Developing and Testing the Usability of a Novel Child Abuse Clinical Decision Support System: Mixed Methods Study.

BACKGROUND: Despite the impact of physical abuse on children, it is often underdiagnosed, especially among children evaluated in general emergency departments (EDs) and those belonging to racial or ethnic minority groups. Electronic clinical decision support (CDS) can improve the recognition of child physical abuse. OBJECTIVE: We aimed to develop and test the usability of a natural language processing-based child abuse CDS system, known as the Child Abuse Clinical Decision Support (CA-CDS), to alert ED clinicians about high-risk injuries suggestive of abuse in infants' charts. METHODS: Informed by available evidence, a multidisciplinary team, including an expert in user design, developed the CA-CDS prototype that provided evidence-based recommendations for the evaluation and management of suspected child abuse when triggered by documentation of a high-risk injury. Content was customized for medical versus nursing providers and initial versus subsequent exposure to the alert. To assess the usability of and refine the CA-CDS, we interviewed 24 clinicians from 4 EDs about their interactions with the prototype. Interview transcripts were coded and analyzed using conventional content analysis. RESULTS: Overall, 5 main categories of themes emerged from the study. CA-CDS benefits included providing an extra layer of protection, providing evidence-based recommendations, and alerting the entire clinical ED team. The user-centered, workflow-compatible design included soft-stop alert configuration, editable and automatic documentation, and attention-grabbing formatting. Recommendations for improvement included consolidating content, clearer design elements, and adding a hyperlink with additional resources. Barriers to future implementation included alert fatigue, hesitancy to change, and concerns regarding documentation. Facilitators of future implementation included stakeholder buy-in, provider education, and sharing the test characteristics. On the basis of user feedback, iterative modifications were made to the prototype. CONCLUSIONS: With its user-centered design and evidence-based content, the CA-CDS can aid providers in the real-time recognition and evaluation of infant physical abuse and has the potential to reduce the number of missed cases.

Natural Language Processing - A Surveillance Stepping Stone to Identify Child Abuse.

OBJECTIVE: We aimed to refine a natural language processing (NLP) algorithm that identified injuries associated with child abuse and identify areas in which integration into a real-time clinical decision support (CDS) tool may improve clinical care. METHODS: We applied an NLP algorithm in "silent mode" to all emergency department (ED) provider notes between July 2021 and December 2022 (n = 353) at 1 pediatric and 8 general EDs. We refined triggers for the NLP, assessed adherence to clinical guidelines, and evaluated disparities in degree of evaluation by examining associations between demographic variables and abuse evaluation or reporting to child protective services. RESULTS: Seventy-three cases falsely triggered the NLP, often due to errors in interpreting linguistic context. We identified common false-positive scenarios and refined the algorithm to improve NLP specificity. Adherence to recommended evaluation standards for injuries defined by nationally accepted clinical guidelines was 63%. There were significant demographic differences in evaluation and reporting based on presenting ED type, insurance status, and race and ethnicity. CONCLUSIONS: Analysis of an NLP algorithm in "silent mode" allowed for refinement of the algorithm and highlighted areas in which real-time CDS may help ED providers identify and pursue appropriate evaluation of injuries associated with child physical abuse.

Mesenchymal stem cells alleviate dexamethasone-induced muscle atrophy in mice and the involvement of ERK1/2 signalling pathway.

BACKGROUND: High dosage of dexamethasone (Dex) is an effective treatment for multiple diseases; however, it is often associated with severe side effects including muscle atrophy, resulting in higher risk of falls and poorer life quality of patients. Cell therapy with mesenchymal stem cells (MSCs) holds promise for regenerative medicine. In this study, we aimed to investigate the therapeutic efficacy of systemic administration of adipose-derived mesenchymal stem cells (ADSCs) in mitigating the loss of muscle mass and strength in mouse model of DEX-induced muscle atrophy. METHODS: 3-month-old female C57BL/6 mice were treated with Dex (20 mg/kg body weight, i.p.) for 10 days to induce muscle atrophy, then subjected to intravenous injection of a single dose of ADSCs ([Formula: see text] cells/kg body weight) or vehicle control. The mice were killed 7 days after ADSCs treatment. Body compositions were measured by animal DXA, gastrocnemius muscle was isolated for ex vivo muscle functional test, histological assessment and Western blot, while tibialis anterior muscles were isolated for RNA-sequencing and qPCR. For in vitro study, C2C12 myoblast cells were cultured under myogenic differentiation medium for 5 days following 100 [Formula: see text]M Dex treatment with or without ADSC-conditioned medium for another 4 days. Samples were collected for qPCR analysis and Western blot analysis. Myotube morphology was measured by myosin heavy chain immunofluorescence staining. RESULTS: ADSC treatment significantly increased body lean mass (10-20%), muscle wet weight (15-30%) and cross-sectional area (CSA) (~ 33%) in DEX-induced muscle atrophy mice model and down-regulated muscle atrophy-associated genes expression (45-65%). Hindlimb grip strength (~ 37%) and forelimb ex vivo muscle contraction property were significantly improved (~ 57%) in the treatment group. Significant increase in type I fibres (~ 77%) was found after ADSC injection. RNA-sequencing results suggested that ERK1/2 signalling pathway might be playing important role underlying the beneficial effect of ADSC treatment, which was confirmed by ERK1/2 inhibitor both in vitro and in vivo. CONCLUSIONS: ADSCs restore the pathogenesis of Dex-induced muscle atrophy with an increased number of type I fibres, stronger muscle strength, faster recovery rate and more anti-fatigue ability via ERK1/2 signalling pathway. The inhibition of muscle atrophy-associated genes by ADSCs offered this treatment as an intervention option for muscle-associated diseases. Taken together, our findings suggested that adipose-derived mesenchymal stem cell therapy could be a new treatment option for patient with Dex-induced muscle atrophy.

