SECTION I: INTRODUCTION
Population growth rate in the past decades over the world has been increasing with a very significant percentage. The United States (US) Census Bureau predict the population growth in the next four decades by over 41% (Pallin, Espinola, & Camargo, 2014). Given the increasing amount of the population becoming older, more aging individuals will comprise a growing portion of emergency department (ED) patients in the upcoming years (Albert, McCaig, & Ashman, 2013). Pallin et al., (2014) highlights that a recent investigation determines the quantity of EDs visits foresee to occur based on US population aging. The impact of population age calls then for the government to increase health centers so as to cater for the increasing population. In consequence, failure to act has led to the overcrowding within the health services centers ED. In specification, crowd management in the ED is a problem for all hospitals across the United States, and can also raise serious adverse consequences for health care, quality, and patient safety. Crowding and poor patient flow process causes patients to remain ED longer than necessary. ED overcrowding also endangers patient security and time intervals for suitable treatment. Continuity for the patients who need urgent medical attention is minimal due to the congestion within the emergency department (Arkum, Briggs, Patel, Datillo, Bove & Birkhahn, 2010). Limitation of physical space justifies the need to expand services in the health centers to minimize the waiting time.
Emergency department establishment is crucial and important especially in consideration of the overpopulated healthcare centers. The attention patient receives in the ED considerably impact patient satisfaction and the quality of care outcomes. The patient expectation of health care services continues to increase, and their interest is to receive attention promptly. ED responsibility is to accept a patient, triage, stabilize and execute treatment with different conditions which could require immediate, urgent or semi-urgent attention. In overcrowded EDs, the average option utilization of this time is to treat patients holding up for evaluation. Patients that are waiting to be assess in crowded EDs, the typical alternative use of this time is to treat patients waiting to be seen. Triage is the prioritization of patient consideration in light of sickness/harm, seriousness, diagnosis, and service accessibility. Patients, therefore, need assistance in a review on the urgency of the treatment. The intention for triage is to recognize patients requiring immediate attention to supply the correct level of care and treatment, set priorities and transfer the patient in a short time (Reza, Khorasani, Azizi, Ali & Rahgozar, 2013).
According to Welch, Asplin, Stone, Davidson, Augustine, and Schuur (2010) EDs, hospitals and health system work to enhance courses of events and effectiveness of emergency care. Welch et al. (2010) also state more essentially that health centers should utilize standard wording and measurements to quantify and benchmark execution. Administrative bodies, for example, the Center for Medicare Services (CMS) and The Joint Commission (TJC), incorporate ED patient flow principles in their achievement measures and accreditation programs (Welch et al., 2010). For this reason, further administrative stipulations use parameters created by specialists from inside of the specialty who comprehend practice and the implications of ED operations. Lowering interruptions and verifying that patient get the right care at the exact moment of the situation will become evident eventually a favorable critical impact on the nature of considering the patient, and will enhance persistent results and diminish the expense.
The intent of this project is to evaluate the background and sources of data to maintain quality and the integrity of service to the Emergency Department. A data analysis of trends will be presented; performance indicators (PI) are also an accurate form of measurement to assess efficiency, service, and effectiveness.
The emergency department essentially has arisen due to the increased population and also the growth in demand due to disaster across the world. The health system has the responsibility to develop the emergency department to help curb this problem of parading the patients within the waiting room. Patient satisfaction is fundamental as the service provision in time, and a consideration of the urgency of patients’ status is a key in health service. The importance of the emergency department is realized through the satisfaction of the patients by maintaining a quality service.
The healthcare sector needs to recognize waiting time in the emergency department as a problem so that they can be able to work on potential policy remedies. Healthcare centers require then to study different projects which in many cases make up the emergency department. Recognizing the origin of the problem is essential as this helps to find the best ways on how to curb the problem. Evaluating this issue before initializing the implementation of the program will make the achievable simple and to the goal. Comparison with other emergency departments which are believed to be doing well may also help obtain background information about the problems. Consideration of scholarly articles which are dealing with this issue is very critical in determining the United States healthcare centers emergency departments’ requirements. Furthermore, the above research should be conducted to make sure that the project is cater for and all the requirements availed. The impartiality of the research should be on expounding on the causes, benefits and also the procedure which is required to conquer this adversity within the United States health care.
Background of the Problem
Emergency department crowding in the United States has become a national epidemic; this situation is getting worse. Every minute in the United States, an ambulance has deviated from a crowded emergency department. Over the past ten years, patients who show up in the ED have experienced a more long wait of times to be attended, and a greater extend of ED visit length (Horwitz, Green and Bradley, 2010, p.2). Patients with the acutest diseases and accidents are said to be the victims of this crisis. The maximum waiting time recommended for ED provider to see a patient is 15 minutes, back in 2006 the waiting time for the patients who were in need of ED service was 37 minutes which is a very long period for such patients. From the recent study done by the United States Government Accountability Office (GAO), indicates that prolonged time within the healthcare centers reduces the responsiveness of the hospitals (Horwitz, Green, and Bradley, 2010, p.2).
A research study conducted by Sayah, Rogers, Devarajan, Kingsley, and Lobon (2014) asserts that extended time waiting to receive attention in emergency department have demonstrated diminishing patient satisfaction and quality of care outcomes. ED across the nation are confronting delays in evaluating patients. Time to appropriate treatment compromises patient safety, privacy, and confidentiality (Oredsson, Jonsson, Rognes, Lind, Goransson, Ehrenberg, Asplund, Castren & Farrohknia, 2011).
