A meta-model for computer executable dynamic clinical safety checklists

Beyond the self: a novel framework to enhance non-technical team skills for anesthesiologists

Human factors and non-technical skills (NTS) have been identified as essential contributors to both the propagation and prevention of medical errors in the operating room. Despite extensive study and interventions to nurture and enhance NTS in anesthesiologists, gaps to effective team practice and patient safety remain. Furthermore, the link between added NTS training and clinically significant improved outcomes has not yet been demonstrated. We performed a narrative review to summarize the literature on existing systems and initiatives used to measure and nurture NTS in the clinical operating room setting. Controlled interventions performed to nurture NTS (N.=13) were identified and compared. We comment on the body of current evidence and highlight the achievements and limitations of interventions published thus far. We then propose a novel education and training framework to further develop and enhance non-technical skills in both individual anesthesiologists and operating room teams. We use the cardiac anesthesiology environment as a starting point to illustrate its use, with clinical examples. NTS is a key component of enhancing patient safety. Effective framing of its concepts is central to apply individual characteristics and skills in team environments in the OR and achieve tangible, beneficial patient outcomes.

Challenges and Burdens in the Coronary Artery Disease Care Pathway for Patients Undergoing Percutaneous Coronary Intervention: A Contemporary Narrative Review

Clinical and economic burdens exist within the coronary artery disease (CAD) care pathway despite advances in diagnosis and treatment and the increasing utilization of percutaneous coronary intervention (PCI). However, research presenting a comprehensive assessment of the challenges across this pathway is scarce. This contemporary review identifies relevant studies related to inefficiencies in the diagnosis, treatment, and management of CAD, including clinician, patient, and economic burdens. Studies demonstrating the benefits of integration and automation within the catheterization laboratory and across the CAD care pathway were also included. Most studies were published in the last 5-10 years and focused on North America and Europe. The review demonstrated multiple potentially avoidable inefficiencies, with a focus on access, appropriate use, conduct, and follow-up related to PCI. Inefficiencies included misdiagnosis, delays in emergency care, suboptimal testing, longer procedure times, risk of recurrent cardiac events, incomplete treatment, and challenges accessing and adhering to post-acute care. Across the CAD pathway, this review revealed that high clinician burnout, complex technologies, radiation, and contrast media exposure, amongst others, negatively impact workflow and patient care. Potential solutions include greater integration and interoperability between technologies and systems, improved standardization, and increased automation to reduce burdens in CAD and improve patient outcomes.

Quality Improvement in the Preoperative Evaluation: Accuracy of an Automated Clinical Decision Support System to Calculate CHA2DS2-VASc Scores

Background and Objectives: Clinical decision support systems are advocated to improve the quality and efficiency in healthcare. However, before implementation, validation of these systems needs to be performed. In this evaluation we tested our hypothesis that a computerized clinical decision support system can calculate the CHA₂DS₂-VASc score just as well compared to manual calculation, or even better and more efficiently than manual calculation in patients with atrial rhythm disturbances. Materials and Methods: In n = 224 patents, we calculated the total CHA₂DS₂-VASc score manually and by an automated clinical decision support system. We compared the automated clinical decision support system with manually calculation by physicians. Results: The interclass correlation between the automated clinical decision support system and manual calculation showed was 0.859 (0.611 and 0.931 95%-CI). Bland-Altman plot and linear regression analysis shows us a bias of −0.79 with limit of agreement (95%-CI) between 1.37 and −2.95 of the mean between our 2 measurements. The Cohen’s kappa was 0.42. Retrospective analysis showed more human errors than algorithmic errors. Time it took to calculate the CHA₂DS₂-VASc score was 11 s per patient in the automated clinical decision support system compared to 48 s per patient with the physician. Conclusions: Our automated clinical decision support system is at least as good as manual calculation, may be more accurate and is more time efficient.

Intelligent checklists improve checklist compliance in the intensive care unit: a prospective before-and-after mixed-method study

BACKGROUND

We examined whether a context and process-sensitive 'intelligent' checklist increases compliance with best practice compared with a paper checklist during intensive care ward rounds.

METHODS

We conducted a single-centre prospective before-and-after mixed-method trial in a 35 bed medical and surgical ICU. Daily ICU ward rounds were observed during two periods of 8 weeks. We compared paper checklists (control) with a dynamic (digital) clinical checklist (DCC, intervention). The primary outcome was compliance with best clinical practice, measured as the percentages of checked items and unchecked critical items. Secondary outcomes included ICU stay and the usability of digital checklists. Data are presented as median (interquartile range).

RESULTS

Clinical characteristics and severity of critical illness were similar during both control and intervention periods of study. A total of 36 clinicians visited 197 patients during 352 ward rounds using the paper checklist, compared with 211 patients during 366 ward rounds using the DCC. Per ICU round, a median of 100% of items (94.4-100.0) were completed by DCC, compared with 75.1% (66.7-86.4) by paper checklist (P=0.03). No critical items remained unchecked by the DCC, compared with 15.4% (8.3-27.3) by the paper checklist (P=0.01). The DCC was associated with reduced ICU stay (1 day [1-3]), compared with the paper checklist (2 days [1-4]; P=0.05). Usability of the DCC was judged by clinicians to require further improvement.

CONCLUSIONS

A digital checklist improved compliance with best clinical practice, compared with a paper checklist, during ward rounds on a mixed ICU.

