Automatic calculation of the nine equivalents of nursing manpower use score (NEMS) using a patient data management system

Intensive Care Med. 2004 Jul;30(7):1487-90. doi: 10.1007/s00134-004-2239-z. Epub 2004 Apr 15.

Abstract

Objective: The most recent approach to estimate nursing resources consumption has led to the generation of the Nine Equivalents of Nursing Manpower use Score (NEMS). The objective of this prospective study was to establish a completely automatically generated calculation of the NEMS using a patient data management system (PDMS) database and to validate this approach by comparing the results with those of the conventional manual method.

Design: Prospective study.

Setting: Operative intensive care unit of a university hospital.

Patients: Patients admitted to the ICU between 24 July 2002 and 22 August 2002. Patients under the age of 16 years, and patients undergoing cardiovascular surgery or with burn injuries were excluded.

Interventions: None.

Measurements and main results: The NEMS of all patients was calculated automatically with a PDMS and manually by a physician in parallel. The results of the two methods were compared using the Bland and Altman approach, the interclass correlation coefficient (ICC), and the kappa-statistic. On 20 consecutive working days, the NEMS was calculated in 204 cases. The Bland Altman analysis did not show significant differences in NEMS scoring between the two methods. The ICC (95% confidence intervals) 0.87 (0.84-0.90) revealed a high inter-rater agreement between the PDMS and the physician. The kappa-statistic showed good results (kappa>0.55) for all NEMS items apart from the item "supplementary ventilatory care".

Conclusion: This study demonstrates that automatical calculation of the NEMS is possible with high accuracy by means of a PDMS. This may lead to a decrease in consumption of nursing resources.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Child
  • Child, Preschool
  • Delivery of Health Care*
  • Hospital Information Systems / organization & administration
  • Hospital Information Systems / statistics & numerical data*
  • Hospitals, University
  • Humans
  • Intensive Care Units
  • Nursing Staff, Hospital / supply & distribution*
  • Prospective Studies
  • Quality of Health Care
  • Regression Analysis
  • Risk Factors
  • Workforce