Hospitals institution has developed strategies to improve ED patient evaluation process by increasing bed capacity in the ED, improve patient throughput and disposition. The ED is a complex system and being efficient in providing emergency care has become a critical issue for healthcare organizations (Krall, Cornelius & Addison, 2014). The total time a patient is allocated in the ED is essential to improve the patient experience. Krall et al., (2014) identify factors that may influence ED movement this include department size, some emergency physicians (EP), nursing, and ancillary services. EPs are one part of the equation in the assessment process. Doctors regulate the time necessary for their directed assessment, and patient disposition. ED performance metric is used to measure the time patient spend in each interval or focal point in the emergency department. ED metrics are important to establish a relationship from the time the patient arrive at the time the patient is treated, and the time for discharge from the emergency department.
Review and Summary of Relevant Literature
In the year 2002, the number of the emergency department patients had increased by 23% which was marked by a population of 110 million from 1992 (Arkun, Briggs, Patel, Datillo, Bove, & Birkhahn, 2010). The American Hospital Association (AHA, 2002, April) found that nurses in many healthcare centers in the United States worked to their capacity. The rise in the ED indicates that healthcare centers are overpopulated leading to low quality of the service for the ED patients. There are some factors which are associated with the waiting time in ED healthcare, for instance, staffing shortages, lack of patient flow management, and less availability of beds. Research studies statistics show that the numbers of emergency department (ED) clients are steadily increasing. The ED has become the hospital’s front entrance. The ED is now accounting for more than half of all admissions in the United States.
In a research study conducted by McCarthy, Ding, Pines, and Zeger (2011) the authors examine the effect on length of stay when the ED is crowded. The purpose of this study was to measure ED census throughout a specific period. The study was performed during 1-year, in 2010, the researchers obtained daily and hourly census data from Meditech electronic health record. Researchers classified crowding as less than 25 percentile, medium 25 to 75 percentiles, and high as more than 75 percentile. The authors found that 9% of the hours, the overall ED census was 50% higher the median for hourly was 36, and the difference, the overall ED census on none of the days was slightest 50% higher than the average for daily was 161. Also, the authors assert that the effect of crowding on care realization is different meanwhile patients’ remains in the ED.
Arkun et al., (2010) conducted a prospective cross-sectional cohort study the factors that influence emergency department crowding. The explicit purpose of the survey was to evaluate the time patient arrive until the time being seen by a doctor and the total of time patient remains in the ED. In contrast to McCarthy et al. (2011) study, this research includes only all adult patients waiting to be evaluated from Monday to Friday by observation at 8 pm, due to patient volume. Similar to the previous study ED measures included daily census. Findings from this study demonstrate an average of 85% ED capacity, and boarding was an average of 27%. The median time for patient arrive until the time being seen by a doctor was 1.8 hours and the total of time patient remains in the ED was 5.5 hours. In this study, the effect of crowding was related to ED occupancy due to physical space, and ED process efficiency.
In addition to the rising demand for service, as a consequence has led to long waiting times, crowded conditions, and patients being held in hallways, and highly variable care and outcomes. For this reason, the importance of planning quality services based on the needs of these patients is necessary. One of the major factors which have contributed to prolonged waiting time in ED is triage. There has been discrimination of the patients as the order of first come first serve is not attended. Therefore, it ends up patients who have been in the waiting room for a certain period staying there for some more hours.
Burstrom, Starrin, Engstrom, and Thulesius (2013) qualitative study examine waiting time at a Swedish emergency department ED from 2009 until 2011. The authors used grounded theory to compare one ED group data was obtained by observation and literature data. Later a comparison was done with two other Swedish emergency department. The objective of this study was to reduce unacceptable waiting time in the ED. The author’s highlights ED unacceptable conditions such as physical crowding, contact searching, and high demand of critical situations. Accordingly, when staff cannot decrease unacceptable waiting time, this situation causes staff irritation, embarrassment, and finally termination. Burstrom et al., (2013) recommends managing waiting time by improving patient movement through ED, talking and calming patients can help change patient waiting experience.
Previous studies indicate that using the results obtained from satisfaction surveys can have a profound effect on the quality of services. Also, previous studies showed that to provide optimal ED services and win patient satisfaction, research which base on interventions is necessary for ED areas that include clinical processes, physical environment, nursing services, staff behavior and treatment of patients and waiting time. In 2009, Reza, Khorasani, Azizi, Ali, and Rahgozar (2013) conducted a quasi-experimental design study to determine triage effect on wait time and patient satisfaction after receiving treatment. This study divided the population in two experiment and control group and applied a t-test, Mann-Whitney, and frequency analysis to evaluate the results of triage after treatment is provide in triage and patient satisfaction. Findings demonstrate a difference among wait time in the control group was 10.69 minutes, and the result from experiment group was 8.91 minutes. Patient satisfaction revealed little satisfaction in the control group and triaged patient had a high satisfaction score. Reza et al., (2013) suggests that education of nursing staff role in ED triage, and acceleration in providing ED service may enhance the quality of care service and therefore, patient satisfaction.
Sayah, Rogers, Devarajan, Kingsley and Lobon (2014) research study examine waiting times, patient movement and care experience in the ED. The authors of this study conducted a pre-and post-intervention analysis to evaluate the impact of the project development. This project aim was to work with clinical staff habits to change their practice, and staff embrace new collaborative process to put the patient experience first. This study findings show a significant improvement in the emergency transportation to the hospitals. The emergency transportation time of departure demonstrate decrease from a mean of 148 hours to 0 hours. ED length of stay drop from 204 minutes to 132 minutes and patient satisfaction reach the goal and demonstrate an increase from 12th percentile to 59th percentile. The study also shows quality improvement from 71% to 97%; patient left without being seen reduce from 4.1% to 0.9%. Sayah et al., (2014) study confirm that necessary expenditure is not needed to develop new strategies to improve ED efficiently and operationally.
In 2015, the Joint Commission defined a delay in treatment is when a patient does not get treatment whether it be a medication, test, therapy, or any treatment that had been ordered for them in the time frame in which it was assumed to be performed. In 2014, Joint Commission safety and quality office investigated sentinel events from 2010-2014, and informed that 522 events were the consequence of waiting to receive treatment. As a result of these events 415 patients died, 77 obtained permanent loss to function, and 24 patients had unexpected additional care or extended length of stay.
