Post-Hospitalization Home Monitoring Programs During the COVID-19 Pandemic: Survey Results from the Hospital Medicine Re-engineering Network (HOMERuN).

BACKGROUND: During the coronavirus disease 2019 (COVID-19) pandemic, hospitals and healthcare systems launched innovative responses to emerging needs. The creation and use of programs to remotely follow patient clinical status and recovery after COVID-19 hospitalization has not been thoroughly described. OBJECTIVE: To characterize deployment of remote post-hospital discharge monitoring programs during the COVID-19 pandemic METHODS: Electronic surveys were administered to leaders of 83 US academic hospitals in the Hospital Medicine Re-engineering Network (HOMERuN). An initial survey was completed in March 2021 with follow-up survey completed in July 2022. RESULTS: There were 35 responses to the initial survey (42%) and 15 responses to the follow-up survey (43%). Twenty-two (63%) sites reported a post-discharge monitoring program, 16 of which were newly developed for COVID-19. Physiologic monitoring devices such as pulse oximeters were often provided. Communication with medical teams was often via telephone, with moderate use of apps or electronic medical record integration. Programs launched most commonly between January and June 2020. Only three programs were still active at the time of follow-up survey. CONCLUSIONS: Our findings demonstrate rapid, ad hoc development of post-hospital discharge monitoring programs during the COVID-19 pandemic but with little standardization or evaluation. Additional study could identify the benefits of these programs, instruct their potential application to other disease processes, and inform further development as part of emergency preparedness for upcoming crises.

Analysis of Clinical Criteria for Discharge Among Patients Hospitalized for COVID-19: Development and Validation of a Risk Prediction Model.

BACKGROUND: Patients hospitalized with COVID-19 can clinically deteriorate after a period of initial stability, making optimal timing of discharge a clinical and operational challenge. OBJECTIVE: To determine risks for post-discharge readmission and death among patients hospitalized with COVID-19. DESIGN: Multicenter retrospective observational cohort study, 2020-2021, with 30-day follow-up. PARTICIPANTS: Adults admitted for care of COVID-19 respiratory disease between March 2, 2020, and February 11, 2021, to one of 180 US hospitals affiliated with the HCA Healthcare system. MAIN MEASURES: Readmission to or death at an HCA hospital within 30 days of discharge was assessed. The area under the receiver operating characteristic curve (AUC) was calculated using an internal validation set (33% of the HCA cohort), and external validation was performed using similar data from six academic centers associated with a hospital medicine research network (HOMERuN). KEY RESULTS: The final HCA cohort included 62,195 patients (mean age 61.9 years, 51.9% male), of whom 4704 (7.6%) were readmitted or died within 30 days of discharge. Independent risk factors for death or readmission included fever within 72 h of discharge; tachypnea, tachycardia, or lack of improvement in oxygen requirement in the last 24 h; lymphopenia or thrombocytopenia at the time of discharge; being ≤ 7 days since first positive test for SARS-CoV-2; HOSPITAL readmission risk score ≥ 5; and several comorbidities. Inpatient treatment with remdesivir or anticoagulation were associated with lower odds. The model's AUC for the internal validation set was 0.73 (95% CI 0.71-0.74) and 0.66 (95% CI 0.64 to 0.67) for the external validation set. CONCLUSIONS: This large retrospective study identified several factors associated with post-discharge readmission or death in models which performed with good discrimination. Patients 7 or fewer days since test positivity and who demonstrate potentially reversible risk factors may benefit from delaying discharge until those risk factors resolve.

Hospitalist Shared Leadership for Safety, Health, and Well-Being at Work: United States, 2022‒2023.

We assessed how hospitalists frame workplace safety, health, and well-being (SHW); their perception of hospital supports for SHW; and whether and how they are sharing leadership responsibility for each other's SHW. Our findings highlight the important role of local support for hospitalist SHW and reveal the systemic, hospital-wide problems that may impede their SHW. We believe that positioning hospitalists as leaders for SHW will result in systems-wide changes in practices to support the SHW of all care team members. (Am J Public Health. 2024;114(S2):S162-S166. https://doi.org/10.2105/AJPH.2024.307573).

