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The American Journal of Managed Care March 2011
Fracture Risk Tool Validation in an Integrated Healthcare Delivery System
Joan C. Lo, MD; Alice R. Pressman, MS, PhD; Malini Chandra, MS; and Bruce Ettinger, MD
Improving Endoscopy Completion: Effectiveness of an Interactive Voice Response System
Joan M. Griffin, PhD; Erin M. Hulbert, MS; Sally W. Vernon, PhD; David Nelson, PhD; Emily M. Hagel, MS; Sean Nugent, BA; Alisha Baines Simon, MS; Ann Bangerter, BS; and Michelle van Ryn, PhD
Quality of Anticoagulation Control Among Patients With Atrial Fibrillation
Osnat C. Melamed, MD, MSc; Gilad Horowitz, MD; Asher Elhayany, MD; and Shlomo Vinker, MD
Healthcare Spending and Preventive Care in High-Deductible and Consumer-Directed Health Plans
Melinda Beeuwkes Buntin, PhD; Amelia M. Haviland, PhD; Roland McDevitt, PhD; and Neeraj Sood, PhD
Regulating the Medical Loss Ratio: Implications for the Individual Market
Jean M. Abraham, PhD; and Pinar Karaca-Mandic, PhD
On Telephone-Based Disease Management: Wrong Diagnosis, Right Prescription
Christobel Selecky; Reply by Brenda Motheral, BPharm, MBA, PhD
Connecting Statewide Health Information Technology Strategy to Payment Reform
John S. Toussaint, MD; Christopher Queram, MA; and Josephine W. Musser
Health Information Technology and Physicians' Perceptions of Healthcare Quality
Hai Fang, PhD, MPH; Karen L. Peifer, PhD, MPH, RN; Jie Chen, PhD; and John A. Rizzo, PhD
COPD-Related Healthcare Utilization and Costs After Discharge From a Hospitalization or Emergency Department Visit on a Regimen of Fluticasone Propionate-Salmeterol Combination Versus Other Maintenanc
Anand A. Dalal, PhD, MBA; Manan Shah, PhD; Anna O. D'Souza, PhD; and Douglas W. Mapel, MD
Currently Reading
Telemonitoring With Case Management for Seniors With Heart Failure
Marcia J. Wade, MD, FCCP, MMM; Akshay S. Desai, MD, MPH; Claire M. Spettell, PhD; Aaron D. Snyder, BA; Virginia McGowan-Stackewicz, RN, CCM; Paula J. Kummer, RN, BA; Maureen C. Maccoy, RN, MBA; and Ra

Telemonitoring With Case Management for Seniors With Heart Failure

Marcia J. Wade, MD, FCCP, MMM; Akshay S. Desai, MD, MPH; Claire M. Spettell, PhD; Aaron D. Snyder, BA; Virginia McGowan-Stackewicz, RN, CCM; Paula J. Kummer, RN, BA; Maureen C. Maccoy, RN, MBA; and Ra
An Internet-based telehealth intervention for elderly heart failure patients found no discernible incremental impact on morbidity or mortality compared with case management alone.

Objective: To assess the impact of supplementing nurse case management with Internet-connected telemonitoring on clinical outcomes in an elderly heart failure (HF) population.

Study Design: Randomized clinical trial allocating high-risk HF subjects to the telehealth system with case management (THCM) versus case management (CM) alone.

Methods: Medicare Advantage members with HF and recent hospitalization were randomized to THCM or CM. Consenting participants received THCM for 6 months or the health plan’s usual Medicare specialized CM as long as deemed necessary. The primary outcome measure was a composite of all-cause hospitalization, ED visit, or death. Because only a subset of those who were randomized consented and participated, the strategies were evaluated as-treated rather than by intention-to-treat, with multivariate adjustment in logistic regression models for confounding introduced by postrandomization exclusions.

Results: The treated sample size was 164 subjects in THCM and 152 in CM. Treatment arms did not differ significantly for the primary composite outcome (45% for THCM vs 40% for CM, relative risk 1.18; P = .22). Telehealth alerts prompted frequent telephonic contact, increasing THCM case managers’ workload. The participant population overall had 42% fewer inpatient days during the intervention period compared with the previous year.

Conclusions: Despite effective implementation of an Internet-based telehealth intervention in an elderly HF population, there was no discernible impact on overall morbidity or mortality. Notably, limited postrandomization participation decreased power to detect a difference. The reduction in days hospitalized for trial participants overall underscores the benefit of CM for such HF patients.

