Use of Remote Monitoring Is Associated With Lower Risk of Adverse Outcomes Among Patients With Implanted Cardiac Defibrillators
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We examined the association between the use of remote patient monitoring (RPM) of implantable cardioverter defibrillators (ICD) and all-cause mortality and rehospitalization among patients undergoing initial ICD implant.
Methods and Results—
A limited data set was constructed from Boston Scientific ALTITUDE Registry and National Cardiovascular Data Registry ICD Registry between January 2006 and March 2010. Vital status was determined using the Social Security Death Master File. All-cause mortality up to 3 years was compared in patients who used RPM with those who did not use RPM. Time-dependent frailty Cox models quantified the association between RPM use and all-cause mortality. Analyses were repeated in subgroups based on age, sex, race, ICD type, indication, and cardiomyopathy pathogenesis. Similar methodology examined the association between RPM use and all-cause rehospitalization in patients enrolled in Medicare fee-for-service patients ≥65 years. The study cohort (n=37 742, age 67±13, 72% male) had a 3-year mortality of 20.9% (median follow-up 832 days). In multivariable analyses, patients using RPM (n=22 023, 58%) had lower risk of mortality compared with those not using RPM (hazard ratio 0.67, 95% confidence interval 0.64–0.71, P<0.0001). The 3-year all-cause rehospitalization rate in the Medicare population (n=15 254) was 69.3% (median follow-up 922 days). Risk of rehospitalization of patients using RPM (n=9150, 60%) was lower than those not using RPM (hazard ratio 0.82, 95% confidence interval 0.80–0.84, P<0.0001). Findings were consistent across subgroups.
Among patients undergoing initial ICD implant, RPM use is associated with significantly lower risk of adverse outcomes.
WHAT IS KNOWN
Essentially all implantable cardioverter defibrillators have the capacity for remote patient monitoring of device function and patient status.
Prior studies have shown that only half of patients with implantable cardioverter defibrillators actually transmit information using remote patient monitoring
WHAT THE STUDY ADDS
Analyzed data from the implantable cardioverter defibrillator Registry to assess the association of use of remote patient monitoring with outcomes up to 3 years after device implantation.
Patients with implantable cardioverter defibrillators who transmitted data using remote monitoring were at substantially lower risk of death and readmission compared with patients who did not transmit data.
Findings were consistent across multiple subgroups, including age, sex, pathogenesis of cardiomyopathy, and device type.
Implantable cardiac defibrillators (ICD) improve the survival of appropriately selected patients at risk of sudden cardiac arrest as a result of ventricular tachyarrhythmias.1 Nevertheless, the long-term mortality and morbidity of patients who receive ICDs remains substantial, and there is a continued need to further address the risk of adverse events. Remote patient monitoring (RPM) is a promising method for improving the outcomes of patients with ICDs. The majority of currently available ICDs possess the capacity for RPM, and many have the capability for wireless RPM, allowing for automatic remote device interrogation and monitoring of device- and disease-specific parameters. Using RPM, clinicians can monitor patients’ clinical status between office visits and intervene early if signs of device malfunction or clinical deterioration are detected.2 Remote monitoring of ICDs is believed to be beneficial from a device safety standpoint and improves healthcare efficiency by reducing the need for in-person device follow-up.3 Preliminary evidence suggests an association between RPM and improved clinical outcomes,4 and professional societies have endorsed its routine use.5–10
Editorial see p 1010
Nevertheless, despite the near universal availability of RPM, this technology is not uniformly used in practice.11 One barrier to its widespread adoption may be continued uncertainty regarding its effect on patient outcomes. Incorporating RPM into routine clinical care requires the reorganization of office workflow and resource allocation.12 Clinicians may be more likely to make that investment if there were more robust evidence regarding the impact of RPM on clinical outcomes, including mortality and rehospitalization. To address this gap in knowledge, we examined the association of RPM use and all-cause mortality and rehospitalization among patients undergoing first-time ICD implantation.
Data Sets and Derivation of Study Population
The study was performed by linking the following data sources: (1) the ACCF National Cardiovascular Data Registry (NCDR) ICD Registry, (2) the Boston Scientific Corporation ALTITUDE database, (3) the Social Security Death Master File, and (4) Medicare administrative claims data.
