Effects of a virtual voice-based coach delivering problem-solving treatment on emotional distress and brain function: A pilot RCT in depression and anxiety

Consumer-based voice assistants have the ability to deliver evidence-based treatment, but their therapeutic potential is largely unknown. In a pilot trial of a virtual voice-based coach, Lumen, delivering problem-solving treatment, adults with mild-to-moderate depression and/or anxiety were randomized to the Lumen intervention (n = 42) or waitlist control (n = 21). The main outcomes included changes in neural measures of emotional reactivity and cognitive control, and Hospital Anxiety and Depression Scale [HADS] symptom scores over 16 weeks. Participants were 37.8 years (SD = 12.4), 68% women, 25% Black, 24% Latino, and 11% Asian. Activation of the right dlPFC (neural region of interest in cognitive control) decreased in the intervention group but increased in the control group, with an effect size meeting the prespecified threshold for a meaningful effect (Cohen\u27s d = 0.3). Between-group differences in the change in activation of the left dlPFC and bilateral amygdala were observed, but were of smaller magnitude (d = 0.2). Change in right dlPFC activation was also meaningfully associated (r ≥ 0.4) with changes in self-reported problem-solving ability and avoidance in the intervention. Lumen intervention also led to decreased HADS depression, anxiety, and overall psychological distress scores, with medium effect sizes (Cohen\u27s d = 0.49, 0.51, and 0.55, respectively), compared with the waitlist control group. This pilot trial showed promising effects of a novel digital mental health intervention on cognitive control using neuroimaging and depression and anxiety symptoms, providing foundational evidence for a future confirmatory study

Listening and question-asking behaviors in resident and nurse handoff conversations: A prospective observational study

OBJECTIVE: To characterize interactivity during resident and nurse handoffs by investigating listening and question-asking behaviors during conversations. MATERIALS AND METHODS: Resident (n = 149) and nurse (n = 126) handoffs in an inpatient medicine unit were audio-recorded. Handoffs were coded based on listening behaviors (active and passive), question types (patient status, coordination of care, clinical reasoning, and framing and alignment), and question responses. Comparisons between residents and nurses for listening and question-asking behaviors were performed using the Wilcoxon rank-sum tests. A Poisson regression model was used to investigate differences in the question-asking behaviors between residents and nurses, and the association between listening and question-asking behaviors. RESULTS: There were no significant differences between residents and nurses in their active (18% resident vs 39% nurse handoffs) or passive (88% resident vs 81% nurse handoffs) listening behaviors. Question-asking was common in resident and nurse handoffs (87% vs 98%) and focused primarily on patient status, co-ordination, and framing and alignment. Nurses asked significantly more questions than residents (Mresident = 2.06 and Mnurse = 5.52) by a factor of 1.76 (P \u3c 0.001). Unit increase in listening behaviors was associated with an increase in the number of questions during resident and nurse handoffs by 7% and 12%, respectively. DISCUSSION AND CONCLUSION: As suggested by the Joint Commission, question-asking behaviors were common across resident and nurse handoffs, playing a critical role in supporting resilience in communication and collaborative cross-checks during conversations. The role of listening in initiating question-asking behaviors is discussed

Interdisciplinary handover between obstetric nursing and neonatal physician teams: An observational study

Objective: We investigated the content and quality of communication of interservice interprofessional handover between obstetric nurses and neonatal physicians for high-risk deliveries. Design: Observational study. Setting: Labour and delivery unit at a tertiary care hospital. Method: We audio-recorded handovers between obstetric and neonatal teams (n=50) and conducted clinician interviews (n=29). A handover content framework was developed and used to qualitatively code missing core and ancillary content and their potential for adverse events. Results: 26 (52%) handovers missed one or more clinical content elements; a third of the handovers missed at least one core clinical content element. Increase in the number of missed clinical content elements increased the odds of potential adverse events by 2.39 (95% CI1.18 to 5.37). Both residents and nurses perceived handovers to be of low quality and inconsistent and attributed it to the lack of a structured handover process. Conclusion: Streamlining handover processes by instituting standardisation approaches for both information organisation and communication can improve the quality of neonatal handovers

Autoregressive Language Models For Estimating the Entropy of Epic EHR Audit Logs

EHR audit logs are a highly granular stream of events that capture clinician activities, and is a significant area of interest for research in characterizing clinician workflow on the electronic health record (EHR). Existing techniques to measure the complexity of workflow through EHR audit logs (audit logs) involve time- or frequency-based cross-sectional aggregations that are unable to capture the full complexity of a EHR session. We briefly evaluate the usage of transformer-based tabular language model (tabular LM) in measuring the entropy or disorderedness of action sequences within workflow and release the evaluated models publicly.Comment: Extended Abstract presented at Machine Learning for Health (ML4H) symposium 2023, December 10th, 2023, New Orleans, United States, 10 page

Learning, Performance, and Analysis Support for Complex Software Applications

We propose a three-part framework describing support tools for users of complex software applications such as enterprise resource planning and decision support systems. The model is motivated by the objectives of learning, performance, and analysis and is grounded in the theories of constructivism, pragmatism, and reflection respectively. This mapping is supported both by results of prior research and by a case study formative evaluation of a complex, cognitive support system developed for antiterrorism resource allocation. The work contributes to the field of system usability by providing an integrative framework linking established theoretical positions with empirical research on human-computer interaction

