Evaluation of an Evidence-based Algorithm for Patients with Acute Respiratory Failure: A Quality Improvement Project
| dc.contributor.advisor | Thaxton, Cheryl | |
| dc.contributor.author | Wilson, LaTisha | |
| dc.contributor.committeeMember | Smith, Melanie | |
| dc.date.accessioned | 2022-06-28T13:51:10Z | |
| dc.date.available | 2022-06-28T13:51:10Z | |
| dc.date.issued | 2022-01-20 | |
| dc.description.abstract | Background: The past decade, and particularly the past few years, there has been an increased focus on early recognition and responding to deteriorating hospitalized patients. One emerging approach gaining support is the use of early warning scoring (EWS) systems. These systems are designed to detect potential patient deterioration which can lead to initiate early intervention and management, such as increasing nursing attention and informing the provider. However, many hospitals across the United States are not utilizing these systems (Casserly, 2015). The Epic Deterioration Index (EDI) is an EWS. For patients at risk for acute respiratory failure (ARF), the utilization of EDI can promote early detection, which will lead to timely intervention and improve patients’ outcomes. In addition, the EDI can help promoting awareness of the need for institutions to independently validate evidence-based practice algorithms for timely intervention to prevent failure to rescue in patients with ARF. The purpose of this quality improvement (QI) project is to evaluate the implementation of an ARF evidence-based algorithm in the intermediate unit (IMU) to help facilitate timely intervention to patients at risk. Method: IMU providers were given instruction and training in the use of EDI in the context of the hospital’s electronic medical records system. Post-intervention data associated with patient intubation or unplanned transfers to the intensive care unit (ICU) was collected and analyzed against similar pre-intervention data. Statistical analyses of changes in patient care were based in the Pearson’s chi-square procedure. Results: There was a reduction but not statistically significant in the difference of pre- and post-intervention on intubation rates and unplanned transfer to the ICU. However, there was a statistically significant in the use of EWS reports to prompt use of the evidence-based clinical algorithm and promoting appropriate patient care. Conclusion: The evidence-based algorithm utilization is a valid tool to alert healthcare providers in identifying a deteriorating patient condition for timely escalation of care. | en_US |
| dc.identifier.uri | https://hdl.handle.net/11274/13759 | |
| dc.language.iso | en_US | en_US |
| dc.subject | Acute respiratory failure | en_US |
| dc.subject | Critical care | en_US |
| dc.subject | Early warning score | en_US |
| dc.subject | Acute respiratory failure algorithm | en_US |
| dc.subject | Intermediate care unit | en_US |
| dc.subject | Failure to rescue | en_US |
| dc.subject | Epic deterioration index | en_US |
| dc.title | Evaluation of an Evidence-based Algorithm for Patients with Acute Respiratory Failure: A Quality Improvement Project | en_US |
| dc.type | Doctoral Project | en_US |
| thesis.degree.college | College of Nursing | en_US |
| thesis.degree.department | Nursing | en_US |
| thesis.degree.grantor | Texas Woman's University | en_US |
| thesis.degree.level | Doctoral | en_US |
| thesis.degree.name | Doctor of Nursing Practice | en_US |