Impact of Artificial Intelligence-Enhanced Insertable Cardiac Monitors on Device Clinic Workflow and Resource Utilization
Background: Insertable cardiac monitors (ICMs) are essential for managing arrhythmias but often generate large numbers of transmissions and false alerts. Integrating artificial intelligence (AI) as part of the ICM workflow can reduce this burden. However, its impact on clinic workflow and resource u...
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Elsevier
2025-04-01
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| Series: | JACC: Advances |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772963X25000730 |
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| author | Aashish Katapadi, MD Nikhila Chelikam, MBBS, MSCR Sarah Rosemas, MPH Lucas Higuera, MA, PhD Ilyas Colombowala, MD Shanti Bansal, MD Douglas Darden, MD Naga Venkata K. Pothenini, MD Scott Koerber, DO Rangarao Tummala, MD Peter Park, MD Rakesh Gopinathannair, MD Dhanunjaya Lakkireddy, MD Rajesh Kabra, MD |
| author_facet | Aashish Katapadi, MD Nikhila Chelikam, MBBS, MSCR Sarah Rosemas, MPH Lucas Higuera, MA, PhD Ilyas Colombowala, MD Shanti Bansal, MD Douglas Darden, MD Naga Venkata K. Pothenini, MD Scott Koerber, DO Rangarao Tummala, MD Peter Park, MD Rakesh Gopinathannair, MD Dhanunjaya Lakkireddy, MD Rajesh Kabra, MD |
| author_sort | Aashish Katapadi, MD |
| collection | DOAJ |
| description | Background: Insertable cardiac monitors (ICMs) are essential for managing arrhythmias but often generate large numbers of transmissions and false alerts. Integrating artificial intelligence (AI) as part of the ICM workflow can reduce this burden. However, its impact on clinic workflow and resource utilization must be better understood. Objectives: The aim of the study was to assess the impact of AI-enhanced ICMs on clinic workflow and resource utilization. Methods: A cross-sectional analysis was conducted using real-world, deidentified ICM remote monitoring data from Octagos Health, which included 140 U.S. device clinics between July 2022 and April 2024. Nonactionable alerts (NAAs) were defined as false or repetitive alerts transmitted on the remote monitoring platforms but dismissed by device technicians and not forwarded to clinicians for review. We compared NAAs generated by AI-enhanced vs non-AI-enhanced ICMs and estimated associated staffing hours, resources, and costs extrapolated for a clinic managing 600 ICM patients. Results: Among 19,320 patients (mean age: 69 ± 13.5 years; 47.3% male), 68% had non-AI-enhanced ICMs, and 32% had AI-enhanced ICMs. The mean annual NAA volume per 600-ICM clinic was 5,078 for non-AI-enhanced ICMs and 2,110 for AI-enhanced ICMs, resulting in 559 fewer staffing hours (956 vs 397 hours; 95% CI: 513-605 hours; P value < 0.001) and $29,470 in annual savings ($20,929 vs $50,399; 95% CI: $27,035-$31,904; P value < 0.001). Conclusions: Compared to non-AI-enhanced ICMs, AI-enhanced ICMs significantly reduce NAAs, leading to a projected decrease in clinic workload and associated costs, potentially improving workflow and health care efficiency. |
| format | Article |
| id | doaj-art-2981cd56bbb2400ea6fc92a5b4b9f308 |
| institution | DOAJ |
| issn | 2772-963X |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | JACC: Advances |
| spelling | doaj-art-2981cd56bbb2400ea6fc92a5b4b9f3082025-08-20T02:51:39ZengElsevierJACC: Advances2772-963X2025-04-014410165610.1016/j.jacadv.2025.101656Impact of Artificial Intelligence-Enhanced Insertable Cardiac Monitors on Device Clinic Workflow and Resource UtilizationAashish Katapadi, MD0Nikhila Chelikam, MBBS, MSCR1Sarah Rosemas, MPH2Lucas Higuera, MA, PhD3Ilyas Colombowala, MD4Shanti Bansal, MD5Douglas Darden, MD6Naga Venkata K. Pothenini, MD7Scott Koerber, DO8Rangarao Tummala, MD9Peter Park, MD10Rakesh Gopinathannair, MD11Dhanunjaya Lakkireddy, MD12Rajesh Kabra, MD13Kansas City Heart Rhythm Institute, Overland Park, Kansas, USAKansas City Heart Rhythm Institute, Overland Park, Kansas, USAMedtronic Cardiac Rhythm Management, Mounds View, Minnesota, USAMedtronic Cardiac Rhythm Management, Mounds View, Minnesota, USAHouston Electrophysiology Associates, Houston, Texas, USA; Octagos Health, Houston, Texas, USAHouston Heart