Clinical Decision Support as a Prevention Tool for Medication Errors in the Operating Room: A Retrospective Cross-Sectional Study.

BACKGROUND: Medication errors in the operating room have high potential for patient harm. While electronic clinical decision support (CDS) software has been effective in preventing medication errors in many nonoperating room patient care areas, it is not yet widely used in operating rooms. The purpose of this study was to determine the percentage of self-reported intraoperative medication errors that could be prevented by CDS algorithms. METHODS: In this retrospective cross-sectional study, we obtained safety reports involving medication errors documented by anesthesia clinicians between August 2020 and August 2022 at a 1046-bed tertiary care academic medical center. Reviewers classified each medication error by its stage in the medication use process, error type, presence of an adverse medication event, and its associated severity and preventability by CDS. Informational gaps were corroborated by retrospective chart review and disagreements between reviewers were resolved by consensus. The primary outcome was the percentage of errors that were preventable by CDS. Secondary outcomes were preventability by CDS stratified by medication error type and severity. RESULTS: We received 127 safety reports involving 80 medication errors, and 76/80 (95%) of the errors were classified as preventable by CDS. Certain error types were more likely to be preventable by CDS than others (P < .001). The most likely error types to be preventable by CDS were wrong medication (N = 36, 100% rated as preventable), wrong dose (N = 30, 100% rated as preventable), and documentation errors (N = 3, 100% rated as preventable). The least likely error type to be preventable by CDS was inadvertent bolus (N = 3, none rated as preventable). CONCLUSIONS: Ninety-five percent of self-reported medication errors in the operating room were classified as preventable by CDS. Future research should include a randomized controlled trial to assess medication error rates and types with and without the use of CDS.

EAP 2.0: reimagining the role of the employee assistance program in the new workplace.

Mental illness is a highly prevalent problem that affects millions of individuals. Like many other previous natural disasters and terrorist attacks, the recent Covid-19 pandemic has placed an enormous stress on the world and its workforce. In many ways the pandemic revealed gaps in the quality and availability of mental health resources, and, by magnifying the intense demand, it also spurred innovation. Telemedicine and virtual trauma-related services became examples of ways in which evaluation, treatment and counselling services could be delivered directly and efficiently to people who were confined to their dwellings and hospital beds. For many, the workplace has been a source of stress but also a vital component of one's self-worth, day-to-day purpose, and a resource for wellness programs and brief counselling services, not to mention, at least in many countries like the United States, a source for health insurance. The employee assistance program (EAP) is an example of a workplace-counselling and triage service that has enormous potential to meet the growing needs of individuals both in 'normal' times and during disasters. By better understanding the EAP's current structure alongside the advent of new technologies, it may be possible to develop a new and improved EAP model to meet a changing global landscape. For EAP to succeed and ultimately be scalable in an increasingly competitive and value-conscious marketplace, its processes of care will first require a bottom-up review with meaningful outcomes data. This will be necessary to drive continuous quality improvement and to demonstrate EAP 2.0's value to both employer and employee alike.

The Additional Cost of Perioperative Medication Errors.

ABSTRACT: The purpose of this report was to estimate the additional annual cost to the U.S. healthcare system attributable to preventable medication errors (MEs) in the operating room. The ME types were iteratively grouped by their associated harm (or potential harm) into 13 categories, and we determined the incidence of operations involving each ME category (number of operations involving each category/total number of operations): (1) delayed or missed required perioperative antibiotic (1.4% of operations); (2) prolonged hemodynamic swings (7.6% of operations); (3) untreated postoperative pain >4/10 (18.9% of operations); (4) residual neuromuscular blockade (2.9% of operations); (5) oxygen saturation <90% due to ME (1.8% of operations); (6) delayed emergence (1.1% of operations); (7) untreated new onset intraoperative cardiac arrhythmia (0.72% of operations); (8) medication documentation errors (7.6% of operations); (9) syringe swaps (5.8% of operations); (10) presumed hypotension with inability to obtain a blood pressure reading (2.2% of operations); (11) potential for bacterial contamination due to expired medication syringes (8.3% of operations); (12) untreated bradycardia <40 beats/min (1.1% of operations); and (13) other (13.0% of operations). Through a PubMed search, we determined the likelihood that the ME category would result in downstream patient harm such as surgical site infection or acute kidney injury, and the additional fully allocated cost of care (in 2021 U.S. dollars) for each potential downstream patient harm event. We then estimated the cost of the MEs across the U.S. healthcare system by scaling the number of MEs to the total number of annual operations in the United States (N = 19,800,000). The total estimated additional fully allocated annual cost of care due to perioperative MEs was $5.33 billion U.S. dollars.

