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Abstract

Introduction

A wide range of study designs have been utilized in evaluations of home telemonitoring and these studies have produced conflicting outcomes over the years. While some of the research has shown that telemonitoring is beneficial in reducing all-cause mortality, hospital admission, length of stay in hospital and emergency room visits, other studies have not shown such benefits. This study, therefore, aims to examine several home telemonitoring study designs and the influence of study design on study outcomes.

Method

Articles were obtained by searching PubMed database with the term heart failure combined with the following terms: telemonitoring, telehealth, home monitoring, and remote monitoring. Searches were limited to randomized controlled trial conducted between year January 1, 2000 and February 6, 2021. The characteristics of the study designs and study outcomes were extracted and analyzed.

Result

Our review of 34 randomized controlled trials of heart failure telemonitoring did not show any significant influence of study design on reduction in number of hospitalizations and/or decrease in mortality. Studies that were done outside North America (USA and Canada) and studies that selected patients at high risk of re-hospitalization were more likely to result in decreased hospitalization and/or mortality, though this was not statistically significant. All the studies that met our inclusion criteria were from high-income countries and only one study enrolled patients at high risk of re-hospitalization.

Conclusion

There is a need for more studies to understand why telemonitoring studies in Europe were more likely to reduce hospital admission and mortality compared to those in North America. There is also a need for more studies on the effect of telemonitoring in patients at high risk of hospital readmission.

Keywords

Heart failure telemonitoring telehealth home monitoring remote monitoring

Introduction

The use of various electronic devices to track patients’ health status while at home, an intervention that has been named “telemonitoring,” has continued to gain traction in the medical field. Telemonitoring allows patients and their health care providers to monitor and record their weight, blood pressure, and other parameters. Health care professionals obtain the information that has been measured and recorded through communication technology.^1,2 This technique is especially useful for patients with chronic disease, which is encouraged by their health care providers to monitor some of their vital signs daily. Rather than having to continuously present to clinics or hospitals to have these measurements taken, patients can record this data from the comfort of their homes.^1,2 This is usually accompanied by frequent communication with a health care professional, telephonically or via video call, for additional assessment and recommendations. Telemonitoring may lead to an improved quality of care, reduced risk of readmission to hospital, better patients’ satisfaction, and other benefits.^1,2

Heart failure is a chronic disease and a major public health problem, with a prevalence of over 5.8 million in the USA and over 23 million worldwide.³ Heart failure is a complex clinical syndrome caused by structural or functional impairment of ventricular filling or blood ejection and manifests as dyspnea, fatigue, and/or fluid retention.⁴ Heart failure is associated with high morbidity and mortality and recurrent admissions after an index hospitalization for heart failure, with a 50% readmission rate, and a 25%–35% incidence of death at 12 months.³ Usually, patients tend to start gaining weight because of fluid retention, get short of breath or have worsening leg swelling, few days prior to them needing admission for intravenous medications.^3,5 If proper interventions are made in a timely manner by adjusting the home medications, these admissions could be avoided. However, it will be challenging for patients who are monitoring themselves to make what may be perceived as complex decisions on medication management and so sharing of data with health care providers is an important aspect of home telemonitoring. Home telemonitoring in heart failure patients could potentially be associated with better clinical outcomes. However, telemonitoring studies in heart failure patients have produced conflicting outcomes over the years. While some studies showed that telemonitoring was beneficial in reducing all-cause mortality, hospital admission, length of stay in the hospital, and emergency room visits,^6–8 others did not show such benefits.^9–12 The diversity of telemonitoring study designs and outcomes makes it imperative to carefully review the impact of study design on study outcomes. This literature review aims to examine the different home telemonitoring study designs and their influence on study outcomes.