HiMAL: Multimodal Hierarchical Multi-task Auxiliary Learning framework for predicting Alzheimer\u27s disease progression

OBJECTIVE: We aimed to develop and validate a novel multimodal framework MATERIALS AND METHODS: HiMAL utilized multimodal longitudinal visit data including imaging features, cognitive assessment scores, and clinical variables from MCI patients in the Alzheimer\u27s Disease Neuroimaging Initiative dataset, to predict at each visit if an MCI patient will progress to AD within the next 6 months. Performance of HiMAL was compared with state-of-the-art single-task and multitask baselines using area under the receiver operator curve (AUROC) and precision recall curve (AUPRC) metrics. An ablation study was performed to assess the impact of each input modality on model performance. Additionally, longitudinal explanations regarding risk of disease progression were provided to interpret the predicted cognitive decline. RESULTS: Out of 634 MCI patients (mean [IQR] age: 72.8 [67-78], 60% male), 209 (32%) progressed to AD. HiMAL showed better prediction performance compared to all state-of-the-art longitudinal single-modality singe-task baselines (AUROC = 0.923 [0.915-0.937]; AUPRC = 0.623 [0.605-0.644]; all DISCUSSION: Clinically informative model explanations anticipate cognitive decline 6 months in advance, aiding clinicians in future disease progression assessment. HiMAL relies on routinely collected electronic health records (EHR) variables for proximal (6 months) prediction of AD onset, indicating its translational potential for point-of-care monitoring and managing of high-risk patients

Characterizing the patterns of electronic health record-integrated secure messaging use: Cross-sectional study

BACKGROUND: Communication among health care professionals is essential for the delivery of safe clinical care. Secure messaging has rapidly emerged as a new mode of asynchronous communication. Despite its popularity, relatively little is known about how secure messaging is used and how such use contributes to communication burden. OBJECTIVE: This study aims to characterize the use of an electronic health record-integrated secure messaging platform across 14 hospitals and 263 outpatient clinics within a large health care system. METHODS: We collected metadata on the use of the Epic Systems Secure Chat platform for 6 months (July 2022 to January 2023). Information was retrieved on message volume, response times, message characteristics, messages sent and received by users, user roles, and work settings (inpatient vs outpatient). RESULTS: A total of 32,881 users sent 9,639,149 messages during the study. Median daily message volume was 53,951 during the first 2 weeks of the study and 69,526 during the last 2 weeks, resulting in an overall increase of 29% (P=.03). Nurses were the most frequent users of secure messaging (3,884,270/9,639,149, 40% messages), followed by physicians (2,387,634/9,639,149, 25% messages), and medical assistants (1,135,577/9,639,149, 12% messages). Daily message frequency varied across users; inpatient advanced practice providers and social workers interacted with the highest number of messages per day (median 19). Conversations were predominantly between 2 users (1,258,036/1,547,879, 81% conversations), with a median of 2 conversational turns and a median response time of 2.4 minutes. The largest proportion of inpatient messages was from nurses to physicians (972,243/4,749,186, 20% messages) and physicians to nurses (606,576/4,749,186, 13% messages), while the largest proportion of outpatient messages was from physicians to nurses (344,048/2,192,488, 16% messages) and medical assistants to other medical assistants (236,694/2,192,488, 11% messages). CONCLUSIONS: Secure messaging was widely used by a diverse range of health care professionals, with ongoing growth throughout the study and many users interacting with more than 20 messages per day. The short message response times and high messaging volume observed highlight the interruptive nature of secure messaging, raising questions about its potentially harmful effects on clinician workflow, cognition, and errors

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 (\u3c1%), 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

Risk factors associated with physician trainee concern over missed educational opportunities during the COVID-19 pandemic

BACKGROUND: The COVID-19 pandemic resulted in a transformation of clinical care practices to protect both patients and providers. These changes led to a decrease in patient volume, impacting physician trainee education due to lost clinical and didactic opportunities. We measured the prevalence of trainee concern over missed educational opportunities and investigated the risk factors leading to such concerns. METHODS: All residents and fellows at a large academic medical center were invited to participate in a web-based survey in May of 2020. Participants responded to questions regarding demographic characteristics, specialty, primary assigned responsibility during the previous 2 weeks (clinical, education, or research), perceived concern over missed educational opportunities, and burnout. Multivariable logistic regression was used to assess the relationship between missed educational opportunities and the measured variables. RESULTS: 22% (301 of 1375) of the trainees completed the survey. 47% of the participants were concerned about missed educational opportunities. Trainees assigned to education at home had 2.85 [95%CI 1.33-6.45] greater odds of being concerned over missed educational opportunities as compared with trainees performing clinical work. Trainees performing research were not similarly affected [aOR = 0.96, 95%CI (0.47-1.93)]. Trainees in pathology or radiology had 2.51 [95%CI 1.16-5.68] greater odds of concern for missed educational opportunities as compared with medicine. Trainees with greater concern over missed opportunities were more likely to be experiencing burnout (p = 0.038). CONCLUSIONS: Trainees in radiology or pathology and those assigned to education at home were more likely to be concerned about their missed educational opportunities. Residency programs should consider providing trainees with research or at home clinical opportunities as an alternative to self-study should future need for reduced clinical hours arise