Postdischarge Noninvasive Telemonitoring and Nurse Telephone Coaching Improve Outcomes in Heart Failure Patients With High Burden of Comorbidity.

BACKGROUND: Noninvasive telemonitoring and nurse telephone coaching (NTM-NTC) is a promising postdischarge strategy in heart failure (HF). Comorbid conditions and disease burden influence health outcomes in HF, but how comorbidity burden modulates the effectiveness of NTM-NTC is unknown. This study aims to identify patients with HF who may benefit from postdischarge NTM-NTC based on their burden of comorbidity. METHODS AND RESULTS: In the Better Effectiveness After Transition - Heart Failure trial, patients hospitalized for acute decompensated HF were randomized to postdischarge NTM-NTC or usual care. In this secondary analysis of 1313 patients with complete data, comorbidity burden was assessed by scoring complication and coexisting diagnoses from index admissions. Clinical outcomes included 30-day and 180-day readmissions, mortality, days alive, and combined days alive and out of the hospital. Patients had a mean of 5.7 comorbidities and were stratified into low (0-2), moderate (3-8), and high comorbidity (≥9) subgroups. Increased comorbidity burden was associated with worse outcomes. NTM-NTC was not associated with readmission rates in any comorbidity subgroup. Among high comorbidity patients, NTM-NTC was associated with significantly lower mortality at 30 days (hazard ratio 0.25, 95% confidence interval 0.07-0.90) and 180 days (hazard ratio 0.51, 95% confidence interval 0.27-0.98), as well as more days alive (160.1 vs 140.3, P = .029) and days alive out of the hospital (152.0 vs 133.2, P = .044) compared with usual care. CONCLUSIONS: Postdischarge NTM-NTC improved survival among patients with HF with a high comorbidity burden. Comorbidity burden may be useful for identifying patients likely to benefit from this management strategy.

Systemic Exposure, Metabolism, and Elimination of [14C]-Labeled Amino Lipid, Lipid 5, after a Single Administration of mRNA Encapsulating Lipid Nanoparticles to Sprague-Dawley Rats.

The emerging therapeutic modality of lipid nanoparticle (LNP)-encapsulated mRNAs has demonstrated promising clinical results when used as vaccines and is currently being tested in formulations for a wide range of targeted chronic disease treatments. These therapeutics are multicomponent assemblages of well-characterized naturally occurring molecules in addition to xenobiotic molecules, whose in vivo distributions are poorly understood. Here, the metabolic outcome and in vivo elimination of heptadecan-9-yl 8-((2-hydroxyethyl) (8-(nonyloxy)-8-oxooctyl)amino)octanoate (Lipid 5), a key xenobiotic amino lipid in LNP formulations, were assessed after intravenous administration of 14C-labeled Lipid 5 to Sprague-Dawley rats. Intact Lipid 5 was predominantly cleared from plasma within 10 hour after dosing, with only small quantities (<1% of 14C dose) of a single diacid metabolite detected after 10 hour. Lipid 5 was rapidly metabolized via ester hydrolysis into aliphatic alcohols and diacidic amino head group moieties, which were further metabolized via ß-oxidation. Overall, >90% of the administered Lipid 5-derived 14C was recovered in urine (65%) and feces (35%), predominantly as oxidative metabolites, within 72 hour after dosing, indicating rapid renal and hepatic elimination. In vitro metabolite identification after incubation with human, nonhuman primate, and rat hepatocytes showed similar metabolites to those found in vivo. No meaningful differences were observed in Lipid 5 metabolism or elimination by sex. In conclusion, Lipid 5, a critical amino lipid component of LNPs for mRNA therapeutic delivery, showed minimal exposure, rapid metabolism, and near-complete elimination of 14C metabolites in rats. SIGNIFICANCE STATEMENT: Heptadecan-9-yl 8-((2-hydroxyethyl) (8-(nonyloxy)-8-oxooctyl)amino)octanoate (Lipid 5) is a key component of lipid nanoparticles used for the delivery of mRNA-based medicines; understanding the rates and routes of its clearance is crucial to assessing its long-term safety in lipid nanoparticle technology. This study conclusively established the rapid metabolism, and near-complete elimination of intravenously administered [14C]Lipid 5 in rats via both liver and kidney as oxidative metabolites derived from ester hydrolysis and subsequent ß-oxidation.

