Performance of point-of-care severity scores to predict prognosis in patients admitted through the emergency department with COVID-19.

BACKGROUND: Identifying COVID-19 patients at the highest risk of poor outcomes is critical in emergency department (ED) presentation. Sepsis risk stratification scores can be calculated quickly for COVID-19 patients but have not been evaluated in a large cohort. OBJECTIVE: To determine whether well-known risk scores can predict poor outcomes among hospitalized COVID-19 patients. DESIGNS, SETTINGS, AND PARTICIPANTS: A retrospective cohort study of adults presenting with COVID-19 to 156 Hospital Corporation of America (HCA) Healthcare EDs, March 2, 2020, to February 11, 2021. INTERVENTION: Quick Sequential Organ Failure Assessment (qSOFA), Shock Index, National Early Warning System-2 (NEWS2), and quick COVID-19 Severity Index (qCSI) at presentation. MAIN OUTCOME AND MEASURES: The primary outcome was in-hospital mortality. Secondary outcomes included intensive care unit (ICU) admission, mechanical ventilation, and vasopressors receipt. Patients scored positive with qSOFA ≥ 2, Shock Index > 0.7, NEWS2 ≥ 5, and qCSI ≥ 4. Test characteristics and area under the receiver operating characteristics curves (AUROCs) were calculated. RESULTS: We identified 90,376 patients with community-acquired COVID-19 (mean age 64.3 years, 46.8% female). 17.2% of patients died in-hospital, 28.6% went to the ICU, 13.7% received mechanical ventilation, and 13.6% received vasopressors. There were 3.8% qSOFA-positive, 45.1% Shock Index-positive, 49.8% NEWS2-positive, and 37.6% qCSI-positive at ED-triage. NEWS2 exhibited the highest AUROC for in-hospital mortality (0.593, confidence interval [CI]: 0.588-0.597), ICU admission (0.602, CI: 0.599-0.606), mechanical ventilation (0.614, CI: 0.610-0.619), and vasopressor receipt (0.600, CI: 0.595-0.604). CONCLUSIONS: Sepsis severity scores at presentation have low discriminative power to predict outcomes in COVID-19 patients and are not reliable for clinical use. Severity scores should be developed using features that accurately predict poor outcomes among COVID-19 patients to develop more effective risk-based triage

Going From an Academic Medical Center to a Community Hospital: Patient Experiences with TransfersGoing from an academic medical center to a community hospital: Patient experiences with transfers

Academic medical centers (AMCs) often operate at or near full capacity, which leads to delays in care while smaller community hospitals may have excess capacity. To address this issue and to match patient needs to care acuity, patients may be transferred from an AMC emergency department for direct admission to a community hospital. We aimed to explore the experiences and perspectives of patients who were transferred. We randomly selected patients transferred between February 2019 and February 2020. We conducted structured thirty-minute interviews containing fixed response and open-ended questions focusing on the transfer rationale and experience, care quality, and patient financial outcomes. We used descriptive statistics to summarize questions with fixed responses and thematic analysis for open-ended questions. We interviewed a total of 40 patients. While most (88%) understood the rationale for transfer, many (60%) did not feel they had agency in the decision despite the voluntary nature of the program. Patients generally had a positive experience with the transfer (65%) and valued the expedited admission. However, some highlighted issues with transfer-related billing and the mismatch between the expectations of presenting to an academic hospital and the reality of being admitted to a community one. We conclude that patients are amenable to transfers for an expedited admission and understand the rationale for such transfers. However, participants should receive a clear explanation of benefits to them, guidance that the program is voluntary, and protection from financial risk Experience Framework This article is associated with the Patient, Family & Community Engagement lens of The Beryl Institute Experience Framework (https://www.theberylinstitute.org/ExperienceFramework). Access other PXJ articles related to this lens. Access other resources related to this lens

Development and evaluation of a concise nurse-driven non-pharmacological delirium reduction workflow for hospitalized patients: An interrupted time series study.

We created a concise nurse-driven delirium reduction workflow with the aim of reducing delirium rates and length of stay for hospitalized adults. Our nurse-driven workflow included five evidence-based daytime sunrise interventions (patient room lights on, blinds up, mobilization/out-of-bed, water within patients reach and patient awake) and five nighttime turndown interventions (patient room lights off, blinds down, television off, noise reduction and pre-set bedtime). Interventions were also chosen because fidelity could be quickly monitored twice daily without patient interruption from outside the room. To evaluate the workflow, we used an interrupted time series study design between 06/01/17 and 05/30/22 to determine if the workflow significantly reduced the units delirium rate and average length of stay. Our workflow is feasible to implement and monitor and initially significantly reduced delirium rates but not length of stay. However, the reduction in delirium rates were not sustained following the emergence of the COVID-19 pandemic

A Focused Screening and Clinical Intervention with Streamlined Outpatient Linkage for Hospitalized Patients with Opioid Use Disorder Experiencing Homelessness

BackgroundPatients experiencing homelessness have higher rates of substance use and related mortality, often driven by opioid overdose. Conversely, opioid use disorder (OUD) is a leading risk factor for homelessness. Our goal was to test the efficacy of an electronic health record (EHR) screen in identifying this vulnerable population during hospitalization and to assess the feasibility of a bundled intervention in improving opioid safety.MethodsWe assessed patients' housing status, substance use, previous MOUD treatment, barriers to MOUD treatment and readiness to take MOUD in and out of the hospital. For each post discharge follow up call, patients were asked about their MOUD status, barriers accessing treatment, current substance use, and housing status. We also assessed team members perceptions and experiences of the study.ResultsWe enrolled 32 patients with housing insecurity and OUD. The mean age was 44, the majority self-identified as male (78%), and mostly as White (56%) or Black (38%). At each follow up within the 6-months post-discharge, reach rates were low: 40% of enrollees answered at least 1 call and the highest reach rate (31% of patients) occurred at week 4. At the third and sixth-month follow ups, >50% of subjects still taking MOUD were also using opioids.ConclusionOur clinician augmented EHR screen accurately identified inpatients experiencing OUD and PEH. This intervention showed high rates of attrition among enrolled patients, even after providing cellphones. The majority of patients who were reached remained adherent to MOUD though they reported significant barriers

Automated telephone follow-up programs after hospital discharge: Do older adults engage with these programs?

