A Machine Learning Method for Allocating Scarce COVID-19 Monoclonal Antibodies.

Importance: During the COVID-19 pandemic, the effective distribution of limited treatments became a crucial policy goal. Yet, limited research exists using electronic health record data and machine learning techniques, such as policy learning trees (PLTs), to optimize the distribution of scarce therapeutics. Objective: To evaluate whether a machine learning PLT-based method of scarce resource allocation optimizes the treatment benefit of COVID-19 neutralizing monoclonal antibodies (mAbs) during periods of resource constraint. Design, Setting, and Participants: This retrospective cohort study used electronic health record data from October 1, 2021, to December 11, 2021, for the training cohort and data from June 1, 2021, to October 1, 2021, for the testing cohort. The cohorts included patients who had positive test results for SARS-CoV-2 and qualified for COVID-19 mAb therapy based on the US Food and Drug Administration's emergency use authorization criteria, ascertained from the patient electronic health record. Only some of the qualifying candidates received treatment with mAbs. Data were analyzed between from January 2023 to May 2024. Main Outcomes and Measures: The primary outcome was overall expected hospitalization, assessed as the potential reduction in overall expected hospitalization if the PLT-based allocation system was used. This was compared to observed allocation using risk differences. Results: Among 9542 eligible patients in the training cohort (5418 female [56.8%]; age distribution: 18-44 years, 4151 [43.5%]; 45-64 years, 3146 [33.0%]; and ≥65 years, 2245 [23.5%]), a total of 3862 (40.5%) received mAbs. Among 6248 eligible patients in the testing cohort (3416 female [54.7%]; age distribution: 18-44 years, 2827 [45.2%]; 45-64 years, 1927 [30.8%]; and ≥65 years, 1494 [23.9%]), a total of 1329 (21.3%) received mAbs. Treatment allocation using the trained PLT model led to an estimated 1.6% reduction (95% CI, -2.0% to -1.2%) in overall expected hospitalization compared to observed treatment allocation in the testing cohort. The visual assessment showed that the PLT-based point system had a larger reduction in 28-day hospitalization compared with the Monoclonal Antibody Screening Score (maximum overall hospitalization difference, -1.0% [95% CI, -1.3% to -0.7%]) in the testing cohort. Conclusions and Relevance: This retrospective cohort study proposes and tests a PLT method, which can be linked to a electronic health record data platform to improve real-time allocation of scarce treatments. Use of this PLT-based allocation method would have likely resulted in fewer hospitalizations across a population than were observed in usual care, with greater expected reductions than a commonly used point system.

Association between monoclonal antibody therapy, vaccination, and longer-term symptom resolution after acute COVID-19.

Effective therapies for reducing post-acute sequelae of COVID-19 (PASC) symptoms are lacking. Evaluate the association between monoclonal antibody (mAb) treatment or COVID-19 vaccination with symptom recovery in COVID-19 participants. The longitudinal survey-based cohort study was conducted from April 2021 to January 2022 across a multihospital Colorado health system. Adults ≥18 years with a positive SARS-CoV-2 test were included. Primary exposures were mAb treatment and COVID-19 vaccination. The primary outcome was time to symptom resolution after SARS-CoV-2 positive test date. The secondary outcome was hospitalization within 28 days of a positive SARS-CoV-2 test. Analysis included 1612 participants, 539 mAb treated, and 486 with ≥2 vaccinations. Time to symptom resolution was similar between mAb treated versus untreated patients (adjusted hazard ratio (aHR): 0.90, 95% CI: 0.77-1.04). Time to symptom resolution was shorter for patients who received ≥2 vaccinations compared to those unvaccinated (aHR: 1.56, 95% CI: 1.31-1.88). 28-day hospitalization risk was lower for patients receiving mAb therapy (adjusted odds ratio [aOR]: 0.31, 95% CI: 0.19-0.50) and ≥2 vaccinations (aOR: 0.33, 95% CI: 0.20-0.55), compared with untreated or unvaccinated status. Analysis included 1612 participants, 539 mAb treated, and 486 with ≥2 vaccinations. Time to symptom resolution was similar between mAb treated versus untreated patients (adjusted hazard ratio (aHR): 0.90, 95% CI: 0.77-1.04). Time to symptom resolution was shorter for patients who received ≥2 vaccinations compared to those unvaccinated (aHR: 1.56, 95% CI: 1.31-1.88). 28-day hospitalization risk was lower for patients receiving mAb therapy (adjusted odds ratio [aOR]: 0.31, 95% CI: 0.19-0.50) and ≥2 vaccinations (aOR: 0.33, 95% CI: 0.20-0.55), compared with untreated or unvaccinated status. COVID-19 vaccination, but not mAb therapy, was associated with a shorter time to symptom resolution. Both were associated with lower 28-day hospitalization.