(Am J Manag Care. 2011;17(3):e71-e79)

Medicare Advantage members with heart failure and recent hospitalization were randomized to home telemonitoring with case management or case management alone.


  • In 6 months, there was no significant difference in rates of hospital admission, emergency department visits, or death between the 2 groups.


  • Overall, telemonitoring increased the case manager activity required per participant, and participant satisfaction and adherence were high.


  • A 42% reduction in inpatient days during the intervention period compared with the previous year suggested positive overall impact of case management.
Heart failure (HF) is a major public health problem in the United States. It represents the most common cause for hospitalization among elderly Americans1 and was the nation’s most expensive medical condition to treat in 2005, costing $76 billion. While recent advances in medical treatments for HF have improved patient outcomes, overall morbidity and mortality remain high,2 with approximately 30% to 40% of patients requiring readmission within 6 months of hospitalization.

We conducted a randomized controlled clinical trial to explore the impact of supplementing nurse case management (CM) with the Intel Health Guide System (HGS) in an elderly population with HF and a high risk for rehospitalization. The goal was to assess impact on outcomes and quality of life, and also to assess the feasibility of utilizing an Internet-based telemonitoring technology to facilitate CM in an elderly HF population with multiple comorbidities.



The study design was a prospective, randomized, active controlled study, in which members were allocated to the telehealth system with CM (THCM) or to CM alone.

Study Population

Aetna Medicare Advantage members with medical and pharmacy benefits were identified through analysis of claims and eligibility information. Criteria for invitation to the study were residence in New Jersey, New York, or Pennsylvania; medical claims for chronic HF in medical claims in the past 3 years; inpatient admission or 2 or more emergency department (ED) visits for any cause within the 6 months before identification; and high risk for a subsequent admission or ED visit based on the health plan’s proprietary predictive model.

Exclusion criteria included claims or utilization records indicating a terminal condition, end-stage renal disease, dementia, use of a ventricular assist device, active listing for cardiac transplantation, completed heart transplant, or requirement for chronic or ongoing intravenous HF medication. Members managed in the health plan’s CM program within the 30 days prior to randomization were also excluded.

Recruitment, consent procedures, and study design were approved by Western Institutional Review Board (Olympia, WA, Protocol 20081787). Oral and written consent to telehealth and the study were sought after randomization for THCM. For those assigned to CM, consent was implied by their oral agreement to participate in CM. Participation began for both groups as telehealth systems were deployed between December 2008 and June 2009.

Case Management

All participants in both arms of the study received Aetna Medicare’s current standard CM services, which are designed to meet the frequently complex needs of older adults. These services began upon enrollment. For CM, case closure occurred when member goals were deemed met. For THCM, CM continued throughout the monitoring period. Thus, in some cases THCM members received CM longer than members in CM alone. Nonparticipants among both randomized groups continued to be eligible for identification and outreach for CM. Case managers were not directly responsible for patient care, but worked closely with the members, physicians, subspecialty providers,  and others to facilitate care to manage the complex cardiac, oncologic, psychiatric, social, other medical, and/or end-of-life needs of the participants. Identified needs were addressed on scheduled calls with the member (typically 2-3 times per week initially, with frequency decreasing as issues resolved). Common issues covered included health education, safety and emergency measures, medication regimen, and care coordination needs.

Telehealth Monitoring With Case Management Group

In addition to the CM intervention outlined above, the THCM subjects received home monitoring of weight and blood pressure. They also answered questions about adherence and their health regimen through their use of the HGS.

Telehealth System Description

The Intel HGS is a US Food and Drug Administration–approved system comprising a touch screen, a remote patient management unit placed in the member’s home, and a case manager user interface accessed via secure Internet link through a broadband connection. A wired blood pressure monitor and a wireless weight scale transmitted patient data to the CM team. The system was also programmed to ask members about their health status, activities, and medication adherence, and to offer and show educational videos. HGS telemonitoring sessions were administered weekdays at a time the participant selected, according to the member-customized rotocol the case manager had entered. Alerts to the case manager occurred when measurements or response violated threshold values set in alignment with the Seventh report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure blood pressure guidelines,3 HF management guidelines,4,5 and the physician’s care plan. Participants in THCM transmitted their weight and blood pressure as often as every weekday. Periodically, they were asked to input responses about medication adherence, exercise, and any recent ED visits or hospital stays. The HGS-mediated data flow between the participants and case managers catalyzed frequent CM interactions between the participant, his or her case manager, and the participant’s physician. Educational content was also available to participants on demand  through the HGS. Case managers were instructed to check the Web-based clinical user interface for alerts on each member’s condition and to respond with care coordination assistance as needed. Case managers modified members’ care protocols and thresholds as needed to follow the protocol and the physician’s care plans.

