MétaCan
Menu
Back to cohort
Record W3131034160 · doi:10.3122/jabfm.2021.s1.200237

On the Front (Phone) Lines: Results of a COVID-19 Hotline

2021· article· en· W3131034160 on OpenAlex
David Margolius, Mary E. Hennekes, Jimmy Yao, Douglas Einstadter, Douglas Gunzler, Nabil El Hage Chehade, Ashwini R. Sehgal, Yasir Tarabichi, Adam T. Perzynski

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Journal of the American Board of Family Medicine · 2021
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 and healthcare impacts
Canadian institutionsPopulation Health Research Institute
Fundersnot available
KeywordsHotlineMedicineTelehealthEmergency departmentMedicaidMedical emergencyHealth careLogistic regressionEmergency medicineTelemedicineCohortPandemicFamily medicineCoronavirus disease 2019 (COVID-19)DiseaseInternal medicineInfectious disease (medical specialty)Nursing

Abstract

fetched live from OpenAlex

<h3>Background:</h3> Severe acute respiratory syndrome coronavirus (SARS-CoV-2) and the associated coronavirus disease of 2019 (COVID-19) have presented immense challenges for health care systems. Many regions have struggled to adapt to disruptions to health care practice and use systems that effectively manage the demand for services. <h3>Methods:</h3> This was a cohort study using electronic health records at a health care system in northeast Ohio that examined the effectiveness of the first 5 weeks of a 24/7 physician-staffed COVID-19 hotline including social care referrals for patients required to self-isolate. We describe clinical diagnosis, patient characteristics (age, sex race/ethnicity, smoking status, insurance status), and visit disposition. We use logistic regression to evaluate associations between patient characteristics, visit disposition and subsequent emergency department use, hospitalization, and SARS-Cov-2 PCR testing. <h3>Participants:</h3> In 5 weeks, 10,112 patients called the hotline (callers). Of these, 4213 (42%) were referred for a physician telehealth visit (telehealth patients). Mean age of callers was 42 years; 67% were female, 51% white, and 46% were on Medicaid/uninsured. <h3>Results:</h3> Common caller concerns included cough, fever, and shortness of breath. Most telehealth patients (79%) were advised to self-isolate at home, 14% were determined to be unlikely to have COVID-19, 3% were advised to seek emergency care, and 4% had miscellaneous other dispositions. A total of 287 patients (7%) had a subsequent emergency department visit, and 44 (1%) were hospitalized with a COVID-19 diagnosis. Of the callers, 482 (5%) had a COVID-19 test reported, with 69 (14%) testing positive. Among patients advised to stay at home, 83% had no further face-to-face visits. In multivariable results, only a physician recommendation to seek emergency care was associated with emergency department use (odds ratio = 4.73, 95% confidence interval = 1.37-16.39, <i>P</i> = .014). Only older age was associated with having a positive test result. Patients with social needs and interest in receiving help were offered services to meet their needs including food deliveries (n = 92), behavioral health telephone visits (n = 49), and faith-based comfort calls from pastoral care personnel (n = 37). <h3>Conclusions and Relevance:</h3> Robust, physician-directed telehealth services can meet a wide range of clinical and social needs during the acute phase of a pandemic, conserving scarce resources such as personal protective equipment and testing supplies and preventing the spread of infections to patients and health care workers.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.018
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.546
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.115
GPT teacher head0.405
Teacher spread0.290 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it