Biodistribution of Lipid 5, mRNA, and Its Translated Protein Following Intravenous Administration of mRNA-Encapsulated Lipid Nanoparticles in Rats.

RNA-based therapeutics and vaccines represent a novel and expanding class of medicines, the success of which depends on the encapsulation and protection of mRNA molecules in lipid nanoparticle (LNP)-based carriers. With the development of mRNA-LNP modalities, which can incorporate xenobiotic constituents, extensive biodistribution analyses are necessary to better understand the factors that influence their in vivo exposure profiles. This study investigated the biodistribution of heptadecan-9-yl 8-((2-hydroxyethyl)(8-(nonyloxy)-8-oxooctyl)amino)octanoate (Lipid 5)-a xenobiotic amino lipid-and its metabolites in male and female pigmented (Long-Evans) and nonpigmented (Sprague Dawley) rats by using quantitative whole-body autoradiography (QWBA) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) techniques. After intravenous injection of Lipid 5-containing LNPs, 14C-containing Lipid 5 ([14C]Lipid 5) and radiolabeled metabolites ([14C]metabolites) were rapidly distributed, with peak concentrations reached within 1 hour in most tissues. After 10 hours, [14C]Lipid 5 and [14C]metabolites concentrated primarily in the urinary and digestive tracts. By 24 hours, [14C]Lipid 5 and [14C]metabolites were localized almost exclusively in the liver and intestines, with few or no concentrations detected in non-excretory systems, which is suggestive of hepatobiliary and renal clearance. [14C]Lipid 5 and [14C]metabolites were completely cleared within 168 hours (7 days). Biodistribution profiles were similar between QWBA and LC-MS/MS techniques, pigmented and nonpigmented rats, and male and female rats, excluding the reproductive organs. In conclusion, the rapid clearance through known excretory systems, with no evidence of redistribution for Lipid 5 or accumulation of [14C]metabolites, provides confidence for the safe and effective use of Lipid 5-containing LNPs. SIGNIFICANCE STATEMENT: This study demonstrates the rapid, systemic distribution of intact and radiolabeled metabolites of Lipid 5, a xenobiotic amino lipid component of novel mRNA-LNP medicines, and its effective clearance without substantial redistribution after intravenous administration; additionally, findings were consistent between different mRNAs encapsulated within LNPs of similar composition. This study confirms the applicability of current analytical methods for lipid biodistribution analyses, and taken together with appropriate safety studies, supports the continued use of Lipid 5 in mRNA-medicines.

Exploring the Impact of COVID-19 on Women Hospitalists: A Mixed-Gender Qualitative Analysis.

BACKGROUND: Women physicians have faced persistent challenges, including gender bias, salary inequities, a disproportionate share of caregiving and domestic responsibilities, and limited representation in leadership. Data indicate the COVID-19 pandemic further highlighted and exacerbated these inequities. OBJECTIVE: To understand the pandemic's impact on women physicians and to brainstorm solutions to better support women physicians. DESIGN: Mixed-gender semi-structured focus groups. PARTICIPANTS: Hospitalists in the Hospital Medicine Reengineering Network (HOMERuN). APPROACH: Six semi-structured virtual focus groups were held with 22 individuals from 13 institutions comprised primarily of academic hospitalist physicians. Rapid qualitative methods including templated summaries and matrix analysis were applied to identify major themes and subthemes. KEY RESULTS: Four key themes emerged: (1) the pandemic exacerbated perceived gender inequities, (2) women's academic productivity and career development were negatively impacted, (3) women held disproportionate roles as caregivers and household managers, and (4) institutional pandemic responses were often misaligned with workforce needs, especially those of women hospitalists. Multiple interventions were proposed including: creating targeted workforce solutions and benefits to address the disproportionate caregiving burden placed on women, addressing hospitalist scheduling and leave practices, ensuring promotion pathways value clinical and COVID-19 contributions, creating transparency around salary and non-clinical time allocation, and ensuring women are better represented in leadership roles. CONCLUSIONS: Hospitalists perceived and experienced that women physicians faced negative impacts from the pandemic in multiple domains including leadership opportunities and scholarship, while also shouldering larger caregiving duties than men. There are many opportunities to improve workplace conditions for women; however, current institutional efforts were perceived as misaligned to actual needs. Thus, policy and programmatic changes, such as those proposed by this cohort of hospitalists, are needed to advance equity in the workplace.

