An alert tool to promote lung protective ventilation for possible acute respiratory distress syndrome. Issue 2 (8th July 2022)

• Record Type: Journal Article
• Authors: Knighton, Andrew J; Kuttler, Kathryn G; Ranade-Kharkar, Pallavi; Allen, Lauren; Throne, Taylor; Jacobs, Jason R; Carpenter, Lori; Winberg, Carrie; Johnson, Kyle; Shrestha, Neer; Ferraro, Jeffrey P; Wolfe, Doug; Peltan, Ithan D; Srivastava, Rajendu; Grissom, Colin K
• Is Part Of: JAMIA open. Volume 5:Issue 2(2022)
• Publication Date: 2022-07-08
• Subjects: clinical decision support systems -- acute lung injury -- acute respiratory distress syndrome -- computerized ventilation protocols -- lung protective ventilation; Medical informatics -- Periodicals; 610.285
• DOI: 10.1093/jamiaopen/ooac050
• Languages: English
• ISSNs: 2574-2531

Abstract

Abstract: Objective: Computer-aided decision tools may speed recognition of acute respiratory distress syndrome (ARDS) and promote consistent, timely treatment using lung-protective ventilation (LPV). This study evaluated implementation and service (process) outcomes with deployment and use of a clinical decision support (CDS) synchronous alert tool associated with existing computerized ventilator protocols and targeted patients with possible ARDS not receiving LPV. Materials and Methods: We performed an explanatory mixed methods study from December 2019 to November 2020 to evaluate CDS alert implementation outcomes across 13 intensive care units (ICU) in an integrated healthcare system with >4000 mechanically ventilated patients annually. We utilized quantitative methods to measure service outcomes including CDS alert tool utilization, accuracy, and implementation effectiveness. Attitudes regarding the appropriateness and acceptability of the CDS tool were assessed via an electronic field survey of physicians and advanced practice providers. Results: Thirty-eight percent of study encounters had at least one episode of LPV nonadherence. Addition of LPV treatment detection logic prevented an estimated 1812 alert messages (41%) over use of disease detection logic alone. Forty-eight percent of alert recommendations were implemented within 2 h. Alert accuracy was estimated at 63% when compared to gold standard ARDS adjudication, with sensitivity of 85% and positive predictive value of 62%. Fifty-seven percent of survey respondents observed one or more benefits associated with the alert. Conclusion: Introduction of a CDS alert tool based upon ARDS risk factors and integrated with computerized ventilator protocol instructions increased visibility to gaps in LPV use and promoted increased adherence to LPV. Lay Summary: Clinical decision support (CDS) tools may speed recognition of acute respiratory distress syndrome (ARDS), a serious medical condition diagnosed in about 10% patients admitted to hospital intensive care units (ICUs). CDS tools can also promote consistent, timely patient treatment using evidence-based, lung-protective ventilation (LPV). This study evaluated outcomes associated with the deployment and use of a CDS alert tool alerting clinicians of patients with possible ARDS not receiving LPV. The study was conducted across 13 ICUs in an integrated healthcare system with >4000 mechanically ventilated patients annually. Thirty-eight percent of patient encounters with possible ARDS had at least one episode of LPV nonadherence. Combining LPV treatment detection and ARDS detection logic prevented an estimated 1812 alert messages (41%) over use of ARDS detection logic alone. Forty-eight percent of alert recommendations were implemented within 2 h. Eighty-five percent of people with ARDS had a positive result for possible ARDS using the disease detection logic with 62% of patients identified with possible ARDS having the disease. Fifty-seven percent of clinicians surveyed observed benefits associated with the alert. Introduction of a CDS alert tool increased visibility to gaps in LPV use and promoted increased adherence to LPV.