DEVELOPING A SEARCHABLE QUESTION USING THE PICO(T) FORMAT
After you have identified your clinical practice issue (MSN FNP) or management issue (MSN Administration):
Describe the issue and include why you feel it is an issue (SBAR).
Create a PICO(T) table for your issue.
Write your question using the PICO(T).
Sample PICO(T) Table (see Table 2.2 in Melnyk & Fineout-Overholt textbook for example)
Time (if applicable)
Follow the format below. Use this Word template with APA formatting (Word) (Links to an external site.).
Note: Format is attached and Table 2.2 in Melnyk & Fineout-Overholt textbook is attached
Patient safety is greatly enhanced by the use of electronic medical devices, which provide life-saving assistance and physiological monitoring across a hospital’s care facilities. There are medical technologies on the market now that are designed to notify medical professionals of any changes in the physiological characteristics of a patient before they are damaged (Winters et al., 2018). However, alarm fatigue develops when doctors are exposed to a large number of medical device alerts, resulting in alarm desensitization and delayed reaction. For instance, in one event that involved twenty-five consecutive operations for chronic diabetic management, 8,975 alarms occurred. Each operation recorded 1.2 alarms per minute, or an average of 359 alerts (Hravnak et al., 2018). With so many alerts going off, people are either responding too slowly or missing alarms altogether. A growing concern for patient safety is that of alarm weariness, which has been linked to an increase in the number of alerts in healthcare. Alarm fatigue is a well-known issue, yet alarm-related incidents are often overlooked, and research into possible solutions is still in its infancy.
Clinicians utilize a variety of devices and technologies to keep tabs on their patients’ health, which is becoming increasingly computerized. When a patient’s state deviates from a specified typical range, most healthcare equipment generate audio or visual alerts to inform physicians. In order to assist doctors in determining the best course of action in the event of an alarm, many devices produce a variety of voices, sounds, and pitches based on the severity of the alert (Hravnak et al., 2018). In some instances, electrical or mechanical faults, such as drained batteries in a device, might trigger system status or non-clinical alerts. However, excessive alert frequency and a high incidence of false alarms can lead to alarm fatigue, making device alarms dangerous to patient safety and hindering professional decision-making (Winters et al., 2018). Clinical staff, particularly nurses, might have alarm fatigue as a result of overexposure to safety alarms, leading to alarms being missed or responses being delayed.
As a nurse, alarm fatigue is a serious problem since it can lead to patient harm and even death. Indeed, over five hundred patients have died as a result of false alarms, according to various sources. For instance, eighty percent to ninety-eight percent of ECG monitor warnings are erroneous or clinically inconsequential, according to research (Winters et al., 2018). As a result, healthcare facilities are looking for the “magic bullet” in order to deal with this issue in an effective and efficient manner. Nurses who hear too many of these annoying alerts begin to question the accuracy of the devices they are tasked with monitoring, leading them to reduce the level, ignore, or disable the alarms altogether. This negatively impacts the safety of patients since nurses ignore even clinically significant alarms.
In an acute healthcare setting, how effective is technological education compared to no education in reducing alarm fatigue within six months?
|Problem||Acute healthcare setting|
|Comparison||No technological education|
|Outcome||Reducing alarm fatigue|
For patient safety and reduced sentinel incidents resulting from improper alarm handling, alarm fatigue has to be addressed. Alarm fatigue can be alleviated in part by promoting technological literacy. This intervention approach is designed to collect data and information on the various sounds generated by multiple medical technology. This will help nurses distinguish between false and significant clinical alarms.
Hravnak, M., Pellathy, T., Chen, L., Dubrawski, A., Wertz, A., Clermont, G., & Pinsky, M. R. (2018). A call to alarms: current state and future directions in the battle against alarm fatigue. Journal of electrocardiology, 51(6), S44-S48. https://www.sciencedirect.com/science/article/abs/pii/S0022073618304722
Winters, B. D., Cvach, M. M., Bonafide, C. P., Hu, X., Konkani, A., O’Connor, M. F., … & Kane-Gill, S. L. (2018). Technological distractions (part 2): a summary of approaches to manage clinical alarms with intent to reduce alarm fatigue. Critical care medicine, 46(1), 130-137. https://journals.lww.com/ccmjournal/Abstract/2018/01000/Technological_Distractions__Part_2___A_Sum