Mapping the process of ICU care delivery to improve treatment decisions in acute respiratory failure.

Evidence suggests system-level norms and care processes influence individual patients' medical decisions, including end-of-life decisions for patients with critical illnesses like acute respiratory failure. Yet, little is known about how these processes unfold over the course of a patient's critical illness in the intensive care unit (ICU). Our objective was to map current-state ICU care delivery processes for patients with acute respiratory failure and to identify opportunities to improve the process. We conducted a process mapping study at two academic medical centers, using focus groups and semi-structured interviews. The 70 participants represented 17 distinct roles in ICU care, including interprofessional medical ICU and palliative care clinicians, surrogate decision makers, and patient survivors. Participants refined and endorsed a process map of current-state care delivery for all patients admitted to the ICU with acute respiratory failure requiring mechanical ventilation. The process contains four critical periods for active deliberation about the use of life-sustaining treatments. However, active deliberation steps are inconsistently performed and frequently disrupted, leading to prolongation of life-sustaining treatment by default, without consideration of patients' individual goals and priorities. Interventions to standardize active deliberation in the ICU may improve treatment decisions for ICU patients with acute respiratory failure.

Academic Detailing as a Health Information Technology Implementation Method: Supporting the Design and Implementation of an Emergency Department-Based Clinical Decision Support Tool to Prevent Future Falls.

BACKGROUND: Clinical decision support (CDS) tools that incorporate machine learning-derived content have the potential to transform clinical care by augmenting clinicians' expertise. To realize this potential, such tools must be designed to fit the dynamic work systems of the clinicians who use them. We propose the use of academic detailing-personal visits to clinicians by an expert in a specific health IT tool-as a method for both ensuring the correct understanding of that tool and its evidence base and identifying factors influencing the tool's implementation. OBJECTIVE: This study aimed to assess academic detailing as a method for simultaneously ensuring the correct understanding of an emergency department-based CDS tool to prevent future falls and identifying factors impacting clinicians' use of the tool through an analysis of the resultant qualitative data. METHODS: Previously, our team designed a CDS tool to identify patients aged 65 years and older who are at the highest risk of future falls and prompt an interruptive alert to clinicians, suggesting the patient be referred to a mobility and falls clinic for an evidence-based preventative intervention. We conducted 10-minute academic detailing interviews (n=16) with resident emergency medicine physicians and advanced practice providers who had encountered our CDS tool in practice. We conducted an inductive, team-based content analysis to identify factors that influenced clinicians' use of the CDS tool. RESULTS: The following categories of factors that impacted clinicians' use of the CDS were identified: (1) aspects of the CDS tool's design (2) clinicians' understanding (or misunderstanding) of the CDS or referral process, (3) the busy nature of the emergency department environment, (4) clinicians' perceptions of the patient and their associated fall risk, and (5) the opacity of the referral process. Additionally, clinician education was done to address any misconceptions about the CDS tool or referral process, for example, demonstrating how simple it is to place a referral via the CDS and clarifying which clinic the referral goes to. CONCLUSIONS: Our study demonstrates the use of academic detailing for supporting the implementation of health information technologies, allowing us to identify factors that impacted clinicians' use of the CDS while concurrently educating clinicians to ensure the correct understanding of the CDS tool and intervention. Thus, academic detailing can inform both real-time adjustments of a tool's implementation, for example, refinement of the language used to introduce the tool, and larger scale redesign of the CDS tool to better fit the dynamic work environment of clinicians.

Understanding clinical implementation coordinators' experiences in deploying evidence-based interventions.

