To evaluate healthcare value of messaging through patient portals based on the relationship of maximum patient message length versus content communicated. 

Patient portals are designed to empower individuals to be partners in their care and reduce administrative burdens. Overall adoption has been positive with studies demonstrating improvement in outcomes with increased use. However, recent studies have shown that high volume of messages increases physician workload and contributes to burnout. Specifically, length of the message has been described as a contributing factor. Here we evaluate a database of messages to determine key descriptive statistics towards identifying methods to increase efficiency in addressing messaging demands.

Retrospective review of patient portal messages through the Epic MyChart platform from January 1 to June 30, 2022 at a single large academic outpatient neurology clinic (general & subspecialities). Message character length was obtained through a basic character count using Microsoft Excel (MAC version 16.65). Descriptive statistics were calculated from the sample to derive insights on patterns. Through an optimization scenario - maximum message length was reduced in order to determine number of messages affected versus content reduced.

There were 10,118 messages from 2,646 patients. Length ranged from 1 to 1500 characters resulting in a total of 2,946,290 characters. Message length followed a decreasing exponential distribution, with majority of messages in lower character ranges. Quartiles from first to fourth were: 88, 202 (median), 386, and 1500 (max). Limiting character count to 750 characters, affected 807 (8%) messages. Reducing these messages to 750 characters decreased the overall character count by 11%.

Patient portal messaging has become an important part of the patient-physician partnership. This analysis evaluated an optimization strategy of reducing character count in order to determine workload impact. Limiting maximum length to 750 characters led to a disproportionate reduction in workload compared to a smaller number of messages affected.