Disasters are increasingly occurring. Therefore, there will be prolonged waiting time as the facilities within the healthcare centers as they are not able to administer services to high numbers of patients. Every day emergency department is operating with over ability to hold patients. For this reason, the emergency medical system will be unable to take in a suddenly increasing mass in demand for medical help after a natural disaster, a widespread disease, or a terrorist attack due to lack of workers in general, which lead patients to wait in the emergency department. One issue that ED services face is the high amount of patients that seek care for non-urgent problems. Arkun, et al., (2010) states that the current environment of the emergency department reduces the quality of attention.
Many of the ED centers have been closed down in the United States due to lack of enough funds and personnel. As a consequence patients who were to visit such ED was forced to move to the other available EDs centers, thus leading to prolonged waiting time due to the high population within the ED. In the United States, there were more than 5000 centers in 1991. In 2006, the centers were identified to be fewer than 4000, yet the number of visits has increased in the same period (Arkun et al., 2010).
In 2014, this author hospital institution length of stay for emergency department patients was over 210 minutes longer than the national average. According to Khurshid, Ashraf, Pandita, Bhat, Jan & Khan (2014), “ED length of stay begins when the patient is first registered or triage in the ED and ends when the patient physically leaves the ED” (p.1329). The ED does not measure the interval of patient ED arrival to ED departure. ED length of stay benchmark should be measurable and be tied to an accountability framework to evaluate trustworthy, complete, and accurate data such as ED process time and ED length of stay; every emergency service should be a measure to assess improvement (BCMA, 2011).
Like many other EDs around the country, the healthcare institution where this author works suffers from similar patient flow issues including long waits, inefficient processes, and poor patient satisfaction. On March 1, 2015, Bella Vista Hospital (BVH) contract South-West emergency medicine practice group. The emergency physician (EP) group have compromise to develop mutual trust and satisfaction with the hospital administrators and medical staff. Emergency physician group goal is to maintain and retain the emergency service contract with a devote attention to issues beyond the provision of high-quality emergency care. The Hospital goal is to provide patients the very best emergency medical care.
Statement of the Problem
Overcrowding in emergency departments is a worldwide problem. Some times of day are busier than others, depending on where an emergency department is located; some patients have to wait longer than others patients (ACEP, 2015). EDs are considered to be a high-risk and high-stress environment. If the capacity of the patients stays exceeded, there is the likelihood of an error occurring within the ED. The Institute of Medicine’s (IOM’s) formulated six dimensions of quality which are patient safety; efficiency; timeliness; effectiveness; patient-centeredness; and equity. Patients that experience long waits to see a physician may be accommodated in the ED, or ambulances diverted away from the hospital close to the patient, as a consequence, all dimension could be compromised. Over the past few years, there several studies that have given clear evidence that ED crowding thoroughly contributes to poor quality health care (Sun et al., 2013, p.7).
Improving movement of patients through emergency department can save time but often adds significant costs. The solutions would have a major impact on reducing boarding and improving the flow of the patients. The consequences of crowding on the patients are related to sick people that wait too long to receive emergency care, patient complications due to waiting time, non-emergent or treatable primary care settings. The trend has implications beyond the ED as it signals problems or dissatisfaction with the performance.
Sayah et al., (2014) study asserts that extended waiting time in the emergency department and patient return times have demonstrated a reduction in patient satisfaction and quality of care. ED across the nation are confronting delays in evaluating patients. Time to obtain a proper treatment compromises patient safety, privacy, and confidentiality (Oredsson et al., 2011). Hospitals organizations have developed strategies to improve ED patient evaluation process by enhancing bed capacity in the ED, improve patient throughput and disposition (Krall, Cornelius & Addison, 2014).
The hospital included in this capstone study has a history of an extended length of stay in the ED, related to increasing the number of patient visits, Fast Track (FT) not being used, and the diminishing opportunity for an emergency physician (EP) evaluate the patient. In 2014, time from ED arrival to ED departure for admitted was 210 minutes (64.3%) higher than the national average which is 135 minutes. In 2015, time from ED arrival to ED departure for admitted was 255 minutes (17.6%) higher than 2014 and 47% higher than the national average. Waiting time is still increasing; as a result, patient satisfaction has a decrease, furthermore, quality of care outcomes. In a study conducted by Khurshid et al., (2014) indicates that ED length of stay begins when the patient is first registered or triage in the ED and ends when the patient physically leaves the ED. The hospital ED performance indicator time from ED arrival to ED departure is not being measured due to poor communication between quality improvement leader and change of ED nursing management leader.
Aim of the Project
The primary objective of this project is to measure ED performance on wait times and visit length and determine how time impact the quality of care outcomes and patient satisfaction wait. In July 2016, the hospital ED started a new triage system; Emergency Severity Index (ESI) this system categorizes ED patients by patient acuity, and patient resource need (AHRQ, 2012). This researcher post- intervention will be to evaluate the effectiveness of triage intervals after the implementation of this five-level system and compare outcomes with the previous four level system.
This quantitative comparative retrospective study will also examine pre- and post- implementation quality of care results, and patient satisfaction scores. Data will be collected on the group’s characteristics, attributes, and experiences. The study will use descriptive statistics such as mean, median, mode and percent.
Significance of the Study
Waiting time determines the satisfaction of the patients in the ED. People are experiencing standard transformation in health related mindset, from an importance on the disease to importance on the patient. The evolution of the health care delivery system in the ED requires the need to provide precise information on the quality of care outcomes. If ED does not satisfy society, the trust is wrecked. If hospitals emergency department is improved the society will greatly benefit on the ED as all the services may be available and the urgency needed by the ED patients is met.