PURPOSE: The fluoroquinolone restriction for the prevention of Clostridioides difficile infection (FIRST) trial is a multisite clinical study in which sites carry out a preauthorization process via electronic health record-based best-practice alert (BPA) to optimize the use of fluoroquinolone antibiotics in acute care settings. Our research team worked closely with clinical implementation coordinators to facilitate the dissemination and implementation of this evidence-based intervention. Clinical implementation coordinators within the antibiotic stewardship team (AST) played a pivotal role in the implementation process; however, considerable research is needed to further understand their role. In this study, we aimed to (1) describe the roles and responsibilities of clinical implementation coordinators within ASTs and (2) identify facilitators and barriers coordinators experienced within the implementation process. METHODS: We conducted a directed content analysis of semistructured interviews, implementation diaries, and check-in meetings utilizing the conceptual framework of middle managers' roles in innovation implementation in healthcare from Urquhart et al. RESULTS: Clinical implementation coordinators performed a variety of roles vital to the implementation's success, including gathering and compiling information for BPA design, preparing staff, organizing meetings, connecting relevant stakeholders, evaluating clinical efficacy, and participating in the innovation as clinicians. Coordinators identified organizational staffing models and COVID-19 interruptions as the main barriers. Facilitators included AST empowerment, positive relationships with staff and oversight/governance committees, and using diverse implementation strategies. CONCLUSION: When implementing healthcare innovations, clinical implementation coordinators facilitated the implementation process through their roles and responsibilities and acted as strategic partners in improving the adoption and sustainability of a fluoroquinolone preauthorization protocol.

Dashboarding to Monitor Machine-Learning-Based Clinical Decision Support Interventions.

BACKGROUND: Existing monitoring of machine-learning-based clinical decision support (ML-CDS) is focused predominantly on the ML outputs and accuracy thereof. Improving patient care requires not only accurate algorithms but also systems of care that enable the output of these algorithms to drive specific actions by care teams, necessitating expanding their monitoring. OBJECTIVES: In this case report, we describe the creation of a dashboard that allows the intervention development team and operational stakeholders to govern and identify potential issues that may require corrective action by bridging the monitoring gap between model outputs and patient outcomes. METHODS: We used an iterative development process to build a dashboard to monitor the performance of our intervention in the broader context of the care system. RESULTS: Our investigation of best practices elsewhere, iterative design, and expert consultation led us to anchor our dashboard on alluvial charts and control charts. Both the development process and the dashboard itself illuminated areas to improve the broader intervention. CONCLUSION: We propose that monitoring ML-CDS algorithms with regular dashboards that allow both a context-level view of the system and a drilled down view of specific components is a critical part of implementing these algorithms to ensure that these tools function appropriately within the broader care system.

Effectiveness of an Emergency Department-Based Machine Learning Clinical Decision Support Tool to Prevent Outpatient Falls Among Older Adults: Protocol for a Quasi-Experimental Study.

BACKGROUND: Emergency department (ED) providers are important collaborators in preventing falls for older adults because they are often the first health care providers to see a patient after a fall and because at-home falls are often preceded by previous ED visits. Previous work has shown that ED referrals to falls interventions can reduce the risk of an at-home fall by 38%. Screening patients at risk for a fall can be time-consuming and difficult to implement in the ED setting. Machine learning (ML) and clinical decision support (CDS) offer the potential of automating the screening process. However, it remains unclear whether automation of screening and referrals can reduce the risk of future falls among older patients. OBJECTIVE: The goal of this paper is to describe a research protocol for evaluating the effectiveness of an automated screening and referral intervention. These findings will inform ongoing discussions about the use of ML and artificial intelligence to augment medical decision-making. METHODS: To assess the effectiveness of our program for patients receiving the falls risk intervention, our primary analysis will be to obtain referral completion rates at 3 different EDs. We will use a quasi-experimental design known as a sharp regression discontinuity with regard to intent-to-treat, since the intervention is administered to patients whose risk score falls above a threshold. A conditional logistic regression model will be built to describe 6-month fall risk at each site as a function of the intervention, patient demographics, and risk score. The odds ratio of a return visit for a fall and the 95% CI will be estimated by comparing those identified as high risk by the ML-based CDS (ML-CDS) and those who were not but had a similar risk profile. RESULTS: The ML-CDS tool under study has been implemented at 2 of the 3 EDs in our study. As of April 2023, a total of 1326 patient encounters have been flagged for providers, and 339 unique patients have been referred to the mobility and falls clinic. To date, 15% (45/339) of patients have scheduled an appointment with the clinic. CONCLUSIONS: This study seeks to quantify the impact of an ML-CDS intervention on patient behavior and outcomes. Our end-to-end data set allows for a more meaningful analysis of patient outcomes than other studies focused on interim outcomes, and our multisite implementation plan will demonstrate applicability to a broad population and the possibility to adapt the intervention to other EDs and achieve similar results. Our statistical methodology, regression discontinuity design, allows for causal inference from observational data and a staggered implementation strategy allows for the identification of secular trends that could affect causal associations and allow mitigation as necessary. TRIAL REGISTRATION: ClinicalTrials.gov NCT05810064; https://www.clinicaltrials.gov/study/NCT05810064. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/48128.

