Abstract Background. This study was done to determine if prolonged wait times in the emergency department (ED) effect overall care and treatment of patients. Methods. This project used questionnaires that were distributed to patients at 6 local emergency rooms, electronic data collected from said facilities, as well as interviews from the nursing staff on duty at the time of distribution of the questionnaires. Data collected was used to determine: 1. ) What is general perception\definition of overcrowding, 2. ) Average wait times from waiting room to beginning of treatment, 3.)
Pt’s impression of care and treatment received, and 4.) Condition of pt’s seen during periods of overcrowding five days out from discharge. Results. This study has not been conducted yet. Conclusion. There is evidence in researching literature on these topics to support that this study should be conducted as there is little to support this topic from a nursing stand point. Keywords. emergency department, overcrowding, throughput, boarding, wait times, patient care. Introduction Emergency departments (ED) through out the United States see roughly 136 million patients each year, based on data from 2009 (National, 2011).
Many of these visits are non-urgent, others are repeat visits for the same problems. Due to these and several other factors the ED’s are becoming overcrowded and the wait times are increasing drastically. On average in 2009, a patient spent a total of four hours and seven minutes in the emergency department (Press, 2009). One would think nowadays, with reimbursement (Medicare and other funding) being based so greatly on patient satisfaction scores that the hospitals would figure a way to resolve this issue. Hospitals cannot control the amount of people that enter their emergency rooms for treatment, nor can they alter the perception of what is considered overcrowding.
The purpose of this study is to determine if wait times, due to overcrowding, effect the care and treatment of patients. In this study, we will be using descriptive-correlating research methods to examine the information received. The analysis of data from the six local hospitals (located in Kentucky), patients and nursing staff will allow us to test whether patient care is adversely affected by delays. The International Review Board has approved this study.
Copies of the permission form (to the IRB) and the informed consent that was given to all participants, has been attached to this study. Definitions Overcrowding: refers to an extreme volume of patients in ED treatment areas, forcing the ED to operate beyond its capacity (Gordon, Billings, Asplin & Rhodes, 2011). Emergency Department: (in a health care facility) a section of an institution that is staffed and equipped to provide rapid and varied emergency care, especially for those who are stricken with sudden and acute illness or who are the victims of severe trauma.
The emergency department may use a triage system of screening, and classifying clients to determine priority needs for the most efficient use of available personnel and equipment (Mosby’s medical dictionary, 2009). Boarding: (A patient who is boarded) – is defined as a patient who remains in the emergency department after the patient has been admitted to the facility, but has not been transferred to an inpatient unit (ACEP, 2011). *Each of my studies collected different types of data and measured it in different ways.
In defining Operational Definition (When applied to data collection, it is a clear, concise, and detailed definition of a measure. It ensures that those collecting data do so consistently), it could be said that each had a different definition of measure. Methods Sample Over a period of six months we surveyed patients that arrived to several local ED’s for evaluation and treatment. Each of the six emergency rooms was visited at least three times a week for data collection. The schedule we used to ensure reliability of random sampling was as follows: Week 1 and 3 from 6am to 11pm.
Every person registered to be seen was asked to participate and was given a survey. Week 2 and 4, the same surveys were distributed but from 2pm to 7am. During those specified times the ED nursing staff was interviewed and each member was asked the same three questions. The only criteria for the study was that the participants (patients), had to be between the ages of 18-70 and you had to be willing to participate in a follow up questionnaire, following your 5th day after discharge from the ED. Those participants that did not meet criteria were excluded from the study.
Variables The ultimate goal of this study is to identify if patient care is compromised. We will use this as our dependent variable. As we assessed the information obtained from the sample group and the nursing interviews, it was determined that if we had alternated days that the questionnaires were distributed or if we had included more of the hospitals in the local metro area, the data received could have been different. Therefore, the independent variables in the study are sample size, and hospital distribution. Research Design.
Using a descriptive correlation design for this study, we have systematically distributed the questionnaires using the same question set, to all persons that sought treatment in any one of six local emergency departments between the months of April and October. Each ED was approached three times a week during specific hours depending on which week it was. This allowed for a variance in the amount of people potentially there at any given time. Once consent was obtained and the criteria was met the questionnaire was filled out by the participants.