Use of an Automated Bilingual Digital Health Tool to Reduce Unhealthy Alcohol Use Among Latino Emergency Department Patients: A Randomized Clinical Trial.

Importance: Alcohol use disorders have a high disease burden among US Latino groups. In this population, health disparities persist, and high-risk drinking has been increasing. Effective bilingual and culturally adapted brief interventions are needed to identify and reduce disease burden. Objective: To compare the effectiveness of an automated bilingual computerized alcohol screening and intervention (AB-CASI) digital health tool with standard care for the reduction of alcohol consumption among US adult Latino emergency department (ED) patients with unhealthy drinking. Design, Setting, and Participants: This bilingual unblinded parallel-group randomized clinical trial evaluated the effectiveness of AB-CASI vs standard care among 840 self-identified adult Latino ED patients with unhealthy drinking (representing the full spectrum of unhealthy drinking). The study was conducted from October 29, 2014, to May 1, 2020, at the ED of a large urban community tertiary care center in the northeastern US that was verified as a level II trauma center by the American College of Surgeons. Data were analyzed from May 14, 2020, to November 24, 2020. Intervention: Patients randomized to the intervention group received AB-CASI, which included alcohol screening and a structured interactive brief negotiated interview in their preferred language (English or Spanish) while in the ED. Patients randomized to the standard care group received standard emergency medical care, including an informational sheet with recommended primary care follow-up. Main Outcomes and Measures: The primary outcome was the self-reported number of binge drinking episodes within the last 28 days, assessed by the timeline followback method at 12 months after randomization. Results: Among 840 self-identified adult Latino ED patients (mean [SD] age, 36.2 [11.2] years; 433 [51.5%] male; and 697 [83.0%] of Puerto Rican descent), 418 were randomized to the AB-CASI group and 422 to the standard care group. A total of 443 patients (52.7%) chose Spanish as their preferred language at enrollment. At 12 months, the number of binge drinking episodes within the last 28 days was significantly lower in those receiving AB-CASI (3.2; 95% CI, 2.7-3.8) vs standard care (4.0; 95% CI, 3.4-4.7; relative difference [RD], 0.79; 95% CI, 0.64-0.99). Alcohol-related adverse health behaviors and consequences were similar between groups. The effect of AB-CASI was modified by age; at 12 months, the relative reduction in the number of binge drinking episodes within the last 28 days in the AB-CASI vs standard care group was 30% in participants older than 25 years (RD, 0.70; 95% CI, 0.54-0.89) compared with an increase of 40% in participants 25 years or younger (RD, 1.40; 95% CI, 0.85-2.31; P = .01 for interaction). Conclusions and Relevance: In this study, US adult Latino ED patients who received AB-CASI had a significant reduction in the number of binge drinking episodes within the last 28 days at 12 months after randomization. These findings suggest that AB-CASI is a viable brief intervention that overcomes known procedural barriers to ED screening, brief intervention, and referral to treatment and directly addresses alcohol-related health disparities. Trial Registration: ClinicalTrials.gov Identifier: NCT02247388.

Ginkgolide B facilitates muscle regeneration via rejuvenating osteocalcin-mediated bone-to-muscle modulation in aged mice.

