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Assessing Intensity of Nursing Care Needs Using Electronically Available Data

Larson Elaine L. PhD RN FAAN CIC; Cohen, Bevin MPH; Liu, Jianfang PhD; Zachariah, Philip MD; Yao, David PhD; Shang, Jingjing PhD, RN
CIN: Computers, Informatics, Nursing: Post Author Corrections: July 07, 2017
doi: 10.1097/CIN.0000000000000375
Feature Article: PDF Only

Although previous research has confirmed that nurse staffing affects patient outcomes, some potentially important factors have not been accounted for in tools to assess relationships between staffing and outcomes. The aim of this project was to develop and test a Nursing Intensity of Care Index using electronically available data from 152 072 patient discharges from three hospitals. Initially, 1765 procedure codes were reviewed; 69 were confirmed as directly increasing nursing workload by at least 15 minutes per shift. Two research staff independently reviewed a random sample of 5 patient days to assess interrater reliability with complete scoring agreement. To assess face validity, eight nurse clinician experts reviewed factors included in the Nursing Intensity of Care Index to assess the accuracy of the nursing time estimates in the tool. To examine concurrent validity, Nursing Intensity of Care Index scores for a random sample of 28 patients from four clinical units were compared with assessments made by a unit-based clinical nurse (low/medium/high intensity) for the same patients on the same day with a Spearman correlation of 0.94. In preliminary testing, data for the Nursing Intensity of Care Index, which accurately reflect nursing care intensity, can be obtained electronically in real time. The next steps will be a discrete-event simulation model and large-scale field trials.

This project was funded in part by the Agency for Healthcare Research and Quality, R01HS024915.

The authors have disclosed that they have no significant relationships with, or financial interest in, any commercial companies pertaining to this article.

Corresponding author: Elaine L. Larson, PhD, RN, FAAN, CIC, Columbia University School of Nursing, 617 W 168th St, Room 330, New York, NY 10032 (Ell23@columbia.edu).

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