The questionnaire contained seven closed-ended questions written at a 5th grade education level, as well as demographics, chief complaint, mode of transportation, and contact information. Once the patient was placed in the room and treatment was initiated the questionnaire was collected. Data received from the hospital retrospectively was used to obtain actual diagnosis, as well as length of stay (discharge or admission). Each of the nurses on shift at the time the surveys were collected were also interviewed, by asking three closed-ended questions to obtain their perspective on the wait time and crowding situation at time of survey.
Instruments-Validity and reliability There has not been a study conducted that has used the same instruments as I chose in my study therefore, there is no known level of reliability. Prior to performing this study we tested all instruments and a level of external validity was identified. Once it was determined that they were valid then we looked at the reliability of the questionnaire as well as the electronic data received from the hospital. The interview questions were also tested for validity and reliability. After preforming these tests, we received a score of 87%.
This indicates that the questions are valid, which will support the reliability of the data in our study. Data Collection The interviews would be recorded and the questionnaire answers would be analyzed in chart form. Electronic data would be used to assist in determining total time in hospital and actual discharge diagnosis. Results After analyzing all the initial data, conducting the follow-up surveys, and adding all of the information in to the final figures, we should have the results of the study. All four points of the initial research questions have been addressed and hopefully answered.
We would complete the analysis and record our findings. Implications to Nursing For the sake of this section, I am going to assume that my hypothesis was proven correct and the study results showed a direct correlation between increased wait times, due to overcrowding, and the overall care and treatment of patients. That being said, I would explain there is direct correlation between the two. To provide the best care for our patients we need to attempt to find ways to reduce wait times and overcrowding that is such an enormous problem in ED’s not only in Kentucky, but nationwide.
Whether nursing staff members make changes within their own department or explore other hospitals ED’s to see what practices they might be able to implement to streamline and improve the delayed times. I would also suggest, that depending on the data received that there is room for additional studies within the same six hospitals. This is what appears to be the leading contributor to the increase wait times and over crowding. Summary In conclusion, we have looked at the overall patient care and treatment and how it coincided with the amount of wait time and level of crowding the hospital was experiencing at the time of visit.
It can be said that there potentially could be a direct correlation and potentially hazardous consequences if care and treatment is delayed, postponed or the acuity of patient is not recognized soon enough. We know that hospitals, especially ED’s are excessively inundated, with millions of visits every year. The faster we build them the faster they fill up. People are using ED’s for primary care, others asking to be seen due to lack of insurance, and the population of older persons is increasing.
There are many reasons for the overcrowding, and even though it’s not the only reason for prolonged wait times, as we read in several other studies, it is a significant contributor. This study is important, because it brings not only the patients view but also the nurses’ view of what overcrowding is, and how it directly has an impact on patient care. The nurses have a critical roll in this crisis. Not only just through educating the patients, and being advocates for them, but nurses can essentially be the cause of major changes within hospitals to fix situations like this.
Whether the answer is a redesign of the ED, implementation of a new faster documentation system, or the creation of a committee to see what in-house procedure could be streamlined to enhance performance, there are definitely ways to assist in solving this situation. Overcrowding and increased wait times are believed to affect the care and treatment of patient care. Literature Reviews Overcrowding in medium-volume emergency departments: Effects of aged patients in emergency departments on wait times for non-emergent triage-level patients.
This research study was intended to identify and quantify the effects of specific age groups on a key time interval for patients in specific triage levels and to estimate the effect on processes used in ED. The specific questions the analysis were to answer: 1. Is there a correlation between aged patients in the ED and extended wait time for non-emergent patients? 2. Is there a relationship between aged patients in the ED and overcrowding? The study showed a significant relationship between aged patients in the ED and extended wait time for non-emergent patients.
Surprisingly, the average wait time decreased during periods of overcrowding in the aged patients presenting to ED. The author never clearly defined what non-emergent patients meant, this made it slightly difficult to critically evaluate the first question. There were also major limitations, addressed by the author, to this study such as data being collected retrospectively and qualitative issues related to age are not included. Also, several patient charts were inaccurate, regarding data and times making them absent/excluded from the study.