Outcome Measures and Statistical Analyses

The primary outcome measure was admission to an acute care hospital, an ED visit, or death during the measurement period, as determined through claims and Medicare eligibility data.

Secondary variables reflecting healthcare utilization were also measured using claims data. Measures included total hospital inpatient days, ED visits, primary care visits, specialist visits, prescriptions filled for selected types of cardiac medication, and the subset of hospital admission and ED visits for cardiovascular cause. Acute hospital inpatient days per member per year for both groups during the intervention period were also compared with the groups’ rate of hospital days in the year leading up to their randomization date.

Participant experience was measured telephonically before and after the intervention period, using the Quality Control Inc SF-12 Health Survey (SF-12) ( For THCM, a member experience and satisfaction survey (5-point Likert scale with responses ranging from strongly disagree to strongly agree) was administered directly via HGS at the end of the study. Descriptive measures included the proportion of telehealth participants completing the planned 6 months’ monitoring and program adherence. Adherence was measured as proportion of the scheduled weekday protocol-based telehealth sessions completed.

Sample Size. Based on a proprietary predictive model showing an anticipated event rate of 49% in 6 months for the control arm, we calculated that a sample size of 138  patients per arm would provide 80% power to detect a statistically significant decrease of 30% in the primary composite outcome with THCM. Calculations were conducted  using SAS version 9.1.3 (SAS Institute Inc, Cary, NC) using an alpha level of .05 for a 1-tailed test of significance.

Analyses. Baseline characteristics were expressed as means and percentages, and compared between the 2 groups using X2 tests and independent t tests. The analysis of the primary outcome was initially conducted according to intention-to-treat for the randomized population. However, since only a fraction of the randomized population ultimately enrolled in the study, the data are presented for the as-treated cohort to better assess the effect of the intervention as utilized in our population. These as-treated analyses compared outcomes for THCM members who consented and had HGS installed with those of members who began the CM intervention during the same time period.

The odds ratio for the primary end point was assessed using logistic regression models adjusted for baseline differences between the 2 groups that persisted after randomization and subsequent dropouts. The multivariate regression analyses also included numerous covariates to control for any differences between the groups, including age, state of residence, presence of various comorbid conditions, and prior cardiac events including coronary artery bypass surgery. Date of randomization was included as a covariate to account for temporal differences. Sensitivity analyses were performed on secondary outcomes capping outliers’ results at the 99th percentile;  since no difference was seen, only the raw data are shown. Poisson regression analyses using generalized estimating equations were used to compare rates of events (number of hospital admissions, number of ED visits, number of acute inpatient hospital days).


Baseline Demographic, Clinical, and Utilization Characteristics

We initially identified 2314 members who met the study eligibility criteria. A total of 114 were excluded before randomization due to loss of health plan coverage or missing contact information. The remaining 2200 were randomized to THCM or CM. In the interval between randomization and study enrollment, there was considerable attrition in  the study cohort. The Figure details the specific reasons for nonparticipation among those initially randomized, such as CM for anotherreason, lack of desire to participate, or lack of success reaching members. Ultimately, 164 members consented and received THCM, and 152 were placed into the CM arm of the study.

The randomized groups were similar in demographics, prior healthcare utilization, and clinical conditions. Average age was 78.1 years, and the average individual had  numerous comorbid conditions. The treated groups included a higher proportion of black/African American members than the nonparticipating group (24.4% of THCM and 20.4% of CM participants vs 16% of nonparticipants; relative risk 1.5 and 1.3, respectively, P <.05), but the groups were statistically similar with respect to other demographic and clinical aspects. Detailed baseline characteristics for the treated groups are shown in Table 1. Treated members in the THCM arm of the study were younger than those  in CM (75.8 vs 77.7 years, P = .015), were more likely to have had coronary bypass surgery (11.1% vs 3.9%, P = .019), and were more likely to be taking angiotensin receptor antagonists (31.1% vs 20.4%, P = .03). The burden of comorbid medical illness was high and was similar between groups, with a median of at least 5 comorbid conditions per person.

Process Results: Uptake, Adherence, Alert Activity, and Interventions

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