Impact of Interprofessional Teamwork on Aligning Intensive Care Unit Care with Patient Goals: A Qualitative Study of Transactive Memory Systems.

Rationale: Although aligning care with patient goals is fundamental to critical care, this process is often delayed and leads to conflict among patients, families, and intensive care unit (ICU) teams. Interprofessional collaboration within ICU teams is an opportunity to improve goal-aligned care, yet this collaboration is poorly understood. A better understanding of how ICU team members work together to provide goal-aligned care may identify new strategies for improvement. Objectives: Transactive memory systems is a theory of group mind that explains how high-performing teams use a shared memory and collective cognition. We applied this theory to characterize the process of interprofessional collaboration within ICU teams and its relationship with goal-aligned care. Methods: We conducted a secondary analysis of focus group (n = 10) and semistructured interview (n = 8) transcripts, gathered during a parent study at two academic medical centers on the process of ICU care delivery in acute respiratory failure. Participants (N = 70) included interprofessional ICU and palliative care team members, surrogates, and patient survivors. We used directed content analysis, applying transactive memory systems theory and its major components (specialization, coordination, credibility) to examine ICU team collaboration. Results: Participants described each ICU profession as having a specialized role in aligning care with patient goals. Different professions have different opportunities to gather knowledge about patient goals and priorities, which results in dispersion of this knowledge among different team members. To share and use this dispersed knowledge, ICU teams rely on an informal coordination process and "side conversations." This process is a workaround for formal channels (e.g., health records, interprofessional rounds) that do not adequately convey knowledge about patient goals. This informal process does not occur if team members are discouraged from asserting their knowledge because of hierarchy or lack of psychological safety. Conversely, coordination succeeds when team members recognize each other as credible sources of valued knowledge. Conclusions: We found that ICU team members work together to align care with patient goals and priorities, using transactive memory systems. The successful function of these systems can be disrupted or promoted by ICU organizational and cultural factors, which are potential targets for efforts to increase goal-aligned care.

Post-implementation usability evaluation of a human factors-based clinical decision support for pulmonary embolism (PE) diagnosis (Dx): PE Dx Study Part 1.

While there is promise for health IT, such as Clinical Decision Support (CDS), to improve patient safety and clinician efficiency, poor usability has hindered widespread use of these tools. Human Factors (HF) principles and methods remain the gold standard for health IT design; however, there is limited information on how HF methods and principles influence CDS usability "in the wild". In this study, we explore the usability of an HF-based CDS used in the clinical environment; the CDS was designed according to a human-centered design process, which is described in Carayon et al. (2020). In this study, we interviewed 12 emergency medicine physicians, identifying 294 excerpts of barriers and facilitators of the CDS. Sixty-eight percent of excerpts related to the HF principles applied in the human-centered design of the CDS. The remaining 32% of excerpts related to 18 inductively-created categories, which highlight gaps in the CDS design process. Several barriers were related to the physical environment and organization work system elements as well as physicians' broader workflow in the emergency department (e.g., teamwork). This study expands our understanding of the usability outcomes of HF-based CDS "in the wild". We demonstrate the value of HF principles in the usability of CDS and identify areas for improvement to future human-centered design of CDS. The relationship between these usability outcomes and the HCD process is explored in an accompanying Part 2 manuscript.