Streaming by case complexity: Evaluation of a model for emergency department fast track. This article focuses on the evaluation of a new program that was instituted in the Emergency Room called Fast Track. The authors wanted to see if with the development of this change, the wait times, treatment times, Department of Health benchmarks, and percentage of patients completing their treatment changed. One of the major changes was the way patients were streamlined. It was decided that they would base it on complexity as opposed to acuity, severity or disposition.
It was also decided that only senior staff would attend to the Fast Track patients. The evaluation was completed by examining pre/post data on five performance indicators: patient wait time, compliance with Department of Health benchmarks, rate of patients leaving before completing their treatments, and rate of patients re-presenting to ED within 48 hours. The FT was designated their own set of employees, the Dr’s were hired specifically for the area, their were minimum of 2 NP’s and the nursing staff were seasoned as well. Ancillary dept.
’s interaction also changed slightly when referring to the interaction with these patients. The FT was specifically designed, down to even the furniture and exam room setup to attempt to facilitate a faster process. In summation of this article, it appears that all the aspects that were measured or observed appeared to show favorable changes with the institution of this new department. Wait times dropped, compliance is up. The only negative change that was noted was a slight increase in cases that represented within 48 hours.
Emergency department: improving patient satisfaction. This article focused on an initiative aimed at decreasing the length of stay in the emergency room of an urban ED (emergency department), that is a 334-bed teaching hospital that at time of print saw about 40,000 pt’s visits per year. They formed a multidisciplinary committee that was responsible for forming subcommittees to identify and implement solutions that would decrease the length of stay (LOS) in the ED. Ultimately the decision came down to three goals.
First was to decrease the length of stay (LOS) of pt’s being admitted from 343 to 219 minutes, second was to decrease time to discharge from 164 to 131 and finally to score in the top 80th percentile in the Gallup Organization Survey questions: (a) speed and efficiency of the registration process: (b) time spent in the waiting room prior to treatment: (c) time in treatment room before treatment started: (d) overall satisfaction with amount of time spent in the ED: and (e) overall satisfaction with the ED visit.
In table 1 you can see 10 different possible solutions that the committee came up with to address the LOS. These improvement targets were measured monthly and the data was collected and documented which is demonstrated in Figures 1 and 2 as well as the Gallup Patient Satisfaction Indicators in Table 2. Overall it was obvious that many factors contributed to the success of this initiative. In summary it was concluded that since there are so many “hand-offs” between other departments, improving efficiency of the ED is challenging.
It requires intense focus on the goals and a multidisciplinary approach. While the LOS targets were not met, they did not that they met and sustained the highest level of patient satisfaction ever noted. Through continual monitoring and refinement the complex clinical process, it may one day be streamlined and throughput maximized. Several of the articles I found that might have been beneficial to my research I was not able to obtain due to time constraints. I have however, listed several of these articles as well as the abstracts.
If I were to truly be conducting this study all the literature would have been reviewed. Also, that being said there is on study in particular that was conducted by a group of physicians that was published in the Academic Emergency Medicine Journal (listed below and identified with an * preceding the citation), that represents most accurately, what I wish to accomplish with my study. However, I would perform it on and from the nursing point of view and potentially alter some of the variables to accomplish that. Abstract Summaries.
* ED crowding is associated with variable perceptions of care compromise. The objective was to measure the association between ED overcrowding and patient and provider perceptions about whether patient care was compromised. This was a cross-sectional study. After the study was conducted and the data was tabulated it was the concluded that ED crowding is associated with perceptions of compromised emergency care. A descriptive study of heavy emergency department users at an academic emergency department reveals heavy ed users have better access to care than average users.
This study aims to describe the frequent users of an ED in Massachusetts. This study was approved by the IRB and was a retrospective review of electronic records. They looked at patients who had 12 or more visits in a one-year period of time. There were 234 persons who met criteria and attributed for 4633 visits. These patients were labeled as having high-frequency use (HFU). In comparing data between those HFU pt’s and the general ED population there were more similarities than there were differences.
However, it can be said that detailed descriptions of the local HFU may help better inform staff which in turn can lead to better more effective treatment. A one of the many results of this study there was a change in the treatment for sickle cell crisis pain management in this facility. More implementations such as this could possible reduce the HFU’s visits per year. Overcrowded eds mean long waits and increased ‘boarding’ This article discussed the problem of emergency department overcrowding.
