Nursing Value User Stories: A Value Measurement Method for Linking Nurse Contribution to Patient Outcomes

The use of nursing big data sets for value-based measurement is novel. Nursing value measurement depends on the availability of essential data attributes in the electronic health record related to nursing care delivered (what happened, when, and the result seen). Key in measuring value is a standardized structure and format of these attributes for enabling uniform consistent analysis, along with data sets that are sharable and comparable across individuals and groups, time, organization, and practice focus. The foundation of such sharable and comparable data sets would represent at a minimum individual essential nurse care actions and the resulting patient outcome(s). While nurses generate an extraordinary amount of health-related data, healthcare information systems are not designed to collect structured data that reflect the unique attributes of nursing care or support nursing analytic activities that would measure value. More important, the multidimensional features of the nursing process are difficult to untangle and differentiate from other healthcare workers and nonnursing care activities. The complexity of nursing knowledge work has limited the development of nursing data science methods like value measurement and discouraged value versus cost discussions. This article sets out to describe nursing value measurement and an approach that nurse scientists are maximizing through methods adapted from agile project management, including user stories, and business analysis processes to recognize nurses as primary contributors to patient outcomes and value generation. Nursing Value User Story methods deconstruct complex nursing scenarios into user stories that capture nursing actions as standardized data that can be mapped to a common nursing data model. Methods described here are being used in pilot research at Los Angeles Children's Hospital, and results will be available in 2019. This research is being conducted as part of the larger activities described in the annual Nursing Knowledge Big Data conference. There are no funding sources now for the user story methods design. The authors have disclosed that they have no significant relationships with, or financial interest in, any commercial companies pertaining to this article. Corresponding author: Lisa A. Moon, PhD, RN, School of Nursing, University of Minnesota, 308 Harvard St SE, Minneapolis, MN 55455 (moonx222@umn.edu). Copyright © 2019 Wolters Kluwer Health, Inc. All rights reserved.

http://bit.ly/2tkictj