Observational studyJournal of medical Internet research2026
The Role of Measurement in Identifying High-Intensity Secure Message Senders Among Older Adults: Observational Study.
Observational study in Journal of medical Internet research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Use of secure messaging within the patient portal has grown rapidly over recent years, yet clinical workflows, staffing models, and billing practices have generally not been comprehensively adapted to support this increasing volume of messages. Little is known about the characteristics of patients who are high-volume message senders, and we lack a nuanced understanding of patient messaging intensity beyond measures accounting for sheer volume, limiting health system efforts to anticipate message-related workflow demands and allocate resources effectively. Objective: Our objective was to characterize older adult patients (aged ≥65 years) with high secure messaging volume, examining both patient characteristics and other aspects of their messaging intensity, such as messaging frequency, length, and messaging use relative to patient portal logins and health care encounters. Methods: We analyzed electronic medical record and patient portal data from a large academic health system, encompassing 16,023 older adults who sent 199,981 messages over a 12-month period. We developed 5 measures to account for secure messaging intensity. Our primary measure of messaging intensity was based on message volume; high-volume message senders were identified using outlier analysis based on patients' aggregate number of messages sent during the observation period. Additional measures of messaging intensity included identifying individuals with concentrated periods of messaging, message length (character count), a ratio of messages to portal logins, and a ratio of messages to health care encounters. We compared sociodemographic characteristics, health status, and messaging intensity of high-volume secure messaging senders with those of other message senders. Results: Of 16,023 older adult patients who sent at least 1 message during the observation period, 1298 (8.1%) were classified as high-volume message senders; these patients accounted for 39.7% (79,475/199,981) of total messages. High-volume message senders, compared with all other message senders, were more likely to be White (1044/1298, 80.4% vs 10,670/14,725, 72.5%; Conclusions: High-volume message senders represent a small but distinct group of older patients who send a large share of messages to clinicians. Using multiple measures of messaging intensity can provide additional context about patient messaging behavior and help health systems redesign workflows and care delivery models to meet patient communication needs while facilitating sustainable workloads for clinicians.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.