Evaluation of a mandatory quality assurance data capture in anesthesia: a secure electronic system to capture quality assurance information linked to an automated anesthesia record.

BACKGROUND: Efforts 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. METHODS: We 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. RESULTS: The 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%). CONCLUSION: We 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.

Real-time checking of electronic anesthesia records for documentation errors and automatically text messaging clinicians improves quality of documentation.

INTRODUCTION: The quality of electronic anesthesia documentation is important for downstream communication and to demonstrate appropriate diligence to care. Documentation quality will also impact the success of reimbursement contracts that require timely and complete documentation of specific interventions. We implemented a system to improve completeness of clinical documentation and evaluated the results over time. METHODS: We used custom software to continuously scan for missing clinical documentation during anesthesia. We used patient allergies as a test case, taking advantage of a unique requirement in our system that allergies be manually entered into the electronic record. If no allergy information was entered within 15 min of the "start of anesthesia care" event, a one-time prompt was sent via pager to the person performing the anesthetic. We tabulated the daily fraction of cases missing allergy data for the 6 mo before activating the alert system. We then obtained the same data for the subsequent 9 mo. We tested for systematic performance changes using statistical process control methodologies. RESULTS: Before initiating the alert system, the fraction of charts without an allergy comment was slightly more than 30%. This decreased to about 8% after initiating the alerts, and was significantly different from baseline within 5 days. Improvement lasted for the duration of the trial. Paging was suspended on nights, weekends, and holidays, yet weekend documentation performance also improved, indicating that weekday reminders had far-reaching effects. DISCUSSION: Electronic anesthesia documentation performance can be rapidly managed and improved by using an automatic process monitoring and alerting system.

Automated documentation error detection and notification improves anesthesia billing performance.

BACKGROUND: Documentation of key times and events is required to obtain reimbursement for anesthesia services. The authors installed an information management system to improve record keeping and billing performance but found that a significant number of their records still could not be billed in a timely manner, and some records were never billed at all because they contained documentation errors. METHODS: Computer software was developed that automatically examines electronic anesthetic records and alerts clinicians to documentation errors by alphanumeric page and e-mail. The software's efficacy was determined retrospectively by comparing billing performance before and after its implementation. Staff satisfaction with the software was assessed by survey. RESULTS: After implementation of this software, the percentage of anesthetic records that could never be billed declined from 1.31% to 0.04%, and the median time to correct documentation errors decreased from 33 days to 3 days. The average time to release an anesthetic record to the billing service decreased from 3.0+/-0.1 days to 1.1+/-0.2 days. More than 90% of staff found the system to be helpful and easier to use than the previous manual process for error detection and notification. CONCLUSION: This system allowed the authors to reduce the median time to correct documentation errors and the number of anesthetic records that were never billed by at least an order of magnitude. The authors estimate that these improvements increased their department's revenue by approximately $400,000 per year.