Inpatient nursing documentation is rarely reviewed or utilized by other members of the multidisciplinary team. This presentation addresses how one nursing institution transformed a subset of the nursing documentation dataset into a meaningful predictor of deterioration utilized by the multidisciplinary team.
Continuing Education Instructions and Disclosure Information:
Contact hours available until 8/22/2022.
Requirements for Successful Completion: Complete the learning activity in its entirety and complete the online CNE evaluation. You will be able to print your CNE certificate at any time after you complete the evaluation.
Faculty, Planners, and Speakers Conflict of Interest Disclosure:
Conference Planning Committee and Abstract Reviewer Disclosures: Jacqueline Skeith, MS, RN-BC – serves on the Board of Directors for MedAptus, Inc.
No other reviewer or conference planning committee member discloses any actual or potential conflict of interest.
Speakers Conflict of Interest Disclosure: No speaker discloses any actual or potential conflict of interest.
Commercial Support and Sponsorship: No commercial support or sponsorship declared.
Accreditation Statement: This educational activity is jointly provided by Anthony J. Jannetti, Inc. (AJJ) and the American Nursing Informatics Association (ANIA).
Anthony J. Jannetti, Inc. is accredited as a provider of nursing continuing professional development by the American Nurses Credentialing Center’s Commission on Accreditation.
Anthony J. Jannetti, Inc. is a provider approved by the California Board of Registered Nursing, provider number CEP5387.
Learning Outcome: After completing this learning activity, the participant will be able to describe how predictive models can transform discrete nursing documentation into meaningful data for the multidisciplinary team to improve patient outcomes.
Using a Predictive Model and Passive Decision Support tools to Detect Deterioration Earlier and Improve Patient Care
1.00 - CH
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5/3/21 1:47 pm
This was an excellent and informative presentation. Organizations struggle with active alerting. Predictive modeling offers the opportunity for surveillance and early detection of patients at risk for deterioration without the intrusion of an alert which has the potential to disrup a clinician's workflow and may not be heeded.