NSG 6101 W6A1 -Nursing Research Methods

NSG 6101 W6A1 -Nursing Research Methods

NSG 6101 W6A1 -Nursing Research Methods

Methodology

Overcrowded emergency rooms lead to decreased patient satisfaction, medication errors and increased mortality rates.

Research Question

To what extent will a front end, triage process improve flow while maintaining patient safety during high volume situations in hospital emergency rooms?

Research Design

A quasi-experimental quantitative method will be developed to mold the triage/front end process to maintain patient safety and improve flow of the emergency department.  Developing a conceptual model of flow will reduce the negative impacts of overcrowding in the emergency room.  A quasi-experimental design is used to experiment provider led triage on patient flow because of extraneous variables and lack of control over staffing and advanced practice nurse on duty in triage (White & Sabarwal, 2014).  The types of patients and conditions that check in cannot be manipulated.  Staffing can be somewhat controlled but bias can be formed with call outs and motivation and ethics of staff on duty.  Variables will be measured and numerical analysis of data will be performed (Creswell, 2014).

Sample Setting

A local, inner city, for profit hospital with the largest volumes per month within the city of Jacksonville, Florida will be used for sampling and research.  It is thirty-five bed emergency room that sees an average of two hundred fifty patients per day.  This sample setting will allow for the most data to be collected.  Access has been granted through the hospital to pull data and metrics since researcher is affiliated with this organization.  No patient names or identifying information will be used.

Sample Inclusion and Exclusion

The sample will begin on the first day of the month and all patients seen each day for the entire month will be used as the sample size.  The accessible population is approximately seven thousand five hundred subjects.  The sample size used will represent the most accurate data of metrics in overcrowded emergency rooms.

Patients with life threatening emergencies who self-present to the emergency room requiring immediate intervention will be excluded.  Emergency Severity Index (ESI) level four and five patients will go to the express care, non-urgent area for treatment.  Patients self-presenting who will go through the triage, front end process will be ESI level three patients.  This is the target population and best reflects those affected by the front-end process.  The level three group of patients prove to be the biggest area of need to improve flow and patient satisfaction during overcrowding situations.

Sampling Strategy

Nonprobability sampling method will be most beneficial.  Convenience sampling will be used because of the increased accessibility and low cost (Etikan, Musa, & Alkassim, 2016).  Convenience sampling will also help to gain subjects without further delay of time for the research.  One limitation of the study will be the patients who leave against medical advice.  Another limitation will be those who do not receive or fill out satisfaction surveys after discharge.  Also admitted patients will be excluded in this study.

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References

American Association of Colleges of Nursing (AACN).  (2017).  Nursing Research.  Retrieved from http://www.aacnnursing.org

Center for Disease Control and Prevention (CDC).  (2017).  National Center for Health Statistics.  Emergency Department Visits.  Retrieved from www.cdc.gov

Creswell, J. W. (2014). Research Design: Qualitative, Quantitative and Mixed Methods Approaches (4th ed.). Thousand Oaks, CA: Sage.

Elder, E., Johnston, A. Crilly, J.  (2016).  Improving emergency department throughput: An outcomes evaluation of two additional models of care.  International Emergency Nursing, 25, 19-26.  DOI: https://doi.org/10.1016/j.ienj.2015.07.001

Etikan, I., Musa, S. A., & Alkassim, R. S.  (2016). Comparison of Convenience Sampling and Purposive Sampling. American Journal of Theoretical and Applied Statistics, 5(1), 1-4. doi: 10.11648/j.ajtas.20160501.11

George, F., & Evridiki, K. (2015). The Effect of Emergency Department Crowding on Patient Outcomes. Health Science Journal, 9(1), 1-6.

Grafstein, E., Wilson, D., Stenstrom, R., Jones, C., Tolson, M., Poureslami, I., & Scheuermeyer, F.X. (2013). A Regional Survey to Determine Factors Influencing Patient Choices in Selecting a Particular Emergency Department for Care. Academic Emergency Medicine, 20(1), 63-70.  doi:10.1111/acem.12063

Hayden, C., Burlingame, P., Thompson, H., Sabol, V. K.  (2014).  Improving Patient Flow in the Emergency Department by Placing a Family Nurse Practitioner in Triage: A Quality-Improvement Project.  Journal of Emergency Nursing, 40 (4), 346-351.  https://doi.org/10.1016/j.jen.2013.09.011

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Shah, S., Patel, A., Rumoro, D., Hohmann, S., & Fullam, F.  (2015).  Managing patient expectations at emergency department triage.  Patient Experience Journal, 2(2), 6.  Retrieved from http://pxjournal.org/journal/vol2/iss2/6

van der Linden, M. C., Meester, B., & van der Linden, N.  (2016).  Emergency department crowding affects triage processes.  International Emergency Nursing, 29, 27-31.  http://dx.doi.org/10.1016/j.ienj.2016.02.003

Wallingford, J. G., Joshi, N., Callagy, P., Stone, J., Brown, I., & Shen, S. (2017). Introduction of a horizontal and vertical split flow model of Emergency Department Patients as a response to overcrowding. Journal of Emergency Nursing.  doi:10.1016/j.jen.2017.10.017

White, H., & S. Sabarwal (2014). Quasi-experimental Design and Methods.  Methodological Briefs: Impact Evaluation 8, UNICEF Office of Research, Florence.

Yarmohammadian, M. H., Rezaei, F., Haghshenas, A., & Tavakoli, N. (2017). Overcrowding in emergency departments: A review of strategies to decrease future challenges. Journal of Research in Medical Sciences: The Official Journal of Isfahan University of Medical Sciences, 22, 23. http://doi.org/10.4103/1735-1995.200277