Outcomes of a Heart Failure Telemonitoring Program Implemented as the Standard of Care in an Outpatient Heart Function Clinic: Pretest-Posttest Pragmatic Study

Background Telemonitoring (TM) can improve heart failure (HF) outcomes by facilitating patient self-care and clinical decisions. The Medly program enables patients to use a mobile phone to record daily HF readings and receive personalized self-care messages generated by a clinically validated algorithm. The TM system also generates alerts, which are immediately acted upon by the patients’ existing care team. This program has been operating for 3 years as part of the standard of care in an outpatient heart function clinic in Toronto, Canada. Objective This study aimed to evaluate the 6-month impact of this TM program on health service utilization, clinical outcomes, quality of life (QoL), and patient self-care. Methods This pragmatic quality improvement study employed a pretest-posttest design to compare 6-month outcome measures with those at program enrollment. The primary outcome was the number of HF-related hospitalizations. Secondary outcomes included all-cause hospitalizations, emergency department visits (HF related and all cause), length of stay (HF related and all cause), and visits to the outpatient clinic. Clinical outcomes included bloodwork (B-type natriuretic peptide [BNP], creatinine, and sodium), left ventricular ejection fraction, and predicted survival score using the Seattle Heart Failure Model. QoL was measured using the Minnesota Living with Heart Failure Questionnaire (MLHFQ) and the 5-level EuroQol 5-dimensional questionnaire. Self-care was measured using the Self-Care of Heart Failure Index (SCHFI). The difference in outcome scores was analyzed using negative binomial distribution and Poisson regressions for the health service utilization outcomes and linear regressions for all other outcomes to control for key demographic and clinical variables. Results Available data for 315 patients enrolled in the TM program between August 2016 and January 2019 were analyzed. A 50% decrease in HF-related hospitalizations (incidence rate ratio [IRR]=0.50; P<.001) and a 24% decrease in the number of all-cause hospitalizations (IRR=0.76; P=.02) were found when comparing the number of events 6 months after program enrollment with the number of events 6 months before enrollment. With regard to clinical outcomes at 6 months, a 59% decrease in BNP values was found after adjusting for control variables. Moreover, 6-month MLHFQ total scores were 9.8 points lower than baseline scores (P<.001), representing a clinically meaningful improvement in HF-related QoL. Similarly, the MLHFQ physical and emotional subscales showed a decrease of 5.4 points (P<.001) and 1.5 points (P=.04), respectively. Finally, patient self-care after 6 months improved as demonstrated by a 7.8-point (P<.001) and 8.5-point (P=.01) increase in the SCHFI maintenance and management scores, respectively. No significant changes were observed in the remaining secondary outcomes. Conclusions This study suggests that an HF TM program, which provides patients with self-care support and active monitoring by their existing care team, can reduce health service utilization and improve clinical, QoL, and patient self-care outcomes.

[1]  H. Krumholz,et al.  Telemonitoring in patients with heart failure. , 2010, The New England journal of medicine.

[2]  L. Lix,et al.  Assessing the burden of hospitalized and community-care heart failure in Canada. , 2014, The Canadian journal of cardiology.

[3]  J. Stock,et al.  Heteroskedasticity-Robust Standard Errors for Fixed Effects Panel Data Regression , 2006 .

[4]  William E. Griffiths,et al.  Principles of Econometrics , 2008 .

[5]  Heather J Ross,et al.  Mobile Phone-Based Telemonitoring for Heart Failure Management: A Randomized Controlled Trial , 2012, Journal of medical Internet research.

[6]  E. Seto,et al.  Patient Adherence to a Mobile Phone–Based Heart Failure Telemonitoring Program: A Longitudinal Mixed-Methods Study , 2018, JMIR mHealth and uHealth.

[7]  D. Mozaffarian,et al.  The Seattle Heart Failure Model: Prediction of Survival in Heart Failure , 2006, Circulation.

[8]  Patrick Ware,et al.  Evaluating the Implementation of a Mobile Phone–Based Telemonitoring Program: Longitudinal Study Guided by the Consolidated Framework for Implementation Research , 2018, JMIR mHealth and uHealth.

[9]  Farhad Fatehi,et al.  Remote Monitoring of Patients With Heart Failure: An Overview of Systematic Reviews , 2017, Journal of medical Internet research.

[10]  A. Cameron,et al.  Regression-based tests for overdispersion in the Poisson model☆ , 1990 .

[11]  B. Riegel,et al.  An Update on the Self-care of Heart Failure Index , 2009, The Journal of cardiovascular nursing.

[12]  Guy Paré,et al.  Effects of Home Telemonitoring Interventions on Patients With Chronic Heart Failure: An Overview of Systematic Reviews , 2015, Journal of medical Internet research.

[13]  A. Ammerman,et al.  Practice-based evidence in public health: improving reach, relevance, and results. , 2014, Annual review of public health.

[14]  Akshay S. Desai,et al.  Connecting the circle from home to heart-failure disease management. , 2010, The New England journal of medicine.

