10 STRATEGIC POINTS – DPI Project

The 10 Strategic Points

Broad Topic Area

1.      Exploring the prevention and control of left without being seen (LWBS) rate in the emergency room patients.

Literature Review

2.      Literature Review:

a.      Background of the Problem/Gap

Overcrowding in the emergency department (ED) is an increasing global problem. The Institute of Medicine committee has characterized emergency department overcrowding as a: 1. National crisis, 2. Compromises patient safety and timeliness, 3. Threatens patient privacy and confidentiality and often leads to frustration among ED staff (Oredsson et al., 2017). The resultant ED overcrowding described years ago has now become a well-established barrier in access to health care. Low-income people exacerbate the problem by utilization of ED as a primary access point to healthcare. ED overcrowding not only increases the rate of left without being seen but reduces patient satisfaction. It also increases the morbidity and mortality rate and the number of patients that leave without being seen by a physician Fayyaz et al., (2014).

b.      Theoretical Foundations models and theories

Health theories and models have been utilized to promote health and their expected risk factors. The Health Belief Model focuses on taking health preventive measures to prevent or control the disease and represents four constructions of treatment, i.e., perceived severity, barriers, benefits, and susceptibility. The Health Belief Model can be effective in improving knowledge of care providers and nurses for taking preventive measures against the complications associated with the overcrowding emergency department by employing the team-based model in triage.

Another nursing theory of interest is Lewin’s change theory because it focuses on initiating a change that would lead to improved quality healthcare services. It can be supplemented with behavioral change theory to establish a smooth change of practice. Change theory has three phases, namely, unfreezing, change, and refreezing (Udod & Wargner, 2017). In order to identify and examine the factors and forces that influence a situation, the theory requires leaders to reject prior knowledge and replace it with new information. Once the problem is identified, the change agent collects external and internal data as needed, such as patient satisfaction questionnaires, staff surveys. A critical analysis of the data supports the need for change, at which point the change agent determines resistance, identifies potential solutions, and begins to develop consensus regarding the change. Assessing the political climate by determining who will benefit from the change, accessing resources, and having credibility with and respect of the staff will enhance the leader’s ability to increase the driving forces and reduce the restraining forces (Udod & Wagner, 2017). This theory will be helpful in the emergency room by identifying the problem and possible solutions to help reduce the amount of left without being seen in the emergency department.

c.       Review of Literature with Key Organizing Themes and Sub-themes

In this study, I will analyze the risk factors and subsequent health outcomes of patients that did not conclude their care pathway in ED and decided to leave before or during physician visit (LWBS and LDT). The study will classify the population that leaves without being seen based on age, sex, the severity of illness, and waiting times in ED (Bolandifar, 2016). LDT patients are a particular group of patients with heterogeneous characteristics; it is difficult to hypothesize the reasons for their behavior. With regard to successive health outcomes, LWBS and LDT patients have a higher risk of readmission and hospitalization within 2 and 7 days compared to discharged patients. The risk of readmission is higher for LWBS patients, and the risk of hospitalization is higher for LDT patients.

Furthermore, we find a mortality excess of risk for LWBS patients (but not for LDT patients) compared to the reference group. Another study reported a higher percentage of recurrence to medical care for LWBS patients compared to those who had concluded their access. In agreement with our result, two previous surveys found that LWBS patients were in worse condition one or two weeks after accessing ER compared to patients who had received treatment in the ED, more than a quarter of these patients returned to the ED within 14 days, and 4% required hospitalization (Warner et al. 2018).

    Summary

Patients who leave the Emergency Department before the physician’s visit (LWBS) or during treatment (LDT) represent a useful indicator of the emergency care’s quality. Previous research explained that the increase in the rate of wait time promotes a high rate of LWBS. However, there is limited literature that shows the exact time when a patient starts leaving the ED before seeing the doctor. Thus, this DPI project focus on a quantitative study that examines whether a reduction in waiting time can reduce the LWBS. Quantitative research is effective in producing evidence-based findings. The study is significant because it can help clinical staff in ED with proper approaches to improve waiting time and reduce LWBS.

