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Record W4389948948 · doi:10.2196/47080

Patient Portal Use and Risk of Readmissions in Decompensated Cirrhosis: Retrospective Study

2023· article· en· W4389948948 on OpenAlexvenueno aff
Jeremy Louissaint, Jeffrey T. Gibbs, Abhishek Shenoy, Shirley Cohen‐Mekelburg, Anna S. Lok, Elliot B. Tapper

Bibliographic record

VenueJMIR Formative Research · 2023
Typearticle
Languageen
FieldHealth Professions
TopicElectronic Health Records Systems
Canadian institutionsnot available
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institutes of Health
KeywordsMedicinePatient portalCirrhosisHepatic encephalopathyLiver diseaseAscitesPopulationHealth careAlcoholic liver diseaseInternal medicineEmergency medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Patient portals are a common electronic medical record tool that allow for the asynchronous exchange of health information between patients and their health care teams. Patients can leverage patient portals to perform tasks such as viewing test results, reviewing clinical notes, and messaging their health care team. The impact of patient portal use on clinical outcomes in cirrhosis is unknown. OBJECTIVE: In this study, we evaluated the relationship between patient portal use patterns and readmissions in cirrhosis. METHODS: We identified 131 patients with decompensated cirrhosis with an index cirrhosis-related admission between May 1, 2018, and May 1, 2019. We then examined patient portal enrollment and use data during the 6-month period preceding the study period. Portal functions evaluated included sending a message, reading a message, and reading a test result. Use was categorized as active (sending a message) and passive (reading a message or test result) and was further stratified as no, moderate, or frequent use based on the frequency of portal function use compared to the mean. The primary outcomes were 90-day and overall readmissions, adjusted for age, model for end-stage liver disease-sodium, alcohol-related cirrhosis etiology, ascites, and hepatic encephalopathy. Portal functions assessed included sending a message, reading a message, and reading a result; the total number of times a portal function was performed was divided by the number of months the patient was enrolled in the patient portal during the 6-month period. RESULTS: The study population was 50.4% (66/131) female, with a mean age of 58 years. Enrollment in the patient portal was 63.4% (83/131), and there was no significant difference in enrollment based on clinical or demographic characteristics. For the entire cohort, 14.5% (19/131) and 22.1% (29/131) of patients were moderate and frequent active users, respectively. Of those enrolled in the patient portal, 97.6% (81/83) of patients were moderate or frequent passive users for both reading a message and reading a test result. Moderate active users had less 90-day readmissions (odds ratio 0.77, 95% CI 0.60-1.00) and overall readmissions (subdistribution hazard ratio 0.42, 95% CI 0.21-0.84), compared to nonactive users. There was no relationship between readmissions and passive use. CONCLUSIONS: Passive use of the patient portal is very high but is not associated with the risk of readmissions in people with decompensated cirrhosis. However, moderately active use of the patient portal is associated with a reduced risk of readmissions. Further work is needed to identify possible confounders and refine key use behaviors that may be protective with regard to the risk of readmission in this population.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.151
GPT teacher head0.531
Teacher spread0.380 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2023
Admission routes1
Has abstractyes

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