Measuring content overlap during handoff communication using distributional semantics: An exploratory study.

OBJECTIVE: We develop and evaluate a methodological approach to measure the degree and nature of overlap in handoff communication content within and across clinical professions. This extensible, exploratory approach relies on combining techniques from conversational analysis and distributional semantics. MATERIALS AND METHODS: We audio-recorded handoff communication of residents and nurses on the General Medicine floor of a large academic hospital (n=120 resident and n=120 nurse handoffs). We measured semantic similarity, a proxy for content overlap, between resident-resident and nurse-nurse communication using multiple steps: a qualitative conversational content analysis; an automated semantic similarity analysis using Reflective Random Indexing (RRI); and comparing semantic similarity generated by RRI analysis with human ratings of semantic similarity. RESULTS: There was significant association between the semantic similarity as computed by the RRI method and human rating (ρ=0.88). Based on the semantic similarity scores, content overlap was relatively higher for content related to patient active problems, assessment of active problems, patient-identifying information, past medical history, and medications/treatments. In contrast, content overlap was limited on content related to allergies, family-related information, code status, and anticipatory guidance. CONCLUSIONS: Our approach using RRI analysis provides new opportunities for characterizing the nature and degree of overlap in handoff communication. Although exploratory, this method provides a basis for identifying content that can be used for determining shared understanding across clinical professions. Additionally, this approach can inform the development of flexibly standardized handoff tools that reflect clinical content that are most appropriate for fostering shared understanding during transitions of care.

Methodological framework for evaluating clinical processes: A cognitive informatics perspective.

We propose a methodological framework for evaluating clinical cognitive activities in complex real-world environments that provides a guiding framework for characterizing the patterns of activities. This approach, which we refer to as a process-based approach, is particularly relevant to cognitive informatics (CI) research-an interdisciplinary domain utilizing cognitive approaches in the study of computing systems and applications-as it provides new ways for understanding human information processing, interactions, and behaviors. Using this approach involves the identification of a process of interest (e.g., a clinical workflow), and the contributing sequences of activities in that process (e.g., medication ordering). A variety of analytical approaches can then be used to characterize the inherent dependencies and relations within the contributing activities within the considered process. Using examples drawn from our own research and the extant research literature, we describe the theoretical foundations of the process-based approach, relevant practical and pragmatic considerations for using such an approach, and a generic framework for applying this approach for evaluation studies in clinical settings. We also discuss the potential for this approach in future evaluations of interactive clinical systems, given the need for new approaches for evaluation, and significant opportunities for automated, unobtrusive data collection.

Cognitive informatics in biomedicine and healthcare.

Cognitive Informatics (CI) is a burgeoning interdisciplinary domain comprising of the cognitive and information sciences that focuses on human information processing, mechanisms and processes within the context of computing and computer applications. Based on a review of articles published in the Journal of Biomedical Informatics (JBI) between January 2001 and March 2014, we identified 57 articles that focused on topics related to cognitive informatics. We found that while the acceptance of CI into the mainstream informatics research literature is relatively recent, its impact has been significant - from characterizing the limits of clinician problem-solving and reasoning behavior, to describing coordination and communication patterns of distributed clinical teams, to developing sustainable and cognitively-plausible interventions for supporting clinician activities. Additionally, we found that most research contributions fell under the topics of decision-making, usability and distributed team activities with a focus on studying behavioral and cognitive aspects of clinical personnel, as they performed their activities or interacted with health information systems. We summarize our findings within the context of the current areas of CI research, future research directions and current and future challenges for CI researchers.

Bridging gaps in handoffs: a continuity of care based approach.

Handoff among healthcare providers has been recognized as a major source of medical errors. Most prior research has often focused on the communication aspects of handoff, with limited emphasis on the overall handoff process, especially from a clinician workflow perspective. Such a workflow perspective that is based on the continuity of care model provides a framework required to identify and support an interconnected trajectory of care events affecting handoff communication. To this end, we propose a new methodology, referred to as the clinician-centered approach that allows us to investigate and represent the entire clinician workflow prior to, during and, after handoff communication. This representation of clinician activities supports a comprehensive analysis of the interdependencies in the handoff process across the care continuum, as opposed to a single discrete, information sharing activity. The clinician-centered approach is supported by multifaceted methods for data collection such as observations, shadowing of clinicians, audio recording of handoff communication, semi-structured interviews and artifact identification and collection. The analysis followed a two-stage mixed inductive-deductive method. The iterative development of clinician-centered approach was realized using a multi-faceted study conducted in the Medical Intensive Care Unit (MICU) of an academic hospital. Using the clinician-centered approach, we (a) identify the nature, inherent characteristics and the interdependencies between three phases of the handoff process and (b) develop a descriptive framework of handoff communication in critical care that captures the non-linear, recursive and interactive nature of collaboration and decision-making. The results reported in this paper serve as a "proof of concept" of our approach, emphasizing the importance of capturing a coordinated and uninterrupted succession of clinician information management and transfer activities in relation to patient care events.