BACKGROUND: The progressive deterioration of tissue-tissue crosstalk with aging causes a striking impairment of tissue homeostasis and functionality, particularly in the musculoskeletal system. Rejuvenation of the systemic and local milieu via interventions such as heterochronic parabiosis and exercise has been reported to improve musculoskeletal homeostasis in aged organisms. We have shown that Ginkgolide B (GB), a small molecule from Ginkgo biloba, improves bone homeostasis in aged mice by restoring local and systemic communication, implying a potential for maintaining skeletal muscle homeostasis and enhancing regeneration. In this study, we investigated the therapeutic efficacy of GB on skeletal muscle regeneration in aged mice. METHODS: Muscle injury models were established by barium chloride induction into the hind limb of 20-month-old mice (aged mice) and into C2C12-derived myotubes. Therapeutic efficacy of daily administrated GB (12 mg/kg body weight) and osteocalcin (50 µg/kg body weight) on muscle regeneration was assessed by histochemical staining, gene expression, flow cytometry, ex vivo muscle function test and rotarod test. RNA sequencing was used to explore the mechanism of GB on muscle regeneration, with subsequent in vitro and in vivo experiments validating these findings. RESULTS: GB administration in aged mice improved muscle regeneration (muscle mass, P = 0.0374; myofiber number/field, P = 0.0001; centre nucleus, embryonic myosin heavy chain-positive myofiber area, P = 0.0144), facilitated the recovery of muscle contractile properties (tetanic force, P = 0.0002; twitch force, P = 0.0005) and exercise performance (rotarod performance, P = 0.002), and reduced muscular fibrosis (collagen deposition, P < 0.0001) and inflammation (macrophage infiltration, P = 0.03). GB reversed the aging-related decrease in the expression of osteocalcin (P < 0.0001), an osteoblast-specific hormone, to promote muscle regeneration. Exogenous osteocalcin supplementation was sufficient to improve muscle regeneration (muscle mass, P = 0.0029; myofiber number/field, P < 0.0001), functional recovery (tetanic force, P = 0.0059; twitch force, P = 0.07; rotarod performance, P < 0.0001) and fibrosis (collagen deposition, P = 0.0316) in aged mice, without an increased risk of heterotopic ossification. CONCLUSIONS: GB treatment restored the bone-to-muscle endocrine axis to reverse aging-related declines in muscle regeneration and thus represents an innovative and practicable approach to managing muscle injuries. Our results revealed the critical and novel role of osteocalcin-GPRC6A-mediated bone-to-muscle communication in muscle regeneration, which provides a promising therapeutic avenue in functional muscle regeneration.

Exploratory Descriptive Analysis of Smart Speaker Utilization in the Emergency Department During the COVID-19 Pandemic.

BACKGROUND: In March 2020, the U.S. Department of Health and Human Services Office for Civil Rights stated that they would use discretion when enforcing the Health Insurance Portability and Accountability Act regarding remote communication technologies that promoted telehealth delivery during the COVID-19 pandemic. This was in an effort to protect patients, clinicians, and staff. More recently, smart speakers-voice-activated, hands-free devices-are being proposed as productivity tools within hospitals. OBJECTIVE: We aimed to characterize the novel use of smart speakers in the emergency department (ED). METHODS: A retrospective observational study of Amazon Echo Show® utilization from May 2020 to October 2020 in a large academic Northeast health system ED. Voice commands and queries were classified as either patient care-related or non-patient care-related, and then further subcategorized to explore the content of given commands. RESULTS: Of 1232 commands analyzed, 200 (16.23%) were determined to be patient care-related. Of these commands, 155 (77.5%) were clinical in nature (i.e., "drop in on triage") and 23 (11.5%) were environment-enhancing commands (i.e., "play calming sounds"). Among non-patient care-related commands, 644 (62.4%) were for entertainment. Among all commands, 804 (65.3%) were during night-shift hours, which was statistically significant (p < 0.001). CONCLUSIONS: Smart speakers showed notable engagement, primarily being used for patient communication and entertainment. Future studies should examine content of patient care conversations using these devices, effects on frontline staff wellbeing, productivity, patient satisfaction, and even explore opportunities for "smart" hospital rooms.

Real-World Observational Evaluation of Common Interventions to Reduce Emergency Department Prescribing of Opioid Medications.

