AIMS: To evaluate the impact of Home Monitoringtrade mark(HM) remote control on patient medical treatment and on health-care resource utilization. METHODS AND RESULTS: One hundred and seventeen patients received HM pacemakers or defibrillators. A pacing expert nurse consulted daily the website and submitted critical cases to physician. During a mean follow-up of 227 +/- 128 days, 25,210 messages were received (23,545 daily messages and 1665 alert events) resulting in 90.7% of HM supervised days. Fifty-nine minutes/week for the nurse and 12 min/week for the physician were spent for HM data analysis during 267 web-connections. The mean connection time per patient was 115 +/- 60 s. The nurse submitted to the physician 133 critical cases in 56 patients. The diagnosis were atrial fibrillation (47%), ventricular tachyarrhythmias (9%), inappropriate implantable cardioverter defibrillator intervention (4%), unsustained ventricular tachycardia (7%), device suboptimal programming (23%), and impending heart failure (10%). Sixty-six unplanned follow-up in 43 patients led to drug therapy change (44%), device reprogramming (18%), diagnosis confirmation without further intervention (24%), no confirmation (6%), further diagnostic tests (9%). CONCLUSION: HM technology allowed optimization of medical treatment and device programming with low consumption of health-care resource.
AIMS: To evaluate the impact of Home Monitoringtrade mark(HM) remote control on patient medical treatment and on health-care resource utilization. METHODS AND RESULTS: One hundred and seventeen patients received HM pacemakers or defibrillators. A pacing expert nurse consulted daily the website and submitted critical cases to physician. During a mean follow-up of 227 +/- 128 days, 25,210 messages were received (23,545 daily messages and 1665 alert events) resulting in 90.7% of HM supervised days. Fifty-nine minutes/week for the nurse and 12 min/week for the physician were spent for HM data analysis during 267 web-connections. The mean connection time per patient was 115 +/- 60 s. The nurse submitted to the physician 133 critical cases in 56 patients. The diagnosis were atrial fibrillation (47%), ventricular tachyarrhythmias (9%), inappropriate implantable cardioverter defibrillator intervention (4%), unsustained ventricular tachycardia (7%), device suboptimal programming (23%), and impending heart failure (10%). Sixty-six unplanned follow-up in 43 patients led to drug therapy change (44%), device reprogramming (18%), diagnosis confirmation without further intervention (24%), no confirmation (6%), further diagnostic tests (9%). CONCLUSION: HM technology allowed optimization of medical treatment and device programming with low consumption of health-care resource.
Authors: Sergio Dubner; Angelo Auricchio; Jonathan S Steinberg; Panos Vardas; Peter Stone; Josep Brugada; Ryszard Piotrowicz; David L Hayes; Paulus Kirchhof; Günter Breithardt; Wojciech Zareba; Claudio Schuger; Mehmet K Aktas; Michal Chudzik; Suneet Mittal; Niraj Varma Journal: Ann Noninvasive Electrocardiol Date: 2012-01 Impact factor: 1.468
Authors: Abigale L Ottenberg; Keith M Swetz; Luke A Mueller; Samantha Gerhardson; Paul S Mueller Journal: Heart Lung Date: 2013-04-10 Impact factor: 2.210