Effect of acute postsurgical pain trajectories on 30-day and 1-year pain.

Untreated pain after surgery leads to poor patient satisfaction, longer hospital length of stay, lower health-related quality of life, and non-compliance with rehabilitation regimens. The aim of this study is to characterize the structure of acute pain trajectories during the postsurgical hospitalization period and quantify their association with pain at 30-days and 1-year after surgery. This cohort study included 2106 adult (≥18 years) surgical patients who consented to participate in the SATISFY-SOS registry (February 1, 2015 to September 30, 2017). Patients were excluded if they did not undergo invasive surgeries, were classified as outpatients, failed to complete follow up assessments at 30-days and 1-year following surgery, had greater than 4-days of inpatient stay, and/or recorded fewer than four pain scores during their acute hospitalization period. The primary exposure was the acute postsurgical pain trajectories identified by a machine learning-based latent class approach using patient-reported pain scores. Clinically meaningful pain (≥3 on a 0-10 scale) at 30-days and 1-year after surgery were the primary and secondary outcomes, respectively. Of the study participants (N = 2106), 59% were female, 91% were non-Hispanic White, and the mean (SD) age was 62 (13) years; 41% of patients underwent orthopedic surgery and 88% received general anesthesia. Four acute pain trajectory clusters were identified. Pain trajectories were significantly associated with clinically meaningful pain at 30-days (p = 0.007), but not at 1-year (p = 0.79) after surgery using covariate-adjusted logistic regression models. Compared to Cluster 1, the other clusters had lower statistically significant odds of having pain at 30-days after surgery (Cluster 2: [OR = 0.67, 95%CI (0.51-0.89)]; Cluster 3:[OR = 0.74, 95%CI (0.56-0.99)]; Cluster 4:[OR = 0.46, 95%CI (0.26-0.82)], all p<0.05). Patients in Cluster 1 had the highest cumulative likelihood of pain and pain intensity during the latter half of their acute hospitalization period (48-96 hours), potentially contributing to the higher odds of pain during the 30-day postsurgical period. Early identification and management of high-risk pain trajectories can help in ascertaining appropriate pain management interventions. Such interventions can mitigate the occurrence of long-term disabilities associated with pain.

Considering complexity in healthcare systems.

A recent trend in the literature has been to characterize healthcare activities in terms of complex systems theory. Complexity has often been loosely and variously defined, with meanings ranging from "not simple" to "complicated" to "intractable." In this paper, we consider various aspects of complexity and how they relate to modern healthcare practice, with the aim of developing research approaches for studying complex healthcare environments. We propose a theoretical lens for understanding and studying complexity in healthcare systems based on degrees of interrelatedness of system components. We also describe, with relevant caveats, how complex healthcare systems are generally decomposable, rendering them more tractable for further study. The ideas of interrelatedness among the components of a system as a measure of complexity and functional decomposition as a mechanism for studying meaningful subcomponents of a complex system can be used as a framework for understanding complex healthcare systems. Using examples drawn from current literature and our own research, we explain the feasibility of this approach for understanding, studying, and managing complex healthcare systems.

Transmission dynamics: Data sharing in the COVID-19 era.

