Nursing, technologies and medication management: New multidimensional measures of cost and quality

Funded by the Robert Wood Johnson Foundation (RWJF), this project is part of the Interdisciplinary Nursing Quality Research Initiative (INQRI) program, having goals of: (a) “Understanding: Nursing care processes, the nursing workforce and environment, and the impact of innovation on the quality of patient care. Structural, organizational and environmental factors that have a causal effect on the quality of nursing care in acute care settings,” and (b) “Identifying, developing and testing new measures to advance quality nursing research” in the target area of “medication management”.


Building on an existing interdisciplinary research network, this project examines how nurses in the Intensive Care Unit contribute to the quality of medication management when elements of the medication management process involve health information technologies. The application therefore aims to develop new measures of nursing contributions to medication management quality in the face of a growing number of these technologies.

Specific aim #1
Determine how nurses contribute to the quality of medication management when using HIT.


Specific aim #2
Determine if and how nurse contributions to medication management quality change when HIT is used for medication management.


Specific aim #3
Develop new measures of nursing contributions to medication management quality.


Specific aim #4
Determine the cost of nurse contributions to medication management quality.

Work system analysis
Work system analysis consists of observing a nurse during several hours and taking detailed notes on the tasks s/he is performing. These data will help us to understand ICU nurses' work in the context of the EHR implementation. It will also us with data used in the interviews.


Job task analysis
Job task analysis consists of observing nurses and recording the tasks on a tablet PC using a software that keeps track of time. Each task is time-stamped, which produces accurate data on the time spent by nurses on specific tasks. These data will help us determine the percentage of time nurses spend on tasks related to medication management pre- and post-EHR implementation.


Interviews about nursing decision-making during medication management
Based on the observation data and input from the nursing researcher, we will create scenarios of medication management. During a one-hour semi-structured interview, we will ask nurses to say how s/he would make decision when facing different situations (scenarios).


Interviews about nurses' perceptions of medication management
During one-hour semi-structured interviews, we will ask open questions to nurses about their perceptions of medication management, as well as their role in medication management. We will also ask questions about the impact of the implementation of health information technologies such as Electronic Health Record system.


Proactive Risk Assessment
Proactive Risk Assessment is a Human Factors method for determining vulnerabilities in processes and, how people involved in processes can contribute to or recover from breakdowns or failure modes.


Survey
Based on results of the observations and the interviews, we will develop a survey aimed at evaluating nurses' contributions to the quality of medication management, and more specifically the frequency, importance to patient's well-being, and importance to the quality of medication management of a number of nursing actions.


Cost analysis
Using the data obtained through the Job Task Analysis, the time the nurse spends in medication management will be identified. The nursing personnel costs associated with medication management will also be calculated, including cost of nurse time and a proportion of fringe benefits. We will then be able to calculate the total cost of medication management before and after the implementation of the technology.

Project Title: Nursing, technologies and medication management - New multidimensional measures of cost and quality
Grant Number: 61148
Award amount: $ 300,000
Principal Investigators: Pascale Carayon, PhD, Ben-Tzion Karsh, PhD, and Mary Ellen Murray, PhD, RN

For further information, please contact Hélène Faye