Text

theses

ETD doctoral

Purpose
Every day, Emergency Department (ED) nurse leaders must make important staffing and operational decisions to ensure each patient receives timely and quality care. However, the challenges associated with the frequent surges and dips in patient arrivals can make planning ahead a complex responsibility for even the most experienced leaders. Without a reliable strategy or model to estimate ED patient arrivals, nurse leaders will often base departmental needs on the “average” volume of patient arrivals. This approach can be effective sometimes, but there are many days when this strategy leads to ineffective resource utilization, patient safety concerns, and excessive overtime expenditure.

Methodology
This project focused on evaluating the accuracy of a real-time Emergency Department patient arrival estimation (EDPAE) tool for the Adult ED (AED) of a suburban non-profit research and teaching hospital in northern New Jersey. The EDPAE tool’s innovative approach incorporated real-time patient arrival data to generate a daily estimate of future patient arrivals. Estimates produced by the EDPAE tool were compared to those of four common ED patient arrival estimation models that were dependent on historic patient arrivals. The comparison period lasted 305 days (January 1, 2020 – October 31, 2020). Each model was evaluated for accuracy by measuring the variance of each estimate to the actual number of arrivals daily from 1:00 p.m. – 11:59 p.m.

Results
The Novel Coronavirus (COVID-19) pandemic significantly impacted AED patient arrivals for most of the comparison period. To ensure comparison was fair and objective, three approaches were adopted: 1. Comparison of all 305 days (January 1, 2020 – October 31, 2020) 2. Comparison of the 67 days before the start of the pandemic (January 1, 2020 – March 7, 2020) 3. Comparison of days during the pandemic that had a sufficient number of patient arrivals to allow a fair comparison. For each of the three comparison approaches, the EDPAE tool outperformed the four models of the comparison group by generating estimates of greater accuracy.

Implications for Practice
This project illustrated the benefits of incorporating real-time patient arrival data into models used to estimate future arrivals. Patient arrival estimation tools and models are not new concepts, but these models have traditionally been based on retrospective, time-series methodology. The EDPAE tool offers an innovative and novel alternative that can adapt to real-time variables and continue to provide useable estimates even when the traditional models cannot

ETD_11323

DNP

Includes bibliographical references

doi:10.7282/t3-8zw4-0161

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