Evidence map›Paper›PMID 33989015›Full record

ArticleJCO clinical cancer informatics2021

What Oncologists Want: Identifying Challenges and Preferences on Diagnosis Data Entry to Reduce EHR-Induced Burden and Improve Clinical Data Quality.

Franck Diaz-Garelli, Roy Strowd, Tamjeed Ahmed, Thomas W Lycan, Sean Daley, Brian J Wells, Umit Topaloglu

Abstract read
In one paragraph

Article in JCO clinical cancer informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 3 pooled it
–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

8 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Digital Health Data Quality Issues: Systematic Review.Journal of medical Internet research · 2023
    Pooled it
  3. Pooled it
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
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

7 authors.

Franck Diaz-GarelliUniversity of North Carolina at Charlotte, Charlotte, NC.ORCID 0000-0002-4346-3799
Roy StrowdWake Forest School of Medicine, Winston-Salem, NC.ORCID 0000-0001-6651-5267
Tamjeed AhmedTennessee Oncology, Chattanooga, TN.
Thomas W LycanWake Forest School of Medicine, Winston-Salem, NC.ORCID 0000-0001-9475-1558
Sean DaleyUniversity of North Carolina at Charlotte, Charlotte, NC.
Brian J WellsWake Forest School of Medicine, Winston-Salem, NC.ORCID 0000-0001-7310-6525
Umit TopalogluWake Forest School of Medicine, Winston-Salem, NC.ORCID 0000-0002-3241-8773

Funding

Tumor Tissue CoreP30CA012197 · NCI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI Ruben A. Mesa · 1985 to 2026
$55.4M
Wake Forest Clinical and Translational Science AwardUL1TR001420 · NCATS · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI ARD, JAMY D, FOLEY, KRISTIE L · 2015 to 2023
$32.3M
Postdoctoral Research, Instruction, and Mentoring Experience (PRIME)K12GM102773 · NIGMS · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI HOWLETT, ALLYN C · 2013 to 2018
$2.6M
NCATS NIH HHS UL1 TR001420NCI NIH HHS P30 CA012197NIGMS NIH HHS K12 GM102773
6 · The paper itself

Abstract

purposeAccurate recording of diagnosis (DX) data in electronic health records (EHRs) is important for clinical practice and learning health care. Previous studies show statistically stable patterns of data entry in EHRs that contribute to inaccurate DX, likely because of a lack of data entry support. We conducted qualitative research to characterize the preferences of oncological care providers on cancer DX data entry in EHRs during clinical practice.

methodsWe conducted semistructured interviews and focus groups to uncover common themes on DX data entry preferences and barriers to accurate DX recording. Then, we developed a survey questionnaire sent to a cohort of oncologists to verify the generalizability of our initial findings. We constrained our participants to a single specialty and institution to ensure similar clinical backgrounds and clinical experience with a single EHR system.

resultsA total of 12 neuro-oncologists and thoracic oncologists were involved in the interviews and focus groups. The survey developed from these two initial thrusts was distributed to 19 participants yielding a 94.7% survey response rate. Clinicians reported similar user interface experiences, barriers, and dissatisfaction with current DX entry systems including repetitive entry operations, difficulty in finding specific DX options, time-consuming interactions, and the need for workarounds to maintain efficiency. The survey revealed inefficient DX search interfaces and challenging entry processes as core barriers.

conclusionOncologists seem to be divided between specific DX data entry and time efficiency because of current interfaces and feel hindered by the burdensome and repetitive nature of EHR data entry. Oncologists' top concern for adopting data entry support interventions is ensuring that it provides significant time-saving benefits and increasing workflow efficiency. Future interventions should account for time efficiency, beyond ensuring data entry effectiveness.

Indexed as

Data AccuracyOncologistsElectronic Health RecordsHumansMedical OncologyQualitative Research

Identifiers

PMID33989015
PMCPMC8462630

What OpenQuestion holds

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Registered trials

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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.