An improved ED is crucial to an organization. Emergency departments can increase their service capacity by readjusting their ability to move patients through the acute ED areas where the clinical team can evaluate and treat the patient. Nurses also will not have to work in their capacity as they can attend to all the patients at the specified time.
The quality of the ED is rated alongside the waiting time of the patients. Satisfactorily is likely to increase if the quality of the ED is improved. There is an expectation of high turn up of ED patients if the ED is developed is likely to increase. The society health status and also the nurses’ environment working standards are liable to rise due to the availability of certified equipment. This concern confirms the importance and the requirement of improvements within the ED of United States healthcare institutions.
Welch et al., (2010) highlights that hospitals EDs work to enhance the time of attention and productivity of emergency care; more importantly, critical to use approved terminology and metrics to measure performance. Clinical decision-making utilized in ED intervals of care is to ensure that each patient is presenting with various complaints, receive appropriate care promptly.
Emergency department leaders are always facing challenges with better performance measures. To master quality improvement initiatives and benchmark, ED leaders need to be successful in delivering patient care, patient satisfaction, and achieving service initiatives. Also, emergency physicians are required to perform patient care service efficiently, safely, timely and profitable. Metrics are employ to assess efficiency, performance, and progress of a process which in this study is ED waiting time intervals. ED metrics are important to establish a relationship from the time the patient arrives at the time the patient is treated, and the time for disposition (Welch et al., 2010).
This project is similar to Oredsson et al., (2011) study that accent improvement at the time patient steps into triage, and develops evidence base practice interventions to improve movement of the patient in the ED. This project is also similar to Sayah et al., (2014) in which the author evaluate a pre-and post- intervention analysis for an ED process improvement project. Horwitz et al., (2011) research study utilize similar methods of measurement and compares outcome variables that include a triage assessment variable and independent variables. In contrast, this study is dissimilar to Sun et al., (2012) research study that utilized a retrospective method to examine the effect of crowding of a patient admitted in the ED.
This capstone project is significant to the hospital. This project will focus on how to implement strategies to decrease waiting time periods. The goal is to improve performance through the involvement of ED leaders, physicians and employees, so they have participation and ownership of the process. The plan is to create protocols, increase the utilization of Fast Track and improve triage acuity system to facilitate triage efficiency and timelines. Finally, being able to accomplish the project goals.
Nature of the Project
This descriptive quantitative, retrospective, comparative, non-probability consecutive sampling will determine the effectiveness of a pre-and post-intervention analysis of Emergency Severity Index (ESI) triage system and assess the impact of emergency department (ED) waiting time on patient satisfaction and quality of care outcomes. The quantitative methods for analysis will explain the strength and predict the relationship between variables. This study will compare groups to determine if there are differences between the outcomes obtain after being exposed to new triage system. This type of descriptive study may provide valuable information regarding this specific population group.
Meditech is the electronic health record (EHR) of the hospital. Meditech EHR system extracts the information automatically and responds cues quickly with reliability and security. Emergency department medical records data will be abstracted and harvested from the system and may be validated by using a systematic spot check by a second abstraction to ensure the data is accurate. The data will be downloaded by hospital IT and transferred to this researcher Codebook (spreadsheet in Excel). Meditech ED tracker will be used to oversee the patient flow and wait times across the department from a single portal. The EHR will supply the documents and reports needed to satisfy quality measures for ED throughput.
Descriptive statistics will be used to describe the sample population of the independent variables included in the study, visit characteristics and patient sociodemographic factors. Analytical statistics will complete monthly averages for each focal point of the ED throughout times, patient satisfaction, and quality of care outcomes. To conduct comparative analyses, ED will need to benchmark themselves against appropriate counterpart locally or nationally.
Occasionally there are days busier than others, depending on where is the emergency department location, some patients length of stay increase and have a delay in treatment (ACEP, 2015). In 2011, the Journal of Trauma, Resuscitation, and Emergency Medicine published the article “A systematic review of triage-related interventions to improve patient flow in the emergency department,” (p.1). The conclusions from this study revealed that introducing fast track for patients with less severe symptoms results in shorter waiting time, shorter length of stay, and fewer patients leaving without being seen. Also team triage, with a physician in the team, will probably result in shorter waiting time and shorter length of stay and most likely in fewer patients are leaving without being seen (Oredsson et al., 2011, p.7).
Scope of the Project
The scope of the project is to determine patient satisfaction and the quality of care provided in regards to emergency department waiting time and length of visit. Inefficiencies in ED performance and delays of care may negatively impact patient satisfaction and patient outcomes. This quality improvement project will embrace those activities that seek to improve services for the future. Such as, develop ED clinical protocols for patient-specific complaints to help accelerate the delivery of care and decrease waiting time.
The Institute of Medicine defines health care quality as “The extent to which health services provided to individuals and patient populations improve desired health outcomes,” (IOM, 2013). Moran, Burson, and Conrad (2014) indicates that carefully integrates clinical evidence, provided by a socially and technically skilled way accompanying accountability and excellent communication. Being able to improve ED movement process, and place the patient first, will certainly improve ED operational efficiency.
Non-probability consecutive sampling methods will be used in the study for every ED patient during the determined/ selected period. Non-probability sampling is the most commonly employed when data are skewed or when data are scores (Sylvia & Terhaar, 2014). A limitation in nonprobability sampling is that not every element has an equal chance of selection.
Creative Research Systems software will be used to determine the sample size for the pre-implementation period from October, November and December 2015. The sample size calculator for the post-implementation period will be performed after the second period of October, November and December 2016. The confidence level is 95%, with a confidence interval of 5, the total population for the first period was 5571, and the total sample size is 359 subjects (see Appendix A). The study will include only adults’ patients above the age of 18 years, male and female with triage assessment conducted in the ED setting and completed by the nurse, the participant should be able to speak Spanish or English, have any physical or behavioral health condition. Exclusion criteria will be patient triage by ED doctors, and pediatric patients.