Prevalence and Causes of Diagnostic Errors in Hospitalized Patients Under Investigation for COVID-19.

BACKGROUND: The COVID-19 pandemic required clinicians to care for a disease with evolving characteristics while also adhering to care changes (e.g., physical distancing practices) that might lead to diagnostic errors (DEs). OBJECTIVE: To determine the frequency of DEs and their causes among patients hospitalized under investigation (PUI) for COVID-19. DESIGN: Retrospective cohort. SETTING: Eight medical centers affiliated with the Hospital Medicine ReEngineering Network (HOMERuN). TARGET POPULATION: Adults hospitalized under investigation (PUI) for COVID-19 infection between February and July 2020. MEASUREMENTS: We randomly selected up to 8 cases per site per month for review, with each case reviewed by two clinicians to determine whether a DE (defined as a missed or delayed diagnosis) occurred, and whether any diagnostic process faults took place. We used bivariable statistics to compare patients with and without DE and multivariable models to determine which process faults or patient factors were associated with DEs. RESULTS: Two hundred and fifty-seven patient charts underwent review, of which 36 (14%) had a diagnostic error. Patients with and without DE were statistically similar in terms of socioeconomic factors, comorbidities, risk factors for COVID-19, and COVID-19 test turnaround time and eventual positivity. Most common diagnostic process faults contributing to DE were problems with clinical assessment, testing choices, history taking, and physical examination (all p < 0.01). Diagnostic process faults associated with policies and procedures related to COVID-19 were not associated with DE risk. Fourteen patients (35.9% of patients with errors and 5.4% overall) suffered harm or death due to diagnostic error. LIMITATIONS: Results are limited by available documentation and do not capture communication between providers and patients. CONCLUSION: Among PUI patients, DEs were common and not associated with pandemic-related care changes, suggesting the importance of more general diagnostic process gaps in error propagation.

Cirrhosis Inpatients Receive More Opioids and Fewer Nonopioid Analgesics Than Patients Without Cirrhosis.

GOALS/BACKGROUND: Pain is common among cirrhosis patients, particularly those hospitalized with acute illness. Managing pain in this population is challenging due to concern for adverse events and lack of guidelines for analgesic use. We sought to characterize analgesic use among inpatients with cirrhosis compared with matched noncirrhosis controls, as well as hospital-level variation in prescribing patterns. METHODS: We utilized the Vizient Clinical Database, which includes clinical and billing data from hospitalizations at >500 US academic medical centers. We identified cirrhosis patients hospitalized in 2017-2018, and a matched cohort of noncirrhosis patients. Types of analgesic given-acetaminophen (APAP), nonsteroidal anti-inflammatory drugs (NSAIDs), opioids, and adjuvants (eg, gabapentinoids, antidepressants) were defined from inpatient prescription records. Conditional logistic regression was used to associate cirrhosis diagnosis with analgesic use. RESULTS: Of 116,363 cirrhosis inpatients, 83% received at least 1 dose of an analgesic and 58% had regular inpatient analgesic use, rates that were clinically similar to noncirrhosis controls. Cirrhosis inpatients were half as likely to receive APAP (26% vs. 42%, P <0.01) or NSAIDs (3% vs. 7%, P <0.01), but were more likely to receive opioids (59% vs. 54%, P <0.01), particularly decompensated patients (60%). There was notable variation in analgesic prescribing patterns between hospitals, especially among cirrhosis patients. CONCLUSIONS: Analgesic use was common among inpatients, with similar rates among patients with and without cirrhosis. Cirrhosis patients-particularly decompensated patients-were less likely to receive APAP and NSAIDs and more likely to receive opioid analgesics. Because of lack of evidence-based guidance for management of cirrhosis patients with pain, providers may avoid nonopioid analgesics due to perceived risks and consequently may overutilize opioids in this high-risk population.

