Study Results
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Basic Information
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COMPLETED
NA
1660 participants
INTERVENTIONAL
2006-03-31
2010-07-31
Brief Summary
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Telemedical Interventional Monitoring in Heart Failure
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Detailed Description
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Telemonitoring, which bridges clinicians and patients with communication technology, holds promise for closing the gap in HF care (4). This technology has the potential for standardized, widespread implementation (and long-term maintenance) in the near future because it can be easily applied to large patient populations and integrated into the current medical care system. Supporting this potential, preliminary evaluations have suggested that telemonitoring is feasible across a broad spectrum of typical HF patients, relatively inexpensive on a per-patient basis, and highly effective in improving health outcomes. Thus, this approach is ready for rigorous evaluation.
Accordingly, we propose an office-based, multicenter, randomized controlled trial (Tele-HF study) to determine the effectiveness of a telemonitoring strategy in decreasing hospital readmissions and death in patients with HF. Many HF patients experience deterioration in their health status and an increase in weight and symptoms over a period of days and weeks before ultimately presenting to medical attention and requiring hospitalization. Our premise is that a frequent monitoring system can alert clinicians to the early signs and symptoms of decompensation, providing the opportunity for intervention before the patient becomes severely ill and requires hospitalization. Moreover, such a system can engage patients in their care and provide instruction about beneficial self-care strategies. This intervention is not intended to substitute for communication relating to acute care or acute, sudden changes in health status. In these cases, patients are instructed to make direct and immediate contact with their doctor or hospital.
We will use the Pharos Tel-AssuranceTM, an in-home communication system that allows patients to transmit information to their clinicians and provides education to enable patients to actively participate in managing their condition. The system uses conventional telephone lines and does not require the patient to have Internet access. Patients are asked a pre-programmed series of questions and the system automatically uploads the responses to a secure data center. A clinician in each practice can then log on to a secure Internet site using a Web browser to review the patients' responses. The system thus serves as an interface between patients at home and their clinicians, facilitating monitoring of chronic conditions and patient education. While many vendors have potential tools to implement this study, we chose to use Pharos Tel-AssuranceTM because it is simple to use, does not require any equipment in patients' homes and substantial preliminary data suggest high patient and clinician satisfaction with its use. The investigators have no financial interest in this company.
Primary Aim Our primary aim is to determine whether telemonitoring by community-based cardiology office practices reduces the risk of hospital readmission (for any cause) or death after an initial "index hospitalization" for HF. We hypothesize that, among patients recently discharged after a hospitalization for HF, telemonitoring will decrease the rate of rehospitalization or death over 6 months by at least 15% (relative risk reduction). This would yield an absolute risk reduction of 7.5%, so that 1 major adverse event would be averted for every 13 patients.
We have chosen all-cause readmission as part of our primary outcome because poorly controlled HF can result in admissions for a variety of reasons, as the patient becomes weak and susceptible to falls, mental status changes, renal dysfunction, and other debilitating conditions that can result in hospitalization. In addition, from a societal and health system perspective, the overall risk of readmission is more important than disease-specific readmission. Moreover, prior studies suggest that telemonitoring can reduce this outcome.
Secondary Aims
In our secondary aims we will determine whether telemonitoring will:
1. Reduce the rate of all-cause hospital readmission
2. Reduce the rate of hospital readmission for HF
3. Reduce the total number of all-cause and HF-specific hospital readmissions
4. Increase office visits with the clinician receiving information from the telemonitoring system
5. Improve survival after index hospitalization
6. Reduce the cost of inpatient medical care
7. Improve health status
8. Improve patient satisfaction with care
9. Improve patients' self-management of HF
Sub-Group Analyses
The following sub-group analyses will be conducted:
1. Age
2. Sex
3. Race
4. HFPEF vs depressed EF
5. Education
6. Insurance status
7. Self-reported access to care
8. Baseline self-efficacy and self-care
9. Socioeconomic Status
10. Site characteristics
Conditions
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Study Design
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RANDOMIZED
PARALLEL
PREVENTION
NONE
Study Groups
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UC
Usual HF guideline-base care
No interventions assigned to this group
TM
Telemonitoring group plus usual guideline-based HF care
Telemonitoring
Participants in the intervention group are instructed to make a daily toll-free call to an automated telemonitoring system being provided by Pharos Innovations® (Chicago, IL) for 6 months.On each call patients hear a pre-recorded voice that goes through a series of questions about symptoms and the patient's daily weight. Information from the telemonitoring system is automatically downloaded to a secure Internet site for review by clinicians at each practice site.
Interventions
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Telemonitoring
Participants in the intervention group are instructed to make a daily toll-free call to an automated telemonitoring system being provided by Pharos Innovations® (Chicago, IL) for 6 months.On each call patients hear a pre-recorded voice that goes through a series of questions about symptoms and the patient's daily weight. Information from the telemonitoring system is automatically downloaded to a secure Internet site for review by clinicians at each practice site.
Other Intervention Names
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Eligibility Criteria
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Inclusion Criteria
* hospitalized for heart failure within the past 30 days
* access to telephone line
Exclusion Criteria
* has or scheduled for cardiac transplant or LVAD
* scheduled for CABG or PCI within 90 days
* severe valvular disease
* Folstein MMSE score less than 20
* resident of a nursing home
* currently a prisoner
* does not speak English or Spanish
18 Years
ALL
No
Sponsors
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National Institutes of Health (NIH)
NIH
National Heart, Lung, and Blood Institute (NHLBI)
NIH
Yale University
OTHER
Responsible Party
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Yale School of Medicine
Principal Investigators
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Harlan M. Krumholz, M.D.