We created a limited data set from the NCDR ICD Registry that had been previously linked to the Death Master File using direct identifiers, including social security number, to determine vital status. We included patients with an RPM-capable device who underwent first-time device implantation between January 2006 and March 2010. We excluded patients with missing linking fields; received devices by manufacturers other than Boston Scientific; received a nonwireless (wanded) device; underwent device implantation at an institution that did not participate in the ALTITUDE database; had a prior pacemaker or ICD; died during their initial hospital stay, were <21 or >89 years of age, or had a history of cardiac transplant or an epicardial lead because these are rare and not representative of the overall population; were in hospitals not reporting all their implants to the ICD Registry; or had unknown vital status. We then used indirect patient identifiers (age, sex, date of implant, and facility Medicare Provider Number) to link ICD Registry data with a comparable limited data set derived from the ALTITUDE database.11 To examine the association of RPM with risk of rehospitalization, we linked the study cohort with corresponding Medicare fee-for-service administrative claims data for beneficiaries who were ≥65.
For descriptive analyses, the study population was divided into 2 groups based on RPM utilization within the first year after ICD implantation: (1) the No RPM group consisted of patients without any RPM transmissions and (2) the RPM group consisted of patients who had at least 1 transmission within the first year after implantation. We compared patient-, physician-, and hospital-baseline characteristics between the 2 groups. Continuous and categorical variables were examined by t test and χ2 test, respectively.
A multivariable time-dependent Cox model was used to examine the association between the RPM and survival up to 3 years after device implantation.13 In this model, RPM activation was a time-varying covariate to account for differences in the time from ICD implantation to first RPM transmission. The model accounted for clustering of the patients within hospitals through the inclusion of a hospital-specific random effect that has a multiplicative effect on the baseline hazard function. Patients with <3 years of follow-up were censored at the time of last follow-up. The model was adjusted for patient characteristics that may be associated with RPM use and outcomes including: age, sex, race, reason for admission, insurance type, ICD indication and type, presence of comorbidities (eg, diabetes mellitus, hypertension, renal failure, lung disease, heart failure, atrial fibrillation, history of ventricular tachycardia, syncope, sinus node dysfunction, cerebrovascular disease), New York Heart Association Class, left ventricular ejection fraction, laboratory values (serum sodium, blood urea nitrogen, creatinine), presence of periprocedural complications, geographical region, and distance from patient to implanting facility. The model also adjusted for physician and hospital characteristics, including physicians’ proportional use of Boston Scientific devices, hospital location, ownership, teaching status, facility type, and population density. The missing rates of variables included in the model were <1%, except for 3 hospital characteristics obtained from the American Hospital Association Survey (hospital ownership, teaching status, and facility type) for which the missing rate was 3.2%. Multiple imputation techniques were used for missing values, where all predictors were used to impute missing values with fully conditional specification approach. Linear regression method was used for continuous variables and logistic regression method was used for categorical variables. The coefficients of 5 rounds of imputation were combined to obtain the final estimates for the models. The proportional hazard assumption of the time-independent covariates was confirmed by log–log plotting.
The associations between RPM utilization and survival up to 3 years were examined in several prespecified subgroups: age (<65 versus ≥65 years), sex (male versus female), race (white versus nonwhite), ICD type (single/dual chamber versus cardiac resynchronization therapy-defibrillator), device indication (primary versus secondary prevention), and cardiomyopathy pathogenesis (ischemic versus nonischemic). After review of preliminary findings, we added 2 additional analyses. In the first, we restricted the analysis to patients who had been hospitalized specifically for the purposes of ICD implantation. In the second, we restricted the analysis to patients with a history of previous heart failure hospitalization. In these subgroups, the heterogeneity in the relationship between RPM and mortality was assessed with tests of interaction in the multivariable models.
Secondary analyses were performed for mortality using the landmark analysis approach.14 This method ignores all deaths before landmark time and classifies patients into RPM and No RPM groups based on their status at the landmark. Our primary analysis used a landmark of 90 days, and sensitivity analyses were performed using landmarks of 60- and 180-days. Kaplan–Meier survival plots estimated survival functions between the RPM and No RPM groups. To ensure that the RPM and No RPM groups were comparable, logistic regression models, including all the patient-, physician-, and hospital-characteristics, were used to predict the probability of RPM utilization and generate the inverse probability weighting for the RPM and No RPM groups.15 The differences between patient-, physician-, and hospital-characteristics in the weighted RPM and No RPM groups were examined by calculating standardized differences. Small standardized differences (<10%) indicated the balance between the groups. Cox proportional hazard models with inverse probability weighting were used to examine the independent association between RPM utilization and survival up to 3 years.