Problem: The current coronavirus disease 2019 (COVID-19) pandemic underscores the need for building and sustaining public health data infrastructure to support a rapid local, regional, national, and international response. Despite a historical context of public health crises, data sharing agreements and transactional standards do not uniformly exist between institutions which hamper a foundational infrastructure to meet data sharing and integration needs for the advancement of public health. Approach: There is a growing need to apply population health knowledge with technological solutions to data transfer, integration, and reasoning, to improve health in a broader learning health system ecosystem. To achieve this, data must be combined from healthcare provider organizations, public health departments, and other settings. Public health entities are in a unique position to consume these data, however, most do not yet have the infrastructure required to integrate data sources and apply computable knowledge to combat this pandemic. Outcomes: Herein, we describe lessons learned and a framework to address these needs, which focus on: (a) identifying and filling technology "gaps"; (b) pursuing collaborative design of data sharing requirements and transmission mechanisms; (c) facilitating cross-domain discussions involving legal and research compliance; and (d) establishing or participating in multi-institutional convening or coordinating activities. Next steps: While by no means a comprehensive evaluation of such issues, we envision that many of our experiences are universal. We hope those elucidated can serve as the catalyst for a robust community-wide dialogue on what steps can and should be taken to ensure that our regional and national health care systems can truly learn, in a rapid manner, so as to respond to this and future emergent public health crises.

Physician Workflow in Two Distinctive Emergency Departments: An Observational Study.

OBJECTIVES: We characterize physician workflow in two distinctive emergency departments (ED). Physician practices mediated by electronic health records (EHR) are explored within the context of organizational complexity for the delivery of care. METHODS: Two urban clinical sites, including an academic teaching ED, were selected. Fourteen physicians were recruited. Overall, 62 hours of direct clinical observations were conducted characterizing clinical activities (EHR use, team communication, and patient care). Data were analyzed using qualitative open-coding techniques and descriptive statistics. Timeline belts were used to represent temporal events. RESULTS: At site 1, physicians, engaged in more team communication, followed by direct patient care. Although physicians spent 61% of their clinical time at workstations, only 25% was spent on the EHR, primarily for clinical documentation and review. Site 2 physicians engaged primarily in direct patient care spending 52% of their time at a workstation, and 31% dedicated to EHRs, focused on chart review. At site 1, physicians showed nonlinear complex workflow patterns with a greater frequency of multitasking and interruptions, resulting in workflow fragmentation. In comparison, at site 2, a less complex environment with a unique patient assignment system, resulting in a more linear workflow pattern. CONCLUSION: The nature of the clinical practice and EHR-mediated workflow reflects the ED work practices. Physicians in more complex organizations may be less efficient because of the fragmented workflow. However, these effects can be mitigated by effort distribution through team communication, which affords inherent safety checks.

Exposure to COVID-19 patients increases physician trainee stress and burnout.

The coronavirus disease 2019 (COVID-19) pandemic has put considerable physical and emotional strain on frontline healthcare workers. Among frontline healthcare workers, physician trainees represent a unique group-functioning simultaneously as both learners and caregivers and experiencing considerable challenges during the pandemic. However, we have a limited understanding regarding the emotional effects and vulnerability experienced by trainees during the pandemic. We investigated the effects of trainee exposure to patients being tested for COVID-19 on their depression, anxiety, stress, burnout and professional fulfillment. All physician trainees at an academic medical center (n = 1375) were invited to participate in an online survey. We compared the measures of depression, anxiety, stress, burnout and professional fulfillment among trainees who were exposed to patients being tested for COVID-19 and those that were not, using univariable and multivariable models. We also evaluated perceived life stressors such as childcare, home schooling, personal finances and work-family balance among both groups. 393 trainees completed the survey (29% response rate). Compared to the non-exposed group, the exposed group had a higher prevalence of stress (29.4% vs. 18.9%), and burnout (46.3% vs. 33.7%). The exposed group also experienced moderate to extremely high perceived stress regarding childcare and had a lower work-family balance. Multivariable models indicated that trainees who were exposed to COVID-19 patients reported significantly higher stress (10.96 [95% CI, 9.65 to 12.46] vs 8.44 [95% CI, 7.3 to 9.76]; P = 0.043) and were more likely to be burned out (1.31 [95% CI, 1.21 to1.41] vs 1.07 [95% CI, 0.96 to 1.19]; P = 0.002]. We also found that female trainees were more likely to be stressed (P = 0.043); while unmarried trainees were more likely to be depressed (P = 0.009), and marginally more likely to have anxiety (P = 0.051). To address these challenges, wellness programs should focus on sustaining current programs, develop new and targeted mental health resources that are widely accessible and devise strategies for creating awareness regarding these resources.

When past is not a prologue: Adapting informatics practice during a pandemic.