Usability of a perioperative medication-related clinical decision support software application: a randomized controlled trial.

OBJECTIVE: We developed a comprehensive, medication-related clinical decision support (CDS) software prototype for use in the operating room. The purpose of this study was to compare the usability of the CDS software to the current standard electronic health record (EHR) medication administration and documentation workflow. MATERIALS AND METHODS: The primary outcome was the time taken to complete all simulation tasks. Secondary outcomes were the total number of mouse clicks and the total distance traveled on the screen in pixels. Forty participants were randomized and assigned to complete 7 simulation tasks in 1 of 2 groups: (1) the CDS group (n = 20), who completed tasks using the CDS and (2) the Control group (n = 20), who completed tasks using the standard medication workflow with retrospective manual documentation in our anesthesia information management system. Blinding was not possible. We video- and audio-recorded the participants to capture quantitative data (time on task, mouse clicks, and pixels traveled on the screen) and qualitative data (think-aloud verbalization). RESULTS: The CDS group mean total task time (402.2 ± 85.9 s) was less than the Control group (509.8 ± 103.6 s), with a mean difference of 107.6 s (95% confidence interval [CI], 60.5-179.5 s, P < .001). The CDS group used fewer mouse clicks (26.4 ± 4.5 clicks) than the Control group (56.0 ± 15.0 clicks) with a mean difference of 29.6 clicks (95% CI, 23.2-37.6, P < .001). The CDS group had fewer pixels traveled on the computer monitor (59.5 ± 20.0 thousand pixels) than the Control group (109.3 ± 40.8 thousand pixels) with a mean difference of 49.8 thousand pixels (95% CI, 33.0-73.7, P < .001). CONCLUSIONS: The perioperative medication-related CDS software prototype substantially outperformed standard EHR workflow by decreasing task time and improving efficiency and quality of care in a simulation setting.

Development of a Perioperative Medication-Related Clinical Decision Support Tool to Prevent Medication Errors: An Analysis of User Feedback.

OBJECTIVES: Medication use in the perioperative setting presents many patient safety challenges that may be improved with electronic clinical decision support (CDS). The objective of this paper is to describe the development and analysis of user feedback for a robust, real-time medication-related CDS application designed to provide patient-specific dosing information and alerts to warn of medication errors in the operating room (OR). METHODS: We designed a novel perioperative medication-related CDS application in four phases: (1) identification of need, (2) alert algorithm development, (3) system design, and (4) user interface design. We conducted group and individual design feedback sessions with front-line clinician leaders and subject matter experts to gather feedback about user requirements for alert content and system usability. Participants were clinicians who provide anesthesia (attending anesthesiologists, nurse anesthetists, and house staff), OR pharmacists, and nurses. RESULTS: We performed two group and eight individual design feedback sessions, with a total of 35 participants. We identified 20 feedback themes, corresponding to 19 system changes. Key requirements for user acceptance were: Use hard stops only when necessary; provide as much information as feasible about the rationale behind alerts and patient/clinical context; and allow users to edit fields such as units, time, and baseline values (e.g., baseline blood pressure). CONCLUSION: We incorporated user-centered design principles to build a perioperative medication-related CDS application that uses real-time patient data to provide patient-specific dosing information and alerts. Emphasis on early user involvement to elicit user requirements, workflow considerations, and preferences during application development can result in time and money efficiencies and a safer and more usable system.