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.
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 diabetespatients as an opportunity to monitor patient safety. METHODS: We identified adverse and potential adverse events among a diverse group of diabetespatients 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 diseasepatients.
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