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Record W3178664820 · doi:10.1093/intqhc/mzab105

Improving primary care access to respirologists using eConsult

2021· article· en· W3178664820 on OpenAlexaff
Jean-Grégoire Leduc, Clare Liddy, Amir Afkham, Misha Marovac, Sheena Guglani

Bibliographic record

VenueInternational Journal for Quality in Health Care · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicHealthcare Systems and Technology
Canadian institutionsQueensway-Carleton HospitalOttawa HospitalBruyèreMontfort HospitalUniversity of Ottawa
Fundersnot available
KeywordsReferralMedicineSpecialtyPrimary careFamily medicinePediatricsEmergency medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Patients and primary care providers (PCPs) can experience frustration about poor access to specialist care. The Champlain Building Access to Specialists through eConsultation (BASETM) is a secure online platform that allows PCPs to ask a clinical question to 142 different specialty groups. The specialist is expected to respond within 7 days. METHODS: This is a retrospective review of the Champlain BASETM respirology eConsults from January 2017 to December 2018. The eConsults were categorized by types of questions asked by the referring provider and by the clinical content of the referral. Specialists' response time and time spent answering the clinical question were analyzed. Referring providers' close-out surveys were reviewed to assess the impact of the respirology eConsult service on traditional referral rates and clinical course of action. RESULTS: Of the 26 679 cases submitted to the Champlain BASE TM eConsult service, 268 were respirology cases (1%). 91% were sent by family physicians and 9% by nurse practitioners. The median time to respond by specialists was 0.8 days, and the median time billed by specialists was 20 min. The most common topics were pulmonary nodules and masses (16.4%), cough (10.4%), infective problems (8.6%), chronic obstructive pulmonary disease (8.6%) and dyspnea Not Yet Diagnosed (NYD) (7.8%). The most common types of questions asked by PCP were related to investigations warranted (43.1% of cases), general management (17.5%), monitoring (12.6%), need for a respirology referral (12.3%) and drug of choice (6.3%). In 23% of cases, the PCP indicated they were planning to refer the patient for an in-person consultation but no longer needed to after receiving the eConsult advice (avoided referrals). On the other hand, in 13% of cases, the PCP was not going to refer but did after the eConsult (prompted referrals). The eConsult led to a new or additional clinical course of action by the PCP in 49% of cases. In 51% of cases, the PCP suggested the clinical topic would be well suited to a CME event. CONCLUSIONS: Participation in eConsult services can improve timely access to respirologists while potentially avoiding clinic visits and significantly impacting referring PCPs clinical course of action. Using the most common clinical topics and types of questions for CME planning should be considered. Future research may include a cost analysis and provider perspectives on the role of eConsult in respirology care.

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.

How this classification was reachedexpand

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.855
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.120
GPT teacher head0.452
Teacher spread0.331 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2021
Admission routes1
Has abstractyes

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