Forecasting Model Of Forecasting Models

A visit to the emergency department (ED) is usually associated with negative thoughts by most people. It creates preconceived images of overcrowded waiting rooms and routine long waits for treatment (Jarousse, 2011). From 1996 to 2006, ED visits increased annually from 90.3 million to 119.2 million (32% increase). During this same time period, the number of EDs has declined by 186 facilities creating the age old lower supply and greater demand concept (Crane & Noon, 2011). There are many contributing factors that have led to an increase in ED visits. A few of these key drivers include lack of primary care access, rising of the uninsured population, dwindling mental health services, and the growing elderly

Hospital emergency room wait times are the talk of the United States right now. Long wait times can contribute to the problems that decrease the quality of our health care system. Emergency room wait times depend on how busy the day is going, how long it takes for each patient to be seen, and how much staff is on duty. Wait times are also based on your injury as well. If you are there for a broken toe versus a head injury, you are going to be seen after the patient with the head injury despite the fact that you were there first. A case study researched and and written by Kevin Tuttle explains a challenge with a mission to decrease the wait times in the emergency room department.

Appropriate nurse staffing is a complex topic that has arisen as a nationwide healthcare issue within the profession of Registered Nurses (RN). To truly understand the concept of staffing one must understand that staffing and scheduling are often at times used interchangeably although Mensik (2014) noted a distinct difference between the two (p. 2). The American Nurse Association [ANA] (2012) has defined appropriate nurse staffing “as a match of registered nurse expertise with the needs of the recipient of nursing care services in the context of the practice setting and situation” (p. 6). Scheduling, in contrast, involves taking into account factors such as a unit’s historical census numbers along with anticipated surgical volumes

14 million Canadians visit Emergency Departments (ED) every year, and also reported to having the highest use of EDs (Ontario Hospital Association, 2006). ED overcrowding in Canada has become an epidemic. ED overcrowding has been defined as “a situation in which the demand for emergency services exceeds the ability of an (emergency) department to provide quality care within acceptable time frames” (Ontario Ministry of Health and Long Term Care, 2014). This has been an ongoing problem across Canada. Ontario has developed an initiative to reduce ED wait times by implementing a variety of strategies and collaborating with other institutions. This paper describes the Emergency Room National Ambulatory Intuitive (ERNI), an

In the first medical surgical unit, it is forecasted there will be 14,007 patient days in 2015 with the 5:1 ratio, there needs to be 2,802 staff members in this unit. In the second medical surgical unit, there will be 14,086 patient days in 2015 and will need 2,817 staff members. The third unit will have 10,846 patient days and will need 2,170 staff members to meet the standard ratio. The final unit will have 9,936 patient days in 2016 and will need 1,987 staff members.

The additional revenues that were collected due to increase in ICU capacity by 20 beds enhanced the total ED revenues by 10%.4 The efficiency of care delivery is decreased when patients are diverted to other hospitals, they have to wait for long period to receive care or if they are placed on the floors where they do not belong. This is seen often due to delay in discharging patients.3 These delays and inefficiencies are the primary cause of decreased satisfaction among patients, their families, hospital employees, and physicians. They also result in avoidable increases in patient length-of-stay, reduced quality of care, and lost or diminished hospital revenue.3

Queuing is feature of our daily life, whether in an airport, a post office or Emergency Departments(ED), few of us wishes to wait too long for service. The clinical cost of waiting too long for urgent treatment in an ED is all too long for service. Following media headlines, pooled with powerful political agenda lead to, in the late 1990s and the early 2000s many ED in the UK were struggling with high demand and poor patient flow. During this period it

Assess the current Models of Care in their Emergency Departments using the given criteria It is recognised that not all of the Models of Emergency Care are applicable for all NSW Emergency Departments. Decisions to implement them will be made based on the staff, patient presentations and space available in the ED to operate each model. Assess the potential to introduce models to their hospitals that may improve patient care and flow, the patient experience and clinical outcomes

|  "Dynamic models, usually computer-based, that allow the forecaster to make assumptions about the internal variables and external environment in the model" is a definition for which of the following forecasting methodologies?

This research is trying to answer the question of how to reduce overcrowding in emergency rooms? Would people would want to access published wait times provided on the internet, and would this guide a patient make decisions on where they receive their care. The hypothesis being one, crowding maybe reduced with having upfront information, and therefore also provide increased patient satisfaction due to waiting less. Patients would have more choices available to them such as

Tang N, Stein J, Hsia RY et al: Trends and characteristics and US emergency department visits, 1997 – 2007.  JAMA 2010; 304: 664-670

Emergency Departments (ED) overcrowding in Canada has become an epidemic. ED overcrowding has been defined as “a situation in which the demand for emergency services exceeds the ability of an (emergency) department to provide quality care within acceptable time frames” (Ontario Ministry of Health and Long Term Care, 2014). This has been an ongoing problem across Canada. Ontario has developed an initiative to reduce ED wait times by implementing a variety of strategies. This paper describes the Emergency Room NARCS Intuitive (ERNI), an innovative program which focuses on reducing ED wait times and patient satisfaction in order to optimize quality of care.

The SST will require data collected from all computers used to monitor access to the admission system. Additional data will have specific times at which the patient reported to various stations of treatment, and when the patient was discharged. A multivariate trend forecasting method will be more appropriate in this setting; the use of multiple variables about the item being forecasted allows seasons and cycles to be combined with other variables and improve forecast accuracy (Langabeer, 2008). This will give operation managers better forecasting abilities as they will be able to see trends.

Forecasting involves using past data to generate a number, set of numbers, or scenario that corresponds to a future occurrence. It is absolutely essential to short-range and long-range planning.

Business forecasting is the process of studying historical performance for the purpose of using the information gained to project future business conditions so that decisions can be made today that will assist in the achievement of certain goals. Forecasting involves taking historical date and using it to project future data with a mathematical model. Forecasts are extensively used to support business decisions and direct the work of operations managers. In this paper I will introduce different types of forecasting techniques.