Nursing Value WorkgroupA Structured Approach to Measuring Individual Nurse’s
Contribution in Patient Outcomes
ELLEN M. HARPER DNP, RN‐BC, MBA, FAAN
CLINICAL ASSISTANT PROFESSOR
UNIVERSITY OF KANSAS SCHOOL OF NURSING
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Disclosures
Ellen M. Harper:
I have no relevant relationships with commercial interests to disclose.
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PurposeTo measure the value of nursing care as well as the contribution of individual nurses to clinical outcomes and cost.
Develop big data techniques for secondary data analysis that will provide metrics to monitor quality, costs, performance, effectiveness, and efficiency of nursing care.
New Models for Measurement
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One to one ‐ individual patient to individual nurse
Understand variability by nurse attributes i.e. licensure, experience, certification, etc.
Actual nurse staffing cost by staff mix, day of stay, DRG, LOS, nursing unit, etc.
Actual patient outcomes by individual nurse, nurse care team and full care coordination (future)
Nursing Value Sub Groups
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Nursing ValueEllen Harper & John Welton
Research Governance Amy Garcia & Peggy Jenkins
User Story Lisa Moon
Pilot Study Ellen Harper
Business Intelligence Chris Looby
Data Dictionary Cathy Ivory
Data Model John Welton
Data Model v.20
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• Organized by:Patient (Light blue)
Nurse/Provider (Purple)
Cost (Green)
Facility/Entity (Red)
• Incorporates unique RN Identifier• Information system & setting agnostic
Data Dictionary
The starting framework was the nursing model Standard naming of the elements Identification of redundancies What elements are missing? How might the elements be used? What definitions exist in current standards?
Data Dictionary: Structure
User StoriesKey: Develop User Stories to deconstruct complex nursing scenarios into a standardized set of features, item responses and data elements.
What is a User Story?
User Stories use conventional agile information technology processes to succinctly convey information system requirements from the customer / user perspective.
This approach provides a standardized process that can be used to describe nursing value for data analytics and business intelligence purposes.
The tool intentionally links the identified user story features to the Nursing Value Data Model.
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Crosswalk Nurse Classifications
10AMIA 2017 | amia.org
Guiding Principles• Information system and setting agnostic• Use relevant clinical and operational data• Measure patient‐level nursing intensity, patient‐level outcomes and utilization cost per patient.
Research & Data Governance Structure
• Guide future research
• Multi-institution participation
• Share expertise at both academic and practice setting
• Develop collegiality
• Contribute to nursing data science
Pilot Study
Design,
Data Source,
IRB
A descriptive, retrospective analysis of de‐identified data
Secondary use of de‐identified data from one urban pediatric hospital during 2014 – 2016
Data is maintained in the Nursing Value Research Data Warehouse
IRB ‐ University of Kansas, University of Colorado, hospital contributing the data
Linking The Data
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Nurse unique identifier• EHR• HRIS system• Staffing system• Payroll system
Patient unique identifier• EHR• Registration system• Outcomes database
The nurse and patient are linked using metadata within the electronic healthcare systems
Subjects,Variables
43,936 sequential pediatric and neonatal admissions during 2014 –2016
4,645,732 nursing assessments of those subjects yielded an acuity score
Subject length of stay ranged from 0.1 – 479 days, Mean 7.22, skewed to shorter LOS
5 types of nursing units as classified by NDNQI definitions
Nursing Value PublicationsGarcia, A. L. (2017). Variability in acuity in acute care. Journal of Nursing Administration, 47(10), 476–483.
doi:10.1097/nna.0000000000000518 Garcia, A. L., & Jenkins, P. (2018). The Nursing Value Model: A Structured approach to measuring nursing Care. Studies in health
technology and informatics, 250, 261‐263. doi:10.3233/978‐1‐61499‐872‐3‐261Garcia, A.L., E.M. Harper, and J.M. Welton, National Clinical Research Networks: Where Is the Nurse? Nursing Economics, 2019.
37(2): p. 100‐102.Harper, E. M., Ivory, C. H., Moon, L. A., & Garcia, A. (2017, November). A structured approach to measuring individual nurse’s
contribution in patient outcomes. Paper presented at the AMIA 2017 Annual Symposium, Washington D.C. Harper, E.M., Welton, J.M., Baird, J., Blake, N., Luker, G., Garcia, A., Buslon, D., Ritter, D. (2018). Working with large data: lessons
learned. Nursing EconomicS. 36(6) p. 301‐303.Jenkins, P., Garcia, A., Farm‐Franks, D., Choromanski, L., & Welton, J. M. (2018). Academic/practice/industry collaboration to
develop nursing value research data warehouse governance. Nursing Economic$, 36(5), 207‐251. Jenkins, P., & Welton, J. (2014). Measuring direct nursing cost per patient in the acute care setting. Journal of Nursing
Administration, 44(5), 257‐262. doi: 10.1097/NNA.0000000000000064.Moon, L., Clancy, G., Welton, J., Harper, E., (2019) Nursing Value User Stories: A Value Measurement Method for Linking Nurse
Contribution to Patient Outcomes. CIN. 37(3) p. 178‐179.Welton JM, Harper EM. (2015) Nursing care value‐based financial models. Nursing Economic$. 33:1,14‐19. 6
Welton, J. M., & Harper, E. H. (2018). Using NOC to Measure Nursing Care Value in Clinical Practice. In S. Morehead, E. A. Swanson, M. Johnson, & M. L. Maas (Eds.), Nursing Outcomes Classification (NOC): Measurement of Health Outcomes (pp. 29, 45‐47). St. Louis, MO. Elsevier: Els.
Welton, J.M. & Harper, E.M. (2017). Case study: Value‐based nursing care model development. In Nursing Knowledge and Practice Enabled by Big Data. Editors – Connie Delaney, Judy Warren, Charlotte Weaver, Tom Clancy and Roy Simpson. Published by Springer.
Welton, J.M. & Harper, E.M. (2016). Measuring nursing value from the electronic health record, Stud Health Technol Inform, 225, 63‐7.
Welton, J. M., & Harper, E. M. (2016). Measuring Nursing Care Value. Nursing Economic$, 34(1), 7‐14Welton, J. M., & Harper, E. M. (2015). Nursing care value‐based financial models. Nursing Economic$, 33(1), 14‐25.Welton, J. M. (2016). What's a nurse's value? Making cents of care. Nursing Economic$, 34(2), 57, 81.
