Military Nursing Outcomes Database (MilNOD IV): Analysis & Expansion

Abstract

Purpose: To extend MilNOD to additional sites and to determine the associations between nurse staffing and patient and nurse outcomes. Design: This observational, correlational study included multiple sources of data: prospectively collected longitudinal staffing, retrospectively collected adverse events, cross-sectional nursing and patient surveys, and annual pressure ulcer and restraint prevalence surveys. Methods: The following indicators were collected at the nursing unit: nurse staffing, patient days, patient turnover, and patient acuity. Patient falls and nurse medication administration errors were extracted from occurrence reports. Nurse needlestick injuries were obtained from occupational health or risk management reports. Pressure ulcer and restraint data were collected by prevalence survey at least annually. Annual nursing surveys included education, experience, job satisfaction, and an evaluation of the nursing work environment. Patient surveys included satisfaction with care. Sample: The sample includes over 115,000 shifts from 57 units in 13 military hospitals; 1586 nursing surveys; 1721 patient satisfaction surveys; and 1684 pressure ulcer/restraint prevalence participants. Instrumentation: The Patient Satisfaction with Nursing Care Questionnaire, the Practice Environment Scale of the Nursing Work Index, and a series of single item measures were used. Analysis: Bayesian hierarchical logistic regression analysis was used to examine shift level staffing associations with adverse events. Hierarchical linear models were used to analyze nurse job satisfaction, patient satisfaction, and work environment outcomes. Findings: There were substantial effects of staffing on adverse events at the shift level, such that better RN skill mix, more hours of care, and a higher proportion of civilian staff resulted in lower patient and nurse adverse events.

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Document Details

Document Type
Technical Report
Publication Date
Mar 29, 2011
Accession Number
ADA619200

Entities

People

  • Patricia A. Patrician

Organizations

  • Geneva Foundation

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Business Administration
  • Data Science
  • Databases
  • Health Care
  • Health Services
  • Information Retrieval
  • Information Science
  • Knowledge Management
  • Medical Personnel
  • Military Hospitals
  • Military Medicine
  • Military Personnel
  • Patient Care
  • Personnel Management
  • Regression Analysis
  • Surveys
  • Wounds And Injuries

Fields of Study

  • Medicine

Readers

  • Computational Modeling and Simulation
  • Gulf War Illness and Chronic Multisymptom Illness in Veterans.
  • Medical or Health Care Field.

Technology Areas

  • AI & ML