Rhythm, Houston, Texas, USA; Octagos Health, Houston, Texas, USAKansas City Heart Rhythm Institute, Overland Park, Kansas, USAKansas City Heart Rhythm Institute, Overland Park, Kansas, USAKansas City Heart Rhythm Institute, Overland Park, Kansas, USAKansas City Heart Rhythm Institute, Overland Park, Kansas, USAKansas City Heart Rhythm Institute, Overland Park, Kansas, USAKansas City Heart Rhythm Institute, Overland Park, Kansas, USAKansas City Heart Rhythm Institute, Overland Park, Kansas, USAKansas City Heart Rhythm Institute, Overland Park, Kansas, USA; Address for correspondence: Dr Rajesh Kabra, Kansas City Heart Rhythm Institute, 5100 W 110th Street, Suite 200, Overland Park, Kansas 66211, USA.Background: Insertable cardiac monitors (ICMs) are essential for managing arrhythmias but often generate large numbers of transmissions and false alerts. Integrating artificial intelligence (AI) as part of the ICM workflow can reduce this burden. However, its impact on clinic workflow and resource utilization must be better understood. Objectives: The aim of the study was to assess the impact of AI-enhanced ICMs on clinic workflow and resource utilization. Methods: A cross-sectional analysis was conducted using real-world, deidentified ICM remote monitoring data from Octagos Health, which included 140 U.S. device clinics between July 2022 and April 2024. Nonactionable alerts (NAAs) were defined as false or repetitive alerts transmitted on the remote monitoring platforms but dismissed by device technicians and not forwarded to clinicians for review. We compared NAAs generated by AI-enhanced vs non-AI-enhanced ICMs and estimated associated staffing hours, resources, and costs extrapolated for a clinic managing 600 ICM patients. Results: Among 19,320 patients (mean age: 69 ± 13.5 years; 47.3% male), 68% had non-AI-enhanced ICMs, and 32% had AI-enhanced ICMs. The mean annual NAA volume per 600-ICM clinic was 5,078 for non-AI-enhanced ICMs and 2,110 for AI-enhanced ICMs, resulting in 559 fewer staffing hours (956 vs 397 hours; 95% CI: 513-605 hours; P value < 0.001) and $29,470 in annual savings ($20,929 vs $50,399; 95% CI: $27,035-$31,904; P value < 0.001). Conclusions: Compared to non-AI-enhanced ICMs, AI-enhanced ICMs significantly reduce NAAs, leading to a projected decrease in clinic workload and associated costs, potentially improving workflow and health care efficiency.http://www.sciencedirect.com/science/article/pii/S2772963X25000730AIartificial intelligencecardiac arrhythmiashealth economicsinsertable cardiac monitorsremote monitoring |
| spellingShingle | Aashish Katapadi, MD Nikhila Chelikam, MBBS, MSCR Sarah Rosemas, MPH Lucas Higuera, MA, PhD Ilyas Colombowala, MD Shanti Bansal, MD Douglas Darden, MD Naga Venkata K. Pothenini, MD Scott Koerber, DO Rangarao Tummala, MD Peter Park, MD Rakesh Gopinathannair, MD Dhanunjaya Lakkireddy, MD Rajesh Kabra, MD Impact of Artificial Intelligence-Enhanced Insertable Cardiac Monitors on Device Clinic Workflow and Resource Utilization JACC: Advances AI artificial intelligence cardiac arrhythmias health economics insertable cardiac monitors remote monitoring |
| title | Impact of Artificial Intelligence-Enhanced Insertable Cardiac Monitors on Device Clinic Workflow and Resource Utilization |
| title_full | Impact of Artificial Intelligence-Enhanced Insertable Cardiac Monitors on Device Clinic Workflow and Resource Utilization |
| title_fullStr | Impact of Artificial Intelligence-Enhanced Insertable Cardiac Monitors on Device Clinic Workflow and Resource Utilization |
| title_full_unstemmed | Impact of Artificial Intelligence-Enhanced Insertable Cardiac Monitors on Device Clinic Workflow and Resource Utilization |
| title_short | Impact of Artificial Intelligence-Enhanced Insertable Cardiac Monitors on Device Clinic Workflow and Resource Utilization |
| title_sort | impact of artificial intelligence enhanced insertable cardiac monitors on device clinic workflow and resource utilization |
| topic | AI artificial intelligence cardiac arrhythmias health economics insertable cardiac monitors remote monitoring |
| url | http://www.sciencedirect.com/science/article/pii/S2772963X25000730 |
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