Development of a Post Anesthesia Care Unit Nursing Patient Classification System: The Indirect Care Component. Executive Summary

Abstract

The purpose of this study was to determine the Indirect Care time (including Nonproductive time) expressed as a proportion of Available time; this eventually will be combined with Direct Care time and Unavailable for Care time to determine nursing requirements consistent with currently accepted nurse staffing standards methodology. To determine that Indirect Care and Nonproductive proportions for the Army Post Anesthesia Care Unit (PACU) nursing units, a stratified work sampling design was used. Using weighted stratified sampling, the required sample size of nine sites was selected from the low, medium, and high workload strata proportionate to the number of sites from the total universe that occurred within each stratum. Using 5% accuracy (95% confidence interval length) and .65 as an approximation of the Indirect Care time proportion, it was estimated that at least 364 data point per site were required. Actual sample resulted in an accuracy of at least 4.3%. Data collection was distributed over a work cycle for PACU, defined as one week of the measured unit's hours of operation. A minimum of one observation session per hour and a maximum of six observation sessions per hour were scheduled to insure representative sampling of nursing activities throughout the day. Upon analysis of the collected data, it was found that each of the workload stratum-specific proportions was within 3% of the overall combined Indirect Care and Nonproductive time proportions of 76.8%.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1991
Accession Number
ADA247909

Entities

People

  • Bonnie L. Jennings
  • John L. Carty
  • Karen A. Seipp
  • Ruth E. Rea

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Accuracy
  • Anesthesia
  • Availability
  • Classification
  • Health Care
  • Health Services
  • Information Exchange
  • Intervals
  • Logistics Management
  • Manpower
  • Observation
  • Patient Care
  • Sampling
  • Security
  • Technical Information Centers
  • Workload

Readers

  • Mathematics or Statistics
  • Medical or Health Care Field.
  • Regression Analysis.