Large Hospital System Successfully Adopts CPOE for Radiology

Article

Broad adoption of a computerized physician order entry system with imaging decision support showed ability to improve health care delivery.

A computerized physician order entry (CPOE) system with imaging decision support was broadly accepted by clinicians at a large hospital system, with nearly all radiology studies being ordered through the system, according to a new study published in the February issue of the Journal of the American College of Radiology.

Researchers from the Brigham and Women’s Hospital in Boston assessed if CPOE would be used and accepted by clinicians throughout the hospital system, thereby improving delivery of health care by using image testing meaningfully rather than habitually. The study took place from January 2000 to June 2010 in outpatient, emergency department (ED), and in inpatient settings. A total of 4.1 million diagnostic studies were performed during that period.

Results showed that overall use of CPOE rose from 0.5 percent to 94.6 percent (2000 to 2010). Adoption varied across clinical settings, with an average of 89.8 percent use in the patient units and 99.2 percent in the ED. Areas slower to adopt the system were the surgical subspecialties and where physicians, such as obstetricians, spent the most time away from their computers.
Meaningful use (that is, fewer orders for low-yield tests) of electronically created orders rose from 0.4 percent to 61.9 percent (2000 to 2010) and electronically signed orders rose from 0.4 percent to 92.2 percent (2000 to 2010).

By adopting the CPOE decision support system, not only is the quality of care improved, but waste is reduced because of fewer inappropriate procedures, researchers said. “The meaningful use of health care IT can improve patient safety, efficiency, and the quality of care,” the authors wrote.

Recent Videos
SNMMI: What Tau PET Findings May Reveal About Modifiable Factors for Alzheimer’s Disease
Emerging Insights on the Use of FES PET for Women with Lobular Breast Cancer
Can Generative AI Reinvent Radiology Reporting?: An Interview with Samir Abboud, MD
Mammography Study Reveals Over Sixfold Higher Risk of Advanced Cancer Presentation with Symptom-Detected Cancers
Combining Advances in Computed Tomography Angiography with AI to Enhance Preventive Care
Study: MRI-Based AI Enhances Detection of Seminal Vesicle Invasion in Prostate Cancer
What New Research Reveals About the Impact of AI and DBT Screening: An Interview with Manisha Bahl, MD
Can AI Assessment of Longitudinal MRI Scans Improve Prediction for Pediatric Glioma Recurrence?
A Closer Look at MRI-Guided Adaptive Radiotherapy for Monitoring and Treating Glioblastomas
Incorporating CT Colonography into Radiology Practice
Related Content
© 2025 MJH Life Sciences

All rights reserved.