Characteristics of electronic patient-provider messaging system utilisation in an urban health care organisation.
BACKGROUND
Research suggests that electronic messaging can improve patient engagement. Studies indicate that a 'digital divide' may exist, where certain patient populations may be using electronic messaging less frequently. This study aims to determine which patient characteristics are associated with different levels of usage of an electronic patient-provider messaging system in a diverse urban population.


METHODS
Cross-sectional electronic health record data were extracted for patients 10 years of age or older who live in New York City and who visited a set of clinics between 1 July 2011 and 30 June 2012. Regression analyses determined which participant characteristics were associated with the sending of electronic messages.


RESULTS
Older, female, English-speaking participants of white race who received more messages, had any diagnoses, more office visits and a provider who sent messages were more likely to send more messages. Non-Millennial, non-white participants who received fewer messages, had more office visits, any diagnoses, a provider who saw fewer patients with patient portal accounts, lived in a low socioeconomic status neighbourhood, and did not have private insurance were more likely to send zero messages.


CONCLUSIONS
This study found significant differences in electronic messaging usage based on demographic, socioeconomic and health-related patient characteristics. Future studies are needed to support these results and determine the causes of observed associations.
University of Washington, USA. smikles@uw.edu.
Sean Patrick
SP
Mikles
Thelma J
TJ
Mielenz
D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D002648:Child; D003430:Cross-Sectional Studies; D057286:Electronic Health Records / Q000706:statistics & numerical data*; D034742:Electronic Mail / Q000706:statistics & numerical data*; D005260:Female; D006304:Health Status; D006801:Humans; D008297:Male; D008875:Middle Aged; D009519:New York City; D012044:Regression Analysis; D012737:Sex Factors; D012959:Socioeconomic Factors; D019037:Urban Health Services / Q000706:statistics & numerical data*; D055815:Young Adult