According to a report issued by Press Ganey, overcrowding results in longer periods of time spent in the ED, which can in turn affect patient satisfaction. The report showed that despite long waits in the ED, patients tended to report better overall experiences if ED staff explained the reason for the delay and if nurses were present in the waiting rooms. Delays in implementing admission orders for critical care patients associated with length of stay in emergency departments in six mid-atlantic states.
The purpose of this study was to examine critical care patients’ length of stay and time held in the ED once admitted to determine if (1) holding critical care patients in the ED after admission was related to skilled nursing shortages and or limitations in available resources and (2) admission orders or test may have been overlooked during this time. After this descriptive- comparative study was completed it was found that there was direct correlations between increased length of stay and delays in implementation of admission orders while in the ED and tests missed or delayed upon arrival at the critical care unit.
Who is sleeping in our beds? factors predicting the ed boarding of admitted patients for more than 2 hours The purpose of this study was to determine whether the frequency of ED boarding could be predicted by specific factors such as type and timing of ED visit or whether the characteristics of the patient affected those decisions. Using a retrospective review of administrative data for a 1-year period did this. Using Chi-square and logistic regression to determine whether the likelihood of being boarded for mote that 2 hours could be predicted.
Slightly more than half of the patients remained in the ED for more than 2 hours following an admission order. It was suggested that boarding was highest for those who were medical admission and admitted on a weekday or during night shift. In conclusion the findings suggest that, in addition to their usual responsibilities, ED nurses are providing care to a group of inpatients that tend to have high medical and nursing care needs. References (2009). Mosby’s medical dictionary. (8 ed. ). Elsevier. ACEP. (2011, January). Definition of boarded patients. Retrieved from http://www. acep.
org/content. aspx? id=75791 Blank, F. , Hennemand, P. , Smithline, H. , Santoro, J. , Provost, D. , & Maynard, A. (2005). A descriptive study of heavy emergency department users at an academic emergency department reveals heavy ed users have better access to care than average users. JEN: Journal of Emergency Nursing, 31(2), 139-44. Clark, K. , & Normile, L. (2002). Delays in implementing admission orders for critical care patients associated with length of stay in emergency departments in six mid-atlantic states. JEN:Journal of Emergency Nursing, 28(6), 489-95. Gordon, J. , Billings, J., Asplin, B. , & Rhodes , K. (2011).
Safety net research in emergency medicine: proceedings of the academic emergency medicine consensus conference on “the unraveling safety net”. Academic Emergency Medicine, 8(11), 1024-9. Hodgins, M. , Moore, N. , & Legere, L. (2011). Who is sleeping in our beds? factors predicting the ed boarding of admitted patients for more than 2 hours. . JEN:Journal of Emergency Nursing, 37(3), 225-30. Ieraci, S. , Digiusto, E. , Sonntag, P. , Dann, L. , & Fox, D. (2008). Streaming by case complexity: Evaluation of a model for emergency department fast track.
Emergency Medicine Australasia, 20, 241-249. doi: 10. 1111/j. 1742-6723. 2008. 01087. x Knapman, M. , & Bonner, A. (2010). Overcrowding in medium-volume emergency departments: Effects of aged patients in emergency departments on wait times for non-emergent triage-level patients. International Journal of Nursing, 16, 310-317. National Center for Health Statistics. Health, United States, 2011: With Special Feature on Socioeconomic Status and Health. Hyattsville, MD. 2012. pg. 334 *Pines, J. , Garson, C. , Baxt, W. , Rhodes, K. , Shofer, F. , & Hollander, J. (2007).
Ed crowding is associated with variable perceptions of care compromise. Academic Emergency Medicine, 14(12), 1176-81. Potera, C. (2009). Overcrowded eds mean long waits and increased ‘boarding’. American Journal of Nursing, 109(9), 22-22. Press Ganey. (2009). Emergency Department Pulse Report: Patient Perspectives on American Health Care. Retrieved from: http://www. pressganey. com/researchresources/hospitals/emergencyDepartment. aspx Walrath, J. , Tomallo-Bowman, R. , & Maguire, J. (2004). Emergency department: improving patient satisfaction. Nursing Economics, 22(2), 71-74.