BACKGROUND: Prior work on opioid prescribing has examined dosing defaults, interruptive alerts, or "harder" stops such as electronic prescribing of controlled substances (EPCS), which has become increasingly required by state policy. Given that real-world opioid stewardship policies are concurrent and overlapping, the authors examined the effect of such policies on emergency department (ED) opioid prescriptions. METHODS: The researchers performed observational analysis of all ED visits discharged between December 17, 2016, and December 31, 2019, across seven EDs of a hospital system. Four interventions were examined in chronological order, with each successive intervention added on top of all previous interventions: 12-pill prescription default, EPCS, electronic health record (EHR) pop-up alert, and 8-pill prescription default. The primary outcome was opioid prescribing, which was described as number of opioid prescriptions per 100 discharged ED visits and modeled as a binary outcome for each visit. Secondary outcomes included prescription morphine milligram equivalents (MME) and non-opioid analgesia prescriptions. RESULTS: A total of 775,692 ED visits were included in the study. Compared to the preintervention period, cumulative reductions in opioid prescribing were seen with incremental interventions, including after adding a 12-pill default (odds ratio [OR] 0.88, 95% confidence interval [CI] 0.82-0.94), after adding EPCS (OR 0.7, 95% CI 0.63-0.77), after adding pop-up alerts (OR 0.67, 95% CI 0.63-0.71), and after adding an 8-pill default (OR 0.61, 95% CI 0.58-0.65). CONCLUSION: EHR-implemented solutions such as EPCS, pop-up alerts, and pill defaults had varying but significant effects on reducing ED opioid prescribing. Policy makers and quality improvement leaders might achieve sustainable improvements in opioid stewardship while balancing clinician alert fatigue through policy efforts promoting implementation of EPCS and default dispense quantities.

Is dexamethasone-induced muscle atrophy an alternative model for naturally aged sarcopenia model?

Background: Primary sarcopenia is usually known as age-related skeletal muscle loss; however, other factors like endocrine, lifestyle and inflammation can also cause muscle loss, known as secondary sarcopenia. Although many studies have used different sarcopenia animal models for exploring the underlying mechanism and therapeutic approaches for sarcopenia, limited study has provided evidence of the relevance of these animal models. This study aims to investigate the similarity and difference in muscle qualities between primary and secondary sarcopenia mice models, using naturally aged mice and dexamethasone-induced mice. Methods: 21-month-old mice were used as naturally aged primary sarcopenia mice and 3-month-old mice received daily intraperitoneal injection of dexamethasone (20 mg/ kg body weight) for 10 days were used as secondary sarcopenia model. This study provided measurements for muscle mass and functions, including Dual-energy X-ray absorptiometry (DXA) scanning, handgrip strength test and treadmill running to exhaustion test. Besides, muscle contraction, muscle fibre type measurements and gene expression were also performed to provide additional information on muscle qualities. Results: The results suggest two sarcopenia animal models shared a comparable decrease in forelimb lean mass, muscle fibre size, grip strength and muscle contraction ability. Besides, the upregulation of protein degradation genes was also observed in two sarcopenia animal models. However, only primary sarcopenia mice were identified with an early stage of mtDNA deletion. Conclusion: Collectively, this study evaluated that the dexamethasone-induced mouse model could be served as an alternative model for primary sarcopenia, according to the comparable muscle mass and functional changes. However, whether dexamethasone-induced mice can be used as an animal model when studying the molecular mechanisms of sarcopenia needs to be carefully evaluated. The translational potential of this article: The purpose of sarcopenia research is to investigate appropriate treatments for reversing the loss of skeletal muscle mass and functions. Using animal models for the preclinical study could predict the safety and efficacy of the treatments. This study compared the typical age-related sarcopenia mice model and dexamethasone-induced secondary sarcopenia mice to provide evidence of the pathological and functional changes in the mice models.

Bioactive glass-elicited stem cell-derived extracellular vesicles regulate M2 macrophage polarization and angiogenesis to improve tendon regeneration and functional recovery.

Effective countermeasures for tendon injury remains unsatisfactory. Mesenchymal stem cell-derived extracellular vesicles (MSC-EVs)-based therapy via regulation of Mφ-mediated angiogenesis has emerged as a promising strategy for tissue regeneration. Still, approaches to tailor the functions of EVs to treat tendon injuries have been limited. We reported a novel strategy by applying MSC-EVs boosted with bioactive glasses (BG). BG-elicited EVs (EVB) showed up-regulation of medicinal miRNAs, including miR-199b-3p and miR-125a-5p, which play a pivotal role in M2 Mφ-mediated angiogenesis. EVB accelerated angiogenesis via the reprogrammed anti-inflammatory M2 Mφs compared with naïve MSC-EVs (EVN). In rodent Achilles tendon rupture model, EVB local administration activated anti-inflammatory responses via M2 polarization and led to a spatial correlation between M2 Mφs and newly formed blood vessels. Our results showed that EVB outperformed EVN in promoting tenogenesis and in reducing detrimental morphological changes without causing heterotopic ossification. Biomechanical test revealed that EVB significantly improved ultimate load, stiffness, and tensile modulus of the repaired tendon, along with a positive correlation between M2/M1 ratio and biomechanical properties. On the basis of the boosted nature to reprogram regenerative microenvironment, EVB holds considerable potential to be developed as a next-generation therapeutic modality for enhancing functional regeneration to achieve satisfying tendon regeneration.

