• Hui Zheng, Eric T Pierce, Robert A Peterfreund, John L Walsh, William D Driscoll, Aparna Subramanian, Shaji Anupama, Melissa Weaver, Theresa Morris, Sarah Arnholz, and Stephen F Spring.
• Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Jackson 439, 55 Fruit Street, Boston, MA 02114, USA. RPeterfreund@Partners.org
• Anesth. Analg.. 2011 May 1;112(5):1218-25.

BackgroundEfforts to assure high-quality, safe, clinical care depend upon capturing information about near-miss and adverse outcome events. Inconsistent or unreliable information capture, especially for infrequent events, compromises attempts to analyze events in quantitative terms, understand their implications, and assess corrective efforts. To enhance reporting, we developed a secure, electronic, mandatory system for reporting quality assurance data linked to our electronic anesthesia record.MethodsWe used the capabilities of our anesthesia information management system (AIMS) in conjunction with internally developed, secure, intranet-based, Web application software. The application is implemented with a backend allowing robust data storage, retrieval, data analysis, and reporting capabilities. We customized a feature within the AIMS software to create a hard stop in the documentation workflow before the end of anesthesia care time stamp for every case. The software forces the anesthesia provider to access the separate quality assurance data collection program, which provides a checklist for targeted clinical events and a free text option. After completing the event collection program, the software automatically returns the clinician to the AIMS to finalize the anesthesia record.ResultsThe number of events captured by the departmental quality assurance office increased by 92% (95% confidence interval [CI] 60.4%-130%) after system implementation. The major contributor to this increase was the new electronic system. This increase has been sustained over the initial 12 full months after implementation. Under our reporting criteria, the overall rate of clinical events reported by any method was 471 events out of 55,382 cases or 0.85% (95% CI 0.78% to 0.93%). The new system collected 67% of these events (95% confidence interval 63%-71%).ConclusionWe demonstrate the implementation in an academic anesthesia department of a secure clinical event reporting system linked to an AIMS. The system enforces entry of quality assurance information (either no clinical event or notification of a clinical event). System implementation resulted in capturing nearly twice the number of events at a relatively steady case load.© 2011 International Anesthesia Research Society

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