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Methods Inf Med 2007; 46(04): 410-415
DOI: 10.1160/ME0387
 
Schattauer GmbH

Impact of Different Sampling Strategies on Score Results of the Nine Equivalents of Nursing Manpower Use Score (NEMS)

A. Junger
1   Department of Anesthesiology, Intensive Care Medicine, Pain Therapy, University Hospital Giessen and Marburg, Campus Giessen, Giessen, Germany
,
B. Hartmann
1   Department of Anesthesiology, Intensive Care Medicine, Pain Therapy, University Hospital Giessen and Marburg, Campus Giessen, Giessen, Germany
,
J. Klasen
1   Department of Anesthesiology, Intensive Care Medicine, Pain Therapy, University Hospital Giessen and Marburg, Campus Giessen, Giessen, Germany
,
F. Brenck
1   Department of Anesthesiology, Intensive Care Medicine, Pain Therapy, University Hospital Giessen and Marburg, Campus Giessen, Giessen, Germany
,
R. Röhrig
1   Department of Anesthesiology, Intensive Care Medicine, Pain Therapy, University Hospital Giessen and Marburg, Campus Giessen, Giessen, Germany
,
G. Hempelmann
1   Department of Anesthesiology, Intensive Care Medicine, Pain Therapy, University Hospital Giessen and Marburg, Campus Giessen, Giessen, Germany
› Author Affiliations
Further Information

Publication History

Publication Date:
20 January 2018 (online)

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Summary

Objective: Prospective observational study to assess the impact of two differentsampling strategies on the score results of the NEMS, used widely to estimate the amount of nursing workload in an ICU.

Methods: NEMS scores of all patients admitted to the surgical ICU over a one-year period were automatically calculated twice a day with a patient data management system for each patient day on ICU using two differentsampling strategies (NEMSindividual: 24-hour intervals starting from the time of admission; NEMS8a.m.: 24-hour intervals starting at 8 a.m.).

Results: NEMSindividual and NEMS8a.m. were collected on 3236 patient days; 687 patients were involved. Significantly lower scores were found for the NEMS8a.m. (25.0 ± 8.7) compared to the NEMSindividual (26.1 ± 8.9, p <0.01); the interclass correlation coefficient (ICC) was good but not excellent: 0.78. The inter-rater correlation between the two NEMS scores was high or very high (κ = 0.6-1.0) for six out of nine variables of the NEMS.

Conclusions: Different sampling strategies produce different score values, especiallydueto the end of stay. This has to betaken into accountwhen using the NEMS in quality assurance projects and multi-center studies.

Keywords

Data management system - computerized patient record - risk score - sampling strategies - TISS score - NEMS
 

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