COVID-19 surge readiness: use cases demonstrating how hospitals leveraged digital identity access management for infection control and pandemic response.

BACKGROUND: Surging volumes of patients with COVID-19 and the high infectiousness of SARS-CoV-2 challenged hospital infection control/safety, staffing, care delivery and operations as few crises have. Imperatives to ensure security of patient information, defend against cybersecurity threats and accurately identify/authenticate patients and staff were undiminished, which fostered creative use cases where hospitals leveraged identity access and management (IAM) technologies to improve infection control and minimise disruption of clinical and administrative workflows. METHODS: Working with a leading IAM solution provider, implementation personnel in the USA and UK identified all hospitals/health systems where an innovative use of IAM technology improved facility infection control and pandemic response management. Interviews/communications with hospital clinical informatics leaders collected information describing the use case deployed. RESULTS: Eight innovative/valuable hospital use cases are described: symptom-free attestation by clinicians at shift start; detection of clinician exposure/contact tracing; reporting of clinician temperature checks; inpatient telehealth consults in isolation units; virtual visits between isolated patients and families; touchless single sign-on authentication; secure access enabled for rapid expansion of personnel working remotely; and monitoring of temporary worker attendance. DISCUSSION: No systematic, comprehensive survey of all implemented IAM client sites was conducted, and other use cases may be undetected. A standardised reporting/information sharing vehicle is needed whereby IAM use cases aiding facility pandemic response and infection control can be disseminated. CONCLUSIONS: Clinical care, infection control and facility operations were improved using IAM solutions during COVID-19. Facility end-user innovation in how IAM solutions are deployed can improve infection control/patient safety, care delivery and clinical workflows during surges of epidemic infectious diseases.

Alerting Clinicians to 1-Year Mortality Risk in Patients Hospitalized With Heart Failure: The REVEAL-HF Randomized Clinical Trial.

Importance: Heart failure is a major cause of morbidity and mortality worldwide. The use of risk scores has the potential to improve targeted use of interventions by clinicians that improve patient outcomes, but this hypothesis has not been tested in a randomized trial. Objective: To evaluate whether prognostic information in heart failure translates into improved decisions about initiation and intensity of treatment, more appropriate end-of-life care, and a subsequent reduction in rates of hospitalization or death. Design, Setting, and Participants: This was a pragmatic, multicenter, electronic health record-based, randomized clinical trial across the Yale New Haven Health System, comprising small community hospitals and large tertiary care centers. Patients hospitalized for heart failure who had N-terminal pro-brain natriuretic peptide (NT-proBNP) levels of greater than 500 pg/mL and received intravenous diuretics within 24 hours of admission were automatically randomly assigned to the alert (intervention) or usual-care groups. Interventions: The alert group had their risk of 1-year mortality calculated using an algorithm that was derived and validated using similar historic patients in the electronic health record. This estimate, including a categorical risk assessment, was presented to clinicians while they were interacting with a patient's electronic health record. Main Outcomes and Measures: The primary outcome was a composite of 30-day hospital readmissions and all-cause mortality at 1 year. Results: Between November 27, 2019, through March 7, 2021, 3124 patients were randomly assigned to the alert (1590 [50.9%]) or usual-care (1534 [49.1%]) group. The alert group had a median (IQR) age of 76.5 (65-86) years, and 796 were female patients (50.1%). Patients from the following race and ethnicity groups were included: 13 Asian (0.8%), 324 Black (20.4%), 136 Hispanic (8.6%), 1448 non-Hispanic (91.1%), 1126 White (70.8%), 6 other ethnicity (0.4%), and 127 other race (8.0%). The usual-care group had a median (IQR) age of 77 (65-86) years, and 788 were female patients (51.4%). Patients from the following race and ethnicity groups were included: 11 Asian (1.4%), 298 Black (19.4%), 162 Hispanic (10.6%), 1359 non-Hispanic (88.6%), 1077 White (70.2%), 13 other ethnicity (0.9%), and 137 other race (8.9%). Median (IQR) NT-proBNP levels were 3826 (1692-8241) pg/mL in the alert group and 3867 (1663-8917) pg/mL in the usual-care group. A total of 284 patients (17.9%) and 270 patients (17.6%) were admitted to the intensive care unit in the alert and usual-care groups, respectively. A total of 367 patients (23.1%) and 359 patients (23.4%) had a left ventricular ejection fraction of 40% or less in the alert and usual-care groups, respectively. The model achieved an area under the curve of 0.74 in the trial population. The primary outcome occurred in 619 patients (38.9%) in the alert group and 603 patients (39.3%) in the usual-care group (P = .89). There were no significant differences between study groups in the prescription of heart failure medications at discharge, the placement of an implantable cardioverter-defibrillator, or referral to palliative care. Conclusions and Relevance: Provision of 1-year mortality estimates during heart failure hospitalization did not affect hospitalization or mortality, nor did it affect clinical decision-making. Trial Registration: ClinicalTrials.gov Identifier NCT03845660.