We developed a multivariable time-dependent Cox model to examine the association between the RPM activation and all-cause rehospitalization up to 3 years after device implantation.13 In the model, rehospitalizations were considered as potentially recurrent events and accounted for the same factors used in the survival analyses. In the rehospitalization models, patients were censored at the time point of last follow-up or death. The association between RPM and all-cause rehospitalization was further examined in the prespecified subgroups identified above. Finally, we repeated the landmark analyses examining time to first rehospitalization at 90 days after device implantation, with sensitivity analyses using 60- and 180-day landmarks. Analyses again used Cox proportional hazard models with inverse probability weighting to examine the independent association between RPM utilization (inverse probability weight) and rehospitalization. We performed all analyses on SAS Version 9.3 (SAS Inc., Cary, NC). P values presented are 2-sided, and <0.05 were considered statistically significant.
Derivation of Study Cohorts
Derivation of the study cohorts is shown in Figure 1. After applying the exclusion criteria, we identified a cohort of 54 349 eligible patients for whom mortality data were available. This cohort was linked to the ALTITUDE data set, yielding a final mortality cohort of 37 742 patients. In order to examine rehospitalization, we restricted the analysis to patients at least 65 years of age enrolled in Medicare fee-for-service. This resulted in a cohort of 15 254 patients for whom rehospitalization data were available.
Table 1 shows the baseline characteristics of patients using RPM within the first year after implant compared with those who did not. Overall, there were relatively small differences in the baseline characteristics of the 2 groups. As previously described,11 a higher proportion of patients in the RPM group were white, had private insurance, had been electively admitted for the ICD implantation, had a QRS duration >120 ms and left bundle branch block, and had received cardiac resynchronization therapy-defibrillator. A higher proportion of the No RPM group had a history of diabetes mellitus, renal dysfunction, and hyponatremia. In addition, there were differences in RPM use based on geography, population density, distance to implanting facility, and physicians’ use of Boston Scientific devices.
|Patient Characteristics||No RPM Group (N=16890)||RPM Group (N=20852)||P Value|
|Mean age in years±SD (range)||66.5±13.0 (21–89)||67.5±12.1 (21–89)||<0.0001|
|≤50||2035 (12.0%)||1948 (9.3%)||<0.0001|
|50–60||3103 (18.4%)||3510 (16.8%)|
|60–70||4475 (26.5%)||5889 (28.2%)|
|70–80||4870 (28.8%)||6756 (32.4%)|
|>80||2407 (14.3%)||2749 (13.2%)|
|Male||12 268 (72.6%)||14 775 (70.9%)||0.0001|
|White non-Hispanic||11 752 (69.6%)||17 466 (83.8%)||<0.0001|
|Black non-Hispanic||2897 (17.2%)||2148 (10.3%)|
|Hispanic||1372 (8.1%)||656 (3.1%)|
|Other||848 (5.0%)||567 (2.7%)|
|Medicare||10 494 (62.1%)||13 421 (64.4%)||<0.0001|