Data and information technology are key to every aspect of our response to the current coronavirus disease 2019 (COVID-19) pandemic-including the diagnosis of patients and delivery of care, the development of predictive models of disease spread, and the management of personnel and equipment. The increasing engagement of informaticians at the forefront of these efforts has been a fundamental shift, from an academic to an operational role. However, the past history of informatics as a scientific domain and an area of applied practice provides little guidance or prologue for the incredible challenges that we are now tasked with performing. Building on our recent experiences, we present 4 critical lessons learned that have helped shape our scalable, data-driven response to COVID-19. We describe each of these lessons within the context of specific solutions and strategies we applied in addressing the challenges that we faced.

Protocol for the Effectiveness of an Anesthesiology Control Tower System in Improving Perioperative Quality Metrics and Clinical Outcomes: the TECTONICS randomized, pragmatic trial.

Introduction: Perioperative morbidity is a public health priority, and surgical volume is increasing rapidly. With advances in technology, there is an opportunity to research the utility of a telemedicine-based control center for anesthesia clinicians that assess risk, diagnoses negative patient trajectories, and implements evidence-based practices. Objectives: The primary objective of this trial is to determine whether an anesthesiology control tower (ACT) prevents clinically relevant adverse postoperative outcomes including 30-day mortality, delirium, respiratory failure, and acute kidney injury. Secondary objectives are to determine whether the ACT improves perioperative quality of care metrics including management of temperature, mean arterial pressure, mean airway pressure with mechanical ventilation, blood glucose, anesthetic concentration, antibiotic redosing, and efficient fresh gas flow. Methods and analysis: We are conducting a single center, randomized, controlled, phase 3 pragmatic clinical trial. A total of 58 operating rooms are randomized daily to receive support from the ACT or not. All adults (eighteen years and older) undergoing surgical procedures in these operating rooms are included and followed until 30 days after their surgery. Clinicians in operating rooms randomized to ACT support receive decision support from clinicians in the ACT. In operating rooms randomized to no intervention, the current standard of anesthesia care is delivered. The intention-to-treat principle will be followed for all analyses. Differences between groups will be presented with 99% confidence intervals; p-values <0.005 will be reported as providing compelling evidence, and p-values between 0.05 and 0.005 will be reported as providing suggestive evidence. Registration: TECTONICS is registered on ClinicalTrials.gov, NCT03923699; registered on 23 April 2019.

Efficiency of Emergency Physicians: Insights from an Observational Study using EHR Log Files.

OBJECTIVE: With federal mandates and incentives since the turn of this decade, electronic health records (EHR) have been widely adopted and used for clinical care. Over the last several years, we have seen both positive and negative perspectives on its use. Using an analysis of log files of EHR use, we investigated the nature of EHR use and their effect on an emergency department's (ED) throughput and efficiency. METHODS: EHR logs of time spent by attending physicians on EHR-based activities over a 6-week period (n = 2,304 patients) were collected. For each patient encounter, physician activities in the EHR were categorized into four activities: documentation, review, orders, and navigation. Four ED-based performance metrics were also captured: door-to-provider time, door-to-doctor time, door-to-disposition time, and length of stay (LOS). Association between the four EHR-based activities and corresponding ED performance metrics were evaluated. RESULTS: We found positive correlations between physician review of patient charts, and door-to-disposition time (r = 0.43, p < 0.05), and with LOS (r = 0.48, p < 0.05). There were no statistically significant associations between any of the other performance metrics and EHR activities. CONCLUSION: The results highlight that longer time spent on reviewing information on the EHR is potentially associated with decreased ED throughput efficiency. Balancing these competing goals is often a challenge of physicians, and its implications for patient safety is discussed.

Comparative assessment of content overlap between written documentation and verbal communication: an observational study of resident sign-outs.