Demystifying the long noncoding RNA landscape of small EVs derived from human mesenchymal stromal cells.

INTRODUCTION: The regenerative capacity of mesenchymal stromal cells or medicinal signaling cells (MSCs) is largely mediated by their secreted small extracellular vesicles (sEVs), and the therapeutic efficacy of sEVs can be enhanced by licensing approaches (e.g., cytokines, hypoxia, chemicals, and genetic modification). Noncoding RNAs within MSC-derived sEVs (MSC-sEVs) have been demonstrated to be responsible for tissue regeneration. However, unlike miRNA fingerprints, which have been explored, the landscape of long noncoding RNAs (lncRNAs) in MSC-sEVs remains to be described. OBJECTIVES: To characterize lncRNA signatures in sEVs of human adipose-derived MSCs with or without inflammatory cytokine licensing and depict MSC-sEV-specific and MSC-enriched lncRNA repertoires. METHODS: sEVs were isolated from MSCs with or without TNF-α and IFN-γ (20 ng/mL) stimulation. High-throughput lncRNA sequencing and an in silico approach were employed to analyze the profile of lncRNAs in sEVs and predict lncRNA-protein interactomes. RESULTS: sEVs derived from human MSCs and fibroblasts carried a unique landscape of lncRNAs distinct from the lncRNAs inside these cells. Compared with fibroblast-derived sEVs (F-sEVs), 194 MSC-sEV-specific and 8 upregulated lncRNAs in MSC-sEVs were considered "medicinal signaling lncRNAs"; inflammatory cytokines upregulated 27 lncRNAs in MSC-sEVs, which were considered "licensing-responsive lncRNAs". Based on lncRNA-protein interactome prediction and enrichment analysis, we found that the proteins interacting with medicinal signaling lncRNAs or licensing-responsive lncRNAs have a tight interaction network involved in chromatin remodeling, SWI/SNF superfamily type complexes, and histone binding. CONCLUSION: In summary, our study depicts the landscape of lncRNAs in MSC-sEVs and predicts their potential functions via the lncRNA-protein interactome. Elucidation of the lncRNA landscape of MSC-sEVs will facilitate defining the therapeutic potency of MSC-sEVs and the development of sEV-based therapeutics.

Aligning mission to digital health strategy in academic medical centers.

The strategies of academic medical centers arise from core values and missions that aim to provide unmatched clinical care, patient experience, research, education, and training. These missions drive nearly all activities. They should also drive digital health activities - and particularly now given the rapid adoption of digital health, marking one of the great transformations of healthcare; increasing pressures on health systems to provide more cost-effective care; the pandemic-accelerated funding and rise of well-funded new entrants and technology giants that provide more convenient forms of care; and a more favorable regulatory and reimbursement landscape to incorporate digital health approaches. As academic medical centers emerge from a pandemic-related reactionary digital health posture, where pressures to adopt more digital health technologies mount, a broad digital health realignment that leverages the strengths of such centers is required to accomplish their missions.

Development and Validation of a Natural Language Processing Tool to Identify Injuries in Infants Associated With Abuse.

OBJECTIVES: Medically minor but clinically important findings associated with physical child abuse, such as bruises in pre-mobile infants, may be identified by frontline clinicians yet the association of these injuries with child abuse is often not recognized, potentially allowing the abuse to continue and even to escalate. An accurate natural language processing (NLP) algorithm to identify high-risk injuries in electronic health record notes could improve detection and awareness of abuse. The objectives were to: 1) develop an NLP algorithm that accurately identifies injuries in infants associated with abuse and 2) determine the accuracy of this algorithm. METHODS: An NLP algorithm was designed to identify ten specific injuries known to be associated with physical abuse in infants. Iterative cycles of review identified inaccurate triggers, and coding of the algorithm was adjusted. The optimized NLP algorithm was applied to emergency department (ED) providers' notes on 1344 consecutive sample of infants seen in 9 EDs over 3.5 months. Results were compared with review of the same notes conducted by a trained reviewer blind to the NLP results with discrepancies adjudicated by a child abuse expert. RESULTS: Among the 1344 encounters, 41 (3.1%) had one of the high-risk injuries. The NLP algorithm had a sensitivity and specificity of 92.7% (95% confidence interval [CI]: 79.0%-98.1%) and 98.1% (95% CI: 97.1%-98.7%), respectively, and positive and negative predictive values were 60.3% and 99.8%, respectively, for identifying high-risk injuries. CONCLUSIONS: An NLP algorithm to identify infants with high-risk injuries in EDs has good accuracy and may be useful to aid clinicians in the identification of infants with injuries associated with child abuse.