Method

Articles were obtained by searching PubMed database with the term heart failure, combined with the following terms: telemonitoring, telehealth, home monitoring, and remote monitoring. Searches were limited to randomized controlled trials conducted between January 1, 2000 and February 6, 2021. The searches produced a total of 461 articles, of which 281 were unique articles. One additional article identified through other sources was added. The 282 abstracts were independently reviewed by two researchers to assess if they met the inclusion and exclusion criteria to be included in the review. To be included in the review, the articles must have been randomized controlled trials of heart failure patients, written in English, involving patients that were self-measuring their vital signs (such as blood pressure, weight, pulse) at home, while using a device or technology that transmitted the data to health care professionals. Articles excluded include articles not in English (n = 9), articles on telemonitoring study protocol (n = 28), articles that used implantable devices such as pacemakers (n = 43), articles that did not include self-monitoring or did not measure heart failure patients’ hospitalization or mortality (n = 109), articles on teleconsulting (n = 31), articles studying another disease in heart failure patients (n = 15), and articles that pooled results for patients with heart failure and patients with other illnesses (n = 13) (Figure 1). For articles that included heart failure patients as well as patients with other illnesses but provided separate results, we reported only the result of the heart failure patients.

Figure 1.

Article selection process.

The characteristics of the study designs and study outcomes were extracted and analyzed. Descriptive analysis of the characteristics and outcomes of the study was done using mean and frequency. Bivariate and multivariate analyses of the effect of different study variables on positive study outcome (reduction in the number of hospitalization and/or decrease in mortality) were done using chi-square, t-test and logistic regression, with a p value of 0.05 considered as significant. The statistical analysis was done using IBM SPSS version 27. The study population, design, duration, outcomes of interest, significant findings as well as the country each study was performed in was categorized for each of the 34 included papers, and this data is reported in Table 4.

Table 4.

Papers included in the review.

Article	No of HF patients	Duration in months	Country	Positive outcome: reduced hospitalization and/or mortality	Lead clinician	Frequency of patients measuring and transmitting vital signs	Telemonitoring group scheduled patient education	Control group had patient education	Only elderly patients	Recently hospitalized patients
Koehler et al. (TIM-HF2)⁶	1571	12–13	Germany	Yes	Physician	Daily	Yes	No	No	No
Cleland et al.⁷	418	8	Germany, Netherlands, and UK	Yes	Nurse	Daily	Yes	No	No	Yes
Villani et al.⁸	80	12	Italy	Yes	Nurse	Daily	No	No	Yes	Yes
Koehler et al.⁹	710	26	Germany	No	Physician	Daily	No	No	No	No
Kotooka et al.¹⁰	181	15	Japan	No	Nurse	Daily	No	No	No	Yes
Pekmezaris et al.¹¹	104	3	USA	No	Nurse	Daily	Yes	No	No	Yes
Kalter-Leibovici et al.¹²	1360	32	Israel	No	Nurse	Daily	Yes	No	No	No
Chaudhry et al.¹³	1653	6	USA	No	Physician	Daily	No	No	No	Yes
Woodend et al.¹⁴	121^a	3	Canada	No	Nurse	Daily	Yes	No	No	Yes
Dendale et al.¹⁵	160	6	Belgium	Yes	Nurse	Daily	No	No	No	Yes
Nouryan et al.¹⁶	89	6	USA	No	Nurse	Daily	Yes	Yes	Yes	No
Seto et al.¹⁷	100	6	Canada	No	Physician	Daily	No	No	No	No
Weintraub et al.¹⁸	188	3	USA	Yes	Nurse	Daily	Yes	Yes	No	Yes
Blum et al.¹⁹	156	27	USA	No	Nurse practitioner	Daily	No	No	No	No
Dansky et al.²⁰	284	4	USA	No	Nurse	Daily	No	No	No	No
Kashem et al.²¹	48	12	USA	Yes	Nurse	Daily	No	No	No	No
Benatar et al.²²	216	12	USA	Yes	Nurse	Daily	No	Yes	No	Yes
Pedone et al.²³	96	6	Italy	Yes	Physician	Weight daily, BP twice daily and oxygen thrice daily	No	No	Yes	No
Wade et al.²⁴	316	6	USA	No	Case manager	Daily	Yes	Yes	Yes	No
Comín-Colet et al.²⁵	178	6	Spain	Yes	Nurse	Daily	No	No	No	Yes
Olivari et al.²⁶	339	12	Italy	No	Non-clinician	Daily	No	No	Yes	No
Lyngå et al.²⁷	319	12	Sweden	No	Nurse	Daily	No	No	No	No
Scherr et al.²⁸	120	6	Austria	Yes	Physician	Daily	No	No	No	Yes
Antonicelli et al.²⁹	57	12	Italy	Yes	Clinical team	Weekly	Yes	No	Yes	No
Giordano et al.³⁰	460	12	Italy	Yes	Nurse	Daily	Yes	No	No	No
Ong et al.³¹	1437	6	USA	No	Nurse	Daily	Yes	No	No	Yes
Mortara et al.³²	306	12	UK, Poland, and Italy	No	Nurse	Weekly	No	No	No	No
Madigan et al.³³	99	6	USA	No	Nurse	Daily	No	No	No	No
Dar et al.³⁴	182	6	UK	No	Nurse	Daily	No	No	No	Yes
Vuorinen et al.³⁵	94	6	Finland	No	Nurse	Weekly	No	No	No	No
Tompkins et al.³⁶	390	6	USA	No	Nurse	Daily	No	No	No	No
Goldberg et al.³⁷	280	6	USA	Yes	Nurse	Daily	No	No	No	No
Soran et al.³⁸	315	6	USA	No	Nurse	Daily	No	No	Yes	No
Galinier et al.³⁹	937	18	France	No	Nurse	Daily	Yes	No	No	No