OBJECTIVE: Effective sign-outs involve verbal communication supported by written or electronic documentation. We investigated the clinical content overlap between sign-out documentation and face-to-face verbal sign-out communication. METHODS: We audio-recorded resident verbal sign-out communication and collected electronically completed ("written") sign-out documentation on 44 sign-outs in a General Medicine service. A content analysis framework with nine sign-out elements was used to qualitatively code both written and verbal sign-out content. A content overlap framework based on the comparative analysis between written and verbal sign-out content characterized how much written content was verbally communicated. Using this framework, we computed the full, partial, and no overlap between written and verbal content. RESULTS: We found high a high degree of full overlap on patient identifying information [name (present in 100% of sign-outs), age (96%), and gender (87%)], past medical history [hematology (100%), renal (100%), cardiology (79%), and GI (67%)], and tasks to-do (97%); lesser degree of overlap for active problems (46%), anticipatory guidance (46%), medications/treatments (15%), pending labs/studies/procedures (7%); and no overlap for code status (<1%), allergies (0%) and medical record number (0%). DISCUSSION AND CONCLUSION: Three core functions of sign-outs are transfer of information, responsibility, and accountability. The overlap-highlighting what written content was communicated-characterizes how these functions manifest during sign-outs. Transfer of information varied with patient identifying information being explicitly communicated and remaining content being inconsistently communicated. Transfer of responsibility was explicit, with all pending and future tasks being communicated. Transfer of accountability was limited, with limited discussion of written contingency plans.

Reasons for computerised provider order entry (CPOE)-based inpatient medication ordering errors: an observational study of voided orders.

OBJECTIVE: Medication voiding is a computerised provider order entry (CPOE)-based discontinuation mechanism that allows clinicians to identify erroneous medication orders. We investigated the accuracy of voiding as an indicator of clinician identification and interception of a medication ordering error, and investigated reasons and root contributors for medication ordering errors. METHOD: Using voided orders identified with a void alert, we conducted interviews with ordering and voiding clinicians, followed by patient chart reviews. A structured coding framework was used to qualitatively analyse the reasons for medication ordering errors. We also compared clinician-CPOE-selected (at time of voiding), clinician-reported (interview) and chart review-based reasons for voiding. RESULTS: We conducted follow-up interviews on 101 voided orders. The positive predictive value (PPV) of voided orders that were medication ordering errors was 93.1% (95% CI 88.1% to 98.1%, n=94). Using chart review-based reasons as the gold standard, we found that clinician-CPOE-selected reasons were less reflective (PPV=70.2%, 95% CI 61.0% to 79.4%) than clinician-reported (interview) (PPV=86.1%, 95%CI 78.2% to 94.1%) reasons for medication ordering errors. Duplicate (n=44) and improperly composed (n=41) ordering errors were common, often caused by predefined order sets and data entry issues. A striking finding was the use of intentional violations as a mechanism to notify and seek ordering assistance from pharmacy service. Nearly half of the medication ordering errors were voided by pharmacists. DISCUSSION: We demonstrated that voided orders effectively captured medication ordering errors. The mismatch between clinician-CPOE-selected and the chart review-based reasons for error emphasises the need for developing standardised operational descriptions for medication ordering errors. Such standardisation can help in accurately identifying, tracking, managing and sharing erroneous orders and their root contributors between healthcare institutions, and with patient safety organisations.

Effect of number of open charts on intercepted wrong-patient medication orders in an emergency department.

To reduce the risk of wrong-patient errors, safety experts recommend allowing only one patient chart to be open at a time. Due to the lack of empirical evidence, the number of allowable open charts is often based on anecdotal evidence or institutional preference, and hence varies across institutions. Using an interrupted time series analysis of intercepted wrong-patient medication orders in an emergency department during 2010-2016 (83.6 intercepted wrong-patient events per 100 000 orders), we found no significant decrease in the number of intercepted wrong-patient medication orders during the transition from a maximum of 4 open charts to a maximum of 2 (b = -0.19, P = .33) and no significant increase during the transition from a maximum of 2 open charts to a maximum of 4 (b = 0.08, P = .67). These results have implications regarding decisions about allowable open charts in the emergency department in relation to the impact on workflow and efficiency.

Emergency Physicians' Perceived Influence of EHR Use on Clinical Workflow and Performance Metrics.

OBJECTIVE: Over the last decade, electronic health records (EHRs) have shaped clinical practice. In this article, we investigated the perceived effects of EHR use on clinical workflow and meaningful use (MU) performance metrics. MATERIALS AND METHODS: Semistructured interviews were conducted with 20 (n = 20) physicians at two urban emergency departments. Interview questions focused on time spent on EHR use, changes in clinical practices with EHR use, and the effect of MU performance metrics on clinical workflow. Qualitative coding using grounded theory and descriptive analyses were performed to provide descriptive insights. RESULTS: Physicians reported that EHRs improved their clinical workflow, especially on MU-related activities including door-to-doctor time and admit decision time. EHR use also affected physicians work efficiency, quality of care provided, and overall patient safety. CONCLUSION: Physicians' perception of EHRs is likely to influence their practices. With negative perceptions of EHR usability problems, positive aspects of EHR use, including the influence on MU performance metrics, may be overridden.

