA
2  Harvard Medical School, Boston, MA
3  Brigham and Women’s Hospital, Boston, MA
› Author Affiliations
Further Information

Correspondence to:

Molly Kantor
Cannon Society, Harvard Medical School
260 Longwood Ave., Rm 233
Bston, MA 02115
Phone: 215–588–2328   

Publication History

received: 08 February 2011

accepted: 25 May 2011

Publication Date:
16 December 2017 (online)

 

Summary

Background: Computer-based clinical decision support (CDS) systems have been shown to improve quality of care and workflow efficiency, and health care reform legislation relies on electronic health records and CDS systems to improve the cost and quality of health care in the United States; however, the heterogeneity of CDS content and infrastructure of CDS systems across sites is not well known.

Objective: We aimed to determine the scope of CDS content in diabetes care at six sites, assess the capabilities of CDS in use at these sites, characterize the scope of CDS infrastructure at these sites, and determine how the sites use CDS beyond individual patient care in order to identify characteristics of CDS systems and content that have been successfully implemented in diabetes care.

Methods: We compared CDS systems in six collaborating sites of the Clinical Decision Support Consortium. We gathered CDS content on care for patients with diabetes mellitus and surveyed institutions on characteristics of their site, the infrastructure of CDS at these sites, and the capabilities of CDS at these sites.

Results: The approach to CDS and the characteristics of CDS content varied among sites. Some commonalities included providing customizability by role or user, applying sophisticated exclusion criteria, and using CDS automatically at the time of decision-making. Many messages were actionable recommendations. Most sites had monitoring rules (e.g. assessing hemoglobin A1c), but few had rules to diagnose diabetes or suggest specific treatments. All sites had numerous prevention rules including reminders for providing eye examinations, influenza vaccines, lipid screenings, nephropathy screenings, and pneumococcal vaccines.

Conclusion: Computer-based CDS systems vary widely across sites in content and scope, but both institution-created and purchased systems had many similar features and functionality, such as integration of alerts and reminders into the decision-making workflow of the provider and providing messages that are actionable recommendations.


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Conflicts of interest

The authors declare that they have no conflicts of interest in the research presented.


Correspondence to:

Molly Kantor
Cannon Society, Harvard Medical School
260 Longwood Ave., Rm 233
Bston, MA 02115
Phone: 215–588–2328