CLINICAL TRIAL REGISTRATION

NCT03599856.

Specialization of Business Process Model and Notation Applications in Medicine—A Review

Process analysis and process modeling are a current topic that extends to many areas. This trend of using optimization and modeling techniques in various specific areas has led to the question of how widespread these approaches are overall in medical specializations. We compiled a list of 272 medical disciplines that we used as a search string with the Business Process Model and Notation (BPMN) for a Web of Science database search. Thus, we found a total of 485 documents that we subjected to the exclusion criteria. We analyzed the remaining 108 articles using bibliometric and content analyses to find answers to three research questions. This systematic review was carried out using the procedure proposed by Kitchenham and following the Preferred Items of the Systematic Review and Meta-Analysis Report (PRISMA). Due to the broad scope of the medical field, it was no surprise that for almost 85% of the sought-after medical specializations, we could not identify any publications in the given database when applying the BPMN. We analyzed the impact of upgrades to the BPMN on publishing. The keyword analysis showed a diametrical difference between the authors’ keywords and the so-called “Keywords Plus”, and we categorized the publications according to the purpose of applying the BPMN. However, the growing interest in combining BPMN with other approaches brings new challenges in practice.

Digital Cognitive Aids to Support Adaptation of Surgical Processes to COVID-19 Protective Policies

Surgical processes are rapidly being adapted to address the COVID-19 pandemic, with changes in procedures and responsibilities being made to protect both patients and medical teams. These process changes put new cognitive demands on the medical team and increase the likelihood of miscommunication, lapses in judgment, and medical errors. We describe two process model driven cognitive aids, referred to as the Narrative View and the Smart Checklist View, generated automatically from models of the processes. The immediate perceived utility of these cognitive aids is to support medical simulations, particularly when frequent adaptations are needed to quickly respond to changing operating room guidelines.

Application, verification and correction from an elaborate checklist with some of the recommendations («do and do not do») of the SEMICYUC working groups

OBJECTIVE

Based on some of the recommendations of the SEMICYUC working groups, we developed a checklist and applied it in 2 periods, analyzing their behavior as a tool for improving safety.

DESIGN

A comparative pre- and post-intervention longitudinal study was carried out.

SETTING

The Intensive Care Unit (ICU) of a 400-bed university hospital.

PATIENTS

Random cases series in 2 periods separated by 6 months.

INTERVENTIONS

We developed a checklist with 24 selected indicators that were randomly applied to 50 patients. Verification was conducted by a professional not related to care (prompter). We analyzed the results and compliance index and carried out corrective measures with training. With 6 months of preparation, we again applied the random checklist to 50 patients (post-intervention period) and compared the compliance indexes between the two timepoints.

RESULTS

There were no differences in demographic characteristics or evolution between the periods. The compliance index at baseline was 0.86±0.12 versus 0.91±0.52 in the post-intervention period (P=.023). An acceptable compliance index was obtained with the 24 indicators, though at baseline the compliance index was<0.85 for 5 recommendations. These detected non-compliances were worked upon through training in the second phase of the study. The post-intervention checklist evidenced improvement in compliance with the recommendations.

CONCLUSIONS

The checklist used to assess compliance with a selection of recommendations of the SEMICYUC applied and moderated by a prompter was seen to be a useful instrument allowing us to identify points for improvement in the management of Intensive Care Unit patients, increasing the quality and safety of care.

Process Driven Guidance for Complex Surgical Procedures

Surgical team processes are known to be complex and error prone. This paper describes an approach that uses a detailed, validated model of a medical process to provide the clinicians who carry out that complex process with offline and online guidance to help reduce errors. Offline guidance is in the form of a hypertext document describing all the ways the process can be carried out. Online guidance is in the form of a context-sensitive and continually updated electronic "checklist" that lists next steps and needed resources, as well as completed steps. In earlier work, we focused on providing such guidance for single-clinician or single-team processes. This paper describes guiding the collaboration of multiple teams of clinicians through complex processes with significant concurrency, complicated exception handling, and precise and timely communication. We illustrate this approach by applying it to a highly complex, high risk subprocess of cardiac surgery.

Toward Improving Surgical Outcomes by Incorporating Cognitive Load Measurement into Process-Driven Guidance

This paper summarizes the accomplishments and recent directions of our medical safety project. Our process-based approach uses a detailed, rigorously-defined, and carefully validated process model to provide a dynamically updated, context-aware and thus, "Smart" Checklist to help process performers understand and manage their pending tasks [7]. This paper focuses on support for teams of performers, working independently as well as in close collaboration, in stressful situations that are life critical. Our recent work has three main thrusts: provide effective real-time guidance for closely collaborating teams; develop and evaluate techniques for measuring cognitive load based on biometric observations and human surveys; and, using these measurements plus analysis and discrete event process simulation, predict cognitive load throughout the process model and propose process modifications to help performers better manage high cognitive load situations. This project is a collaboration among software engineers, surgical team members, human factors researchers, and medical equipment instrumentation experts. Experimental prototype capabilities are being built and evaluated based upon process models of two cardiovascular surgery processes, Aortic Valve Replacement (AVR) and Coronary Artery Bypass Grafting (CABG). In this paper we describe our approach for each of the three research thrusts by illustrating our work for heparinization, a common subprocess of both AVR and CABG. Heparinization is a high-risk error-prone procedure that involves complex team interactions and thus highlights the importance of this work for improving patient outcomes.