Problem Statement

3.      Problem Statement:

Patients who leave without being seen (LWBS) are at risk for worsening morbidity due to delay in diagnosis and treatment. Besides, high LWBS has been shown to negatively impact several domains of quality, such as timeliness, safety, and patient-centeredness. Given this, LWBS rates have been recognized by the Center for Medicare and Medicaid service as a critical ED quality metric, which is now requiring hospitals to report on this quality metric annually. In addition to the impact on quality, high LWBS rates are directly associated with lost hospital revenues (Houston et al., 2015).

Since the ED often served as the first interaction between the hospital and its patients, poor ED performance affected the institutional reputation and contributed to the stagnant ED volume levels. Improving the patient experience and quality of care in the ED was essential. Thus, it becomes necessary to explore preventive measures, which are being taken by healthcare professionals to prevent the incidence of this problem. Patients who left without being seen (LWBS) face the risk of worsening complications, delayed diagnosis, treatment, and even death. Implementing a Clinical Interprofessional Team in Triage (CITiT) is bound to reduce ED overcrowding and patient wait times of door to physician (Yarmohammadian et al., 2017)

Clinical/
PICOT Questions

4.      Clinical/PICOT Questions:

To what degree does the implementation of the clinical inter-professional team in triage (CITiT) help in decreasing the number of patients who left without being seen by a physician when compared to usual Registered nurse only among ambulatory and non-ambulatory patients in the emergency department in Broward County, Florida within 4-6 weeks?

P: Emergency department patients

I: Clinical inter-professional team in triage

C: RN only triage

O: Patients who left without being seen by a physician

T: 4-6 weeks

Sample

5.      Sample (and Location):

The sample of this study will be healthcare professionals, allied staff, patients, and patients’ families. The sample selected through convenience sampling comprises al patients who presented to the ED between 12:00 pm and 9:00 pm during weekdays. The setting is a hospital’s ED, whereby this facility has 247 beds. The ED has 25 beds and yearly visits of 25 089. The patient sample is calculated on all patients who visited the ED during the time the CITiT was in progress.

A). Location: Emergency department hospital in Broward County, Florida.

b).  The population of interest: Emergency department patients

c).  Sample: A sample size of about 60 participants.

d).  Inclusion Criteria

§  Patients seeking primary care in ED

e.   Exclusion Criteria

§  Patients who do not live in the US

Define Variables/ Hypotheses (Quantitative)

or

Describe Phenomena

(Qualitative)

6.      Define Variables and Level of Measurement:

a.       Independent Variable: is the wait time in the emergency department  

b.      Dependent Variable: is the LWBS or patient dissatisfaction

Q1:  What is the average waiting time in the ED identified?

Q2: What is the percentage of patients who left without being seen by doctors after or before two hours of waiting?

Q3: How many patients were satisfied with the waiting time of more or less than two hours?

Variable 1: the average waiting time

Variable 2: number of LWBS cases

Variable 3: number of satisfied or dissatisfied patients

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Methodology and Design

Methodology and Design:  

Quantitative research methodology is utilized where a pre-intervention and post-intervention design to compare the benchmark times before the CITiT program during times of high patient census during the weekdays.  Comparison of the CITiT and non- CITiT will be made. After placing the CITiT, an expert from the quality assurance would extract the data for the time the project is in implementation. The CITiT intervention is informed by the fact that the time between 12:00 pm and 10:00 pm as the busiest times during weekdays and the same when the LWBS are likely to be highest marked with the highest dissatisfaction levels.

Purpose Statement

Purpose Statement:

The purpose of this quantitative retrospective project is to find out whether or not the implementation of clinical inter-professional team-based in triage reduces emergency department left without being seen when compared to RN only triage in Broward County Hospital in 4-6 weeks.

Data Collection Approach

Data Collection Approach:

Data will be collected through questionnaires and observation checklists. Firstly, I will obtain permission from the relevant authorities in the hospital to gather information. The validity and reliability of the research instruments will be tested through the test-retest method. Bolarinwa (2015) argues that the validity of research instruments is the ability to provide accurate illustrations of the statistical measurements taken from the phenomenon under investigation. The questionnaire can validate opinions, behaviors, variability, and sample population (Brace, 2018). After that, questionnaires will be distributed to patients within the facility to share their feelings about the services they received in the hospital. Patients will be required to indicate the maximum time which they are willing to wait in the ED before being attended (Willette et al., 2017). The observation checklist will be used to fill in in the data observed from medical records to gather data.

