The Role of Measurement in Identifying High-Intensity Secure Message Senders Among Older Adults: Observational Study
Journal of Medical Internet Research ·
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%; <.001), have higher comorbidity scores (2.6 vs 1.8; <.001), and higher incidence of cancer (465/1298, 35.8% vs 3354/14,725, 22.8%; <.001) and dementia (107/1298, 8.2% vs 889/14,725, 6.1%; <.002). High-volume message senders were also more likely to be identified as having concentrated periods of messaging, to send longer messages, and to send more messages in relation to patient portal logins and health care encounters. 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.