BP: blood pressure; TIM-HF: telemedical interventional management in patients with heart failure.

Article included heart failure patients as well as patients with other illnesses but the only result of heart failure patients reported.

Results

Our study involved a review of 34 randomized controlled trials on heart failure and telemonitoring conducted between January 1, 2000 and February 6, 2021. A total of 13,364 patients were recruited in all the 34 studies with a mean of 393, standard deviation of 453 and a range of 48–1653 (Table 1). There was no statistically significant relationship between the number of patients in the studies and study outcome (p = 0.34) (Table 2). The mean duration of study was 10 months with standard deviation of 7 months and range of 3–32 months. There was no statistically significant relationship between the duration of the studies and study outcome (p = 0.35) (Table 2). The positive outcomes of interest in our review were the reduced number of hospitalizations and/or decrease in mortality. Thirteen of the 34 studies (38%) reported a positive outcome (reduction in the number of hospitalization and/or decrease in mortality).

Table 1.

Characteristics of studies included in the review.

Number of studies included in review	34
Number of patients in studies reviewed	13,364; Mean: 393, SD: 453
Mean duration of study (months)	9.9, SD: 6.9
	Number of studies	Percentage
Country of study
North America	16	47.1
Others	18	52.9
Telemonitoring reduced hospitalization and/or mortality
Yes	13	38.2
No	21	61.8
Person responsible for monitoring patients’ data
Nurse	26	76.5
Physician	6	17.6
Others (case manager, non-clinical staff)	2	5.9
Frequency of patients measuring and transmitting data
Daily	31	91.2
Weekly	3	8.8
Scheduled nurse led patient education or interaction included as part of intervention
Yes	9	26.5
No	25	73.5
Recruited only elderly (≥65 years) patients in study
Yes	7	20.6
No	27	79.4
Recruited only recently (<6 weeks) hospitalized patients
Yes	13	38.2
No	21	61.8
Recruited only patients at high risk of re-hospitalization
Yes	1	2.9
No	33	97.1

Table 2.

Bivariate analysis of study characteristics and study outcomes.

	Telemonitoring reduced hospitalization and/or mortality	Telemonitoring had no effect on hospitalization and/or mortality	p value
Number of patients in study	297.85	452	0.34
Duration of study in months	8.69	10.7	0.35
Country of study
North America	4 (25%)	12 (75%)	0.13
Others	9 (50%)	9 (50%)
Person responsible for monitoring patients’ data
Nurse	10 (38.5%)	16 (61.5%)	0.45
Physician	3 (50%)	3 (50%)
Others (case manager, non-clinical staff)	0 (0%)	2 (100%)
Frequency of patients measuring and transmitting data
Daily	12 (38.7%)	19 (61.3%)	0.85
Weekly	1 (33.3%)	2 (66.7%)
Scheduled nurse led patient education or interactions included as part of intervention
Yes	4 (44.4%)	5 (55.6%)	0.65
No	9 (36%)	16 (64%)
Recruited only elderly (≥65 years) patients in study
Yes	3 (42.9%)	4 (57.1%)	0.77
No	10 (37%)	17 (63%)
Recruited only recently (< 6 weeks) hospitalized patients
Yes	7 (53.8%)	6 (46.2%)	0.14
No	6 (28.6%)	15 (71.4%)
Recruited only patients at high risk of re-hospitalization
Yes	1 (100%)	0 (0%)	0.19
No	12 (36.4%)	21 (63.6%)

