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A Data Mining Approach to Determine Sepsis Guideline Impact on Inpatient Mortality and Complications
Sepsis incidents have doubled from 2000 through 2008, and hospitalizations for these diagnoses have increased by 70%. The use of the Surviving Sepsis Campaign (SSC) guidelines can lead to earlier diagnosis and treatment; however, the effectiveness of the SSC guidelines in preventing complications fo...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Medical Informatics Association
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5001751/ https://www.ncbi.nlm.nih.gov/pubmed/27570669 |
Sumario: | Sepsis incidents have doubled from 2000 through 2008, and hospitalizations for these diagnoses have increased by 70%. The use of the Surviving Sepsis Campaign (SSC) guidelines can lead to earlier diagnosis and treatment; however, the effectiveness of the SSC guidelines in preventing complications for this population is unclear. The overall purpose of this study was to apply SSC guideline recommendations to EHR data for patients with severe sepsis or septic shock and determine guideline compliance as well as its impact on inpatient mortality and sepsis complications. Propensity Score Matching in conjuction with Bootstrap Simulation were used to match patients with and without exposure to the SSC recommendations. Findings showed that EHR data could be used to estimate compliance with SSC recommendations as well as the effect of compliance on outcomes. Compliance with guideline recommendations ranged from 9% to 100%. For individual recommendations with sufficient data, association with outcomes varied. Checking lactate influenced four outcomes; however, two were negative and two positive. Use of a ventilator for patients with respiratory distress had a positive association with three outcomes. |
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