The Impact of Nurse Experience and Sequential Organ Failure Assessment on Nurses’ Workflow in an Intensive Care Unit

The purpose of this study is to understand the impact of Nurse Experience (NE) and Sequential Organ Failure Assessment (SOFA) on nurses’ workflow and process time in an Intensive Care Unit (ICU). In this study, a combination of data from the time-motion study observations, ICU nurses’ Real-Time Location System (RTLS), and the Real-Time Measurement System (RTMS) data were used to develop multiple Hierarchical Task Analysis (HTA) charts. HTA chart helped us to identify the ICU nurses’ workflow patterns. The results showed that ICU nurses spent over 47% of their time on performing primary care (in-room activities) and 25% on out-of-room activities. Furthermore, NE levels and SOFA scores had significant impacts on the average process time of nurse handoff, in-room Electronic Medical Record (EMR) charting, and the workflow patterns of out-of-room activities and out-of-room EMR usage. The outcomes of this study will provide a detailed workflow of ICU nurses and might help nurse managers to conduct a better strategy for improving ICU nurse’s workflow.

PASER: A Pattern-Based Approach to Service Requirements Analysis

Inconsistent specification are an inevitable intermediate product of a service requirements engineering process. In order to reduce requirements inconsistencies, we propose PASER, a Pattern-based Approach to Service Requirements analysis. The PASER approach first extracts the process information from service documents via natural language processing (NLP) techniques, then uses a requirements modeling language – Workflow-Patterns-based Process Language (WPPL) — to build the process model. Finally, through matching with workflow patterns, the inconsistencies in service requirements are identified and resolved by checking against a set of checking rules. We have conducted a preliminary experiment to evaluate it. An ATM service case study is presented as a running example to illustrate our approach.