Effect of In-Person vs Video Training and Access to All Functions vs a Limited Subset of Functions on Portal Use Among Inpatients
Post-publication record
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Bibliographic record
Abstract
Importance: Inpatient portals provide patients with clinical data and information about their care and have the potential to influence patient engagement and experience. Although significant resources have been devoted to implementing these portals, evaluation of their effects has been limited. Objective: To assess the effects of patient training and portal functionality on use of an inpatient portal and on patient satisfaction and involvement with care. Design, Setting, and Participants: This randomized clinical trial was conducted from December 15, 2016, to August 31, 2019, at 6 noncancer hospitals that were part of a single health care system. Patients who were at least 18 years of age, identified English as their preferred language, were not involuntarily confined or detained, and agreed to be provided a tablet to access the inpatient portal during their stay were eligible for participation. Data were analyzed from May 1, 2019, to March 15, 2021. Interventions: A 2 × 2 factorial intervention design was used to compare 2 levels of a training intervention (touch intervention, consisting of in-person training vs built-in video tutorial) and 2 levels of portal function availability (tech intervention) within an inpatient portal (all functions operational vs a limited subset of functions). Main Outcomes and Measures: The primary outcomes were inpatient portal use, measured by frequency and comprehensiveness of use, and patients' satisfaction and involvement with their care. Results: Of 2892 participants, 1641 were women (56.7%) with a median age of 47.0 (95% CI, 46.0-48.0) years. Most patients were White (2221 [76.8%]). The median Charlson Comorbidity Index was 1 (95% CI, 1-1) and the median length of stay was 6 (95% CI, 6-7) days. Notably, the in-person training intervention was found to significantly increase inpatient portal use (incidence rate ratio, 1.34 [95% CI, 1.25-1.44]) compared with the video tutorial. Patients who received in-person training had significantly higher odds of being comprehensive portal users than those who received the video tutorial (odds ratio, 20.75 [95% CI, 16.49-26.10]). Among patients who received the full-tech intervention, those who also received the in-person intervention used the portal more frequently (incidence rate ratio, 1.36 [95% CI, 1.25-1.48]) and more comprehensively (odds ratio, 22.52; [95% CI, 17.13-29.62]) than those who received the video tutorial. Patients who received in-person training had higher odds (OR, 2.01 [95% CI, 1.16-3.50]) of reporting being satisfied in the 6-month postdischarge survey. Similarly, patients who received the full-tech intervention had higher odds (OR, 2.06 [95%CI, 1.42-2.99]) of reporting being satisfied in the 6-month postdischarge survey. Conclusions and Relevance: Providing in-person training or robust portal functionality increased inpatient engagement with the portal during the hospital stay. The effects of the training intervention suggest that providing personalized training to support use of this health information technology can be a powerful approach to increase patient engagement via portals. Trial Registration: ClinicalTrials.gov Identifier: NCT02943109.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".