Secure Text Messaging in Healthcare: Latent Threats and Opportunities to Improve Patient Safety

Standardized Communication

A standardized language eliminates the burden of individuals to parse and translate each individual text message. A standardized algorithm for language, urgency, and expectations (ie, response before escalation) would help define the interaction in the clinical setting.¹⁶ Moving toward standardized, meaningful “quick messages,” one of our centers has implemented a campaign to “stick to the FACS,” where the following four standard quick messages are available for users: (1) “FYI no response needed,” (2) “ACTION needed within X min,” (3) “CONCERN can we talk or meet,” and (4) “STAT immediate response required.” These quick messages, developed with frontline stakeholders, represent the majority of requests exchanged by providers, and help standardize expectations and task prioritization.

Targeted Training

Targeted training and culture change efforts might help institutions counteract the broader impact of asynchronous messaging on communication skills and behaviors. Highlighting the contrast between clinical and casual communication with an emphasis on examples, scenarios, or role-playing has the potential to emphasize why and how clinical communication with STMS requires a careful, deliberate approach. For instance, safety culture training at one of our institutions features a scenario that illustrates the potential for miscommunication and missed connection between a nurse and a physician on the wards. The scenario gives way to discussion between participants about the shortcomings of text messaging and allows the facilitator to segue into the “dos and don’ts” of text messaging and when a phone call might be more appropriate.

Innovate

Finally, creatively harnessing the technology and data underlying these STMS may uncover methods to identify and mitigate communication errors in real time. For instance, using trigger methods to create a “ripple in the pond,” whereby a floor nurse reaching out with an urgent text automatically loops in the charge nurse of the unit. Building a chatbot or a virtual assistant functionality by leveraging user behavior patterns and natural language processing to provide text-based guidance to users might help busy clinicians connect to the key decision-makers on their team. For example, in response to an unanswered text, a virtual assistant might reach out to the waiting provider as follows: “you texted the resident 20 minutes ago and they haven’t replied, would you like to call the fellow instead?” The data-rich nature of these systems implies that they are ripe for automated solutions that can respond to behavioral- or text-based patterns to augment the existing operation and safety infrastructure.

The transition of healthcare communication systems toward STMS is already well underway. These systems, despite their flaws, are undoubtedly an improvement over legacy paging systems and, if properly implemented, offer several benefits to large healthcare systems. However, the communication needs in the healthcare setting are vastly different from the personal communication needs in everyday text messaging. As clinicians at the forefront of these transitions, we have the opportunity to critically assess the unique communication requirements in our hospital settings and help shape the way STMS are implemented in our hospitals. Pausing to deliberate about the limitations and the vulnerabilities of the current messaging systems for our acute clinical needs, including how they impact training and education, will allow us to proactively design and implement better communication systems that improve patient safety.