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Secure Messaging and COVID-19: A Content Analysis of Patient-Clinician Communication During the Pandemic
Jordan M Alpert1, Gemme Campbell-Salome2, Cayle Gao3
1College of Journalism and Communications, University of Florida, Gainesville, Florida, USA.
Abstract:
Coronavirus disease 2019 (COVID-19) immediately impacted patient-clinician communication, particularly in the oncology setting. Relatedly, secure messaging (SM) usage greatly increased, yet it is unknown what was discussed and whether the technology was utilized to disseminate information. This study aimed at identifying the most frequently discussed topics using SM as well as at understanding how the communication process transpired during the early stages of the pandemic. A mixed-methods design was utilized, consisting of a content analysis of more than 4,200 secure messages, aggregated into 1,454 patient-clinician discussions. Data were collected from February 2020 to May 2020. Discussions were from various oncology departments and included physicians, physician assistants, and nurses. Based on the identified categories, a thematic analysis was conducted to understand the nuances occurring within discussions. Out of the 1,454 discussions, 26% (n = 373) related to COVID-19. Of the COVID-19 discussion, the most frequently coded category was "changes, adjustments, and re-arranging care" (65%, n = 241), followed by "risk for COVID-19" (24%, n = 90), "precautions inside the hospital" (18%, n = 66), and "precautions outside the hospital" (14%, n = 52). Natural language processing techniques were used to confirm the validity of the results. Thematic analysis revealed that patients were proactive in rescheduling appointments, expressed anxiety about being immunocompromised, and clinicians were uncertain about providing recommendations related to COVID-19. The COVID-19 outbreak revealed the need for responsive and effective public health communication. The SM can disseminate information from trusted sources, clinicians, but can be better utilized to deliver tailored information for specific patient populations.
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