Using electronic consultations to identify hematology education needs in primary care
Bibliographic record
Abstract
Abstract BackgroundTopics covered in primary care Continuing Professional Development (CPD) activities often do not reflect the real-world learning needs of physicians, leading to dissatisfaction and poor engagement. Few studies have rigorously evaluated the learning needs of primary care physicians (PCPs) as they relate to hematology. One way to objectively assess these needs is through analysis of questions submitted by PCPs to hematologists via an electronic consultation (eConsult) platform.The Champlain BASE eConsult service is a secure, web-based platform that allows PCPs to communicate directly with specialists for patient care advice. We analyzed the content of hematology eConsults to objectively assess PCP learning needs. These insights could be used to inform the planning and development of future hematology CPD activities. MethodsWe conducted a retrospective cross-sectional study of questions submitted by PCPs to hematologists between January 2018 and December 2022 on the Champlain BASE™ eConsult Service in Ottawa, Ontario, Canada. One hundred eConsults per year were randomly selected, for a total convenience sample size of 500 eConsults. Demographic data, including age and sex of patients, occupation of PCP (family doctor vs nurse practitioner), and response time taken by the hematologist, were collected and summarized. Questions were classified by content area and question type using the International Classification for Primary Care, version 3 (ICPC-3) framework. A subset of eConsults was analyzed in triplicate to ensure consistency, and discrepancies were resolved by consensus. We used descriptive statistics to identify the most common content areas and question types asked by PCPs to hematologists and summarized them in an ordered list by frequency. ResultsA total of 453 eConsults (90.6%) were initiated by physicians, and 47 (9.4%) were initiated by nurse practitioners. The average age of patients was 57.5 years (range 18.7 – 101.2 years), and 61.6% were female. A total of 743 unique questions were identified in the 500 eConsults, with more than one question being asked in almost half of all eConsults (42.2%). The average time taken by hematologists to answer an eConsult was 15.1 +/- 8.4 minutes.The most common content categories pertained to monoclonal gammopathy of undetermined significance (MGUS) (11.2%), anemia (8.6%), polycythemia (7.0%), elevated ferritin (6.8%), thrombocytopenia (6.5%), and lymphocytosis (6.1%). The most common type of questions asked by PCPs pertained to diagnosis, with 54.4% focusing on the recognition of specific signs and symptoms. This was followed by questions related to management, including appropriate referral pathways (16.4%) and condition-specific treatment strategies (14.5%). Conclusion The most common PCP knowledge gaps identified by this study pertained to MGUS, anemia, and polycythemia. Analysis of eConsult data can objectively identify PCP knowledge gaps, which can in turn inform the development of hematology-specific CPD curricula for PCPs.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".