Introduction
The health care sector is in need of reducing patients’ prolonged stays in emergency departments. As a result, it is crucial to develop an efficient system for predicting the length of patients’ stay and, consequently, decreasing its duration. Overall, the productive solution should be an analysis of the conditions that might considerably influence people’s health at the moment to create further advanced treatment methods to reduce the time spent in the emergency department.
Main body
To begin with, the utilization of the emergency department’s resources usually appears to be ineffective since patients with a high length of stay are not transferred to appropriate departments. As a result, instead of being early transported to Clinical Decision Unit, clients remain in the ED, resulting in decreased efficacy of the department’s operations. However, this issue can be tackled to benefit the health sector in the following way: the development of a database that can predict the length of a patient’s stay and, therefore, the need to transfer one might improve ED’s resource utilization. In addition, this system should also evaluate the proper methods for quick, though productive, treatment of people’s diseases provoked by the drastically emerged condition. To be more exact, individuals suffer from the same reasons, like infections spread, weather change, decrease in water quality, or air pollution in the specific region. Through a thorough analysis of the first clients suffering from the same condition, the database can collect similar symptoms so that the treatment method can be developed to reduce the stays’ length of the people with the same problem.
Furthermore, to advance the efficiency of the database, numerous sets of data should be collected to perform previously stated actions. In order to predict the length of stay, the system might implement the information from the patients’ cards to calculate the average length of stay due to a specific disease. The advanced database should be programmed to identify the admitted individuals through the Event Monitor software to determine “ED frequent flyers, patients who have used the ED three or more times in the past six months” (Michelen et al., 2006, p. 62). Consequently, at the next visit, the program should inform the institution of the previous patients’ stays to conduct a thorough examination of their health to recognize the reasons for frequent ED visits (Michelen et al., 2006). Additionally, if previously the clients in severe conditions were in the emergency department for more than four hours, the database can inform the unit to transfer them to Clinical Decision Unit. This way, the ED will not waste its resources inefficiently, and the department’s operations will still be productive since the institution will be able to treat other patients more productively.
Therefore, to ensure effective performance of the database, the information should be frequently upgraded to accurately summarize the possibilities of patients’ stay and the reasons for admissions. For instance, to reduce the length of ED frequent flyers, nurses need to input the results of analyses and the treatment methods for each visit. As a result, when the individual is admitted to the ED again, doctors will need to examine recent symptoms, compare them to those from the database, and identify the proper medicine for the patient. At the same time, nurse managers need to pick experts for a daily survey of weather or area conditions to determine the possible reasons for the clients’ visits. On and whole, the information inputted into the database by specialists will be applied to predict the conditions that might result in the growing numbers of patients with the same problem.
As for the data input, to maintain the efficiency of both databases’ responsibilities, the information should be updated differently. To be more particular, ED nurses should input data during each individual’s visit to predict the one’s length of stay. However, for evaluating possible conditions that might influence the growing numbers of admitted patients, the recent news needs to be examined on a daily basis.
On and whole, the information for reducing the length of ED frequent flyers should be accessed by the nurses when the patient is admitted. To be more precise, ED staff might use any devices to have access to the database, such as tablets or smartphones. This way, the employees will be able to quickly examine the required data to have the means for an efficient treatment of an individual in the short term. The same method of access should be used for identifying the current conditions that might lead to the numerous clients suffering from the same problem, whether it is climate change or infections spreading. Still, the summarized data by the database might be discussed in the morning brief meetings by the nurse managers to inform the ED staff of the possible situations they might face this day.
Summary
To sum up, this database is an efficient tool for reducing the patient’s length of stay to increase the efficacy of the emerging department’s operations and resource usage. In addition, this system is helpful for predicting the conditions that might lead to the possibly growing numbers of admitted individuals due to the same problem. Overall, the database appears to yield numerous benefits for the ED and its staff since it assists in the employees’ job performance, and the system is not challenging to use on a daily basis.
Reference
Michelen, W., Martinez, J., Lee, A., & Wheeler, D. P. (2006). Reducing frequent flyer emergency department visits. Journal of Health Care for the Poor and Underserved, 17(1S), 59–69. Web.