Retrospective analysis of the human-centered design process used to develop a clinical decision support in the emergency department: PE Dx Study Part 2.

With the growing implementation and use of health IT such as Clinical Decision Support (CDS), there is increasing attention on the potential negative impact of these technologies on patients (e.g., medication errors) and clinicians (e.g., increased workload, decreased job satisfaction, burnout). Human-Centered Design (HCD) and Human Factors (HF) principles are recommended to improve the usability of health IT and reduce its negative impact on patients and clinicians; however, challenges persist. The objective of this study is to understand how an HCD process influences the usability of health IT. We conducted a systematic retrospective analysis of the HCD process used in the design of a CDS for pulmonary embolism diagnosis in the emergency department (ED). Guided by the usability outcomes (e.g., barriers and facilitators) of the CDS use "in the wild" (see Part 1 of this research in the accompanying manuscript), we performed deductive content analysis of 17 documents (e.g., design session transcripts) produced during the HCD process. We describe if and how the design team considered the barriers and facilitators during the HCD process. We identified 7 design outcomes of the HCD process, for instance designing a workaround and making a design change to the CDS. We identify gaps in the current HCD process and demonstrate the need for a continuous health IT design process.

Usability of a Human Factors-based Clinical Decision Support in the Emergency Department: Lessons Learned for Design and Implementation.

OBJECTIVE: To evaluate the usability and use of human factors (HF)-based clinical decision support (CDS) implemented in the emergency department (ED). BACKGROUND: Clinical decision support can improve patient safety; however, the acceptance and use of CDS has faced challenges. Following a human-centered design process, we designed a CDS to support pulmonary embolism (PE) diagnosis in the ED. We demonstrated high usability of the CDS during scenario-based usability testing. We implemented the HF-based CDS in one ED in December 2018. METHOD: We conducted a survey of ED physicians to evaluate the usability and use of the HF-based CDS. We distributed the survey via Qualtrics, a web-based survey platform. We compared the computer system usability questionnaire scores of the CDS between those collected in the usability testing to use of the CDS in the real environment. We asked physicians about their acceptance and use of the CDS, barriers to using the CDS, and areas for improvement. RESULTS: Forty-seven physicians (56%) completed the survey. Physicians agreed that diagnosing PE is a major problem and risk scores can support the PE diagnostic process. Usability of the CDS was reported as high, both in the experimental setting and the real clinical setting. However, use of the CDS was low. We identified several barriers to the CDS use in the clinical environment, in particular a lack of workflow integration. CONCLUSION: Design of CDS should be a continuous process and focus on the technology's usability in the context of the broad work system and clinician workflow.

Understanding the "Swiss Cheese Model" and Its Application to Patient Safety.

ABSTRACT: This article reviews several key aspects of the Theory of Active and Latent Failures, typically referred to as the Swiss cheese model of human error and accident causation. Although the Swiss cheese model has become well known in most safety circles, there are several aspects of its underlying theory that are often misunderstood. Some authors have dismissed the Swiss cheese model as an oversimplification of how accidents occur, whereas others have attempted to modify the model to make it better equipped to deal with the complexity of human error in health care. This narrative review aims to provide readers with a better understanding and greater appreciation of the Theory of Active and Latent Failures upon which the Swiss cheese model is based. The goal is to help patient safety professionals fully leverage the model and its associated tools when performing a root cause analysis as well as other patient safety activities.

Using flow disruptions to understand healthcare system safety: A systematic review of observational studies.

