Nurse dose: validation and refinement of a concept

Res Theory Nurs Pract. 2010;24(3):159-71. doi: 10.1891/1541-6577.24.3.159.

Abstract

In this article, we report the results of two studies aimed at validating the concept of nurse dose. The first study examined the relevance of the critical attributes and empirical indicators in accurately reflecting the concept of nurse dose. Ten experts in staffing research rated the relevance of the attributes and indicators. The second study explored the factorial structure of the nurse dose concept. Data on the nurse dose indicators were obtained from 26 inpatient units. The operationalization of nurse dose was refined based on the two studies' results. Nurse dose is posited as a structural variable capturing nurses' capacity to deliver high quality care in acute care hospitals. It is defined as the level (i.e., number and type) of nursing staff required to provide care that produces intended patient outcomes. Nurse dose is reflected in two attributes: (1) active ingredients representing the essential elements that distinguish nurses from other health care professionals and operationalized in nurses' theoretical and practical knowledge, and skill mix; and (2) intensity representing the potential for nurse-patient interactions and operationalized in terms of amount (indicated by full-time equivalent) and frequency (indicated by nurse-patient ratio and hours per patient day). The concept of nurse dose has the potential for guiding future staffing research.

Publication types

  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Acute Disease / nursing
  • Analysis of Variance
  • Clinical Competence
  • Factor Analysis, Statistical
  • Health Services Needs and Demand
  • Humans
  • Length of Stay / statistics & numerical data
  • Michigan
  • Models, Nursing*
  • Nurse-Patient Relations
  • Nursing Administration Research
  • Nursing Staff, Hospital / education
  • Nursing Staff, Hospital / organization & administration*
  • Ontario
  • Personnel Staffing and Scheduling / organization & administration*
  • Principal Component Analysis
  • Quality of Health Care / organization & administration*
  • Time and Motion Studies
  • Workload / statistics & numerical data*