title: Use of remote monitoring of newly implanted cardioverter-defibrillators: insights from the patient related determinants of ICD remote monitoring (PREDICT RM) study.
abstract: BACKGROUND
  Current guidelines recommend using remote patient monitoring (RPM) for implantable cardioverter-defibrillators, but the patterns of adoption of this technology have not been described. Successful use of RPM depends on (1) the enrollment of the patient into an RPM system and (2) subsequent activation of RPM by the enrolled patient. We examined RPM enrollment and activation rates and the patient, physician, and institutional determinants of RPM use.
  
  
  RESULTS
  Information about the use of RPM-capable devices was obtained from the Boston Scientific Corporation ALTITUDE program and linked to the National Cardiovascular Data Registry ICD Registry. Patients were first categorized as RPM-enrolled and RPM-not enrolled, and the RPM-enrolled patients were further categorized into RPM-active and RPM-inactive groups based on whether they transmitted RPM data. Variables associated with RPM enrollment and activation were identified with the use of multivariable logistic regression. Among 39 158 patients with newly implanted RPM-capable devices, 62% (n=24 113) were RPM-enrolled. Of those enrolled, 76% (n=18 289, or 47% of the entire cohort) activated their device. RPM enrollment was highly variable among institutions. The hospital-specific median odds ratio for RPM enrollment was 3.43, signifying that physician or institutional factors are associated with RPM enrollment. In contrast, the hospital-specific median odds ratio for RPM activation was 1.69. Age, race, health insurance, geographic location, and health-related factors were similarly associated with both RPM enrollment and activation.
  
  
  CONCLUSIONS
  RPM technology is used in less than half of eligible patients. Lack of enrollment into RPM systems is the major cause of underutilization, and this primarily relates to the local practice environment.
authors.affiliation: Section of Cardiovascular Medicine, Department of Medicine, Yale University School of Medicine and Center of Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, CT (J.G.A., H.B., Y.W., S.I.C., J.P.C.); Boston Scientific Corporation, St. Paul, MN (P.J., K.S.); Division of Cardiology, University of Colorado Anschutz Medical Campus, Aurora (P.V., F.A.M.); and Division of Cardiovascular Medicine, University of Southern California, Los Angeles (L.A.S.).
authors.forename: Joseph G
authors.initials: JG
authors.lastname: Akar
authors.forename: Haikun
authors.initials: H
authors.lastname: Bao
authors.forename: Paul
authors.initials: P
authors.lastname: Jones
authors.forename: Yongfei
authors.initials: Y
authors.lastname: Wang
authors.forename: Sarwat I
authors.initials: SI
authors.lastname: Chaudhry
authors.forename: Paul
authors.initials: P
authors.lastname: Varosy
authors.forename: Frederick A
authors.initials: FA
authors.lastname: Masoudi
authors.forename: Kenneth
authors.initials: K
authors.lastname: Stein
authors.forename: Leslie A
authors.initials: LA
authors.lastname: Saxon
authors.forename: Jeptha P
authors.initials: JP
authors.lastname: Curtis
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D015331:Cohort Studies; D016757:Death, Sudden, Cardiac / Q000453:epidemiology* / Q000517:prevention & control*; D017147:Defibrillators, Implantable / Q000706:statistics & numerical data*; D015716:Electrocardiography, Ambulatory / Q000706:statistics & numerical data*; D005260:Female; D006761:Hospitals / Q000706:statistics & numerical data; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D010043:Outcome and Process Assessment, Health Care; D010358:Patient Participation / Q000706:statistics & numerical data*; D012042:Registries / Q000706:statistics & numerical data; D012307:Risk Factors
keywords: population; registries; risk factors