Evaluation of Automated Reminders to Reduce Sepsis Mortality Rates

Sepsis is still a leading cause of death in the United States despite extensive research and modern advancement in technology. Early recognition of sepsis and timely management strategies are important for effective reduction of sepsis-related morbidity and mortality. Guided by the logic model, the...

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Main Author: Lindo, Maria M
Format: Others
Language:en
Published: ScholarWorks 2017
Subjects:
Online Access:https://scholarworks.waldenu.edu/dissertations/3401
https://scholarworks.waldenu.edu/cgi/viewcontent.cgi?article=4504&context=dissertations
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spelling ndltd-waldenu.edu-oai-scholarworks.waldenu.edu-dissertations-45042019-10-30T01:12:03Z Evaluation of Automated Reminders to Reduce Sepsis Mortality Rates Lindo, Maria M Sepsis is still a leading cause of death in the United States despite extensive research and modern advancement in technology. Early recognition of sepsis and timely management strategies are important for effective reduction of sepsis-related morbidity and mortality. Guided by the logic model, the purpose of this project was to evaluate the effectiveness of electronic reminders in enhancing clinical decision-making among 30 nurses in 3 medical-surgical units. The practice-focused question addressed the effectiveness of electronic reminders for early recognition and initiation of goal-directed treatment of sepsis in hospitalized patients on medical-surgical units in an effort to reduce sepsis mortality rates. Data were collected from a randomized convenience sample using a self-constructed questionnaire and through observation. The observations were aimed at assessing whether the nurses adhered to the sepsis protocol, while the questionnaire captured the participants' perceptions regarding the use of automated alerts measured on a 5-point Likert scale. Statistical analysis involved the use of frequencies and percentages, positive predictive value (PPV), and negative predictive value (NPV). The results indicated that all the nurses adhered to sepsis protocol. The sepsis-related mortality rate, mean response time, and rate of severe sepsis at the hospital were reduced by 17.2%, 14 minutes, and 11.1%, respectively. It was concluded that automatic alert systems improve nurses' ability to recognize early symptoms of sepsis and their ability to initiate Code Sepsis. However, replication of this study using a large sample size could provide findings that are more generalizable. Electronic reminders may promote positive social change because earlier recognition of sepsis by nurses may lead to a reduction of healthcare costs through improved management of sepsis patients in acute care settings. 2017-01-01T08:00:00Z text application/pdf https://scholarworks.waldenu.edu/dissertations/3401 https://scholarworks.waldenu.edu/cgi/viewcontent.cgi?article=4504&context=dissertations Walden Dissertations and Doctoral Studies en ScholarWorks Automated Reminders Early Recognition Early Treatment Hospitalized Patients Mortality Rates Sepsis Medicine and Health Sciences Nursing Public Health Education and Promotion
collection NDLTD
language en
format Others
sources NDLTD
topic Automated Reminders
Early Recognition
Early Treatment
Hospitalized Patients
Mortality Rates
Sepsis
Medicine and Health Sciences
Nursing
Public Health Education and Promotion
spellingShingle Automated Reminders
Early Recognition
Early Treatment
Hospitalized Patients
Mortality Rates
Sepsis
Medicine and Health Sciences
Nursing
Public Health Education and Promotion
Lindo, Maria M
Evaluation of Automated Reminders to Reduce Sepsis Mortality Rates
description Sepsis is still a leading cause of death in the United States despite extensive research and modern advancement in technology. Early recognition of sepsis and timely management strategies are important for effective reduction of sepsis-related morbidity and mortality. Guided by the logic model, the purpose of this project was to evaluate the effectiveness of electronic reminders in enhancing clinical decision-making among 30 nurses in 3 medical-surgical units. The practice-focused question addressed the effectiveness of electronic reminders for early recognition and initiation of goal-directed treatment of sepsis in hospitalized patients on medical-surgical units in an effort to reduce sepsis mortality rates. Data were collected from a randomized convenience sample using a self-constructed questionnaire and through observation. The observations were aimed at assessing whether the nurses adhered to the sepsis protocol, while the questionnaire captured the participants' perceptions regarding the use of automated alerts measured on a 5-point Likert scale. Statistical analysis involved the use of frequencies and percentages, positive predictive value (PPV), and negative predictive value (NPV). The results indicated that all the nurses adhered to sepsis protocol. The sepsis-related mortality rate, mean response time, and rate of severe sepsis at the hospital were reduced by 17.2%, 14 minutes, and 11.1%, respectively. It was concluded that automatic alert systems improve nurses' ability to recognize early symptoms of sepsis and their ability to initiate Code Sepsis. However, replication of this study using a large sample size could provide findings that are more generalizable. Electronic reminders may promote positive social change because earlier recognition of sepsis by nurses may lead to a reduction of healthcare costs through improved management of sepsis patients in acute care settings.
author Lindo, Maria M
author_facet Lindo, Maria M
author_sort Lindo, Maria M
title Evaluation of Automated Reminders to Reduce Sepsis Mortality Rates
title_short Evaluation of Automated Reminders to Reduce Sepsis Mortality Rates
title_full Evaluation of Automated Reminders to Reduce Sepsis Mortality Rates
title_fullStr Evaluation of Automated Reminders to Reduce Sepsis Mortality Rates
title_full_unstemmed Evaluation of Automated Reminders to Reduce Sepsis Mortality Rates
title_sort evaluation of automated reminders to reduce sepsis mortality rates
publisher ScholarWorks
publishDate 2017
url https://scholarworks.waldenu.edu/dissertations/3401
https://scholarworks.waldenu.edu/cgi/viewcontent.cgi?article=4504&context=dissertations
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