Expert-augmented machine learning.

Machine learning is proving invaluable across disciplines. However, its success is often limited by the quality and quantity of available data, while its adoption is limited by the level of trust afforded by given models. Human vs. machine performance is commonly compared empirically to decide whether a certain task should be performed by a computer or an expert. In reality, the optimal learning strategy may involve combining the complementary strengths of humans and machines. Here, we present expert-augmented machine learning (EAML), an automated method that guides the extraction of expert knowledge and its integration into machine-learned models. We used a large dataset of intensive-care patient data to derive 126 decision rules that predict hospital mortality. Using an online platform, we asked 15 clinicians to assess the relative risk of the subpopulation defined by each rule compared to the total sample. We compared the clinician-assessed risk to the empirical risk and found that, while clinicians agreed with the data in most cases, there were notable exceptions where they overestimated or underestimated the true risk. Studying the rules with greatest disagreement, we identified problems with the training data, including one miscoded variable and one hidden confounder. Filtering the rules based on the extent of disagreement between clinician-assessed risk and empirical risk, we improved performance on out-of-sample data and were able to train with less data. EAML provides a platform for automated creation of problem-specific priors, which help build robust and dependable machine-learning models in critical applications.

Adaptability on Shifting Ground: a Rapid Qualitative Assessment of Multi-institutional Inpatient Surge Planning and Workforce Deployment During the COVID-19 Pandemic.

BACKGROUND: During the initial wave of COVID-19 hospitalizations, care delivery and workforce adaptations were rapidly implemented. In response to subsequent surges of patients, institutions have deployed, modified, and/or discontinued their workforce plans. OBJECTIVE: Using rapid qualitative methods, we sought to explore hospitalists' experiences with workforce deployment, types of clinicians deployed, and challenges encountered with subsequent iterations of surge planning during the COVID-19 pandemic across a collaborative of hospital medicine groups. APPROACH: Using rapid qualitative methods, focus groups were conducted in partnership with the Hospital Medicine Reengineering Network (HOMERuN). We interviewed physicians, advanced practice providers (APP), and physician researchers about (1) ongoing adaptations to the workforce as a result of the COVID-19 pandemic, (2) current struggles with workforce planning, and (3) evolution of workforce planning. KEY RESULTS: We conducted five focus groups with 33 individuals from 24 institutions, representing 52% of HOMERuN sites. A variety of adaptations was described by participants, some common across institutions and others specific to the institution's location and context. Adaptations implemented shifted from the first waves of COVID patients to subsequent waves. Three global themes also emerged: (1) adaptability and comfort with dynamic change, (2) the importance of the unique hospitalist skillset for effective surge planning and redeployment, and (3) the lack of universal solutions. CONCLUSIONS: Hospital workforce adaptations to the COVID pandemic continued to evolve. While few approaches were universally effective in managing surges of patients, and successful adaptations were highly context dependent, the ability to navigate a complex system, adaptability, and comfort in a chaotic, dynamic environment were themes considered most critical to successful surge management. However, resource constraints and sustained high workload levels raised issues of burnout.

Discharge Practices for COVID-19 Patients: Rapid Review of Published Guidance and Synthesis of Documents and Practices at 22 US Academic Medical Centers.

