Evidence map›Paper›PMID 37544770›Full record

ArticleHealth informatics journal

Physicians differ in their perceptions of sensitive medical records: Survey and interview study.

Ipsha Banerjee, Kazi Syed, Aishwarya Potturu, Venkata Svs Pragada, Rishika S Sharma, Anita Murcko, Darwyn Chern, Michael Todd, Padma Aking, Ali Al-Yaqoobi and 18 more

Abstract read
In one paragraph

Article in Health informatics journal. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. FHIR Granular Sensitive Data Segmentation.Applied clinical informatics · 2025
    Article
  2. Article
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

28 authors.

Ipsha BanerjeeArizona State University, Scottsdale, AZ, US.ORCID 0009-0000-2801-7718
Kazi SyedArizona State University, Scottsdale, AZ, US.
Aishwarya PotturuArizona State University, Scottsdale, AZ, US.
Venkata Svs PragadaArizona State University, Scottsdale, AZ, US.
Rishika S SharmaArizona State University, Scottsdale, AZ, US.
Anita MurckoArizona State University, Scottsdale, AZ, US.ORCID 0000-0002-2424-0987
Darwyn ChernCopa Health, Phoenix, AZ, US.
Michael ToddArizona State University, Phoenix, AZ, US.
Padma AkingTrinity Integrated Medicine, Phoenix, AZ, US.
Ali Al-YaqoobiUniversity of Arizona, Phoenix, AZ, US.
Patricia BaylessCreighton University, Phoenix, AZ, US.
Winona BelmonteCopa Health, Phoenix, AZ, US.
Teresa CuadraNew York City Zen Center for Contemplative Care, New York, NY, US.
Trudy DockinsCopa Health, Phoenix, AZ, US.
Christina EldredgeUniversity of South Florida, Tampa, FL, US.
Robert El-KarehUniversity of California San Diego, La Jolla, CA, US.
Gregory GaleUnited States, Scottsdale, AZ, US.
Edward GentileOptum Behavioral Health, Tucson, AZ, US.
Edward KalpasArizona State University, Scottsdale, AZ, US.
Meghan MorrisArizona State University, Scottsdale, AZ, US.
Laurel MuellerArizona Osteopathic Medical Association, Phoenix, AZ, US.
Dorothy PiekutCopa Health, Phoenix, AZ, US.
Mindy K RossUniversity of California, Los Angeles, CA, US.ORCID 0000-0001-7974-4309
John SarrisCopa Health, Phoenix, AZ, US.
Gagandeep SinghUniversity of Arizona, Phoenix, AZ, US.
Shalini TharaniCopa Health, Phoenix, AZ, US.
Mark WallaceMayo Clinic, Scottsdale, AZ, US.
Maria Adela GrandoArizona State University, Scottsdale, AZ, US.ORCID 0000-0002-5769-8556

Funding

SHARES: Substance use HeAlth REcord SharingR01DA056984 · NIDA · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI MARIA ADELA GRANDO · 2023 to 2026
$2.6M
My Data Choices, evaluation of effective consent strategies for patients with behavioral health conditionsR01MH108992 · NIMH · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI GRANDO, MARIA ADELA · 2016 to 2020
$2.0M
NIDA NIH HHS R01 DA056984NIMH NIH HHS R01 MH108992
6 · The paper itself

Abstract

Physician categorizations of electronic health record (EHR) data (e.g., depression) into sensitive data categories (e.g., Mental Health) and their perspectives on the adequacy of the categories to classify medical record data were assessed. One thousand data items from patient EHR were classified by 20 physicians (10 psychiatrists paired with ten non-psychiatrist physicians) into data categories via a survey. Cluster-adjusted chi square tests and mixed models were used for analysis. 10 items were selected per each physician pair (100 items in total) for discussion during 20 follow-up interviews. Interviews were thematically analyzed. Survey item categorization yielded 500 (50.0%) agreements, 175 (17.5%) disagreements, 325 (32.5%) partial agreements. Categorization disagreements were associated with physician specialty and implied patient history. Non-psychiatrists selected significantly (

Indexed as

Health Records, PersonalPhysiciansElectronic Health RecordsHumansPatientsQualitative Researchdata security and confidentialityElectronic health recordshealthcare policyhuman factorsprivacy

Identifiers

PMID37544770
PMCPMC13196690

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

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.