|Medicaid||1269 (7.5%)||849 (4.1%)|
|Governmental insurance||181 (1.1%)||195 (0.9%)|
|Commercial/HMO||4209 (24.9%)||5958 (28.6%)|
|Non-US insurance/none||737 (4.4%)||429 (2.1%)|
|Elective admission for ICD||9446 (55.9%)||13 980 (67.0%)||<0.0001|
|Cardiac||2955 (17.5%)||2394 (11.5%)|
|Noncardiac||3781 (22.4%)||4045 (19.4%)|
|Unknown||681 (4.0%)||413 (2.0%)|
|Diabetes mellitus||6990 (41.4%)||7588 (36.4%)||<0.0001|
|Renal failure/dialysis||874 (5.2%)||591 (2.8%)||<0.0001|
|Ejection fraction ≤35%||15 149 (89.7%)||18 441 (88.4%)||0.0005|
|BUN ≤20, mg/dL||7929 (46.9%)||10 643 (51.0%)||<0.0001|
|20–40||6853 (40.6%)||8260 (39.6%)|
|>40||2085 (12.3%)||1908 (9.2%)|
|Sodium ≤135, mmol/L||3175 (18.8%)||3125 (15.0%)||<0.0001|
|135–145||13 492 (79.9%)||17 480 (83.8%)|
|>145||191 (1.1%)||198 (0.9%)|
|Single chamber||2774 (16.4%)||2648 (12.7%)||<0.0001|
|Dual chamber||5333 (31.6%)||5762 (27.6%)|
|Biventricular||8762 (51.9%)||12 421 (59.6%)|
|Quartiles of physicians’ proportional use of Boston Scientific ICD devices,%|
|≤11||5063 (30.0%)||5157 (24.7%)||<0.0001|
|11–18||4410 (26.1%)||5158 (24.7%)|
|18–28||3909 (23.1%)||5428 (26.0%)|
|>28||3508 (20.8%)||5109 (24.5%)|
|Adverse events||579 (3.4%)||599 (2.9%)||0.0020|
|Public||1377 (8.2%)||1408 (6.8%)||<0.0001|
|Not-for-profit||12 467 (73.8%)||15 768 (75.6%)|
|Private||2585 (15.3%)||2909 (14.0%)|
|Unknown||461 (2.7%)||767 (3.7%)|
|Council of teaching hospitals||5415 (32.1%)||5781 (27.7%)||<0.0001|
|Teaching||4162 (24.6%)||5547 (26.6%)|
|Other||6852 (40.6%)||8757 (42.0%)|
|Unknown||461 (2.7%)||767 (3.7%)|
|CABG||14 276 (84.5%)||17 970 (86.2%)||<0.0001|
|CATH||647 (3.8%)||490 (2.3%)|
|Other||1506 (8.9%)||1625 (7.8%)|
|Unknown||461 (2.7%)||767 (3.7%)|
|New England||615 (3.6%)||769 (3.7%)||<0.0001|
|Atlantic||7149 (42.3%)||6460 (31.0%)|
|Central||5763 (34.1%)||9828 (47.1%)|
|Mountain||905 (5.4%)||987 (4.7%)|
|Pacific||1966 (11.6%)||2037 (9.8%)|
|Other||492 (2.9%)||771 (3.7%)|
|Distance from patient to facility, miles|
|≤25||12 363 (73.2%)||13 734 (65.9%)||<0.0001|
|25–50||2164 (12.8%)||3387 (16.2%)|
|50–100||1205 (7.1%)||2160 (10.4%)|
|>100||1072 (6.3%)||1435 (6.9%)|
|Population density per sq mile, persons|
|≤3000||14 252 (84.4%)||19 098 (91.6%)||<0.0001|
|Mean number of monthly transmissions (SD)||NA||4.3 (1.6)||<0.0001|
Time-Dependent Cox Models
Among study patients, median follow-up was 832 days (Q1, 623; Q3, 1126), and the 1- and 3-year mortality was 9.4% and 20.9%, respectively. In multivariable analyses, patients using RPM had significantly lower risk of mortality compared with patients who did not (hazard ratio [HR] 0.67, 95% confidence interval [CI] 0.64–0.71, P<0.0001). In all prespecified subgroups, the mortality risk of patients who used RPM was lower than that of patients who did not. Most interaction P values were >0.05 with the exception of the comparison of ICD and cardiac resynchronization therapy-defibrillator devices, where the association between RPM and lower risk of mortality was stronger in the ICD group (interaction P value =0.02; Table 2).