Country of study and study outcome

Sixteen studies were done in North America (USA: 14, Canada: 2) (47%), and the rest were performed mainly in Europe, with Italy having the highest number of studies (five studies). While only 25% of studies done in North America had a positive outcome (reduction in the number of hospitalization and/or decrease in mortality), 50% of studies done in other countries had a positive outcome. However, there was no statistically significant difference in outcome based on the region where the study was conducted (p = 0.09) (Table 3)

Table 3.

Multivariate analysis of study characteristics and study outcomes.

	SE	Sig.	Odds ratio	95% Confidence interval (C.I.) for odds ratio
	SE	Sig.	Odds ratio	Lower	Upper
Number of patients in study	0.001	0.380	0.999	0.996	1.001
Duration of study	0.089	0.446	0.935	0.786	1.112
Region of study (North America versus others)	0.968	0.092	0.195	0.029	1.302
Frequency of measuring and transmitting vital signs (daily versus weekly)	1.538	0.470	3.038	0.149	61.874
Scheduled patient education (yes versus no)	1.005	0.434	0.456	0.064	3.264
Recruited elderly patients (yes versus no)	1.032	0.824	0.795	0.105	6.011
Recruited recently hospitalized patients (yes versus no)	0.972	0.514	0.530	0.079	3.566

Type of patients recruited in the studies and study outcome

There was a diversity of heart patients recruited in the studies. Some studies recruited only patients with systolic heart failure while most studies included both systolic and diastolic heart failure patients. While some studies recruited patients, who were recently hospitalized for heart failure, others recruited only elderly patients. Our analysis did not show a statistically significant difference in study outcomes based on the type of patients recruited in the study. Only 54% of studies that recruited patients recently hospitalized for heart failure, defined as heart failure hospitalization within 6 weeks of being recruited in the study, had a positive outcome (p = 0.14). There was no difference in outcomes in studies that recruited only elderly patients (≥ 65 years) and those that did not (p = 0.77) (Table 2). However, the only study that enrolled patients at high risk of readmission, defined as patients with New York Heart Association class III/IV patients with at least two of the following: >2 heart failure in the last 6 months, age greater than 70 years and more than one comorbidity such as diabetes and renal failure, had a positive outcome (100%).⁸

Health care professional involved in study and study outcome

Different types of health care professionals were involved in the studies including nurses, internists, cardiologists, case managers, and clinical psychologists. In 26 studies (77%), the nurses were the primary health care professionals in charge of monitoring the data from the patient and informing the physicians of abnormal values. Additionally, the nurses were also responsible for calling the patient to follow up on abnormal values and advising them on the next steps. Physicians were the lead in six studies (18%), where the physicians reviewed the data and contacted the patient if values were abnormal with instructions on the next steps. One of the studies was led by a case manager and another by a non-clinician. In total, 39% of the studies led by nurses, 50% of the studies led by physicians and 0% of the studies led by case manager or non-clinician had a positive outcome. However, there was no statistically significant relationship between the type of health professional leading the study and the outcome of the study (p = 0.45) (Table 2).

Frequency of measuring and transmitting patient data and study outcome

All the studies involved patients self-measuring their vital signs and transmitting the numbers to a health care professional who reviewed the data and contacted the patient if necessary. Most studies required patients to measure and transmit their weight, blood pressure, and heart rate. Most studies also required patients to answer simple symptom questions such as whether they were having shortness of breath, swelling of the legs, etc. Some studies included measuring and transmitting peripheral oxygen levels and heart rhythms from single-lead electrocardiogram. Most studies (91%) required patients to measure and transmit their vital signs at least once daily, while 9% required weekly measurement of vital signs and transmission of vital signs. There was no association between the frequency of data measurement and transmission and the study outcomes (p = 0.85) (Table 2).