Real-world use of nirmatrelvir-ritonavir in COVID-19 outpatients during BQ.1, BQ.1.1., and XBB.1.5 predominant omicron variants in three U.S. health systems: a retrospective cohort study.

Background: Ritonavir-boosted Nirmatrelvir (NMV-r), a protease inhibitor with in vitro activity against SARS-CoV-2, can reduce risk of progression to severe COVID-19 among high-risk individuals infected with earlier variants, but less is known about its effectiveness against omicron variants BQ.1/BQ.1.1/XBB.1.5. We sought to evaluate effectiveness of NMV-r in BQ.1/BQ.1.1/XBB.1.5 omicron variants by comparing hospitalisation rates to NMV-r treated patients during a previous omicron phase and to contemporaneous untreated patients. Methods: We conducted a retrospective observational cohort study of non-hospitalised adult patients with SARS-CoV-2 infection using real-world data from three health systems in Colorado and Utah, and compared hospitalisation rates in NMV-r-treated patients in a BA.2/BA.2.12.1/BA.4/BA.5 variant-predominant (first) phase (April 3, 2022-November 12, 2022), with a BQ.1/BQ.1.1/XBB.1.5 variant-predominant (second) phase (November 13, 2022-March 7, 2023). In the primary analysis, we used Firth logistic regression with a two-segment (phase) linear time model, and pre-specified non-inferiority bounds for the mean change between segments. In a pre-specified secondary analysis, we inferred NMV-r effectiveness in a cohort of treated and untreated patients infected during the second phase. For both analyses, the primary outcome was 28-day all-cause hospitalisation. Subgroup analyses assessed treatment effect heterogeneity. Findings: In the primary analysis, 28-day all-cause hospitalisation rates in NMV-r treated patients in the second phase (n = 12,061) were non-inferior compared to the first phase (n = 25,075) (198 [1.6%] vs. 345 [1.4%], adjusted odds ratio (aOR): 0.76 [95% CI 0.54-1.06]), with consistent results among secondary endpoints and key subgroups. Secondary cohort analyses revealed additional evidence for NMV-r effectiveness, with reduced 28-day hospitalisation rates among treated patients compared to untreated patients during a BQ.1/BQ.1.1/XBB.1.5 predominant phase (198/12,061 [1.6%] vs. 376/10,031 [3.7%], aOR 0.34 [95% CI 0.30-0.38), findings robust to additional sensitivity analyses. Interpretation: Real-world evidence from major US healthcare systems suggests ongoing NMV-r effectiveness in preventing hospitalisation during a BQ.1/BQ.1.1/XBB.1.5-predominant phase in the U.S, supporting its continued use in similar patient populations. Funding: U.S. National Institutes of Health.

A multimodal strategy to improve race/ethnic group equity in administration of neutralizing monoclonal antibody treatment for COVID-19 outpatients.