|Subgroups||Survival Hazard Ratio (95% CI)||Interaction P Value||Rehospitalization Hazard Ratio (95% CI)||Interaction P value|
|Male||0.68 (0.64–0.72)||0.33||0.82 (0.80–0.84)||0.25|
|Female||0.66 (0.60–0.73)||0.80 (0.77–0.84)|
|White||0.66 (0.63–0.70)||0.10||0.80 (0.78–0.82)||<0.0001|
|Non-white||0.74 (0.66–0.83)||0.90 (0.85–0.95)|
|ICD||0.61 (0.57–0.67)||0.02||0.82 (0.79–0.86)||0.52|
|CRT-D||0.71 (0.67–0.75)||0.81 (0.78–0.83)|
|Primary prevention||0.68 (0.64–0.71)||0.09||0.80 (0.78–0.82)||0.03|
|Secondary prevention||0.66 (0.58–0.75)||0.92 (0.86–0.98)|
|Ischemic||0.68 (0.64–0.73)||0.34||0.84 (0.81–0.86)||<0.0001|
|Non-ischemic||0.66 (0.61–0.72)||0.77 (0.73–0.80)|
|Admitted for this procedure:||0.67 (0.63–0.71)||0.81 (0.78–0.84)|
|History of HF hospitalization:||0.70 (0.66–0.75)||0.84 (0.81–0.87)|
For all 3 mortality landmark analyses (60-, 90-, and 180-day landmarks), the standardized differences for all characteristics between the weighted RPM and No RPM groups were <10% (Table I in the Data Supplement). Kaplan–Meier survival curves demonstrated consistently lower mortality in RPM patients compared with the No RPM patients (all P<0.001). The 90-day curves are shown in Figure 2. The adjusted hazard of mortality up to3 years was significantly lower among RPM patients compared with No RPM patients: 60-day landmark (HR 0.78, 95% CI 0.73–0.82), 90-day landmark (HR 0.80, 95% CI 0.76–0.84), 180-day landmark (HR 0.76, 95% CI 0.72–0.80).
All-cause rehospitalization was evaluated among 15 254 Medicare fee-for-service recipients. The 3-year all-cause rehospitalization rate was 69.3% with a median follow-up of 922 days (Q1, 662; Q3, 1195). Patients who used RPM had a significantly lower risk of rehospitalization compared with those who did not use RPM (HR 0.82, 95% CI 0.80–0.84, P<0.0001). In subgroup analyses, the risk of 3-year rehospitalization rate of patients using RPM was consistently lower than that of patients who did not, with a more pronounced effect in whites, primary prevention, and nonischemic cardiomyopathy (Table 2). In landmark analyses, the inverse probability weight adjusted Kaplan–Meier curves demonstrated modestly lower rates of rehospitalization among patients who used RPM compared with those who did not use RPM. The 90-day curves are shown in Figure 3. The adjusted hazard of rehospitalization up to 3 years was significantly lower among RPM patients compared with No RPM patients for the 60-day landmark (HR 0.92, 95% CI 0.88–0.97) and the 90-day landmark (HR 0.93, 95% CI 0.88–0.98), but not for the 180-day landmark (HR 0.95, 95% CI 0.90–1.01).
In this observational study of patients undergoing first-time ICD implantation, patients who used wireless RPM had a significantly lower risk of death and rehospitalization compared with those who did not. The lower risk of adverse outcomes was observed in all patient subgroups. Given that RPM is underutilized, despite its widespread availability, our findings provide evidence supporting broader use of this technology.
This study builds on earlier analyses demonstrating an association between RPM use and survival.4 However, that study lacked detailed information about the characteristics of patients who did and did not use RPM, which raised concerns about residual confounding.16 Using detailed clinical information captured by the NCDR ICD Registry, our study found an association between RPM use and survival that persisted after adjustment for a large number of clinical and nonclinical factors. Furthermore, we demonstrated a similar association between RPM use and lower risk of hospital rehospitalization.
There are multiple potential explanations for the association between RPM use and improved clinical outcomes. Remote monitoring provides a mechanism through which physicians can immediately respond to changes in clinical status and manage accordingly (eg, onset of atrial and ventricular arrhythmias). Prior studies have demonstrated that RPM improves device safety through continuous monitoring of device integrity, allowing rapid intervention in case of device or lead malfunction (eg, impending lead or battery failure in a pacemaker-dependent patient).3,17–19 Patients who use RPM may also be more engaged in their healthcare and more connected with their healthcare providers. Thus, RPM utilization may directly promote patient engagement or may simply be a marker for patients who are inherently more connected to their medical care. Importantly, our findings are consistent with the IN-TIME trial, which randomized heart failure patients with ICDs to remote monitoring or standard follow-up. The study demonstrated improved survival and disease-specific health status in the remote monitoring arm compared with the standard follow-up patients.20,21 However, use of RPM in the IN-TIME trial was not representative of usual clinical practice because RPM transmissions were sent in parallel to both the treating physicians as well as a central monitoring unit whose role was to ensure that RPM transmissions are reviewed by the physicians and acted upon accordingly. Our study suggests that the use of RPM under real-world conditions without central monitoring may be associated with lower risk of adverse outcomes.