Role: PRINCIPAL_INVESTIGATOR
Yale University
Sarwat I Chaudhry, MD
Role: STUDY_DIRECTOR
Yale University
Jennifer Mattera, MPH
Role: STUDY_DIRECTOR
Yale University
Locations
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Cardiology Associates
Mobile, Alabama, United States
UC Irvine Medical Center
Orange, California, United States
UCLA Harbor Medical Center
Torrance, California, United States
Department of Cardiology at Bridgeport Hospital
Bridgeport, Connecticut, United States
Cardiology Associates of New Haven
New Haven, Connecticut, United States
Howard University Hospital
Washington D.C., District of Columbia, United States
Integrated Care / Cardiovascular Consultants of South Florida
Tamarac, Florida, United States
Piedmont Hospital Research Institute
Atlanta, Georgia, United States
Morehouse School of Medicine/Cardiology
Atlanta, Georgia, United States
Emory University
Atlanta, Georgia, United States
The Queen's Medical Center
Honolulu, Hawaii, United States
Loyola University Medical Center
Maywood, Illinois, United States
Indiana Heart Physicians
Indianapolis, Indiana, United States
Iowa City Heart Center
Iowa City, Iowa, United States
Chabert Medical Center
Houma, Louisiana, United States
Heart Clinic of Louisiana
Marrero, Louisiana, United States
Cardiology Associates, LLC
Tupelo, Mississippi, United States
Truman Medical Center/Cardiology
Kansas City, Missouri, United States
St. Luke's Hospital / Mid-America Heart Institute
Kansas City, Missouri, United States
Washington University
St Louis, Missouri, United States
Cardiology Diagnostics
St Louis, Missouri, United States
Cooper Health System Cardiology
Camden, New Jersey, United States
Hackensack University Medical Center
Hackensack, New Jersey, United States
St. Joseph's Regional Medical Center / Cardiology Associates
Paterson, New Jersey, United States
New York University/Cardiology
New York, New York, United States
Forsyth Medical Center
Winston-Salem, North Carolina, United States
MetroHealth Medical Center, Heart & Vascular Center
Cleveland, Ohio, United States
The Dayton Heart Center
Dayton, Ohio, United States
Oregon Health and Science University
Portland, Oregon, United States
University of Pittsburgh
Pittsburgh, Pennsylvania, United States
Cardiology Specialists, Ltd.
Westerly, Rhode Island, United States
Baylor University Medical Center
Dallas, Texas, United States
Sentara Cardiology Consultants, Ltd.
Norfolk, Virginia, United States
Countries
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References
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Jayaram NM, Khariton Y, Krumholz HM, Chaudhry SI, Mattera J, Tang F, Herrin J, Hodshon B, Spertus JA. Impact of Telemonitoring on Health Status. Circ Cardiovasc Qual Outcomes. 2017 Dec;10(12):e004148. doi: 10.1161/CIRCOUTCOMES.117.004148.
Steventon A, Chaudhry SI, Lin Z, Mattera JA, Krumholz HM. Assessing the reliability of self-reported weight for the management of heart failure: application of fraud detection methods to a randomised trial of telemonitoring. BMC Med Inform Decis Mak. 2017 Apr 18;17(1):43. doi: 10.1186/s12911-017-0426-4.
Mortazavi BJ, Downing NS, Bucholz EM, Dharmarajan K, Manhapra A, Li SX, Negahban SN, Krumholz HM. Analysis of Machine Learning Techniques for Heart Failure Readmissions. Circ Cardiovasc Qual Outcomes. 2016 Nov;9(6):629-640. doi: 10.1161/CIRCOUTCOMES.116.003039. Epub 2016 Nov 8.
Krumholz HM, Chaudhry SI, Spertus JA, Mattera JA, Hodshon B, Herrin J. Do Non-Clinical Factors Improve Prediction of Readmission Risk?: Results From the Tele-HF Study. JACC Heart Fail. 2016 Jan;4(1):12-20. doi: 10.1016/j.jchf.2015.07.017. Epub 2015 Dec 2.
Qian F, Parzynski CS, Chaudhry SI, Hannan EL, Shaw BA, Spertus JA, Krumholz HM. Racial Differences in Heart Failure Outcomes: Evidence From the Tele-HF Trial (Telemonitoring to Improve Heart Failure Outcomes). JACC Heart Fail. 2015 Jul;3(7):531-538. doi: 10.1016/j.jchf.2015.03.005.
Bikdeli B, Wayda B, Bao H, Ross JS, Xu X, Chaudhry SI, Spertus JA, Bernheim SM, Lindenauer PK, Krumholz HM. Place of residence and outcomes of patients with heart failure: analysis from the telemonitoring to improve heart failure outcomes trial. Circ Cardiovasc Qual Outcomes. 2014 Sep;7(5):749-56. doi: 10.1161/CIRCOUTCOMES.113.000911. Epub 2014 Jul 29.
Chaudhry SI, Mattera JA, Curtis JP, Spertus JA, Herrin J, Lin Z, Phillips CO, Hodshon BV, Cooper LS, Krumholz HM. Telemonitoring in patients with heart failure. N Engl J Med. 2010 Dec 9;363(24):2301-9. doi: 10.1056/NEJMoa1010029. Epub 2010 Nov 16.
Other Identifiers
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0502027466
Identifier Type: -
Identifier Source: org_study_id
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