This systematic review provides information on the methodologies, measurements and classification systems used in observational studies of flow disruptions in clinical environments. The PRISMA methodology was applied and authors searched two databases (PubMed and Web of Science) for studies meeting the following inclusion criteria: (a) were conducted in a healthcare setting, (b) explored systems-factors leading to deviations in care processes, (c) were prospective and observational, (d) classified observations, and (e) were original research studies published in peer-reviewed journals. Thirty studies were analyzed and a variety of methods were identified for observer training, data collection and observation classification. Although primarily applied in surgery, comparable research has been successfully conducted in other venues such as trauma care, and delivery rooms. The findings of this review were synthesized into a framework of considerations for conducting rigorous methodological studies aimed at understanding clinical systems.

Usage of a Web-Based Workplace and Symptom Self-Management Intervention Tool to Improve Work Ability for Breast Cancer Survivors.

This work aimed to evaluate the usage of a web-based intervention (WISE: Work ability Improvement through Symptom and Ergonomic strategies) developed to improve work ability for women recently diagnosed with breast cancer. Twenty-two women undergoing adjuvant treatment for breast cancer were provided access to WISE. This website includes content pages (e.g., information on ergonomics, symptom management, and other work-related resources) and worksheets (e.g., journals to track symptoms or goals). It could be personalized based on individual work activities and symptoms. Measures assessed at 3 months included usage of the website and perceived usefulness. Thirteen of the 22 participants (60%) accessed WISE; 11 personalized their information. Content and worksheet pages had 97 and 79 visits, respectively. Most frequently visited pages were "setting goals" (i.e., prioritize and track symptoms; 45 visits) and "steps to creating your WISE plan" (i.e., incorporate symptom and ergonomic strategies; 16 visits). Median duration time was 11.05 (range 0.35-79.55) minutes. Usefulness of the content and worksheet pages assessed via a 7-point Likert scale (1 = strongly disagree, 7 = strongly agree) was 5.08 (SD = 1.59) and 4.26 (SD = 2.03), respectively. Participants were likely to recommend WISE to other women undergoing cancer treatment (mean = 6.11; SD = 1.05). The majority of participants personalized WISE work and symptom strategies. Overall, participants agreed that WISE content pages were useful and would recommend WISE for other breast cancer survivors. Results support that majority of breast cancer survivors, undergoing treatment with curative intent, accessed a web-based intervention that provided personalized information on workplace and symptom strategies.

Collaborative design and implementation of a clinical decision support system for automated fall-risk identification and referrals in emergency departments.

Of the 3 million older adults seeking fall-related emergency care each year, nearly one-third visited the Emergency Department (ED) in the previous 6 months. ED providers have a great opportunity to refer patients for fall prevention services at these initial visits, but lack feasible tools for identifying those at highest-risk. Existing fall screening tools have been poorly adopted due to ED staff/provider burden and lack of workflow integration. To address this, we developed an automated clinical decision support (CDS) system for identifying and referring older adult ED patients at risk of future falls. We engaged an interdisciplinary design team (ED providers, health services researchers, information technology/predictive analytics professionals, and outpatient Falls Clinic staff) to collaboratively develop a system that successfully met user requirements and integrated seamlessly into existing ED workflows. Our rapid-cycle development and evaluation process employed a novel combination of human-centered design, implementation science, and patient experience strategies, facilitating simultaneous design of the CDS tool and intervention implementation strategies. This included defining system requirements, systematically identifying and resolving usability problems, assessing barriers and facilitators to implementation (e.g., data accessibility, lack of time, high patient volumes, appointment availability) from multiple vantage points, and refining protocols for communicating with referred patients at discharge. ED physician, nurse, and patient stakeholders were also engaged through online surveys and user testing. Successful CDS design and implementation required integration of multiple new technologies and processes into existing workflows, necessitating interdisciplinary collaboration from the onset. By using this iterative approach, we were able to design and implement an intervention meeting all project goals. Processes used in this Clinical-IT-Research partnership can be applied to other use cases involving automated risk-stratification, CDS development, and EHR-facilitated care coordination.