Although professional societies advocate use of RPM,5,6 this technology is underutilized.11,22 The reasons for RPM underutilization are multifactorial and include concerns about reimbursement, resources, availability, staff coverage, device clinic restructuring, medico-legal issues, as well as uncertainty regarding the impact of RPM on patient outcomes. Some studies have shown benefit in using telemonitoring in management of heart failure, but large randomized trials have not consistently demonstrated improved clinical outcomes, thereby raising questions regarding the utility of this approach to patient care.23–25 However, remote monitoring of ICDs is different because the technology can be wireless, automatic, and achieved with minimal active patient participation. Newer generation RPM modules have mobile phone capability, which may further increase utilization. The present study suggests that RPM is associated with lower risk of mortality and rehospitalization in the real-world, and we think that the weight of the available evidence justifies strong consideration of its routine use in clinical practice. Additional large, randomized clinical trials would provide more definitive evidence of the effect of RPM on outcomes.
The safety and reliability of RPM are well-established. RPM has been associated with lower healthcare costs by reducing in-person office visits and patients also generally prefer it to conventional device follow-up,.2,3 However, there is a pressing need to understand how to efficiently and effectively incorporate RPM into clinical practice. RPM utilization requires the management of large amounts of information, and this may involve a significant reconfiguration of practice patterns and office workflow.12 The system has the capability of serving as a disease management solution and has the advantage of an established wireless infrastructure that is capable of direct communication with electronic medical records. Although many providers routinely use RPM, insights into the organizational strategies and enabling structures that promote the successful integration of RPM into clinical practice have not been identified and shared broadly across the community of implanting physicians.
This study is observational and patients were not randomly assigned to a monitoring strategy. Although we used appropriate analytic approaches to minimize the effect of measured confounders, unmeasured confounding cannot be excluded. Second, the only outcomes were all-cause mortality and all-cause rehospitalization. Additional research will be needed to determine the association of RPM use and cause-specific rehospitalization. This represents a statistical challenge given the use of time-dependent multivariable Cox models. Third, although we have detailed information about patients at the time of implantation, we do not have information about changes in patient status and medical therapy during the follow-up period and could not examine differences in device programming. Finally, analyses were restricted to patients receiving Boston Scientific devices. Although most ICDs have the capacity for RPM, the technology and interfaces differ across manufacturers, and the extent to which our findings are generalizable to other devices is not known.
In a population of patients undergoing first-time ICD implant, the use of RPM was associated with significantly lower risk of adverse outcomes. Given the widespread availability of RPM on current ICDs, these findings provide evidence supporting broader utilization of this technology.
This study represents a collaboration between the American College of Cardiology Foundation (ACCF), the Yale/New Haven Hospital Center for Outcomes Research and Evaluation (CORE), and the Boston Scientific Corporation. The views expressed in this article represent those of the authors and do not necessarily represent the official views of the NCDR or its associated professional societies identified at www.ncdr.com. ICD Registry is an initiative of the American College of Cardiology Foundation and the Heart Rhythm Society. We thank Ms Bonnie Garmisa for her invaluable help in organizing this project and preparing the article.
Sources of Funding
Dr Akar served on a steering committee for Biotronik and is a consultant for Biosense Webster. Drs Curtis and Bao and Mr Wang receive salary support from the ACC NCDR to provide analytic services and with the Centers for Medicare & Medicaid Services to support development of quality measures. Dr Curtis holds equity interest in Medtronic. Dr Saxon receives research support from Boston Scientific, Medtronic, and St Jude Medical and serves on advisory boards for Boston Scientific and St Jude Medical. Dr Masoudi has a contract with the American College of Cardiology for his role as Senior Medical Officer, NCDR. Dr Stein and Mr Jones receive salary from and hold equity interest in Boston Scientific. The other authors report no conflicts.
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