Introduction: Racial and ethnic minority groups have higher rates of SARS-CoV-2 infection, severe illness, and death; however, they receive monoclonal antibody (mAb) treatment at lower rates than non-Hispanic White patients. We report data from a systematic approach to improve equitable provision of COVID-19 neutralizing monoclonal antibody treatment. Methods: Treatment was administered at a community health urgent care clinic affiliated with a safety-net urban hospital. The approach included a stable treatment supply, a same-day test and treat model, a referral process, patient outreach, and financial support. We analyzed the race/ethnicity data descriptively and compared proportions using a chi-square test. Results: Over 17 months, 2524 patients received treatment. Compared to the demographics of county COVID-19-positive cases, a greater proportion of patients who received mAb treatment were Hispanic (44.7% treatment vs. 36.5% positive cases, p < 0.001), a lower proportion were White Non-Hispanic (40.7% treatment vs. 46.3% positive cases, p < 0.001), equal proportion were Black (8.2% treatment vs. 7.4% positive cases, P = 0.13), and equal proportion occurred for other race patients. Discussion: Implementation of multiple systematic strategies to administer COVID-19 monoclonal antibodies resulted in an equitable race/ethnic distribution of treatment.

Housing Status as a Predictor for Outpatient Care Following an Emergency or Urgent Care Encounter with a Behavioral Health Diagnosis: A Multivariable Analysis.

Individuals without stable housing experience high rates of mental illness and seek behavioral health care in emergency care settings. Little is known about the effect of homelessness on outpatient follow-up after utilizing emergency or urgent care for behavioral health care. Patient encounters with behavioral health diagnoses among 7 emergency department (ED) or urgent care (UC) locations over 4 years were used to determine the correlation between housing status and outpatient follow-up within 90 days. Of 1,160,386 visits by 269,615 unique patients, 55,738 (23%) encounters included a behavioral health diagnosis. Patients with stable housing were twice as likely to follow up with a primary care provider (PCP) and with an outpatient behavioral health provider than patients without housing (aOR 2.60; aOR 2.00, p < 0.0001). Homelessness is associated with difficulty in accessing follow-up behavioral health care. UCs and EDs may use specific interventions to improve outpatient follow-up.

An Innovative Model of Urgent Care for the Underserved: A Case Report of an Urban Hospital-Affiliated Federally Qualified Health Center Urgent Care Clinic.

Medically underserved patients experience significant barriers to affordable acute care. This brief report describes an innovative urban hospital-affiliated federally qualified health center urgent care clinic that successfully meets a medically underserved population's need for accessible, appropriate, and affordable acute care.

Association Between In-Clinic Opioid Administration and Discharge Opioid Prescription in Urgent Care: a Retrospective Cohort Study.

BACKGROUND: Emergency departments increasingly use nonopioid analgesics to manage acute pain and minimize opioid-related harms. Urgent care centers are expanding to lower costs and provide efficient access to healthcare. General internists increasingly work in these acute care settings. Much is known about opioid prescribing in the primary care, inpatient, and emergency department setting. Little is known about opioid prescribing in the urgent care setting and associated outcomes. OBJECTIVES: To assess the association between in-clinic opioid administration and opioid receipt at clinic discharge and on progression to chronic opioid use among urgent care patients. DESIGN: Retrospective cohort study. PARTICIPANTS: Patients, 20 years or older and not on opioid medications, who presented for care to an urgent care clinic within a safety-net healthcare system from June 1, 2016, to April 30, 2019. MAIN MEASURES: We examined the association between the in-clinic administration of oral or intravenous opioids and opioid receipt at clinic discharge. We also examined the association between in-clinic opioid administration and progression to chronic opioid use after six months. KEY RESULTS: The study sample included 34,978 patients, of which 13.8% (n = 4842) received in-clinic opioids and 86.2% (n = 30,136) did not receive in-clinic opioids. After adjusting for age, gender, race/ethnicity, insurance, and pain diagnosis, patients who received in-clinic opioids were more likely to receive opioids at discharge compared to patients who did not receive in-clinic opioids (aOR = 12.30, 95% CI 11.44-13.23). Among a selected cohort of patients, in-clinic opioid administration was associated with progression to chronic opioid use (aOR = 2.12, 95% CI 1.66-2.71). CONCLUSIONS: In-clinic opioid administration was strongly associated with opioid receipt at discharge and progression to chronic opioid use. Increased use of nonopioid analgesics in urgent care could likely reduce this association and limit opioids available for diversion, overdose, and death.