Value-based metrics to measure nurse staffing and assignment

Friday, March 11, 2016: 9:15 AM
Coronado K (Coronado Springs Resort)
John M. Welton, PhD, RN, FAAN , University of Colorado, Aurora, CO
Ellen M Harper, DNP, MBA, RN-BC, FAAN , Cerner Corporation, Kansas City, MO

Handout (595.4 kB)

Purpose:
The presentation provides findings from a national expert panel formed to address nursing care value. This expert panel is a component of the ongoing work on Big Data and Nursing Knowledge Development base in University of MN School of Nursing.

Relevance/Significance:
The expert panel had the following goals: 1. Develop a conceptual model for measuring nursing value. 2. Create a common data dictionary to describe patient, nurse, and system level data elements to be extracted from existing data sets to populate the conceptual model to measure nursing value. 3. Create new nursing business intelligence tools and analytics that will utilize the common data elements to benchmark, compare, and trend nursing value.

Strategy and Implementation:
A 17 member expert panel representing a diverse group across the profession including nurse informaticists, professional organizations (including ANA), researchers, and nurse executives conducted 10 conference calls of 1.5 hours each from August 2014 through May 2015. The primary conceptualization of nursing value was to identify each nurse as a unique provider of care and measure nursing as the encounter between a nurse and patient (or family, community). For the second goal, a common data model was developed to allow hospitals and other health care settings to extract a core set of data to measure nursing care at the encounter level and provide a set of financial, quality, and outcomes metrics to measure nursing care at the encounter across many different settings. The final work of the group was to produce a range of financial, quality, and outcomes metrics that are vendor agnostic and setting neutral. These products provides a new informatics tool to measure nursing value.

Evaluation:
The primary method to validate the common data model and metrics was to construct several use cases used to "walk through" the model and measures. Each step involve validating the common data model and outcomes of the analysis across many different nursing care settings. The focus of the model is to identify the unique skills, expertise, and relationship to outcomes of care of individual nurses.

Implications for Practice:
The common data model produced by the expert panel will allow measurement of nursing value - the costs, quality, and outcomes of nursing care at the individual nurse-patient encounter. The model will also allow extraction of similar data across many different settings and future real-time feedback.