Improving Transfusion Safety in the Operating Room With a Barcode Scanning System Designed Specifically for the Surgical Environment and Existing Electronic Medical Record Systems: An Interrupted Time Series Analysis.

BACKGROUND: Manual processes for verifying patient identification before blood transfusion and documenting this pretransfusion safety check are prone to errors, and compliance with manual systems is especially poor in urgent operating room settings. An automated, electronic barcode scanner system would be expected to improve pretransfusion verification and documentation. METHODS: Audits were conducted of blood transfusion documentation under a manual paper system from January to October 2014. An electronic barcode scanning system was developed to streamline transfusion safety checking and automate documentation. This system was implemented in 58 operating rooms between October and December 2014, with follow-up compliance audits through December 2015. The association of barcode scanner implementation with transfusion documentation compliance was assessed using an interrupted time series analysis. Anesthesia providers were surveyed regarding their opinions on the electronic system. In mid-2016, the scanning system was modified to transfer from the Metavision medical record system to Epic OpTime. Follow-up analysis assessed performance of this system within Epic during 2017. RESULTS: In an interrupted time series analysis, the proportion of units with compliant documentation was estimated to be 19.6% (95% confidence interval [CI], 10.7-25.6) the week before scanner implementation, and 74.4% (95% CI, 59.4-87.4) the week after implementation. There was a significant postintervention level change (odds ratio 10.80, 95% CI, 6.31-18.70; P < .001) and increase in slope (odds ratio 1.14 per 1-week increase, 95% CI, 1.11-1.17; P < .001). After implementation, providers chose to use the new electronic system for 98% of transfusions. Across the 2 years analyzed (15,997 transfusions), the electronic system detected 45 potential transfusion errors in 27 unique patients, and averted transfusion of 36 mismatched blood products into 20 unique patients. A total of 69%, 86%, and 88% of providers reported the electronic system improved patient safety, blood transfusion workflow, and transfusion documentation, respectively. When providers used the barcode scanner, no transfusion errors or reactions were reported. The scanner system was successfully transferred from Metavision to Epic without retraining staff or changing workflows. CONCLUSIONS: A barcode-based system designed for easy integration to different commonly used anesthesia information management systems was implemented in a large urban academic hospital. The system allows a single user with the assistance of a software system to perform and document pretransfusion safety verification. The system improved transfusion documentation compliance, averted potential transfusion errors, and became the preferred method of blood transfusion safety checking.

Application of process improvement principles to increase the frequency of complete airway management documentation.

BACKGROUND: Process improvement in healthcare delivery settings can be difficult, even when there is consensus among clinicians about a clinical practice or desired outcome. Airway management is a medical intervention fundamental to the delivery of anesthesia care. Like other medical interventions, a detailed description of the management methods should be documented. Despite this expectation, airway documentation is often insufficient. The authors hypothesized that formal adoption of process improvement methods could be used to increase the rate of "complete" airway management documentation. METHODS: The authors defined a set of criteria as a local practice standard of "complete" airway management documentation. The authors then employed selected process improvement methodologies over 13 months in three iterative and escalating phases to increase the percentage of records with complete documentation. The criteria were applied retrospectively to determine the baseline frequency of complete records, and prospectively to measure the impact of process improvements efforts over the three phases of implementation. RESULTS: Immediately before the initial intervention, a retrospective review of 23,011 general anesthesia cases over 6 months showed that 13.2% of patient records included complete documentation. At the conclusion of the 13-month improvement effort, documentation improved to a completion rate of 91.6% (P<0.0001). During the subsequent 21 months, the completion rate was sustained at an average of 90.7% (SD, 0.9%) across 82,571 general anesthetic records. CONCLUSION: Systematic application of process improvement methodologies can improve airway documentation and may be similarly effective in improving other areas of anesthesia clinical practice.

Decision support using anesthesia information management system records and accreditation council for graduate medical education case logs for resident operating room assignments.