Patient–health care provider interactions and study outcome

In addition to measuring and transmitting vital signs, some of the studies included scheduled nurse-led patient education or interaction as part of the intervention. The scheduled patient–nurse interactions included patient self-care education, monitoring disease signs and symptoms, adjusting medications using designated protocols, monitoring medication adherence, counseling in the event of an acute change in health status and addressing technical and social issues.^6,7,12

Three studies had scheduled patient–nurse interaction in both the telemonitoring and control group, while nine studies had the interaction in only the telemonitoring group. Of the nine studies that had scheduled patient–nurse interaction in only the telemonitoring group, 44% had a positive outcome (reduction in number of hospitalization and/or decrease in mortality). The scheduled interactions were either weekly, biweekly, or monthly and there was no difference in outcome in the studies that included scheduled nurse-led patient education or interactions and those that did not (p = 0.65).

Discussion

Our review of 34 randomized controlled trials of heart failure telemonitoring did not show any significant influence of study design on hospitalization and/or decrease in mortality in heart failure patients. Studies that were done outside North America (USA and Canada) and studies that selected patients at high risk of re-hospitalization were more likely to have a positive outcome, though this was not statistically significant.

The studies that were done in Europe were more likely to reduce heart failure hospitalization and/or mortality than those in North America. While only 25% of the studies done in North America had a positive outcome (reduction in the number of hospitalization and/or decrease in mortality), 50% of the studies done in other countries (mainly European countries) had a positive outcome, although the difference in outcome was not statistically different (p = 0.09) after adjusting for other covariables. The reason for the difference between studies in Europe and North America is unclear. The study design including the study population, the health care provider leading the study (nurse vs. physician), the frequency of patients measuring and transmitting vital signs, patient–health care provider interactions and the types of patients recruited in the studies (elderly vs. recently hospitalized) were similar in both the European and North American studies. The major difference between the studies in Europe and those in North America was the duration of the study (how long the patients were monitored). The studies in Europe had a mean and mode duration of 12 months respectively, compared to a mean of 7 months and mode of 6 months in North America. However, our analysis did not show any statistically significant relationship between study duration and study outcomes.

Our study did not show any difference in outcomes in studies that recruited only elderly or recently discharged patients and those that did not. We had expected that home telemonitoring might have more beneficial effects in studies that recruited patients with more advanced disease, or patients at high risk of hospital readmission but unfortunately, we only had one study that specifically recruited heart failure patients at high risk of relapse. However, the single study that specifically recruited heart failure patients at high risk of hospital readmission on discharge, which included New York Heart Association class III/IV patients with at least two of the following: greater than two heart failure in the last six months, age greater than 70 years and more than one comorbidity such as diabetes and renal failure had a reduction in mortality and hospital readmission. The ability to detect early signs of clinical decline and perform an intervention early might have been helpful in this group of patients at high risk of hospital readmission. There is a need for more research on the effect of telemonitoring on patients that are at high risk of hospital readmission.

The type of health care professionals involved in the studies, the frequency of measuring and transmitting patients’ vital signs and incorporating scheduled patient–health care provider interaction as part of the intervention did not influence the outcome of the studies. We had anticipated that patients that had home telemonitoring with scheduled weekly, biweekly, or monthly patient–nurse interaction and education as part of the intervention would fare better than those in the usual care group, however, this was not so. This could signify that patient education at hospital discharge and education during regular outpatient follow up clinic visits are sufficient for many heart failure patients.

There are limitations to this study. First, all the randomized controlled studies included in the study were from high-income countries and the results of this study may not be applicable to low- and middle-income countries. In addition, our ability to perform sub-group analysis was limited because of the number of studies included in this review.

In conclusion, our study, focused on examining the influence of study designs on study outcomes, did not show a significant influence of study design on reduction of hospitalization and/or mortality. However, there is need for more studies to understand why telemonitoring studies in Europe were more likely to reduce hospital admission and mortality compared to those in North America. There is also need for more evaluation of the effect of telemonitoring on patients at high risk of hospital readmission.

Footnotes

Author contribution

CAU and MR extracted the data. CAU analyzed and interpreted the data with input from all other authors. CAU and MR wrote the first draft of the paper. AD, MY, SC, and SS reviewed and substantially revised the paper. All authors have read and approved the final version of the article.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Chukwuemeka A. Umeh

References

Maric

Kaan

Ignaszewski

, et al. A systematic review of telemonitoring technologies in heart failure. Eur J Heart Fail 2009; 11: 506–517.