Usability barriers and facilitators of a human factors engineering-based clinical decision support technology for diagnosing pulmonary embolism.

BACKGROUND: Health IT, such as clinical decision support (CDS), has the potential to improve patient safety. However, poor usability of health IT continues to be a major concern. Human factors engineering (HFE) approaches are recommended to improve the usability of health IT. Limited evidence exists on the actual impact of HFE methods and principles on the usability of health IT. OBJECTIVE: To identify and describe the usability barriers and facilitators of an HFE-based CDS prior to implementation in the emergency department (ED). METHODS: We conducted debrief interviews with 32 emergency medicine physicians as a part of a scenario-based simulation study evaluating the usability of the HFE-based CDS. We performed a deductive content analysis of the interviews using the usability criteria of Scapin and Bastien as a framework. RESULTS: We identified 271 occurrences of usability barriers (94) and facilitators (177) of the HFE-based CDS. For instance, we found a facilitator relating to the usability criteria prompting as the PE Dx helps the physician order diagnostic tests following the risk assessment. We found the most facilitators relating to the criteria, minimal actions, e.g. as the PE Dx automatically populates vitals signs (e.g., heart rate) from the chart into the CDS. The majority of the usability barriers related to the usability criteria, compatibility (i.e., workflow integration), which was not explicitly considered in the HFE design of the CDS. For example, the CDS did not support resident and attending physician teamwork in the PE diagnostic process. CONCLUSION: The systematic use of HFE principles in the design of CDS improves the usability of these technologies. In order to further reduce usability barriers, workflow integration should be explicitly considered in the design of health IT.

Workflow integration analysis of a human factors-based clinical decision support in the emergency department.

Numerous challenges with the implementation, acceptance, and use of health IT are related to poor usability and a lack of integration of the technologies into clinical workflow, and have, therefore, limited the potential of these technologies to improve patient safety. We propose a definition and conceptual model of health IT workflow integration. Using interviews of 12 emergency department (ED) physicians, we identify 134 excerpts of barriers and facilitators to workflow integration of a human factors (HF)-based clinical decision support (CDS) implemented in the ED. Using data on these 134 barriers and facilitators, we distinguish 25 components of workflow integration of the CDS, which are described according to four dimensions of workflow integration: time, flow, scope of patient journey, and level. The proposed definition and conceptual model of workflow integration can be used to inform health IT design; this is the purpose of the proposed checklist that can help to ensure consideration of workflow integration during the development of health IT.

Implementing a human factors approach to RCA2 : Tools, processes and strategies.

Root Cause Analysis and Action (RCA2 ) guidelines offer fundamental improvements to traditional RCA. Yet, these guidelines lack robust methods to support a human factors analysis of patient harm events and development of systems-level interventions. We recently integrated a complement of human factors tools into the RCA2 process to address this gap. These tools include the Human Factors Analysis and Classification System (HFACS), the Human Factors Intervention Matrix (HFIX), and a multiple-criterion decision tool called FACES, for selecting effective HFIX solutions. We describe each of these tools and illustrate how they can be integrated into RCA2 to create a robust human factors RCA process called HFACS-RCA2 . We also present qualitative results from an 18-month implementation study within a large academic health center. Results demonstrate how HFACS-RCA2 can foster a more comprehensive, human factors analysis of serious patient harm events and the identification of broader system interventions. Following HFACS-RCA2 implementation, RCA team members (risk managers and quality improvement advisors) also experienced greater satisfaction in their work, leadership gained more trust in RCA findings and recommendations, and the transparency of the RCA process increased. Effective strategies for overcoming implementation barriers, including changes in roles, responsibilities and workload will also be presented.

Results from a prospective longitudinal survey of employment and work outcomes in newly diagnosed cancer patients during and after curative-intent chemotherapy: A Wisconsin Oncology Network study.