Limitations and Delimitations of the Project
This study has several limitations. First, the project will be taken place in one single rural community hospital and may show different tendency than in an urban setting. Like, restrict the results relate to other clinical centers as they may have a different nursing workforce and patient demographics. The second limitation, the results may not apply to hospitals with an emergency department or inpatient volumes different from to those of this group. This model assumes that the types of patients who could be seen would have lengths of stay similar to those average ED patients and that the ED has adequate space and staff to care for additional patients (Lucas, 2009). The target population will be adult emergency department patients. The third limitation, this study will not include pediatric patients, due to low patients’ volume through ED. The reason is that there are two pediatric hospitals nearby the institution. This researcher will not perform a comparison between short waiting time and long waiting time in the ED.
Forth, quantitative design limitation may include reduction of data to numbers that can result in lost information, in quantitative design research methods are inflexible because the instruments cannot be modified once the study begins, and the administration of a structured questionnaire creates a strange situation that may alienate respondents. Fifth, this retrospective study limitation includes the use of existing data from the electronic health record previously taped for research purpose.
The sixth limitation, the sampling method is a nonprobability consecutive sampling, which means that is non-randomly chosen. The inherent bias in this type of sampling exists, meaning that the sample is unlikely to be representative of the population being studied. The study undermines the ability to make generalizations from the sample to the population of this study.
Delimitations
The study will be conducted at a not-for-profit community hospital and located in the West -Coast of Puerto Rico. The uniqueness of the subject will be lost when the electronic health record aggregates data. Donabedian’s model framework focus only on outcomes, does not address causes of waiting time in the ED. This study will not include ancillary services (Laboratory, Radiology, and Respiratory Therapy) turnaround time that may impact emergency department clinical service.
Research Question
PICO question is a mnemonic word that aide to relate the clinical question to recognize the problem (Glasper & Rees, 2013). In the PICO question’s patient population refers to the participants or subjects of the particular issue (Melnyk & Fineout-Overholt, 2011). The intervention is an actual change or improvement process (Glasper & Rees, 2013). The comparison outcome portion of the PICO is similar to the measurable goals (Glasper & Rees, 2013). Also, the PICO question aide with related literature searches in narrowing down the search terms and relevant articles (Glasper & Rees, 2013). The PICO question addressed with the capstone project: Is there a difference in patient satisfaction score and quality of care after the implementation of the emergency acuity five level triage system?
(P)– Population: Emergency department EHR adult population 18>
(I) – Intervention: Evaluate post-implementation results of new triage system (ESI)
(C)- Comparison: Pre- and post- implementation
(O)- Outcome: Patient satisfaction and quality outcomes.
(T)- Time: October, November, and December 2015 and 2016.
Variables
This study will measure the performance of emergency department using the National Quality Forum measures for wait times and length of visit. The outcomes variables of this study will examine ED performance on wait time and length of visit. This study will examine the Center for Medicare & Medicaid Services (CMS) ED crowding using five quality measures. The study will include: 1) The time patient arrives at the ED until the time of disposition; 2) The time a patient arrives until the time of physician evaluation; 3) The average of patient leaves the ED before physician assessment; 4) Median time from ED arrival until the time of patient admission; and 5) Median time the doctor decides to admit until the time of patient disposition for admission (AHRQ, 2011), (see Appendix B).
Patient satisfaction is an essential element for selecting an ED to receive services, or even suggesting it to others (Soleimanpour et al., 2011). This study will use the hospital ED patient satisfaction questionnaire that includes ten questions based on Likert Scale (see Appendix C). The survey will be provided electronically by Survey Monkey after discharge from the ED. Patient satisfaction data comparison will measure October to December 2015 and 2016. Emergency department efficiency of care measurements includes independent variables of quality of care outcomes: triage acuity, the level of pain, and medications given in ED (see Appendix D). Population-specific demographics includes gender, the level of education, time of visit, patient first visit, living location, and patient disposition (see Appendix E).
Theoretical Framework
Quality is the central concern in health care institutions. Donabedian (1980) presented a model for classifying a different method to evaluate the quality of health care in a given scenario. Donabedian’s model is a conceptual model that provides a framework for examining health services and assess the quality of health care (Liu, Singer, Sun & Camargo, 2011). Donabedian model has produced an excellent framework to apply quality concepts in a long way and categorized measures to determine the quality of care. To make a distinction the model design uses three features of care; Structure-Process-Outcomes (Sollecito & Johnson, 2013).
This project will use Donabedian’s model to evaluate a post-implementation process of a new triage assessment system. The framework will be used to assess the quality of care for triage patients into a three-parts approach, “structure-process-outcome.” The structure may refer to characteristics of a setting, human resource or an institution. The process is what is done to give or take, and influences the third step, outcomes, this can be related to the health condition (Liu, Singer, Sun, & Camargo, 2011).
This analyst will apply Donabedian’s model to outline the results of implementing best triage practices usage. In this study, the first step of the design structure refers to the characteristics of the setting in which care is delivered, ED standing order protocols for triage, how the nurse is organized, and nurse qualifications. The process will be attributed to nursing assessment, which includes triage system placement in the correct category for needed care within appropriate timeframe (Eitel et al., 2003). Intervention or treatment the patient receives in triage; pain management and the medication received. Outcomes refer to the result or impact of care on the health condition of patients, and patient satisfaction score (see Appendix F).
Definition of Terms
Waiting time: refers to the duration of time a patient waits in the emergency department before being seen by one of the ED medical staff (Horwitz et al., 2010).
Intervals: define as the period between care points (Reza, Khorasani, Azizi, Ali & Rahgozar, 2013).
Patient satisfaction: is a measure of the degree to which a patient is content with the service received in the ED (Soleimanpour et al., 2011).
Donabedian’s model: this conceptual model assesses the quality of care into three fundamental parts of healthcare: “structure-process-outcome,” (Liu, Singer, Sun, & Camargo, 2011).
