Categorization in Mechanically Ventilated Pediatric Subjects: A Proposed Method to Improve Quality.
BACKGROUND: Thousands of children require mechanical ventilation each year. Although mechanical ventilation is lifesaving, it is also associated with adverse events if not properly managed. The systematic implementation of evidence-based practice through the use of guidelines and protocols has been...
| Publicado en: | Respiratory Care Vol. 61; no. 9; pp. 1168 - 1179 |
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| Autores principales: | , , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Mary Ann Liebert, Inc.
Sep2016
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=118044775&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 118044775 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00201324 4GG jtl: Respiratory Care issn: 00201324 maglogo: N pubinfo: dt: Sep2016 vid: 61 iid: 9 pid: 1365 pub: Mary Ann Liebert, Inc. place: New Rochelle, New York artinfo: ui: 118044775 118044775 118044775 10.4187/respcare.04723 118044775 ppf: 1168 ppct: 11 formats: fmt: @attributes: type: P tig: atl: Categorization in Mechanically Ventilated Pediatric Subjects: A Proposed Method to Improve Quality. aug: au: Walsh, Brian K. Smallwood, Craig D. Rettig, Jordan S. Thompson, John E. Kacmarek, Robert M. Arnold, John H. affil: Department of Anesthesiology, Perioperative, and Pain Medicine, Division of Critical Care Medicine, Boston Children's Hospital and Pediatric Anesthesia, Harvard Medical School, Boston, Massachusetts sug: subj: Respiration, Artificial Statistics and Numerical Data Decision Support Systems, Clinical Utilization Human Quality Improvement Male Female Child Medical Practice, Evidence-Based Retrospective Design Practice Guidelines Protocols Information Technology Intensive Care Units, Pediatric Data Collection, Computer Assisted Electronic Health Records Prospective Studies Algorithms Kruskal-Wallis Test Wilcoxon Signed Rank Test One-Way Analysis of Variance Infant Child, Preschool Heart Rate Respiratory Rate Ventilator-Induced Lung Injury Random Sample Audit Child: 6-12 years Infant: 1-23 months Child, Preschool: 2-5 years Male Female ab: BACKGROUND: Thousands of children require mechanical ventilation each year. Although mechanical ventilation is lifesaving, it is also associated with adverse events if not properly managed. The systematic implementation of evidence-based practice through the use of guidelines and protocols has been shown to mitigate risk, yet variation in care remains prevalent. Advances in health-care technology provided the ability to stream data about mechanical ventilation and therapeutic response. Through these advances, a computer system was developed to enable the coupling of physiologic and ventilation data for real-time interpretation. Our aim was to assess the feasibility and utility of a newly developed patient categorization and scoring system to objectively measure compliance with standards of care. METHODS: We retrospectively categorized the ventilation and oxygenation statuses of subjects within our pediatric ICU utilizing 15 rules-based algorithms. Targets were predetermined based on generally accepted practices. All patient categories were calculated and presented as a percent score (0-100%) of acceptable ventilation, acceptable oxygenation, barotrauma-free, and volutrauma-free states. RESULTS: Two hundred twenty-two subjects were identified and analyzed encompassing 1,578 d of mechanical ventilation. Median age was 3 y, median ideal body weight was 14.7 kg, and 63% were male. The median acceptable ventilation score was 84.6%, and the median acceptable oxygenation score was 70.1% (100% being maximally acceptable). Potential for ventilator-induced lung injury was broken into 2 components: baro-trauma and volutrauma. There was very little potential for barotrauma, with a median barotrauma-free state of 100%. Median potential for a volutrauma-free state was 56.1%. CONCLUSIONS: We demonstrate the first patient categorization system utilizing a coordinated data-banking system and analytics to determine patient status and a surveillance of mechanical ventilation quality. Further research is needed to determine whether interventions such as visual display of variance from goal and patient categorization summaries can improve outcomes. (ClinicalTrials.gov registration NCT02184208.) pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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