Unmet Need
According to UCSF Medical Center, 82% of the text in inpatient progress notes are copied or imported, while the remaining 18% are original entries written by healthcare providers. While the copy-paste function has benefited providers significantly by increasing their work efficiency, the risk presented by potential copy-paste errors are high, with cases reported in which providers are copy-pasting progress notes that were no longer applicable. Patient reports in the U.S. are roughly four times longer than those in other countries, but regulations around copy-paste are very limited. The inability to properly mitigate risks of copy-paste errors could lead to audit nightmares and potentially detrimental aftermaths, such as patient safety repercussions and unfairly canceled insurance. Thus, there is an imperative need to develop a system to mitigate the risk presented by copy-paste errors within healthcare organizations.
Technology Overview
Researchers at Johns Hopkins have developed a copy-paste abuse monitoring system MADOCS, which could be integrated into the current EHR/EMR system without causing unnecessary disruption to the providers’ workflows. Using artificial intelligence and machine learning, MADOCS combines documentation analysis techniques with a text-matching system to create a copy-paste analysis system that identifies high-risk duplication in patient data and potentially prompts the physician to review and confirm that the information is accurate. This invention can help hospital administrators monitor and manage the risk of potential copy-paste errors while the providers continue to take advantage of the copy-paste functionality.
Stage of Development
A working prototype has been developed and demonstrated capability in the EMR of a hospital.
Patent
N/A
Publication
