Characterizing the Process of Urgent Referrals and Transfers to a Large Tertiary Care Apheresis Centre in Ontario
Bibliographic record
Abstract
Background: Therapeutic plasma exchange (TPE) and red blood cell exchange (RBCX) are potentially life-saving treatments. Given the specialized nature of care, apheresis is only offered in 7 centres in Ontario (population: 14.5 million), and therefore effectively functions as a provincial service. Patients can be referred to any apheresis centre, regardless of home local health integration network (LHIN). Referrals are directed by CritiCall Ontario (CritiCall), a 24/7 consultation and referral service funded by the Ontario Ministry of Health and Long-Term Care (MOHLTC). CritiCall facilitates the MOHLTC Life or Limb Policy, which provides that patients with life or limb threatening conditions will receive timely consultation, and if necessary, transfer to an appropriate centre within a best effort window of 4 hours. We used CritiCall data to examine referral, acceptance, and transfer processes of urgent TPE and RBCX apheresis calls to our centre. Methods: Time and process data for all CritiCall transfers to our centre for TPE and RBCX between October 2013 and December 2018 were included. TPE cases were analyzed if transferred for codes related to thrombotic thrombocytopenic purpura (TTP) or other thrombotic microangiopathies, and RBCX cases were analyzed only for acute sickle cell indications (e.g. stroke, acute chest syndrome). As such, we assumed all transfers to be "life or limb." Continuous variables were analyzed by linear regression. Categorical variables were analyzed using nonparametric tests. Data were provided in accordance with the Personal Health Information Protection Act, 2004 (www.criticall.org/Article/Privacy). Results: A total of 69 cases (43 TPE, 26 RBCX) were included. Median patient age was 51 (IQR 37) years for TPE and 29 (IQR 16) for RBCX. Most patients (61%) were female. Total time from referral to patient arrival at our centre was 243 (IQR 168) minutes. The greatest proportion of this total was from patient acceptance to arrival (169 [IQR 108] minutes), whereas time from referral to contact with the physician, and time from contact to patient acceptance were 23 (IQR 53) and 12 (IQR 41) minutes, respectively. The life or limb benchmark was met in 74% of cases, assessing time between acceptance and arrival. Fifty-two percent of the patients were accepted by the first apheresis physician contacted, with an average of 3 physicians contacted before a patient was accepted. Distance between referring and accepting centres was 39 (IQR 39) kilometres, and ground transportation was used most often. A minority of cases (7%) transferred were within our own LHIN. Multiple linear regression examining factors that contribute to total time from referral to arrival demonstrated that distance was independently associated with total time (p<0.001). Transfers took an additional 6.7 minutes for every 10 km between the referring and accepting centres. Male sex was also independently associated with total time (p=0.041), with 55 additional minutes required per transfer of male patients compared to female. Transfer time was not significantly associated with age, procedure (TPE vs. RBCX), mode of transport, number of centres contacted, or within-LHIN referral. Conclusions: We have described the processes of urgent apheresis referrals to our centre. The 4 hour "life or limb" benchmark was met in just under 75% of transfers, with the greatest delay occurring between patient acceptance and arrival. This is important given that time to initiate treatment is associated with better outcomes. Distance between centres is an important factor and potential target for improvement. Our analysis shows that >90% of cases were from outside our LHIN, reflecting a truly provincial catchment. Quality improvement strategies should be aimed at pairing referrals with nearest apheresis centres, and creating efficiency in the interval between patient acceptance and arrival. It is unclear from these data why male sex is associated with longer transfer times, but it is a target for further analysis. There are limitations of this analysis: data were not available for cases that were not ultimately transferred, nor for transfers to other centres. Future work will include examining patterns of province-wide transfers, as well as including blood bank data to further characterize steps involved in initiating aphaeresis. Acknowledgements: We thank M. Shaikh, J. Dempsey, M. Gavel at CritiCall for their contributions. Disclosures Kuo: Pfizer: Consultancy, Research Funding; Celgene: Consultancy; Apellis: Consultancy; Bioverativ: Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Honoraria; Alexion: Consultancy, Honoraria; Bluebird Bio: Consultancy; Agios: Consultancy, Membership on an entity's Board of Directors or advisory committees. Patriquin:Alexion: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Apellis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Octapharma: Honoraria, Membership on an entity's Board of Directors or advisory committees.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".