Outcomes measures: determines the results of a process or activity that can be quantified, and validates data improvement (Sun, Hsia, Weiss, Zingmond, et al., 2013)
Emergency Severity Index (ESI): is an instrument use in emergency department to evaluate patient acuity level in triage, and determine the amount of resource require for care (AHRQ, 2012).
Triage: is a process use to classify and prioritize patient condition at the time patient arrives to provide suitable care (Reza, Khorasani, Azizi, Ali & Rahgozar, 2013).
Summary
The response to the growing demand for measures of ED performance will help hospitals achieve ED length of stay and improve throughput timelines, patient satisfaction and the quality of care outcomes. Without meaningful ED performance measures, it is impossible to gauge the impact of new interventions, strategies, or tools. The standardized performance measures create common terminology and provide an opportunity for comparison and improvement. Because the healthcare environment is constantly changing, organizations have to take decisions on a daily basis, and it is imperative to make adequate decisions to achieve the health care institution goals. ED overcrowding issues must be dealt with urgently through the collaborative action of administrators, front-line emergency physicians, and staff to effect the necessary needed for safe access to emergency care and improve patient movement.
SECTION II: INTRODUCTION
The purpose of this quantitative, retrospective, comparative study is to determine the effectiveness of a pre-and post-implementation analysis to assess the impact of emergency department (ED) waiting time on patient satisfaction and quality of care outcomes. The project design may help learn more about ways to reduce patient turnaround time, assess staff behavior and develop interventions to improve overall emergency department throughput. This design is appropriate for measuring improvement of ED outcomes after interventions and evaluates performance. This study may compare groups to determine if there are differences between the outcomes obtained after being exposed to interventions (Creswell, 2012). This quality improvement project may use data-based methods.
Data collection process may involve the use of patient satisfaction survey, direct performance observation, evaluation of data repository from electronic health record (EHR), and national quality registries. Soleimanpour et al., (2011) state, “patient satisfaction is an essential element for selecting an ED to receive services or even suggesting it to others.”(p. 1). In order to determine patient satisfaction related to ED services, this survey will explore the variables affecting the satisfaction level and causes of dissatisfaction.
The intent of this project is to evaluate the background and sources of data to maintain quality and the integrity of service of the Emergency department. A data analysis of trends will be presented; performance indicators (PI) will also be used as an accurate form of measurement to assess efficiency, service and effectiveness.
Project Design
This quantitative, retrospective, comparative study, may determine the effectiveness of pre-and post-implementation analysis to assess the impact of emergency department (ED) waiting time on patient satisfaction and quality of care outcomes. Quantitative research is used to establish trends or when explanations are need to be made. This design will help establish the importance of the central idea “wait time” and this researcher will rely on statistical analysis of the data, which is typically in numeric form for “patient satisfaction results and quality outcomes.” The quantitative methods for analysis will explain the strength and predict the relationship between variables. This study will compare groups to determine if there are differences between the outcomes obtain after being exposed to interventions (Creswell, 2012).
Quantitative design will address objectivity desired when evaluating a new triage acuity system. Quantitative data are then used to summarize staff feedback on the researchers’ findings. Descriptive statistics will be used to describe the sample population of the independent variables included in the study, visit characteristics and patient specific demographic factors. Analytical statistics will complete monthly averages for each focal point of the ED throughput times, patient satisfaction and quality of care outcomes. To perform comparative analyses, ED may need to benchmark themselves against appropriate counterpart locally or nationally.
After analyzing the findings and methods to improve each interval wait time. This author will focus on how to implement process strategies to decrease waiting time periods. The goal is to improve performance through the involvement of ED leaders, physicians and employees, so they have participation and ownership of the process. The plan is to create protocols, increase the utilization of Fast Track and improve triage acuity system to facilitate triage efficiency and timelines.
This study ED performance measures will evaluate wait times and length of visit by the support of National Quality Forum, Center for Medicare & Medicaid Services (CMS), and the Hospital Inpatient Quality Reporting Program initiative. The simple statistic for comparing two means is the t-test. The t-test has variations that allow making comparisons among two groups on a single dependent variable that is measured at the interval o ratio level. Data analysis of two-sample independent t-test will be used to compare the mean of the “before” data, and the “after” data.
Setting and Sample Population
The project will be conducted at Bella Vista Hospital at Mayaguez, Puerto Rico. The hospital is a 158-bed rural acute care community facility. The emergency department has 41 beds which includes 3 isolation rooms and 8 admission beds, 1 triage room and 1 Fast-Track room with 4 recliners. The ED provides treatment for approximately 22,264 adult patients annually, with an average ED length of stay of 308 minutes. In March 2015, the hospital administration hired an Emergency Physicians group, a talented, cohesive, and dedicated EP group to heighten the community’s confidence in the hospital and strengthens the emergency department position within the hospital. ED clinical staff consists of thirty-five registered nurse, and twelve license nurse practitioner. South-West Emergency Physician group consists of 18 doctors. This researcher will obtain permission to conduct the capstone project from the facility, Permission from American Sentinel University IRB will be obtained in order to start the capstone project.
The target accessible population for the study involves general adult population who attends the emergency department. The participants are adults’ patients above the age of 18 years, male and female with triage assessment conducted in the ED setting and completed by the nurse, the participant should be able to speak Spanish or English, have any physical or behavioral health condition. Exclusion criteria would be patient triage by ED doctors, and pediatric patients. In the study period, a consent form may be provided for all ED patients to participate in the patient satisfaction questionnaire, and will be given to the patients after they agree to complete them.
Non-probability consecutive sampling methods as every ED patient during the selected period of time will be included in the study. Non-probability sampling are the most commonly employed when data are skewed or when data are scores (Sylvia & Terhaar, 2014). First, this researcher may get the sampling frame organized. In order to achieve this process, the institution electronic health record will identify every individual pre- and post-intervention specified time periods, and produce a list of patients.