BACKGROUND: Health systems have developed automated telephone call programs to screen and triage patients post-hospital discharge issues and concerns. The aims of our study were to determine whether and how older adults engage with automated post-hospital discharge telephone programs and to describe the prevalence of patient-reported post-discharge issues. METHODS: We identified all telephone calls made by an urban academic medical center as part of a post-hospital discharge program between May 1, 2018 and April 30, 2019. The program used automated telephone outreach to patients or their caregivers that included 11 distinct steps 3 days post-discharge. All adults discharged home from the hospital, were included, and we categorized patients into ≤64 years, 65-84 years, and ≥85 years age groups. We then compared call reach rate, completeness of 11-step calls and patient-reported issues between age groups. RESULTS: Eighteen thousand and seventy six patients were included. More patients 65-84 years old were reached compared to patients ≤64 years old (84.3% vs. 78.9%, AME 5.52%; 95%CI: 3.58%-7.45%). Completion rates of automated calls for those ≥85 years old were also high. Patients ≥85 years old were more likely to have questions about their follow-up plans and need assistance scheduling appointments compared to those ≤64 years old (19.0% vs. 11.9%, AME 7.0% (95%CI: 2.7%-11.3%). CONCLUSION: Post-hospital automated telephone calls are feasible and effective at reaching older adults. Future work should focus on improving discharge communication to ensure older adults are aware of their follow-up plan and appointments

A Focused Screening and Clinical Intervention with Streamlined Outpatient Linkage for Hospitalized Patients with Opioid Use Disorder Experiencing Homelessness

Background: Patients experiencing homelessness have higher rates of substance use and related mortality, often driven by opioid overdose. Conversely, opioid use disorder (OUD) is a leading risk factor for homelessness. Our goal was to test the efficacy of an electronic health record (EHR) screen in identifying this vulnerable population during hospitalization and to assess the feasibility of a bundled intervention in improving opioid safety. Methods: We assessed patients’ housing status, substance use, previous MOUD treatment, barriers to MOUD treatment and readiness to take MOUD in and out of the hospital. For each post discharge follow up call, patients were asked about their MOUD status, barriers accessing treatment, current substance use, and housing status. We also assessed team members perceptions and experiences of the study. Results: We enrolled 32 patients with housing insecurity and OUD. The mean age was 44, the majority self-identified as male (78%), and mostly as White (56%) or Black (38%). At each follow up within the 6-months post-discharge, reach rates were low: 40% of enrollees answered at least 1 call and the highest reach rate (31% of patients) occurred at week 4. At the third and sixth-month follow ups, >50% of subjects still taking MOUD were also using opioids. Conclusion: Our clinician augmented EHR screen accurately identified inpatients experiencing OUD and PEH. This intervention showed high rates of attrition among enrolled patients, even after providing cellphones. The majority of patients who were reached remained adherent to MOUD though they reported significant barriers

Timing of antibiotic treatment identifies distinct clinical presentations among patients presenting with suspected septic shock.

OBJECTIVE: Recent clinical guidelines for sepsis management emphasize immediate antibiotic initiation for suspected septic shock. Though hypotension is a high-risk marker of sepsis severity, prior studies have not considered the precise timing of hypotension in relation to antibiotic initiation and how clinical characteristics and outcomes may differ. Our objective was to evaluate antibiotic initiation in relation to hypotension to characterize differences in sepsis presentation and outcomes in patients with suspected septic shock. METHODS: Adults presenting to the emergency department (ED) June 2012-December 2018 diagnosed with sepsis (Sepsis-III electronic health record [EHR] criteria) and hypotension (non-resolving for ≥30 min, systolic blood pressure <90 mmHg) within 24 h. We categorized patients who received antibiotics before hypotension (early), 0-60 min after (immediate), and >60 min after (late) treatment. RESULTS: Among 2219 patients, 55% received early treatment, 13% immediate, and 32% late. The late subgroup often presented to the ED with hypotension (median 0 min) but received antibiotics a median of 191 min post-ED presentation. Clinical characteristics notable for this subgroup included higher prevalence of heart failure and liver disease (p < 0.05) and later onset of systemic inflammatory response syndrome (SIRS) criteria compared to early/immediate treatment subgroups (median 87 vs. 35 vs. 20 min, p < 0.0001). After adjustment, there was no difference in clinical outcomes among treatment subgroups. CONCLUSIONS: There was significant heterogeneity in presentation and timing of antibiotic initiation for suspected septic shock. Patients with later treatment commonly had hypotension on presentation, had more hypotension-associated comorbidities, and developed overt markers of infection (eg, SIRS) later. While these factors likely contribute to delays in clinician recognition of suspected septic shock, it may not impact sepsis outcomes