Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: May 13, 2021
Date Accepted: Nov 18, 2021
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Characterizing Patient-Clinician Communication in Millions of Medical Secure Messages
ABSTRACT
Background:
Background:
Patient-clinician secure messaging is an important function in patient portals and enables patients and clinicians to timely communicate on a wide spectrum of issues. With its growing adoption and patient engagement, it is the time to comprehensively study its contents and user behaviors, in order to improve patient-centered care.
Objective:
Objective:
To analyze the secure messages sent by patients and clinicians in a large multispecialty health system at Mayo Clinic – Rochester.
Methods:
Methods:
We performed message-, sender-, and thread-based analyses of more than 5 million secure messages between 2010 to 2017. We summarized the message volumes, patient and clinician population sizes, message counts per patient/clinician, and their trends over the years. In addition, we calculated the time distribution of clinician-sent messages to understand their workloads at different times of a day. We also analyzed the time delay in clinician responses to patient messages to assess their communication efficiency and the back-and-forth rounds to estimate the communication complexity.
Results:
Results:
During 2010-2017, the patient portal at Mayo Clinic – Rochester experienced a significant growth in terms of the count of patient users and the total number of secure messages sent by patients and clinicians. Three clinician categories, namely “physician – primary care”, “RN – specialty”, and “physician – specialty” bore the majority of message volume increase. The patient portal also demonstrated growing trends in message counts per patient and clinician. The “NP/PA – primary care” and “physician – primary care” categories had the heaviest per-clinician workload each year. Most messages by the clinicians were sent from 07:00 to 17:00 during a day. Yet during 17:00-19:00, the physicians sent 5.1% of their daily messages and the NP/PA sent 17.7% of their daily messages on average. Clinicians replied 72.2% of the patient messages within 1 day and 90.6% within 3 days. In 95.1% of the message threads, patients communicated with their clinicians back and forth for no more than 4 rounds.
Conclusions:
Conclusions:
Our study found steady increases in patient adaption of secure messaging system and the average workload per clinician over 8 years. However, most clinicians responded timely to meet the patients’ needs. Our study also revealed differential patient-clinician communication patterns across different practice roles and care settings. These findings suggested opportunities for care teams to optimize messaging tasks and to balance the workload for optimal efficiency.
Citation