BACKGROUND: Postcancer work limitations may affect a substantial proportion of patients and contribute to the "financial toxicity" of cancer treatment. The degree and nature of work limitations and employment outcomes are poorly understood for cancer patients, particularly in the immediate period of transition after active treatment. We prospectively examined employment, work ability, and work limitations during and after treatment. METHODS: A total of 120 patients receiving curative therapy who were employed prior to their cancer diagnosis and who intended to work during or after end of treatment (EOT) completed surveys at baseline (pretreatment), EOT, and 3, 6, and 12 months after EOT. Surveys included measures of employment, work ability, and work limitations. Descriptive statistics (frequencies, percentages, means with standard deviations) were calculated. RESULTS: A total of 111 participants completed the baseline survey. On average, participants were 48 years of age and were mostly white (95%) and female (82%) with a diagnosis of breast cancer (69%). Full-time employment decreased during therapy (from 88% to 50%) and returned to near prediagnosis levels by 12-month follow-up (78%). Work-related productivity loss due to health was high during treatment. CONCLUSIONS: This study is the first to report the effects of curative intent cancer therapy on employment, work ability, and work limitations both during and after treatment. Perceived work ability was generally high overall 12 months after EOT, although a minority reported persistent difficulty. A prospective analysis of factors (eg, job type, education, symptoms) most associated with work limitations is underway to assist in identifying at-risk patients.

Defining team membership in primary care: Qualitative analysis.

Primary healthcare is recognized as a team-based activity. Traditionally, a primary care team is considered to be a group of individuals that work together to satisfy patients' needs for primary care services. Past studies show wide variation in the scope and structure of teams across primary care organizations, indicating ambiguity in the definition of primary care teams. In addition, it remains unclear why certain healthcare professionals are included/excluded from another professional's "team". This study explored the question: "How do healthcare professionals in primary care clinics define who is on their team?" Qualitative content analysis was performed on interview data from clinicians and staff in eight primary care clinics regarding team definitions. All participants acknowledged the importance of working in a team, yet they had very different perspectives on how their teams were defined. Multiple themes emerged including borrowing the expertise of another professional, sharing of patient panel, and policy requirements. This study can inform healthcare professionals and administrators, as well as health IT designers, consultants, architects and researchers interested in primary care teams and how they function in a clinic environment.

Evaluation of Intraoperative Hand-Off Frequency, Duration, and Context: A Mixed Methods Analysis.

BACKGROUND: Hand-offs in the operating room contribute to poor communication, reduced team function, and may be poorly coordinated with other activities. Conversely, they may represent a missed opportunity for improved communication. We sought to better understand the coordination and impact of intraoperative hand-offs. METHODS: We prospectively audio-video (AV) recorded 10 operations and evaluated intraoperative hand-offs. Data collected included percentage of time team members were absent due to breaks, relationships between hand-offs and intraoperative events (incision, surgical counts), and occurrences of simultaneous hand-offs. We also identified announcement that a hand-off had occurred and anchoring, in which team members not involved in the hand-off participated and provided information. RESULTS: Spanning 2919 min of audio-video data, there were 74 hand-offs (range, 4-14 per case) totaling 225.2 min, representing 7.7% of time recorded. Thirty-two (45.1%) hand-offs were interrupted or delayed because of competing activities; eight hand-offs occurred during an instrument or laparotomy pad count. Six cases had simultaneous hand-offs; two cases had two episodes of simultaneous hand-offs. Eight hand-offs included an announcement. Seven included anchoring. Evaluating both temporary and permanent hand-offs, one or more original team members was absent for 40.7% of time recorded and >one team member was absent for 20.5% of time recorded. CONCLUSIONS: Intraoperative hand-offs are frequent and not well coordinated with intraoperative events including counts and other hand-offs. Anchoring and announced hand-offs occurred in a small proportion of cases. Future work must focus on optimizing timing, content, and participation in intraoperative hand-offs.