What Practice Environment Features are Related to Particular Patient Outcomes


Name: Pauline Swiger

Rank: LTC

Organization: UAB School of Nursing

Performance Site: University of Alabama at Birmingham

Year Published: 2016

Abstract Status:


Preventable medical errors account for between 44,000 and 98,000 deaths per year in the United States. Although most errors in health care are related to inadequate systems, nurses are often implicated in errors because of nature of their work at the “sharp end” of patient care.  Nurses are often the last line of defense against errors; catching errors before they occur is part of nursing’s surveillance function. Yet, in work environments that are chaotic and not conducive to good nursing care because of poor staffing or management or both, nurses’ surveillance function suffers. It follows then that one mechanism for improving patient safety is a good practice environment for nurses, which has been linked to quality outcomes. Using the Practice Environment Survey of the Nursing Work Index, most research focuses on a global score to represent the practice environment. Little analysis has been conducted using the subcomponents, or subscales, of the Practice Environment Survey which may give leadership more actionable targets when prioritizing efforts to improve the work environment for nurses. 

The purpose of this study is to determine whether certain components of the practice environment in acute care hospitals are differentially associated with nursing-sensitive patient outcomes.

This study aims to explore how the subscales and individual items of the Practice Environment Survey are associated with medication with and without harm, falls with and without injury, and patient experience.

The study is a secondary analysis of four years of longitudinal panel data from 10 military hospitals. Annual surveys and monthly outcome data have been collected from 45 units over a period of 4 years. Multiple regressions will be used to determine whether each of the subscales alone or in combination with additional workload and hospital control variables is associated with each outcome. These relationships will also be assessed overtime to see if they remain constant from year to year. Tree-structured analysis will be employed to test the combination of individual Practice Environment Survey items that are the strongest predictors of each outcome.

Identification of which subscales or individual Practice Environment Survey items have the strongest association with particular patient outcomes could provide more actionable targets for leaders who aim to improve outcomes via the practice environment throughout the Military Health System.