NSG 6101 W7A1 -Nursing Research Methods

NSG 6101 W7A1 -Nursing Research Methods

NSG 6101 W7A1 -Nursing Research Methods

Extraneous Variables

Extraneous variables include staff call outs, education classes already scheduled and ability of collaborative team to maintain similar staffing compliance.  A set triage team and advanced practice nurse will be assigned to maintain control and compliance throughout the test month.

Instruments

Instrument used is Press Ganey scores from random patient satisfaction surveys.  Surveys are randomly distributed to discharged patients via mail or email.  Surveys cover communication, pain control, cleanliness and responsiveness (Press Ganey, 2017).  Patients will rate their satisfaction from dissatisfied to satisfied.  Scores will be reportedly monthly to hospital of overall ranking in each category.   Scores are based on Likert Scale which is used in healthcare institutions (Alijani, Obyung, Omar, & William, 2015).  Press Ganey scores are widely used in hospitals and prove to be reliable and valid (Presson, Zhang, Abtahi, Kean, Hung, & Tyser, 2017).

Medication errors, wait times and length of stay will be derived from data collection and a pre/post study comparison will be performed.

Description of the Intervention

Development of a better flow process after a quick medical screening exam can be beneficial especially in overcrowding situations.  If an accurate triage is performed and a patient is screened by an advanced practice nurse, flow can be improved.  The sickest will be bedded immediately.  Emergency severity Index (ESI) level fours and fives can be seen in a nonurgent care.  Leaving the need for placement of level three patients not needing a bed (Wallingford, Joshi, Callagy, Stone, Brown, & Shen, 2017).  The vertical flow model introduced provides the most efficient and least costly solution to improve flow especially in overcrowding situations (Wallingford et al., 2017).  To put the plan in action, a staff meeting will be held to announce the changes.

Formulating an accurate triage process is the ultimate setup for success in maintaining adequate patient satisfaction and improving wait times (Reinhardt, 2017).  Once adequate triage is manipulated through appropriate staffing and a provider is placed in triage, patient satisfaction scores will begin to in increase while wait times will start to decrease and length of stays will start to level out (Press Ganey, 2017).  A set/core team will help minimize errors and maintain control as well.  A vertical flow model will allow for the largest group of patients, level three acuity, the best throughput timing possible.

Data Collection Procedures

Medication errors will be measured and data will be collected via the risk management through electronic documentation and variance reports filed.  Researcher will obtain a report of number of medication errors for the month and compare it to previous months to evaluate if there is a decrease in number of errors.  A primary data analysis can be performed by using a two-sample test comparing medication errors before and after study (Gray, Grove, & Sutherland, 2017).

Decreased wait times will be captured based on the patient’s length of stay via electronic medical record.  Time starts once the patient signs in.  The advanced practice nurse will use the electronic medical record charting system to document time of evaluation, capturing the wait time from arrival to provider eval.  Direct measure is used.  Numerical data is provided in number of minutes it takes from patient check in to evaluation.  A monthly report is generated.  A primary data analysis can be performed by developing a pre and posttest sample to compare data before implementation of a provider in triage and after implementation (Sayah, Rogers, & Devarajan, 2014).

Departure time will be time stamped again within the charting system and data will be obtained from the electronic medical record, capturing length of stay in the emergency room.  Numerical data is provided in number of minutes a patient is in the emergency department from check in to departure.  A monthly report is generated.  Direct measure is used with primary data analysis with comparison chart created before and after study implemented (Gray, et al 2017).

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References

Al-Abri, R., & Al-Balushi, A. (2014). Patient Satisfaction Survey as a Tool Towards Quality Improvement. Oman Medical Journal, 29(1), 3-7. doi:10.5001/omj.2014.02

Alijani, G. S., Obyung, K., Omar, A., & William, J. (2015). The Effect of Emergency Waiting Time on Patient Satisfaction.  Academy of Information & Management Sciences Journal, 18(2), 1-16.

Gray, J., Grove, S., & Sutherland, S. (2017). The Practice of Nursing Research: Appraisal, Synthesis, and Generation of Evidence (8 ed.). St. Louis, MO: Elsevier.

Press Ganey.  (2017).  Transforming the Patient Experience.  Retrieved from www.pressganey.com

Presson, A. P., Zhang, C., Abtahi, A. M., Kean, J., Hung, M., & Tyser, A. R. (2017). Psychometric properties of the Press Ganey® Outpatient Medical Practice Survey. Health and Quality of Life Outcomes, 15, 32. http://doi.org/10.1186/s12955-017-0610-3

Reinhardt, M. R.  (2017).  A Systematic Approach to Evaluation of Performance Deficiencies in ED Triage.  Journal of Emergency Nursing, 43(4), 329-332.  http://doi.org/10.1016/j.jen.2017.01.003

Sayah, A., Rogers, L., & Devarajan, K. (2014). Minimizing ED Waiting Times and Improving Patient Flow and Experience of Care. Emergency Medicine International, 1-8. doi:10.1155/2014/981472

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