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Record W4205126297 · doi:10.2196/29496

Understanding Patient Experiences, Opinions, and Actions Taken After Viewing Their Own Radiology Images Online: Web-Based Survey

2021· article· en· W4205126297 on OpenAlexvenueno aff
Evan C. Norris, Ciarra Halaska, Peter B. Sachs, Chen‐Tan Lin, Kate Sanfilippo, Justin M. Honce

Bibliographic record

VenueJMIR Formative Research · 2021
Typearticle
Languageen
FieldMedicine
TopicRadiology practices and education
Canadian institutionsnot available
Fundersnot available
KeywordsPatient portalMedicineRadiologyHealth care

Abstract

fetched live from OpenAlex

BACKGROUND: The ability for patients to directly view their radiology images through secure electronic portals is rare in the American health care system. We previously surveyed patients within our health system and found that a large majority wanted to view their own radiology images online, and we have since implemented this new feature. OBJECTIVE: We aim to understand patient experiences, opinions, and actions taken after viewing their own radiology images online. METHODS: We emailed a web-based survey to patients who recently viewed their radiology images via our electronic patient portal. RESULTS: We sent 1825 surveys to patients and received 299 responses (response rate 16.4%). Patients reported a favorable experience (258/299, 86.3% agree) viewing their radiology images online. Patients found value in reading their radiology reports (288/299, 96.3% agree) and viewing their images (267/299, 89.3% agree). Overall, patients felt that accessing and viewing their radiology images online increased their understanding of their medical condition (258/299, 82.9%), made them feel more in control and reassured (237/299, 79.2% and 220/299, 73.6%, respectively), and increased levels of trust (214/299, 71.6%). Only 6.4% (19/299) of the patients indicated concerns with finding errors, 6.4% (19/299) felt that viewing their images online made them worry more, and 7% (21/299) felt confused when viewing their images online. Of patients who viewed their images online, 45.2% (135/299) took no action with their images, 32.8% (98/299) saved a copy for their records, 25.4% (76/299) shared them with their doctor, and 14.7% (44/299) shared them with another doctor for a second opinion. A total of 9 patients (3%) shared their radiology images on Facebook, Instagram, or both, primarily to inform family and friends. Approximately 10.4% (31/299) of the patients had questions about their radiology images after viewing them online, with the majority (20/31, 65%) seeking out a doctor, and far fewer (5/31, 16%) choosing to ask a family member about their images. Finally, respondents viewed their images online using 1 or more devices, including computers, smartphones, tablets, or a combination of these devices. Approximately 26.7% (103/385) of the responses noted technical difficulties, with the highest incidence rate occurring with smartphones. CONCLUSIONS: We report the first known survey results from patients who viewed their own radiology images through a web-based portal. Patients reported high levels of satisfaction and increased levels of trust, autonomy, reassurance, and medical understanding. Only a small minority of patients expressed anxiety or confusion. We suggest that patient access to radiology images, such as patient access to radiology reports, is highly desired by patients and is operationally practical. Other health care institutions should consider offering patients access to their radiology images online in the pursuit of information transparency.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.320
Threshold uncertainty score0.382

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.313
GPT teacher head0.467
Teacher spread0.153 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations19
Published2021
Admission routes1
Has abstractyes

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