[15]  N. Bansback,et al.  A Time Trade-off-derived Value Set of the EQ-5D-5L for Canada , 2015, Medical care.

[16]  E. Vittinghoff,et al.  Associations of N-terminal pro-B-type natriuretic peptide with kidney function decline in persons without clinical heart failure in the Heart and Soul Study. , 2014, American heart journal.

[17]  Chao Xu,et al.  Effectiveness of telemedicine systems for adults with heart failure: a meta-analysis of randomized controlled trials , 2019, Heart Failure Reviews.

[18]  Michael Böhm,et al.  Impact of Remote Telemedical Management on Mortality and Hospitalizations in Ambulatory Patients With Chronic Heart Failure: The Telemedical Interventional Monitoring in Heart Failure Study , 2011, Circulation.

[19]  Emily Seto,et al.  Developing healthcare rule-based expert systems: Case study of a heart failure telemonitoring system , 2012, Int. J. Medical Informatics.

[20]  J. Cleland,et al.  Telemonitoring in heart failure: Big Brother watching over you , 2014, Heart Failure Reviews.

[21]  T. Greenhalgh,et al.  Understanding heart failure; explaining telehealth – a hermeneutic systematic review , 2017, BMC Cardiovascular Disorders.

[22]  F. Asselbergs,et al.  Algorithms used in telemonitoring programmes for patients with chronic heart failure: A systematic review , 2018, European journal of cardiovascular nursing : journal of the Working Group on Cardiovascular Nursing of the European Society of Cardiology.

[23]  J. Cleland,et al.  Structured telephone support or non-invasive telemonitoring for patients with heart failure , 2016, Heart.

[24]  Stefan Störk,et al.  Efficacy of telemedical interventional management in patients with heart failure (TIM-HF2): a randomised, controlled, parallel-group, unmasked trial , 2018, The Lancet.

[25]  Patrick Ware,et al.  User-Centered Adaptation of an Existing Heart Failure Telemonitoring Program to Ensure Sustainability and Scalability: Qualitative Study , 2018, JMIR cardio.

[26]  Catherine Pope,et al.  Assessing the implementability of telehealth interventions for self-management support: a realist review , 2015, Implementation Science.

[27]  G. Norman,et al.  Interpretation of Changes in Health-related Quality of Life: The Remarkable Universality of Half a Standard Deviation , 2003, Medical care.

[28]  M. Jessup,et al.  Understanding Heart Failure. , 2017, Heart failure clinics.

[29]  Patrick Ware,et al.  Implementation and Evaluation of a Smartphone-Based Telemonitoring Program for Patients With Heart Failure: Mixed-Methods Study Protocol , 2018, JMIR research protocols.

[30]  Majid Sarrafzadeh,et al.  Effectiveness of Remote Patient Monitoring After Discharge of Hospitalized Patients With Heart Failure: The Better Effectiveness After Transition -- Heart Failure (BEAT-HF) Randomized Clinical Trial. , 2016, JAMA internal medicine.

[31]  Russell E Glasgow,et al.  A proposal to speed translation of healthcare research into practice: dramatic change is needed. , 2011, American journal of preventive medicine.

[32]  S. Heo,et al.  Disparities in Heart Failure and other Cardiovascular Diseases among Women , 2012, Women's health.

[33]  S. Pressler Women With Heart Failure Are Disproportionately Studied as Compared With Prevalence: A Review of Published Studies from 2013 , 2016, The Journal of cardiovascular nursing.

[34]  Harlan M. Krumholz,et al.  Recent National Trends in Readmission Rates After Heart Failure Hospitalization , 2010, Circulation. Heart failure.

[35]  S. Liu,et al.  Meta-analysis and meta-regression of telehealth programmes for patients with chronic heart failure , 2013, Journal of telemedicine and telecare.

[36]  E. Seto,et al.  Accounting for Complexity in Home Telemonitoring: A Need for Context-Centred Evidence. , 2018, The Canadian journal of cardiology.

[37]  M. Fornage,et al.  Heart Disease and Stroke Statistics—2017 Update: A Report From the American Heart Association , 2017, Circulation.

[38]  Amit G Singal,et al.  A Primer on Effectiveness and Efficacy Trials , 2014, Clinical and Translational Gastroenterology.

[39]  D. Solís US Food and Drug Administration , 2010 .

[40]  G. Bonsel,et al.  Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L) , 2011, Quality of Life Research.

[41]  N. Bayley,et al.  Failure , 1890, The Hospital.

[42]  G. Ewald,et al.  Remote Monitoring of Patients With Heart Failure: A White Paper From the Heart Failure Society of America Scientific Statements Committee. , 2018, Journal of cardiac failure.

[43]  R. McKelvie,et al.  2017 Comprehensive Update of the Canadian Cardiovascular Society Guidelines for the Management of Heart Failure. , 2017, The Canadian journal of cardiology.

[44]  Jennifer L. Embree,et al.  Comparison of Quality of Life Measures in Heart Failure , 2003, Nursing research.