Article Figures & Data
Figures
- Figure 1
Diabetes dashboard screen.
- Figure 2
Actual time on task for Patient A (conventional electronic health record search) and Patient B (dashboard search).
- Figure 3
Total number of mouse clicks for Patient A (conventional electronic health record search) and Patient B (dashboard search).
- Figure 4
Number of mouse clicks needed to find each data element.
Aspirin = daily use of aspirin; BP = value of last blood pressure; Eye = date of last eye examination; Foot = date of last foot examination; Hb = hemoglobin A1c level; LDL = low-density lipoprotein cholesterol level; Smoke = smoking status; Urine = value of last urine microalbumin-creatinine ratio.
Tables
Date of last HbA1c level Value of last HbA1c level Date of last LDL cholesterol level Value of last LDL cholesterol level Value of last blood pressure Value of last urine microalbumin-creatinine ratio Date of last foot examination Date of last eye examination Smoking status Daily use of aspirin -
HbA1c=hemoglobin A1c; LDL=low-density lipoprotein.
-
Additional Files
Supplemental Table & Figure
Supplemental Table 1. EHR Screens Visited to Find Data Elements for Patient A; Supplemental Figure 1. Representative screenshots of screens visited to gather needed data for patient A.
Files in this Data Supplement:
- Supplemental data: Table - PDF file, 3 pages, 119 KB
- Supplemental data: Figure - PDF file, 3 pages, 487 KB
The Article in Brief
A Diabetes Dashboard and Physician Efficacy and Accuracy in Accessing Data Needed for High-Quality Diabetes Care
Richelle J. Koopman , and colleagues
Background In order for electronic health records (EHRs) to function as effective patient care tools, improvements are needed in a variety of areas, including ease of obtaining information. This study investigates a new "diabetes dashboard" that summarizes information needed to care for diabetes patients.
What This Study Found A diabetes dashboard greatly improves the efficiency and accuracy of finding data. Specifically, the study compares the use of a diabetes dashboard screen with use of a conventional approach of viewing multiple electronic health record screens to find 10 data elements needed for ambulatory diabetes care. The mean time to find all elements using the diabetes dashboard is 1.3 minutes vs. 5.5 minutes using the conventional approach. Participating physicians correctly identify 100 percent of the data requested when using the dashboard vs 94 percent when using the conventional method. Moreover, the average number of mouse clicks is 3 with the diabetes dashboard vs 60 using conventional searching.
Implications
- The authors suggest that, although tools such as the diabetes dashboard require substantial resources to design and develop, they could reduce costs in the long run by saving physician time and preventing unnecessary tests and medical errors.
Related Data
In this issue
Jump to section
Related Articles
Cited By...
- Atrial fibrillation dashboard evaluation using the think aloud protocol
- Variable effectiveness of stepwise implementation of nudge-type interventions to improve provider compliance with intraoperative low tidal volume ventilation
- Understanding Primary Care Provider Attitudes and Behaviors Regarding Cardiovascular Disease Risk and Diabetes Prevention in the Northern Midwest
- Reducing Social Distress for Chronic Disease Patients in Primary Care: An Intervention for Latino Type 2 Diabetes Patients Seen at Community Health Centers
- Physician Information Needs and Electronic Health Records (EHRs): Time to Reengineer the Clinic Note
- An Internet-Based Diabetes Management Platform Improves Team Care and Outcomes in an Urban Latino Population
- Atrial fibrillation anticoagulation care in a large urban family medicine practice
- The clinician-programmer: designing the future of medical practice
- Successful Health Information Technology Implementation Requires Practice and Health Care System Transformation
- In This Issue: From Apprehension to Action
- On the Importance of Using a Multidimensional Sociotechnical Model to Study Health Information Technology