A Southwest hospital experienced an increase in complex patients and in novice nurses. To improve patient outcomes, a process improvement project piloting a predictive model was implemented. The project results indicated a decrease in escalations of care.

Continuing Education Instructions and Disclosure Information:

Contact hours available until 6/30/2026.

Requirements for Successful Completion:
Complete the learning activity in its entirety and complete the online nursing continuing professional development evaluation. You will be able to print your NCPD certificate at any time after you complete the evaluation.

Disclosure of relevant financial relationships with ineligible companies (planners, faculty, reviewers, authors):

Faculty, Planners, and Reviewers Conflict of Interest Disclosure:
The editor, content reviewers, and director of education reported no actual or potential conflict of interest in relation to this continuing nursing education article.

Author(s) Disclosures:
There are no author disclosures to declare.

Commercial Support:
No commercial support 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 continuing nursing education 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 CEP 5387.

Learning Outcome:
After completing this education activity, the learner will report increased knowledge about how predictive models, such as the Deterioration Index Cognitive Computing Model in this study, can be used to identify patients at risk of deterioration to prompt early intervention that potentially improve outcomes and save lives.

John Bowles PhD, RN, CENP

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