BACKGROUND
There is growing interest in the use of interactive telephone technology to support chronic disease management. We used the
implementation of an automated telephone self-management support program for diabetes patients as an opportunity to monitor
patient safety.
METHODS
We identified adverse and potential adverse events among a diverse group of diabetes patients who participated in an automated
telephone health-IT self-management program via weekly interactions augmented by targeted nurse follow-up. We defined an adverse
event (AE) as an injury that results from either medical management or patient self-management, and a potential adverse event
(PotAE) as an unsafe state likely to lead to an event if it persists without intervention. We distinguished between incident,
or new, and prevalent, or ongoing, events. We conducted a medical record review and present summary results for event characteristics
including detection trigger, preventability, potential for amelioration, and primary care provider awareness.
RESULTS
Among the 111 patients, we identified 111 AEs and 153 PotAEs. Eleven percent of completed calls detected an event. Events
were most frequently detected through health IT–facilitated triggers (158, 59%), followed by nurse elicitation (80, 30%),
and patient callback requests (28, 11%). We detected more prevalent (68%) than incident (32%) events. The majority of events
(93%) were categorized as preventable or ameliorable. Primary care providers were aware of only 13% of incident and 60% of
prevalent events.
CONCLUSIONS
Surveillance via a telephone-based, health IT–facilitated self-management support program can detect AEs and PotAEs. Events
detected were frequently unknown to primary providers, and the majority were preventable or ameliorable, suggesting that this
between-visit surveillance, with appropriate system-level intervention, can improve patient safety for chronic disease patients.
KEY WORDS diabetes - ambulatory patient safety - adverse events - telephone care - self-management support