The Next Frontier in Communication and the ECLIPPSE Study: Bridging the Linguistic Divide in Secure Messaging

• Published in: Journal of Diabetes Research Vol. 2017; no. 2017; pp. 1 - 9
• Main Authors: Oryn, Danielle, Ratanawongsa, Neda, Karter, Andrew J., Allen, Jill, Duran, Nicholas, Sarkar, Urmimala, Moffet, Howard H., Lyles, Courtney Rees, Crossley, Scott, McNamara, Danielle, Schillinger, Dean, Liu, Jennifer
• Format: Journal Article
• Language: English
• Published: Cairo, Egypt Hindawi Publishing Corporation 01.01.2017; Hindawi; John Wiley & Sons, Inc; Wiley
• Subjects: Analysis; Automation; Chronic illnesses; Communication; Computational linguistics; Control; Diabetes Mellitus, Type 2; Electronic Health Records; Electronic Mail; Health care disparities; Health care policy; Health insurance; Health Literacy; Hispanic Americans; Hospitals; Humans; Internet; Language processing; Linguistics; Medicaid; Medicare; Natural language interfaces; Pacific Islander people; Patient compliance; Pharmacy; Physician and patient; Physician-Patient Relations; Population; Principal components analysis; Public health; Review; Voice mail; Web portals; Northern California; San Francisco California
• ISSN: 2314-6745; 2314-6753; 2314-6753
• DOI: 10.1155/2017/1348242

Health systems are heavily promoting patient portals. However, limited health literacy (HL) can restrict online communication via secure messaging (SM) because patients’ literacy skills must be sufficient to convey and comprehend content while clinicians must encourage and elicit communication from patients and match patients’ literacy level. This paper describes the Employing Computational Linguistics to Improve Patient-Provider Secure Email (ECLIPPSE) study, an interdisciplinary effort bringing together scientists in communication, computational linguistics, and health services to employ computational linguistic methods to (1) create a novel Linguistic Complexity Profile (LCP) to characterize communications of patients and clinicians and demonstrate its validity and (2) examine whether providers accommodate communication needs of patients with limited HL by tailoring their SM responses. We will study >5 million SMs generated by >150,000 ethnically diverse type 2 diabetes patients and >9000 clinicians from two settings: an integrated delivery system and a public (safety net) system. Finally, we will then create an LCP-based automated aid that delivers real-time feedback to clinicians to reduce the linguistic complexity of their SMs. This research will support health systems’ journeys to become health literate healthcare organizations and reduce HL-related disparities in diabetes care.