Chaudhry

Phillips

Stewart

, et al. Telemonitoring for patients with chronic heart failure: a systematic review. J Card Fail 2007; 13: 56–62.

Jessup

Abraham

Casey

, et al. 2009 Writing Group to Review New Evidence and Update the 2005 Guideline for the Management of Patients with Chronic Heart Failure Writing on Behalf of the 2005 Heart Failure Writing Committee. 2009 Focused update: aCCF/AHA guidelines for the diagnosis and management of heart failure in adults: a report of the American college of cardiology foundation/American heart association task force on practice guidelines: developed in collaboration with the international society for heart and lung transplantation. Circulation 2009; 119: 1977–2016.

Yancy

Jessup

Bozkurt

, et al. ACCF/AHA guideline for the management of heart failure: executive summary: a report of the American college of cardiology foundation/American heart association task force on practice guidelines. Circulation 2013; 128: 1810–1852.

Mosterd

Hoes

. Clinical epidemiology of heart failure. Heart 2007; 93(9): 1137–1146.

Koehler

Deckwart

, et al. Efficacy of telemedical interventional management in patients with heart failure (TIM-HF2): a randomised, controlled, parallel-group, unmasked trial. The Lancet 2018; 392: 1047–1057.

Cleland

Louis

Rigby

, et al. Ten-HMS Investigators. Noninvasive home telemonitoring for patients with heart failure at high risk of recurrent admission and death: the Trans-European Network-Home-Care Management System (TEN-HMS) study. J Am Coll Cardiol 2005; 45: 1654–1664.

Villani

Malfatto

Compare

, et al. Clinical and psychological telemonitoring and telecare of high risk heart failure patients. J Telemed Telecare 2014; 20: 468–475.

Koehler

Winkler

Schieber

, 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. Circulation 2011; 123: 1873–1880.

10.

Kotooka

Kitakaze

Nagashima

, et al. The first multicenter, randomized, controlled trial of home telemonitoring for Japanese patients with heart failure: home telemonitoring study for patients with heart failure (HOMES-HF). Heart Vessels 2018; 33: 866–876.

11.

Pekmezaris

Nouryan

Schwartz

, et al. A randomized controlled trial comparing telehealth self-management to standard outpatient management in underserved black and Hispanic patients living with heart failure. Telemedicine and e-Health 2019; 25: 917–925.

12.

Kalter-Leibovici

Freimark

Freedman

, et al. Disease management in the treatment of patients with chronic heart failure who have universal access to health care: a randomized controlled trial. BMC Med 2017; 15: 1–3.

13.

Chaudhry

Mattera

Curtis

, et al. Telemonitoring in patients with heart failure. N Engl J Med 2010; 363: 2301–2309.

14.

Woodend

Sherrard

Fraser

, et al. Telehome monitoring in patients with cardiac disease who are at high risk of readmission. Heart Lung 2008; 37: 36–45.

15.

Dendale

De Keulenaer

Troisfontaines

, et al. Effect of a telemonitoring-facilitated collaboration between general practitioner and heart failure clinic on mortality and rehospitalization rates in severe heart failure: the TEMA-HF 1 (TElemonitoring in the MAnagement of heart failure) study. Eur J Heart Fail 2012; 14: 333–340.

16.

Nouryan

Morahan

Pecinka

, et al. Home telemonitoring of community-dwelling heart failure patients after home care discharge. Telemedicine and e-Health 2019; 25: 447–454.

17.

Seto

Leonard

Cafazzo

, et al. Mobile phone-based telemonitoring for heart failure management: a randomized controlled trial. J Med Internet Res 2012; 14: e31.

18.

Weintraub

Gregory

Patel

, et al. A multicenter randomized controlled evaluation of automated home monitoring and telephonic disease management in patients recently hospitalized for congestive heart failure: the SPAN-CHF II trial. J Card Fail 2010; 16: 285–292.

19.

Blum

Gottlieb

. The effect of a randomized trial of home telemonitoring on medical costs, 30–day readmissions, mortality, and health-related quality of life in a cohort of community-dwelling heart failure patients. J Card Fail 2014; 20: 513–521.

20.

Dansky

Vasey

Bowles

. Impact of telehealth on clinical outcomes in patients with heart failure. Clin Nurs Res 2008; 17: 182–199.