Disparities in Accessing and Reading Open Notes in the Emergency Department Upon Implementation of the 21st Century CURES Act.

STUDY OBJECTIVE: There is a continued movement toward health data transparency, accelerated by the 21st Century CURES Act, which mandated the automatic and immediate release of clinical notes, often termed "open notes." Differences in utilization among different patient demographics and disproportionately affected populations within the emergency department (ED) are not yet known. METHODS: This was an observational study of 10 EDs and 3 urgent care centers across a single health system over a 13-week period from February 1, 2021 to May 2, 2021. Primary outcomes included the proportion of patients with patient portal access to open notes at the time of encounter, the proportion of patients with access who opened the clinical note, and time from clinical note signing to patient read. RESULTS: Among 98,725 patient visits, less than half (48.9%) had patient portal access, of which 13.7% read an open note. Access was less likely in patients who were under age 18 (odds ratio 0.10, 95% confidence interval 0.08 to 0.11), older than 65 (0.82, 0.73 to 0.93), Black non-Hispanic (0.66, 0.61 to 0.73), non-English speakers, and on public insurance. Patients were less likely to read open notes if they identified as Black non-Hispanic (0.61, 0.57 to 0.66), spoke Spanish (0.70, 0.60 to 0.81), or were on public insurance. CONCLUSION: We identified substantial differences in digital access to clinical notes as well as patient utilization of open notes in a large, diverse sample. Health transparency initiatives must address not only technology adoption broadly but also the unique barriers faced by populations experiencing disadvantage to facilitate equitable access to and awareness about digital health tools without the unintended consequence of expanding disparities.

REVeAL-HF: Design and Rationale of a Pragmatic Randomized Controlled Trial Embedded Within Routine Clinical Practice.

Heart failure (HF) is one of the most common causes of hospitalization in the United States and carries a significant risk of morbidity and mortality. Use of evidence-based interventions may improve outcomes, but their use is encumbered in part by limitations in accurate prognostication. The REVeAL-HF (Risk EValuation And its Impact on ClinicAL Decision Making and Outcomes in Heart Failure) trial is the first to definitively evaluate the impact of knowledge about prognosis on clinical decision making and patient outcomes. The REVeAL-HF trial is a pragmatic, completely electronic, randomized controlled trial that has completed enrollment of 3,124 adults hospitalized for HF, defined as having an N-terminal pro-B-type natriuretic peptide level of >500 pg/ml and receiving intravenous diuretic agents within 24 h of admission. Patients randomized to the intervention had their risk of 1-year mortality generated with information in the electronic health record and presented to their providers, who had the option to give feedback on their impression of this risk assessment. The authors are examining the impact of this information on clinical decision-making (use of HF pharmacotherapies, referral to electrophysiology, palliative care referral, and referral for advanced therapies like heart transplantation or mechanical circulatory support) and patient outcomes (length of stay, post-discharge 30-day rehospitalizations, and 1-year mortality). The REVeAL-HF trial will definitively examine whether knowledge about prognosis in HF has an impact on clinical decision making and patient outcomes. It will also examine the relationship between calculated, perceived, and real risk of mortality in this patient population. (Risk EValuation And Its Impact on ClinicAL Decision Making and Outcomes in Heart Failure [REVeAL-HF]; NCT03845660).

Clinical characteristics and outcomes for 7,995 patients with SARS-CoV-2 infection.