Creative Research Systems survey software sample size calculator was used to determine the number of medical records needed for pre-intervention period which will be July, August, and September 2015. The sample size calculator for the post-intervention period will be done after the second period of July, August, and September 2016. The confidence level is 95%, with a confidence interval of 5, total population for the first period was 5571, and the total sample size will be 359 subjects.
Instrumentation
This researcher will be using for the study, electronic health record (EHR) as a tool to manage the complexities of health care data (Moran, Burson, & Conrad, 2014). EHRs may include the functionality that supports continuous quality improvement, utilization review, risk management, and performance monitoring (Tappen, 2011). Meditech (Client Server Version-magic 6.0) is the hospital electronic health record since 2010. Meditech provides an integrated set of tools for sharing functionality and information between inpatient, practice, and ED settings, as well as features designed specifically around ED workflow. Meditech Company was founded in 1969, and is based in Boston, MA. Meditech design in the reliability and security required for EHR to support excellent patient care in a digital world (Meditech, 2015). The EHR helps with: Triage, Patient Tracking, Clinical Documentation, and Centralized Discharge. A multidisciplinary discharge tool provides the entire care team with single location to manage the discharge process. When patients are admitted from the ED, all of their information including orders, results, and documentation are automatically shared with the acute side in real time. The ED data may also be available for inclusion in the inpatient discharge packet.
Three years ago the hospital started to measure ED patient satisfaction with an in- house survey. Hospital leaders found that patients primarily judge satisfaction based on their expectations. Inefficient ED patient care increase patient load in the waiting area and influence patient’s to leave prior to triage evaluation or completion of ED care. The identified an urgent needs to expedite patient throughput and to measure patient waiting experience in the ED. This project will use hospital ED patient satisfaction questionnaire, which include 10 questions based on Likert Scale, and will be evaluate pre and post- intervention. The official language of Puerto Rico is Spanish, where the study will be conducted. The hospital patient satisfaction questionnaire is available in both language English and Spanish. This satisfaction survey will not include identifiable information, ensuring the protection of the rights and well-being of the human subjects.
Data Collection
This research study will include data collection pre and post-intervention of ED performance from the time patient arrives and when the patient physically leaves the ED. The data includes pre-intervention time periods from July 2015 through September 2015, and a post-intervention time period from July 2016 through September 2016. Data for both periods may be obtained from Meditech, (EHR). The hospital Information Technology department will provide assistance with raw data abstraction and harvested from the system and will be validate, by using a systematic second abstraction to ensure the data is accurate. The data may be downloaded, and transfer to a Codebook which summarizes variables characteristics. The creation of the codebook helps data file and minimize errors with data entry (Kim & Mallory, 2014).
Meditech ED tracker will be used to make easy to oversee patient movement and wait times in each focal point of emergency department from a single portal. A tracker is a screen that provides real time data in Meditech which enables the hospital staff to identify the status or progress of the patient in the system. The system tracker allows to see the information that matters most to the workflow and are completely flexible and preference –driven.
The EHR may also supply the documents and reports needed to satisfy the Meaningful Use Clinical Quality Measures for ED throughput (Meditech, 2015). According to Dell Company (2015) management services provide further assurance that Meditech system and applications are reliable, available and secure. Meditech provides preference-driven documentation functionality to support the full care team. System-wide integration coupled with streamlined assessment capabilities like charting by exception and automatic calculations of data scores, expedite care and save providers valuable time.
Data collection method will involve the use of hospital patient satisfaction survey. Soleimanpour et al., (2011) states “patient satisfaction is an essential element for selecting an ED to receive services or even suggesting it to others.” (p.1).The patient satisfaction survey instrument contain 10 questions base on 5-point Likert scale, with the following answers of very poor, poor, fair, good, and very good. This survey may explore the variables affecting the satisfaction level and causes of dissatisfaction. Standards related to the survey fulfill the satisfaction level of clients presenting the survey in the ED. This questionnaire is similar to patient satisfaction questionnaire used by Reza, Zavareh, Azizi, Ali, and Rahgozar (2013); and Soleimanpour et al., (2011). Confidentiality of responses will be protected, such as links between answers may be minimize and participants identifiers. In order to do this research study permissions will be obtained by American Sentinel University IRB and the Hospital organization where the project will take place.
Data collected may be stored in a hospital-encrypted flash drive and the flash drive may be registered and stored in the organization’s information system where a user-generated password may be required each time it is accessed. In order to assure that the organization’s data is safeguarded, documents on paper may be stored in a a locked filing cabinet in the information management department. All electronic and paper documents, including hospital-encrypted flash drive will be saved for a period of five years after which, all information will be destroyed by the hospital IT department.
Data Analysis Methods and Management
Data analysis for quantitative method may include the use of hospital software and Statistical Package for Social Sciences (SPSS), which is predictive analysis software for statistical data. Descriptive statistics will be used to describe the sample population of the independent variables included in the study, visit characteristics include triage category (emergent, urgent, semi-urgent, non-urgent) and patient specific demographic included gender, level of education, time visit, patient’s first visit, living location, and patient’s disposition.
This study will examine five ED crowding related measures for ED operational performance included: Triage intervals-arrival-to-triage time, triage completion time, door-to-provider, and disposition –discharge and departure to admit. ED throughput times metrics includes: time from ED arrival to ED departure, door to diagnostic evaluation by physician, patient left before being seen, time from ED arrival to ED departure for admitted, and time from admit decision time to time of departure for admitted (AHRQ, 2011, October). Triage assessment included: triage acuity scales that have five levels, 1-resucitation, 2-emergent, 3- urgent, 4-less urgent, 5- nonurgent, (AHRQ, 2012).