The data collection area will be the ED area. According to Torabizadeh et al. (2020), a triage officer within the ED should perform every ED appropriately despite the limited time and scarce information that they have on the patient. At the same, a wrong triage can put the patient at risk as such studies have been developed to measure the reliability and validity of clinicians in professional triage capability using a questionnaire. Psychometric instruments expert developers recommend that the content of the instrument be extracted directly from the population.

Data Analysis Approach

Data Analysis Approach:

Data will be analyzed using SSSP after grouping into themes. Healthcare Emergency Information System (HEIS) will be used to collect data from interviews. Such information will be categorized into themes then analyzed using Special Statistical Software Package (SSSP) to identify the correlation between variables. Thematic areas will include demographic characteristics, health status, ED organization issues, and arrival time and mode. Inferential statistics and descriptive statistics will be used to identify the value of P, thus prevent statistical errors or biases (Kumbhare & Alavina, 2019).  Data analysis will help identify the relationship between dependent and independent variables.

References

Bolandifar, E., DeHoratius, N., Olsen, T., & Wiler, J. L. (2016). Modeling the behavior of patients who leave the ED without being seen. Chicago Booth Research Paper (12-14). https://doi.org/10.2139/ssrn.2427309

Bolarinwa O. A. (2015). Principles and methods of validity and reliability testing of questionnaires used in social and health science researches. The Nigerian postgraduate medical journal, 22(4), 195–201. https://doi.org/10.4103/1117-1936.173959

Brace, I. (2018). Questionnaire design: How to plan, structure and write survey material for effective market research. Kogan Page Publishers

Fayyaz et al. (2014). Missing the boat: odds for the patients who leave ED             without being seen. BMC Emergency medicine 201313:1      Doi:10.1186/1471-227x-13-1

Houston et al. (2015) Waiting for Triage: Unmeasured Time in Patient Flow.         Western journal of emergency medicine,26(1), 38-42 DOI:    10.5811/westjem.2014.11.22824

Kumbhare, D., & Alavinia, S. M. (2019). The Certainty Behind Reporting a Significance Result: What the Clinician Should Know. American Journal of Physical Medicine &Rehabilitation, 98(12), 1147–1150. https://doi.org/10.1097/PHM.0000000000001305

Melnyk, B., & Fineout-Overholt, E., (2015). Evidence-based practice in nursing & healthcare: A guide to best practice (3^rd ed.). Philadelphia, PA: Wolters Kluwer Health.

Oredsson, S., Jonsson, H., Rognes, J., Lind, L., Göransson, K. E., Ehrenberg, A., Asplund, K., Castrén, M., & Farrohknia, N. (2011). A systematic review of triage-related interventions to improve patient flow in emergency departments. Scandinavian journal of trauma, resuscitation and emergency medicine, 19, 43. https://doi.org/10.1186/1757-7241-19-43

Udod,S. & Wagner,J. 2017 Common Change Theories and Application to Different Nursing Situations      Leadership and influencing change in nursing Retrieved from https://leadershipandinfluencingchangeinnursing.pressbooks.com/chapter/chapter-9-common-change-theories-and-application-to-different-nursing-situations/

Warner, L. S. H., Galarraga, J. E., Litvak, O., Davis, S., Granovsky, M., & Pines, J. M. (2018). The impact of hospital and patient factors on            the emergency department decision to admit. The Journal of Emergency Medicine, 54(2), 249-257. https://doi.org/10.1016/j.jemermed.2017.11.024

Willett, W. C., Sampson, L., Stampfer, M. J., Rosner, B., Bain, C., Witschi, J., & Speizer, F.  E. (2017). Reproducibility and validity of a semi quantitative food frequency questionnaire. American Journal of Epidemiology, 185(11), 1109-1123.

Zaccagnini, M. E., & White, K.W., (2017). The doctor of nursing practice essentials: A new model for advanced practice nursing (3^rd ed.). Sudbury, MA: Jones and Bartlett. ISBN-13: 9781449687137

Zeigheimat, F., Ebadi, A., Rahmati-Najarkolaei, F. and Ghadamgahi, F., 2016. An investigation into the effect of health belief model-based education on healthcare behaviors of nursing staff in controlling nosocomial infections. Journal of education and health promotion, 5.