OBJECTIVE: Severe acute respiratory syndrome virus (SARS-CoV-2) has infected millions of people worldwide. Our goal was to identify risk factors associated with admission and disease severity in patients with SARS-CoV-2. DESIGN: This was an observational, retrospective study based on real-world data for 7,995 patients with SARS-CoV-2 from a clinical data repository. SETTING: Yale New Haven Health (YNHH) is a five-hospital academic health system serving a diverse patient population with community and teaching facilities in both urban and suburban areas. POPULATIONS: The study included adult patients who had SARS-CoV-2 testing at YNHH between March 1 and April 30, 2020. MAIN OUTCOME AND PERFORMANCE MEASURES: Primary outcomes were admission and in-hospital mortality for patients with SARS-CoV-2 infection as determined by RT-PCR testing. We also assessed features associated with the need for respiratory support. RESULTS: Of the 28605 patients tested for SARS-CoV-2, 7995 patients (27.9%) had an infection (median age 52.3 years) and 2154 (26.9%) of these had an associated admission (median age 66.2 years). Of admitted patients, 2152 (99.9%) had a discharge disposition at the end of the study period. Of these, 329 (15.3%) required invasive mechanical ventilation and 305 (14.2%) expired. Increased age and male sex were positively associated with admission and in-hospital mortality (median age 80.7 years), while comorbidities had a much weaker association with the risk of admission or mortality. Black race (OR 1.43, 95%CI 1.14-1.78) and Hispanic ethnicity (OR 1.81, 95%CI 1.50-2.18) were identified as risk factors for admission, but, among discharged patients, age-adjusted in-hospital mortality was not significantly different among racial and ethnic groups. CONCLUSIONS: This observational study identified, among people testing positive for SARS-CoV-2 infection, older age and male sex as the most strongly associated risks for admission and in-hospital mortality in patients with SARS-CoV-2 infection. While minority racial and ethnic groups had increased burden of disease and risk of admission, age-adjusted in-hospital mortality for discharged patients was not significantly different among racial and ethnic groups. Ongoing studies will be needed to continue to evaluate these risks, particularly in the setting of evolving treatment guidelines.

Early identification of patients with acute gastrointestinal bleeding using natural language processing and decision rules.

BACKGROUND AND AIM: Guidelines recommend risk stratification scores in patients presenting with gastrointestinal bleeding (GIB), but such scores are uncommonly employed in practice. Automation and deployment of risk stratification scores in real time within electronic health records (EHRs) would overcome a major impediment. This requires an automated mechanism to accurately identify ("phenotype") patients with GIB at the time of presentation. The goal is to identify patients with acute GIB by developing and evaluating EHR-based phenotyping algorithms for emergency department (ED) patients. METHODS: We specified criteria using structured data elements to create rules for identifying patients and also developed multiple natural language processing (NLP)-based approaches for automated phenotyping of patients, tested them with tenfold cross-validation for 10 iterations (n = 7144) and external validation (n = 2988) and compared them with a standard method to identify patient conditions, the Systematized Nomenclature of Medicine. The gold standard for GIB diagnosis was the independent dual manual review of medical records. The primary outcome was the positive predictive value. RESULTS: A decision rule using GIB-specific terms from ED triage and ED review-of-systems assessment performed better than the Systematized Nomenclature of Medicine on internal validation and external validation (positive predictive value = 85% confidence interval:83%-87% vs 69% confidence interval:66%-72%; P < 0.001). The syntax-based NLP algorithm and Bidirectional Encoder Representation from Transformers neural network-based NLP algorithm had similar performance to the structured-data fields decision rule. CONCLUSIONS: An automated decision rule employing GIB-specific triage and review-of-systems terms can be used to trigger EHR-based deployment of risk stratification models to guide clinical decision making in real time for patients with acute GIB presenting to the ED.

Inpatient Telehealth Tools to Enhance Communication and Decrease Personal Protective Equipment Consumption during Disaster Situations: A Case Study during the COVID-19 Pandemic.

BACKGROUND: As the coronavirus disease 2019 pandemic exerts unprecedented stress on hospitals, health care systems have quickly deployed innovative technology solutions to decrease personal protective equipment (PPE) use and augment patient care capabilities. Telehealth technology use is established in the ambulatory setting, but not yet widely deployed at scale for inpatient care. OBJECTIVES: This article presents and describes our experience with evaluating and implementing inpatient telehealth technologies in a large health care system with the goals of reducing use of PPE while enhancing communication for health care workers and patients. METHODS: We discovered use cases for inpatient telehealth revealed as a result of an immense patient surge requiring large volumes of PPE. In response, we assessed various consumer products to address the use cases for our health system. RESULTS: We identified 13 use cases and eight device options. During device setup and implementation, challenges and solutions were identified in five areas: security/privacy, device availability and setup, device functionality, physical setup, and workflow and device usage. This enabled deployment of more than 1,800 devices for inpatient telehealth across seven hospitals with positive feedback from health care staff. CONCLUSION: Large-scale setup and distribution of consumer devices is feasible for inpatient telehealth use cases. Our experience highlights operational barriers and potential solutions for health systems looking to preserve PPE and enhance vital communication.