Data will be loaded in statistical software for further statistical analysis. Descriptive statistics analysis may involve the use of mean, median, mode, range, minimum, and maximum. ED data collected may be further analyzed using inferential statistics. Data analysis of two-sample independent t-test may be used to compare the mean of the “before” data, and the “after” data. In order to enter the information from the surveys into SPSS, this may require for this writer to create a Codebook, which define the characteristics of variables from each participant before data entry in a front easy to understand (Kim, & Mallory, 2014, p.378). Patient satisfaction survey may be collected pre- and post- participation. Survey will be utilized as an instrument of measurement to extrapolate data; the patient will complete the questionnaire through survey monkey.
Ethical Considerations
This researcher will obtain permission to conduct the capstone project from the facility administration. The healthcare institution does not have an Institutional Review Board. This writer is not collecting any identifying information of the patient, ensuring the protection of the rights and well-being of the human subjects. This is a retrospective comparative study and participant consent is waived. Data will be collected from electronic health records.
Patient satisfaction survey participants’ responses may be protected. Links between the answers and participants may be made with mnemonic that may only be known by the researcher. In analyzing the data, survey researcher may be careful about reporting a small subset of results that may disclose any identity of specific individuals. When the project concludes, the researcher will be responsible for the destruction of the survey instrument.
Dissemination of findings from evidence-based practice and research to improve health outcomes of emergency department will be shared with: a) the DNP student’s Capstone chair and committee members; b) American Sentinel University Institutional Board (IRB); c) regulatory officials from the institution where the project is being conducted. The diffusion of the project outcome is just as important, if not more important, than the actual work itself. The project findings will be reported in a systematic fashion, starting with the participant response and a description of the sample characteristics and the clinical setting for a quality improvement (QI) report. This will be followed by the data outcomes, organized over the clinical question and the improvement process.
Internal and External Validity
In this study quality measurements may influence directly on the strength of findings. Internal validity may be at risk by a confounding variable that could influence the results. Demographic trends may be one major confounding factor. Also, been derived from non-randomized sampling, this project is likely to be influenced by potential biases and confounding factors. If the statistics results are significantly different, then gender could be the confounder that impacts the results of the post-intervention on the outcome variable. External validity may be influence by the quality of the sample. If the characteristics of the sample do not represent the population, the findings of the study cannot be generalized.
Summary
In summary, this project study is designed to learn more about ways to reduce patient turnaround time and improve overall emergency department experience. There are no direct benefits for participating in this project. However, learning more about ways to reduce patient waiting time in the emergency department may help decrease patient dissatisfaction and improve quality of care. The subject participation may also aid in the development of new strategies to manage visit length and the needs of care of patients in the emergency department.
The hospital goal is to decrease the average patient’s waiting time in the emergency department(ED), which is a patient safety issue because the patient needs to move to the designated floor as fast as possible to receive specialized care. Improving patient movement through emergency department can save time but often adds significant costs. In deciding where to allocate resources and how to maximize quality care and revenue, the facility must accurately measure and take into account the opportunity loss and potential economic cost of time spent in the ED.
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Appendix A
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Bottom of Form
Bottom of Form
Top of Form
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Figure 1. Sample Size Calculator from Creative Research System, 2016
Appendix B
Table 1
Metrics for Emergency Department Operational Performance
| Triage Intervals | National Average | BVH Average 2015 | BVH Average 2016 |
| Arrival-to-triage time | 10 minutes | ||
| Triage completion time | 10 minutes | ||
| Door-to-provider | 47 minutes | ||
| Disposition | |||
| o Discharge | 16 minutes | ||
| o Departure to admitted | 93 minutes |
Table 2
Performance Indicators
| ED Throughput Times | National Average 2013 | BVH Average 2015 | BVH Average 2016 |
| Time from ED arrival to ED departure | 275 minutes | ||
| Door to diagnostic evaluation by physician | 26 minutes | ||
| Patient left before being seen | 1.9 percent | ||
| Time from ED arrival to ED departure for admitted | 135 minutes | ||
| Time from admit decision time to time of departure for admitted | 96 minutes |
Appendix C
Table 3
Patient Satisfaction Ten Items Questionnaire
| Question | Very poor 1 | Poor 2 | Fair 3 | Good 4 | Very good 5 |
| 1. Friendliness/courtesy of the nurse | |||||
| 2. Length of time to receive nursing care | |||||
| 3. The care provider managed your pain | |||||
| 4. Care provider’s efforts to include you in decisions about your treatment | |||||
| 5. Information the care provider gave you about Medication | |||||
| 6. Instructions the care provider gave you about follow-up care | |||||
| 7. Degree to which care provider talked with you using words you could understand | |||||
| 8. Amount of time the care provider spent with You | |||||
| 9. Trust in nursing staff | |||||
| 10. Likelihood of your recommending our practice to others |
Appendix B
Table 4
Quality of Care Outcomes
| 2015 | 2016 | |
| Triage Acuity | ||
| o emergent | ||
| o urgent | ||
| o semi-urgent | ||
| o non-urgent | ||
| Level of Pain | ||
| o Mild (scale 0-3) | ||
| o Moderate (scale 4-6) | ||
| o Severe (scale 7-10) | ||
| o No Pain | ||
| Medication given in ED | ||
| o 0 | ||
| o 1-3 | ||
| o >3 |
Appendix E
Table 5
Demographic Characteristics
| Population-specific demographic | Percent |
| Gender | |
| Female | |
| Male | |
| Level of education | |
| License & high education | |
| Technician | |
| Diploma | |
| Under diploma | |
| Illiterate | |
| Time of visit | |
| Morning | |
| Evening | |
| Night | |
| Missing | |
| Patient’s first visit | |
| Yes | |
| No | |
| Living location | |
| Urban | |
| Rural | |
| Missing | |
| Patient’s disposition | |
| Discharge | |
| Admission | |
| Expired |
Appendix F
Theoretical Framework
Figure 2 Donabedian’s Model (Adapted for Capstone Project, 201