BACKGROUND: There are currently no evidence-based guidelines that provide standardized criteria for the discharge of COVID-19 patients from the hospital. OBJECTIVE: To address this gap in practice guidance, we reviewed published guidance and collected discharge protocols and procedures to identify and synthesize common practices. DESIGN: Rapid review of existing guidance from US and non-US public health organizations and professional societies and qualitative review using content analysis of discharge documents collected from a national sample of US academic medical centers with follow-up survey of hospital leaders SETTING AND PARTICIPANTS: We reviewed 65 websites for major professional societies and public health organizations and collected documents from 22 Academic Medical Centers (AMCs) in the US participating in the HOspital MEdicine Reengineering Network (HOMERuN). RESULTS: We synthesized data regarding common practices around 5 major domains: (1) isolation and transmission mitigation; (2) criteria for discharge to non-home settings including skilled nursing, assisted living, or homeless; (3) clinical criteria for discharge including oxygenation levels, fever, and symptom improvement; (4) social support and ability to perform activities of daily living; (5) post-discharge instructions, monitoring, and follow-up. LIMITATIONS: We used streamlined methods for rapid review of published guidance and collected discharge documents only in a focused sample of US academic medical centers. CONCLUSION: AMCs studied showed strong consensus on discharge practices for COVID-19 patients related to post-discharge isolation and transmission mitigation for home and non-home settings. There was high concordance among AMCs that discharge practices should address COVID-19-specific factors in clinical, functional, and post-discharge monitoring domains although definitions and details varied.

Reporting and Implementing Interventions Involving Machine Learning and Artificial Intelligence.

Increasingly, interventions aimed at improving care are likely to use such technologies as machine learning and artificial intelligence. However, health care has been relatively late to adopt them. This article provides clinical examples in which machine learning and artificial intelligence are already in use in health care and appear to deliver benefit. Three key bottlenecks toward increasing the pace of diffusion and adoption are methodological issues in evaluation of artificial intelligence-based interventions, reporting standards to enable assessment of model performance, and issues that need to be addressed for an institution to adopt these interventions. Methodological best practices will include external validation, ideally at a different site; use of proactive learning algorithms to correct for site-specific biases and increase robustness as algorithms are deployed across multiple sites; addressing subgroup performance; and communicating to providers the uncertainty of predictions. Regarding reporting, especially important issues are the extent to which implementing standardized approaches for introducing clinical decision support has been followed, describing the data sources, reporting on data assumptions, and addressing biases. Although most health care organizations in the United States have adopted electronic health records, they may be ill prepared to adopt machine learning and artificial intelligence. Several steps can enable this: preparing data, developing tools to get suggestions to clinicians in useful ways, and getting clinicians engaged in the process. Open challenges and the role of regulation in this area are briefly discussed. Although these techniques have enormous potential to improve care and personalize recommendations for individuals, the hype regarding them is tremendous. Organizations will need to approach this domain carefully with knowledgeable partners to obtain the hoped-for benefits and avoid failures.

Randomized Controlled Trials of Electronic Health Record Interventions: Design, Conduct, and Reporting Considerations.

Electronic health record (EHR) systems can be configured to deliver novel EHR interventions that influence clinical decision making and to support efficient randomized controlled trials (RCTs) designed to evaluate the effectiveness, safety, and costs of those interventions. In designing RCTs of EHR interventions, one should carefully consider the unit of randomization (for example, patient, encounter, clinician, or clinical unit), balancing concerns about contamination of an intervention across randomization units within clusters (for example, patients within clinical units) against the superior control of measured and unmeasured confounders that comes with randomizing a larger number of units. One should also consider whether the key computational assessment components of the EHR intervention, such as a predictive algorithm used to target a subgroup for decision support, should occur before randomization (so that only 1 subgroup is randomized) or after randomization (including all subgroups). When these components are applied after randomization, one must consider expected heterogeneity in the effect of the differential decision support across subgroups, which has implications for overall impact potential, analytic approach, and sample size planning. Trials of EHR interventions should be reviewed by an institutional review board, but may not require patient-level informed consent when the interventions being tested can be considered minimal risk or quality improvement, and when clinical decision making is supported, rather than controlled, by an EHR intervention. Data and safety monitoring for RCTs of EHR interventions should be conducted to guide institutional pragmatic decision making about implementation and ensure that continuing randomization remains justified. Reporting should follow the CONSORT (Consolidated Standards of Reporting Trials) Statement, with extensions for pragmatic trials and cluster RCTs when applicable, and should include detailed materials to enhance reproducibility.

