Evidence map›Paper›PMID 40027237›Full record

ArticleGenetics in medicine open2025

Lessons learned in migrating from one commercial genetics clinical decision-making tool to another: Assessment of data integrity and utilization.

Calvin Le, Kevin Tatunay, Wayne Liu, Haibo Lu, Nicole-Ann Rodis, Thomas Nam, Mercy Y Laurino, Marianne E Dubard-Gault

Abstract read
In one paragraph

Article in Genetics in medicine open, 2025. 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

8 authors.

Calvin LeUniversity of Washington, Seattle, WA.
Kevin TatunayFred Hutchinson Cancer Center, Seattle, WA.
Wayne LiuFred Hutchinson Cancer Center, Seattle, WA.
Haibo LuCancerIQ, Chicago, IL.
Nicole-Ann RodisFred Hutchinson Cancer Center, Seattle, WA.
Thomas NamAmbry Genetics, Laguna Beach, CA.
Mercy Y LaurinoFred Hutchinson Cancer Center, Seattle, WA.
Marianne E Dubard-GaultUniversity of Washington, Seattle, WA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Rapid advancements in information technology have greatly influenced clinicians' engagement with patient data for health maintenance. The electronic health record often contains multiple ways to record risk factors and to identify patients at an elevated genetic risk for cancer. However, these variables exist in multiple forms and disparate locations in each commercial electronic health record solution resulting in significant variations in how family history or genetic data is codified. Furthermore, there is pressure to migrate from one commercial solution to another at times, prompting the need for a process ensuring data integrity during such a transition. Methods: Between July and December 2023, the genetics team migrated a family history database from one commercial software solution to another. After the data migration of 13,000 patient records, we reviewed 500 randomly selected charts in both support tools to measure the rate of concordance of information transferred. Results: A total of 461 patient charts were reviewed. Of these, 425 (92.2%) were noted to be concordant. Of the 36 charts that were discordant, 9 had incorrect genetic testing results entered, 19 had missing information, 5 charts contained data recorded on paper before 2017 (legacy data), and 3 had additional information transferred. Conclusion: There was high data integrity after migration from one commercial software solution to another. Although these results can ease clinicians' concerns after such support tool transitions, our effort also highlights areas for improvement in how family and patient genetic data are recorded and utilized for clinical care and research within an institution.

Indexed as

Data integrationData managementFamily historyGeneticsHealth services

Identifiers

PMID40027237
PMCPMC11869494

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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.