Learning optimal opioid prescribing and monitoring: a simulation study of medical residents.

OBJECTIVE: Hospitalized patients often receive opioids. There is a lack of consensus regarding evidence-based guidelines or training programs for effective management of pain in the hospital. We investigated the viability of using an Internet-based opioid dosing simulator to teach residents appropriate use of opioids to treat and manage acute pain. MATERIALS AND METHODS: We used a prospective, longitudinal design to evaluate the effects of simulator training. In face-to-face didactic sessions, we taught 120 (108 internal medicine and 12 family medicine) residents principles of pain management and how to use the simulator. Each trainee completed 10 training and, subsequently, 5 testing trials on the simulator. For each trial, we collected medications, doses, routes and times of administration, pain scores, and a summary score. We used mixed-effects regression models to assess the impact of simulation training on simulation performance scores, variability in pain score trajectories, appropriate use of short- and long-acting opioids, and use of naloxone. RESULTS: Trainees completed 1582 simulation trials (M = 13.2, SD = 6.8), with sustained improvements in their simulated pain management practices. Over time, trainees improved their overall simulated pain management scores (b = 0.05, P < .01), generated lower pain score trajectories with less variability (b = -0.02, P < .01), switched more rapidly from short-acting to long-acting agents (b = -0.50, P < .01), and used naloxone less often (b = -0.10, P < .01). DISCUSSION AND CONCLUSIONS: Trainees translated their understanding of didactically presented principles of pain management to their performance on simulated patient cases. Simulation-based training presents an opportunity for improving opioid-based inpatient acute pain management.

Learning from errors: analysis of medication order voiding in CPOE systems.

OBJECTIVE: Medication order voiding allows clinicians to indicate that an existing order was placed in error. We explored whether the order voiding function could be used to record and study medication ordering errors. MATERIALS AND METHODS: We examined medication orders from an academic medical center for a 6-year period (2006-2011; n = 5 804 150). We categorized orders based on status (void, not void) and clinician-provided reasons for voiding. We used multivariable logistic regression to investigate the association between order voiding and clinician, patient, and order characteristics. We conducted chart reviews on a random sample of voided orders ( n = 198) to investigate the rate of medication ordering errors among voided orders, and the accuracy of clinician-provided reasons for voiding. RESULTS: We found that 0.49% of all orders were voided. Order voiding was associated with clinician type (physician, pharmacist, nurse, student, other) and order type (inpatient, prescription, home medications by history). An estimated 70 ± 10% of voided orders were due to medication ordering errors. Clinician-provided reasons for voiding were reasonably predictive of the actual cause of error for duplicate orders (72%), but not for other reasons. DISCUSSION AND CONCLUSION: Medication safety initiatives require availability of error data to create repositories for learning and training. The voiding function is available in several electronic health record systems, so order voiding could provide a low-effort mechanism for self-reporting of medication ordering errors. Additional clinician training could help increase the quality of such reporting.

Impact of Structured Rounding Tools on Time Allocation During Multidisciplinary Rounds: An Observational Study.

BACKGROUND: Recent research has shown evidence of disproportionate time allocation for patient communication during multidisciplinary rounds (MDRs). Studies have shown that patients discussed later during rounds receive lesser time. OBJECTIVE: The aim of our study was to investigate whether disproportionate time allocation effects persist with the use of structured rounding tools. METHODS: Using audio recordings of rounds (N=82 patients), we compared time allocation and communication breakdowns between a problem-based Subjective, Objective, Assessment, and Plan (SOAP) and a system-based Handoff Intervention Tool (HAND-IT) rounding tools. RESULTS: We found no significant linear dependence of the order of patient presentation on the time spent or on communication breakdowns for both structured tools. However, for the problem-based tool, there was a significant linear relationship between the time spent on discussing a patient and the number of communication breakdowns (P<.05)--with an average of 1.04 additional breakdowns with every 120 seconds in discussion. CONCLUSIONS: The use of structured rounding tools potentially mitigates disproportionate time allocation and communication breakdowns during rounds, with the more structured HAND-IT, almost completely eliminating such effects. These results have potential implications for planning, prioritization, and training for time management during MDRs.