Evidence map›Paper›PMID 42139561›Full record

ArticleJMIR medical informatics2026

Implementation and Evaluation of an Alternative Electronic Health Record Tool for Ordering Blood Products in Pediatric Oncology and Stem Cell Transplantation: Mixed Methods Analysis.

Ally Sarna, Aya Finkelstein, Caroline Malcolmson, Renee Potashner, Natalie Pitch, Alessia Forestieri, Marilyn Cooper, Yuquing Feng, Aryan Patel, Tal Schechter and 3 more

Abstract read
In one paragraph

Article in JMIR medical informatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Ally SarnaDivision of Haematology/Oncology, The Hospital for Sick Children, 555 University Avenue, Toronto, ON, M5G 1X8, Canada, 1 4374296924.ORCID 0009-0002-2323-3248
Aya FinkelsteinDivision of Haematology/Oncology, The Hospital for Sick Children, 555 University Avenue, Toronto, ON, M5G 1X8, Canada, 1 4374296924.ORCID 0009-0005-3428-9273
Caroline MalcolmsonDivision of Haematology/Oncology, The Hospital for Sick Children, 555 University Avenue, Toronto, ON, M5G 1X8, Canada, 1 4374296924.ORCID 0000-0002-3916-7022
Renee PotashnerDivision of Haematology/Oncology, The Hospital for Sick Children, 555 University Avenue, Toronto, ON, M5G 1X8, Canada, 1 4374296924.ORCID 0000-0003-4121-178X
Natalie PitchDepartment of Pediatrics, The Hospital for Sick Children, Toronto, ON, Canada.ORCID 0000-0002-8154-5779
Alessia ForestieriDivision of Haematology/Oncology, The Hospital for Sick Children, 555 University Avenue, Toronto, ON, M5G 1X8, Canada, 1 4374296924.ORCID 0009-0004-5902-1022
Marilyn CooperDivision of Haematology/Oncology, The Hospital for Sick Children, 555 University Avenue, Toronto, ON, M5G 1X8, Canada, 1 4374296924.ORCID 0009-0006-9139-1773
Yuquing FengProgram in Child Health Evaluative Sciences, The Hospital for Sick Children, Peter Gilgan Centre for Research and Learning, Toronto, ON, Canada.ORCID 0009-0000-9174-8935
Aryan PatelWestern University, London, ON, Canada.ORCID 0009-0007-6967-6673
Tal SchechterDivision of Haematology/Oncology, The Hospital for Sick Children, 555 University Avenue, Toronto, ON, M5G 1X8, Canada, 1 4374296924.ORCID 0009-0004-5844-164X
Karim JessaDivision of Pediatric Emergency Medicine, The Hospital for Sick Children, Toronto, ON, Canada.ORCID 0009-0001-7582-8422
Lillian SungDivision of Haematology/Oncology, The Hospital for Sick Children, 555 University Avenue, Toronto, ON, M5G 1X8, Canada, 1 4374296924.ORCID 0000-0003-0951-3091
Adam P YanDivision of Haematology/Oncology, The Hospital for Sick Children, 555 University Avenue, Toronto, ON, M5G 1X8, Canada, 1 4374296924.ORCID 0000-0001-8300-3095

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Repeated blood product ordering is associated with order entry errors and potential patient harm. Traditional electronic health record order sets require repeated re-entry for recurrent transfusions, creating inefficiencies and opportunities for error, and contributing to physician burnout. Historically, we have used order sets to order blood products, which must be re-entered each time a transfusion is needed. Reusable transfusion therapy plans may address these challenges by standardizing and streamlining transfusion workflows. We conducted a pre-post study at a single pediatric academic center, evaluating the implementation of reusable transfusion therapy plans for packed red blood cells and platelets in oncology patients and those undergoing hematopoietic stem cell transplantation. Objective: The primary outcome was to evaluate the proportion of transfusions originating from the transfusion therapy plans during the postimplementation period. Secondary outcomes included evaluating (1) the proportion of eligible patients with applied transfusion therapy plans, (2) changes in transfusion efficiency (time from laboratory result to transfusion release and administration, premedication timing, and estimated overnight pages), and (3) the impact on safety (guideline-concordant dosing, irradiated product ordering, and transfusion thresholds). We also assessed health care practitioner experience using an adaptation of the technology acceptance model survey. Methods: The prestudy period consisted of the 1-year preimplementation, and the postperiod consisted of the 1-year post implementation. We used our institution's enterprise data warehouse (SickKids Enterprise-Wide Data in Azure Repository) to obtain demographic and transfusion details for all eligible patients. The adapted technology acceptance model survey was administered to eligible oncology clinicians. Results: The preimplementation cohort had 558 unique patients who received a total of 2678 transfusions. The postimplementation cohort had 521 unique patients who received 2777 transfusions. During the postimplementation period, 59% of transfusion orders originated from a therapy plan, increasing to 71% in the final month. Compared with order sets, therapy plan-derived transfusions were released and administered significantly faster following laboratory results (P<.001). Guideline-concordant transfusion volumes increased significantly postimplementation for both packed red blood cells and platelets (P<.001), as did the ordering of irradiated blood products (P<.001). No differences were observed in pretransfusion hemoglobin or platelet thresholds between study periods. Use of therapy plans was associated with an average avoidance of 4 overnight blood product entries per night. Survey responses from nurses and providers demonstrated high perceived usefulness and ease of use, with 95% endorsing continued use. Conclusions: Reusable transfusion therapy plans improved efficiency, standardized safe ordering practices, and were highly acceptable to clinicians. This longitudinal, noninterruptive electronic health record intervention represents a scalable approach to supporting high-risk transfusion workflows in pediatric oncology.

Indexed as

Blood TransfusionElectronic Health RecordsMedical OncologyMedical Order Entry SystemsPediatricsStem Cell TransplantationAdolescentChildChild, PreschoolFemaleHumansMaleclinical decision supportelectronic health recordoncologypediatricstransfusion medicine

Identifiers

PMID42139561
PMCPMC13178816

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.