By Andreas Cleve

Across the United States, Public Safety Answering Points (PSAPs) are understaffed. PSAPs are the crucial call centers where operators receive 911 calls and route them to the appropriate emergency service personnel—such as police departments, fire departments, or emergency medical services (EMS). Although staffing is a perennial problem for PSAPs, COVID-19 has further exacerbated the issue and put already overburdened staff under increasing amounts of stress.

At a time when more people are seeking work/life balance and positive mental health, it’s easy to surmise that many PSAP call-takers and dispatchers may be leaving the industry for jobs that are better paid, have nicer schedules, or that don’t require the stressful daily navigation of traumatic events. Yet a study commissioned by the Association of Public-Safety Communications Officials (APCO) International suggests that staffing pressures were being felt by PSAPs even before the pandemic. Among large PSAPs, for example, over 77% reported being consistently below authorized staffing levels. The study also found an average staff retention rate of just 71%—a significant decline from the 81% retention rate noted in a similar APCO survey conducted in 2009.
In a sector where seconds matter, patients’ lives may be at increased risk if PSAP resources are not equipped to manage the workload. However, just as in many other industries, artificial intelligence (AI) technologies could help support PSAP operators in ways that reduce staff burnout and enhance patient outcomes.

Enhance satisfaction and outcomes
Two of the most common reasons for staff burnout are: 1) feeling overwhelmed at work, and 2) not getting the support needed. AI-enabled software can help alleviate both issues and elevate staff satisfaction by acting, in essence, as a personal assistant for PSAP operators. Various AI applications can be used to optimize triaging, automate documentation, transmit information to EMTs or paramedics in near real-time, and analyze calls and dispatched resources for ongoing process improvement.

AI platforms can even be used to make it easier and faster for dispatchers to assist out-of-hospital patients in cardiac arrest. Such technologies “listen” to emergency calls and use advanced algorithms to detect the signs of a cardiac arrest faster and more accurately than humans. While a solution can’t diagnose or make decisions on its own, it can guide the dispatcher by prompting certain questions, advising whether it believes the case involves a cardiac arrest, and allowing the dispatcher to request an ambulance.

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