21.

Kashem

Droogan

Santamore

, et al. Managing heart failure care using an internet-based telemedicine system. J Card Fail 2008; 14: 121–126.

22.

Benatar

Bondmass

Ghitelman

, et al. Outcomes of chronic heart failure. Arch Intern Med 2003; 163: 347–352.

23.

Pedone

Rossi

Cecere

, et al. Efficacy of a physician-led multiparametric telemonitoring system in very old adults with heart failure. J Am Geriatr Soc 2015; 63: 1175–1180.

24.

Wade

Desai

Spettell

, et al. Telemonitoring with case management for seniors with heart failure. Am J Manag Care 2011; 17: e71–e79.

25.

Comín-Colet

Enjuanes

Verdú-Rotellar

, et al. Impact on clinical events and healthcare costs of adding telemedicine to multidisciplinary disease management programmes for heart failure: results of a randomized controlled trial. J Telemed Telecare 2016; 22: 282–295.

26.

Olivari

Giacomelli

Gubian

, et al. The effectiveness of remote monitoring of elderly patients after hospitalisation for heart failure: the renewing health European project. Int J Cardiol 2018; 257: 137–142.

27.

Lyngå

Persson

Hägg-Martinell

, et al. Weight monitoring in patients with severe heart failure (WISH). A randomized controlled trial. Eur J Heart Fail 2012; 14: 438–444.

28.

Scherr

Kastner

Kollmann

, et al. Effect of home-based telemonitoring using mobile phone technology on the outcome of heart failure patients after an episode of acute decompensation: randomized controlled trial. J Med Internet Res 2009; 11: e34.

29.

Antonicelli

Testarmata

Spazzafumo

, et al. Impact of telemonitoring at home on the management of elderly patients with congestive heart failure. J Telemed Telecare 2008; 14: 300–305.

30.

Giordano

Scalvini

Zanelli

, et al. Multicenter randomised trial on home-based telemanagement to prevent hospital readmission of patients with chronic heart failure. Int J Cardiol 2009; 131: 192–199.

31.

Ong

Romano

Edgington

, 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. JAMA Intern Med 2016; 176: 310–318.

32.

Mortara

Pinna

Johnson

, et al. Home telemonitoring in heart failure patients: the HHH study (home or hospital in heart failure). Eur J Heart Fail 2009; 11: 312–318.

33.

Madigan

Schmotzer

Struk

, et al. Home health care with telemonitoring improves health status for older adults with heart failure. Home Health Care Serv Q 2013; 32: 57–74.

34.

Dar

Riley

Chapman

, et al. A randomized trial of home telemonitoring in a typical elderly heart failure population in north west London: results of the home-HF study. Eur J Heart Fail 2009; 11: 319–325.

35.

Vuorinen

Leppänen

Kaijanranta

, et al. Use of home telemonitoring to support multidisciplinary care of heart failure patients in Finland: randomized controlled trial. J Med Internet Res 2014; 16: e282.

36.

Tompkins

Orwat

. A randomized trial of telemonitoring heart failure patients. J Healthc Manag 2010; 55: 312–322.

37.

Goldberg

Piette

Walsh

, et al. Randomized trial of a daily electronic home monitoring system in patients with advanced heart failure: the weight monitoring in heart failure (WHARF) trial. Am Heart J 2003; 146: 705–712.

38.

Soran

Piña

Lamas

, et al. A randomized clinical trial of the clinical effects of enhanced heart failure monitoring using a computer-based telephonic monitoring system in older minorities and women. J Card Fail 2008; 14: 711–717.

39.

Galinier

Roubille

Berdague

, et al. Telemonitoring versus standard care in heart failure: a randomised multicentre trial. Eur J Heart Fail 2020; 22: 985–994.

Home telemonitoring in heart failure patients and the effect of study design on outcome: A literature review

Abstract

Introduction

Method

Result

Conclusion

Keywords

Introduction

Method

Results

Country of study and study outcome

Type of patients recruited in the studies and study outcome

Health care professional involved in study and study outcome

Frequency of measuring and transmitting patient data and study outcome

Patient–health care provider interactions and study outcome

Discussion

Footnotes

Author contribution

Declaration of conflicting interests

Funding

ORCID iD

References