Our goal in this study was to develop decision support systems for resident operating room (OR) assignments using anesthesia information management system (AIMS) records and Accreditation Council for Graduate Medical Education (ACGME) case logs and evaluate the implementations. We developed 2 Web-based systems: an ACGME case-log visualization tool, and Residents Helping in Navigating OR Scheduling (Rhinos), an interactive system that solicits OR assignment requests from residents and creates resident profiles. Resident profiles are snapshots of the cases and procedures each resident has done and were derived from AIMS records and ACGME case logs. A Rhinos pilot was performed for 6 weeks on 2 clinical services. One hundred sixty-five requests were entered and used in OR assignment decisions by a single attending anesthesiologist. Each request consisted of a rank ordered list of up to 3 ORs. Residents had access to detailed information about these cases including surgeon and patient name, age, procedure type, and admission status. Success rates at matching resident requests were determined by comparing requests with AIMS records. Of the 165 requests, 87 first-choice matches (52.7%), 27 second-choice matches (16.4%), and 8 third-choice matches (4.8%) were made. Forty-three requests were unmatched (26.1%). Thirty-nine first-choice requests overlapped (23.6%). Full implementation followed on 8 clinical services for 8 weeks. Seven hundred fifty-four requests were reviewed by 15 attending anesthesiologists, with 339 first-choice matches (45.0%), 122 second-choice matches (16.2%), 55 third-choice matches (7.3%), and 238 unmatched (31.5%). There were 279 overlapping first-choice requests (37.0%). The overall combined match success rate was 69.4%. Separately, we developed an ACGME case-log visualization tool that allows individual resident experiences to be compared against case minimums as well as resident peer groups. We conclude that it is feasible to use ACGME case-log data in decision support systems for informing resident OR assignments. Additional analysis will be necessary to assess the educational impact of these systems.

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.

Awareness during general anesthesia: analysis of contributing causes aided by automatic data capture.

The cause of the awareness under general anesthesia often cannot be definitely determined from retrospective reviews of handwritten records, examinations of equipment, or interviews with clinicians. Failure to deliver the intended concentrations of anesthetic agents to the patient is one possible contributing cause for awareness. An advantage of an automated Anesthesia Information Management System (AIMS) is its ability to electronically capture and preserve case data that might otherwise be lost. We reviewed the AIMS records of 3 anesthetics in which intraoperative awareness was felt to have probably occurred. The details of the reported awareness event were temporally correlated with the anesthetic gas concentrations in an effort to determine if low concentrations were contributing factors. The data captured by the AIMS revealed low levels of inspired or expired inhalation agents during the intervals correlating with apparent patient recall. The findings suggest that failure to deliver sufficient concentrations of anesthetic gases permitted awareness events in these cases. Thus data from automated anesthesia information management in the operating room may help identify causes of awareness, and means to prevent awareness can be instituted.

An observational study of anesthesia record completeness using an anesthesia information management system.

BACKGROUND: Studies of the accuracy and completeness of handwritten anesthesia records demonstrate deficiencies in documentation, suggesting that the quality of anesthesia records can be improved. METHODS: We reviewed all electronic anesthesia records generated during a 1-month period at our institution to ascertain completion rates for six clinical documentation elements: allergies, IV access, electrocardiogram rhythm, ease of mask ventilation, laryngoscopic grade of view, and insertion depth of the endotracheal tube. RESULTS: Of 2838 records, 64% had the necessary free text remark in the allergy element. The free text required to complete endotracheal tube depth documentation appeared in 538 of 918 cases in which the patient was tracheally intubated (59%). Free text documentation of the electrocardiogram rhythm diagnosis appeared at least once in 86% of records. Documentation of mask ventilation characteristics was entered by touch screen from a pick list and was expected in 781 records but appeared in 664 records (85%). Laryngoscopic grade of view documentation was also selected by touch screen and expected in 883 records but present in 811 cases (92%). Any notation of IV access appeared in 84% of records. CONCLUSIONS: We found that electronic clinical anesthesia documentation was often incomplete. Dependence on free text remarks and the record keeping system's inability to automatically present entries in logical sequences consistent with workflow were associated with incomplete data entry. Our results suggest that the user interface for data entry, and the logic that an electronic system uses for preventing omissions and inconsistencies, merit further study and development in order to facilitate clinically useful documentation.

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.