The Effect of Rehospitalization and Emergency Department Visits on Subsequent Adherence to Weight Telemonitoring.

BACKGROUND: Weight telemonitoring may be an effective way to improve patients' ability to manage heart failure and prevent unnecessary utilization of health services. However, the effectiveness of such interventions is dependent upon patient adherence. OBJECTIVE: The purpose of this study was to determine how adherence to weight telemonitoring changes in response to 2 types of events: hospital readmissions and emergency department visits. METHODS: The Better Effectiveness After Transition-Heart Failure trial examined the effectiveness of a remote telemonitoring intervention compared with usual care for patients discharged to home after hospitalization for decompensated heart failure. Participants were followed for 180 days and were instructed to transmit weight readings daily. We used Poisson regression to determine the within-person effects of events on subsequent adherence. RESULTS: A total of 625 events took place during the study period. Most of these events were rehospitalizations (78.7%). After controlling for the number of previous events and discharge to a skilled nursing facility, the rate for adherence decreased by nearly 20% in the 2 weeks after a hospitalization compared with the 2 weeks before (adjusted rate ratio, 0.81; 95% confidence interval: 0.77-0.86; P < .001). CONCLUSIONS: Experiencing a rehospitalization had the effect of diminishing adherence to daily weighing. Providers using telemonitoring to monitor decompensation and manage medications should take advantage of the potential "teachable moment" during hospitalization to reinforce the importance of adherence.

Acute Cerebellar Ataxia in COVID-19 Infection: A Case Report.

BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) has been widely reported to cause symptoms such as fever, cough, sore throat, fatigue, and shortness of breath. Neurologic complications have not been widely reported without associated respiratory symptoms. These neurologic manifestations have been found mostly in the elderly. There has been no report of ataxia or COVID-19 cerebellitis in the young adult population without associated respiratory symptoms. CASE REPORT: Here we report the case of a 30-year-old patient who presented with isolated cerebellar symptoms and was diagnosed with COVID-19 cerebellitis. WHY SHOULD AN EMERGENCY PHYSICIAN BE AWARE OF THIS?: It is important for emergency physicians to know that COVID-19 can have many clinical manifestations and to have a high level of suspicion with acute neurologic symptoms.

Letting a Good Crisis Go to Waste.

The widespread implementation of electronic health records (EHRs) was predicated on hopes that they would rapidly improve care, but initial experiences have been disappointing and thought to be a key part of physician dissatisfaction and burnout. The crisis created by EHR implementation is only in part due to EHRs themselves, and might also be viewed as a crisis that has served to surface longstanding problems in healthcare-ones that if grappled with, will lead to more rapidly effective digital transformation.

Best practices in implementing inpatient pediatric asthma pathways: a qualitative study.

Objective: Clinical pathways (operational versions of practice guidelines) can improve guideline adherence and quality of care for children hospitalized with asthma. However, there is limited guidance on how to implement pathways successfully. Our objective was to identify potential best practices in pathway implementation.Methods: In a previous observational study, we identified higher and lower performing children's hospitals based on hospital-level changes in asthma patient length of stay after implementation of a pathway. In this qualitative study, we conducted semi-structured interviews with a purposive sample of healthcare providers involved in pathway implementation at these hospitals. We used constant comparative methods to develop a conceptual model of potential best practices in implementation.Results: Healthcare providers (n = 24) from 6 higher performing and 2 lower performing hospitals were interviewed about pathway implementation. We identified several practices that addressed barriers and promoted successful pathway implementation: (1) utilizing quality improvement (QI) methodology and a data-driven approach helped overcome inertia of current practice; (2) getting teams to commit to shared goals around asthma care helped overcome disagreements in the implementation process; (3) integrating pathways into the electronic medical record decreased some burdens of implementation; (4) leveraging multidisciplinary teams by developing protocols for nurses and/or respiratory therapists to titrate medications reduced variability in provider practice; and (5) engaging hospital leaders with pathway implementation teams helped secure crucial resources.Conclusions: We identified several potential best practices to support pathway implementation. Hospitals implementing pathways should consider applying these strategies to better ensure success in improving quality of asthma care for children.

