Search

Author(s): Safavi, Kyan C; Deng, Hao; Driscoll, William; Nikolov, Milcho; Tolia, Kalpan; Wiener-Kronish, Jeanine P | Abstract: BackgroundThe traditional paradigm of hospital surgical ward care consists of episodic bedside visits by providers with periodic perusals of the patient's electronic health record (EHR). Vital signs and laboratory results are directly pushed to the EHR but not to providers themselves. Results that require intervention may not be recognized for hours. Remote surveillance programs continuously monitor electronic data and provide automatic alerts that can be routed to multidisciplinary providers. Such programs have not been explored in surgical general care wards.MethodsWe performed a quality improvement observational study of otolaryngology and ophthalmology patients on a general care ward from October 2017 to March 2019 during nighttime hours (17:00-07:00). The study was initiated due to the loss of on-site anesthesiology resources that historically helped respond to acute physiologic deterioration events. We implemented a remote surveillance software program to continuously monitor patients for severe vital signs and laboratory abnormalities and automatically alert the ward team and a remote critical care anesthesiology team. The primary end point was the true positive rate, defined as the proportion of alerts that were associated with a downstream action that changed the care of the patient. This was determined using systematic chart review. The secondary end point, as a measure of alarm fatigue, was the average number of alerts per clinician shift.ResultsThe software monitored 3926 hospital visits and analyzed 1,560,999 vitals signs and 16,635 laboratories. It generated 151 alerts, averaging 2.6 alerts per week. Of these, 143 (94.7%) were numerically accurate and 8 (5.3%) were inaccurate. Hypoxemia with oxygen saturation l88% was the most common etiology (92, 63%) followed by tachycardia g130 beats per minute (19, 13.3%). Among the accurate alerts, 133 (88.1%) were true positives with an associated clinical action. Actions included a change in management 113 (67.7%), new diagnostic test 26 (15.6%), change in discharge planning 20 (12.0%), and change in level of care to the intensive care unit (ICU) 8 (4.8%). As a measure of alarm fatigue, there were 0.4 alerts per clinician shift.ConclusionsIn a surgical general care ward, a remote surveillance software program that continually and automatically monitors physiologic data streams from the EHR and alerts multidisciplinary providers for severe derangements provided highly actionable alarms at a rate that is unlikely to cause alarm fatigue. Such programs are feasible and could be used to change the paradigm of monitoring.

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.

The convergence of multiple recent developments in health care information technology and monitoring devices has made possible the creation of remote patient surveillance systems that increase the timeliness and quality of patient care. More convenient, less invasive monitoring devices, including patches, wearables, and biosensors, now allow for continuous physiological data to be gleaned from patients in a variety of care settings across the perioperative experience. These data can be bound into a single data repository, creating so-called data lakes. The high volume and diversity of data in these repositories must be processed into standard formats that can be queried in real time. These data can then be used by sophisticated prediction algorithms currently under development, enabling the early recognition of patterns of clinical deterioration otherwise undetectable to humans. Improved predictions can reduce alarm fatigue. In addition, data are now automatically queriable on a real-time basis such that they can be fed back to clinicians in a time frame that allows for meaningful intervention. These advancements are key components of successful remote surveillance systems. Anesthesiologists have the opportunity to be at the forefront of remote surveillance in the care they provide in the operating room, postanesthesia care unit, and intensive care unit, while also expanding their scope to include high-risk preoperative and postoperative patients on the general care wards. These systems hold the promise of enabling anesthesiologists to detect and intervene upon changes in the clinical status of the patient before adverse events have occurred. Importantly, however, significant barriers still exist to the effective deployment of these technologies and their study in impacting patient outcomes. Studies demonstrating the impact of remote surveillance on patient outcomes are limited. Critical to the impact of the technology are strategies of implementation, including who should receive and respond to alerts and how they should respond. Moreover, the lack of cost-effectiveness data and the uncertainty of whether clinical activities surrounding these technologies will be financially reimbursed remain significant challenges to future scale and sustainability. This narrative review will discuss the evolving technical components of remote surveillance systems, the clinical use cases relevant to the anesthesiologist's practice, the existing evidence for their impact on patients, the barriers that exist to their effective implementation and study, and important considerations regarding sustainability and cost-effectiveness.

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.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.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%).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.