Do the unlabeled response categories of the Minnesota Living with Heart Failure Questionnaire satisfy the monotonicity assumption of simple-summated scoring?

PURPOSE: Half of the 21-item Minnesota Living with Heart Failure Questionnaire (MLHFQ) response categories are labeled (0 = No, 1 = Very little, 5 = Very much) and half are not (2, 3, and 4). We hypothesized that the unlabeled response options would not be more likely to be chosen at some place along the scale continuum than other response options and, therefore, not satisfy the monotonicity assumption of simple-summated scoring. METHODS: We performed exploratory and confirmatory factor analyses of the MLHFQ items in a sample of 1437 adults in the Better Effectiveness After Transition-Heart Failure study. We evaluated the unlabeled response options using item characteristic curves from item response theory-graded response models for MLHFQ physical and emotional health scales. Then, we examined the impact of collapsing response options on correlations of scale scores with other variables. RESULTS: The sample was 46% female; 71% aged 65 or older; 11% Hispanic, 22% Black, 54% White, and 12% other. The unlabeled response options were rarely chosen. The standard approach to scoring and scores obtained by collapsing adjacent response categories yielded similar associations with other variables, indicating that the existing response options are problematic. CONCLUSIONS: The unlabeled MLHFQ response options do not meet the assumptions of simple-summated scoring. Further assessment of the performance of the unlabeled response options and evaluation of alternative scoring approaches is recommended. Adding labels for response options in future administrations of the MLHFQ should be considered.

Patient Recommendations to Improve the Implementation of and Engagement With Portals in Acute Care: Hospital-Based Qualitative Study.

BACKGROUND: The inclusion of patient portals into electronic health records in the inpatient setting lags behind progress in the outpatient setting. OBJECTIVE: The aim of this study was to understand patient perceptions of using a portal during an episode of acute care and explore patient-perceived barriers and facilitators to portal use during hospitalization. METHODS: We utilized a mixed methods approach to explore patient experiences in using the portal during hospitalization. All patients received a tablet with a brief tutorial, pre- and postuse surveys, and completed in-person semistructured interviews. Qualitative data were coded using thematic analysis to iteratively develop 18 codes that were integrated into 3 themes framed as patient recommendations to hospitals to improve engagement with the portal during acute care. Themes from these qualitative data guided our approach to the analysis of quantitative data. RESULTS: We enrolled 97 participants: 53 (53/97, 55%) women, 44 (44/97, 45%) nonwhite with an average age of 48 years (19-81 years), and the average length of hospitalization was 6.4 days. A total of 47 participants (47/97, 48%) had an active portal account, 59 participants (59/97, 61%) owned a smartphone, and 79 participants (79/97, 81%) accessed the internet daily. In total, 3 overarching themes emerged from the qualitative analysis of interviews with these patients during their hospital stay: (1) hospitals should provide both access to a device and bring-your-own-device platform to access the portal; (2) hospitals should provide an orientation both on how to use the device and how to use the portal; and (3) hospitals should ensure portal content is up to date and easy to understand. CONCLUSIONS: Patients independently and consistently identified basic needs for device and portal access, education, and usability. Hospitals should prioritize these areas to enable successful implementation of inpatient portals to promote greater patient engagement during acute care. TRIAL REGISTRATION: ClinicalTrials.gov NCT00102401; https://clinicaltrials.gov/ct2/show/NCT01970852.