There is moderate evidence that home telehealth can reduce cardiac-related deaths. However, we recommend that this finding be interpreted with extreme caution; few studies have examined mortality rates and its generalizability cannot be determined.
There is moderate evidence associating home telehealth with improvements in functional status that are equal or superior to those seen with usual care. In one instance, an exercise program that used home telehealth appeared to be no less effective than standard hospital-based care, and significantly more effective than a home exercise program without telehealth support. Another recent study also found that telehealth rehabilitation was as effective as conventional care. As this study was retrieved in a final scan of 2011-2012 literature and was not subject to the same level of analysis as the other studies included in this review, we will not attempt to extrapolate beyond the conclusions provided by its authors. See Dalleck et al. (2011) for more details.
There is also moderate evidence that home telehealth has the potential to improve quality of life, but no evidence that this improvement persists in the long-term or is significantly better than that seen with usual care.
Mental health and anxiety do not appear to suffer when home telehealth is used, but it not yet clear whether they improve as a result. Nor does home telehealth consistently improve exercise and eating habits, even when education and lifestyle change support are explicit components of the intervention. Limited improvements have been observed in some cases.
There is limited information available on patient uptake and satisfaction with home telehealth. Attrition due to difficulty using technology does occur, but at a fairly low rate (<10%). Most studies report that the majority of patients accept the technology and are as satisfied as those under usual care. A recent study of roughly 500 patients using a remote ICD (implantable cardioverter defibrillator) monitoring program achieved satisfaction rates of close to 90%, although most participants expressed a desire for more detailed provider feedback. As this study was retrieved in a final scan of 2011-2012 literature and was not subject to the same level of analysis as the other studies included in this review, we will not attempt further analysis of its findings. See Petersen et al. (2012) for more details.
There is some indication that clinical instability predicts use of remote monitoring systems that facilitate immediate and direct patient-provider contact. Further research into differences between patient sub-groups may be helpful in determining which patients are most likely to benefit from home telehealth programs.
Patients can save travel time when in-person appointments are replaced by remote monitoring or tele-appointments. We found few attempts to quantify these savings, perhaps because it is so apparent that they are extremely dependent on the remoteness of the patient population.
Uptake and Use of Technology
Summary: Uptake and use of technology outcomes were reported in 6 studies. Most found that the majority of patients accepted the technology and were as satisfied as those under usual care. Attrition due to difficulty using technology did occur, but at a fairly low rate (<10%). There is some indication that clinical instability predicts use of remote monitoring systems that facilitate immediate and direct patient-provider contact. Further research into differences between patient sub-groups may be helpful in determining which patients are most likely to benefit from home telehealth programs
Study Details: Ease of use was reported by Miller et al. (2007) and Raatikaanen et al. (2008). Miller et al. (2007) state that participants who completed the study (n=64) reported no difficulties using the ‘Health Buddy’, a telephone attachment through which they transmitted data. However, 5 of the 8 patients who withdrew from the intervention group did so because they did not feel their health allowed them to manage the technical requirements of the intervention. In another study, 10 patients (5% of the total study population) dropped out due to an inability to use the telehealth device (Chiantera et al., 2005).
Raatikainen et al. (2008) studied patients with implantable cardioverter defibrillators (ICDs). Data from these devices could be retrieved through remote interrogation and/or transmitted by patients, again using a telephone attachment. The majority of patients reported that device instructions were ‘clear’ or ‘very clear’, and that setting up the device was ‘easy’ or ‘very easy’. The majority of data transmissions (90%) were performed without technical support.
Patient satisfaction was reported by Al-Khatib et al. (2010). The authors found that intervention patients had significantly higher satisfaction with care than the control group at 6 months (survey scores of 88 vs. 75; p=.03). At 12 months, the control group had reached the same level of satisfaction. However, intervention scores had remained unchanged and the difference was no longer significant.
Uptake was reported in Morguet et al. (2008) and Lindsay et al. (2008, 2009). Morguet et al. (2008) offered participants a telephone service that allowed for real-time transmission of ECG signals to providers. Younger age and higher left ventricular ejection fraction were associated with a higher number of calls. For the 29% of calls that were classified as ‘symptom-driven’, repeat percutaneous coronary interventions or angioplasties, and recent successful cardioversions were found to be independent predictors of a patient calling.
Lindsay et al. (2008, 2009) provided patients with computers and access to an online disease management portal that included discussion forums. Study personnel moderated the forums for 6 months, and left them unmoderated for the final 3 months. Message writing between participants increased by 50% from the first phase to the second, while messages to moderators decreased by 23%. While the study design does not allow us to draw any definite conclusions, these findings suggest that the presence of a moderator may have a strong influence on the nature of user participation in online discussion forums.
Recent Developments: A scan of material from 2011-2012, a time period not covered by our initial searches, found 1 additional article that addressed uptake and use of technology (Petersen et al., 2012). Authors studied a cohort of nearly 500 patients who took part in a program involving remote ICD monitoring with provider feedback. Satisfaction rates were close to 90%, although most expressed a desire for more detailed responses. As this study was not subject to the same level of analysis as the other studies included in this review, we will not attempt further analysis. See Petersen et al. (2012) for more details.
Self-Management, Self-Efficacy, and Behaviour Change
Summary: Three Level 2 studies reported on self-management, self-efficacy, and behaviour change outcomes (Barnason et al., 2009; Lindsay et al., 2008; Miller et al., 2007). There is moderate evidence that home telehealth can lead to significantly greater improvements in some aspects of exercise and eating habits than usual care. However, these improvements appear to be limited and specific; no studies achieved an ‘across-the-board’ improvement in exercise or eating habits.
Study Details: Barnason et al. (2009), using a tri-axial accelerometer to measure energy expenditure, reported a ”significant main effect by group (F[1,209] =4.99, P < .05) […] the intervention group had a least square means of 27.9kcal/kg/d of energy expenditure compared with the usual care group of 26.6 kcal/kg/d […]” (p.459). However, there was no significant group or time effect for daily minutes spent in exercise. It appears that the intervention may have increased the intensity with which participants exercised, but not the duration.
Lindsay et al. (2008) reported a significant difference between intervention and control groups in frequency of eating ‘bad’ foods over the first 6 months of their study (mean 13.71 vs. 14.55; p=.040). There were no significant differences between groups in the other health behaviours measured, which included exercise, alcohol consumption, cigarette smoking, and confidence in managing health. Furthermore, the mean number of days that intervention group members spent in moderate exercise dropped significantly during the final 3 months of the 9-month intervention (1.71 vs. 2.63, p=.000) (Lindsay et al., 2009). During this period, participant discussion forums were unmoderated. Whether this effect was attributable to this lack of moderation, a time effect, or a combination of the two cannot be determined at this point.
Miller et al. (2007), using accelerometers, activity diaries, and subscales of the Medical Outcomes Study – Short Form, found no significant differences between groups in physical function and activity levels over time.
Clinical Outcomes, Symptoms, and Health Status
Seven studies report on clinical outcomes, symptoms, and health status outcomes. Of these, 6 were Level 2 evidence (Al-Khatib et al., 2010; Barnason et al., 2006, 2009; Lindsay et al., 2008, 2009; Miller et al., 2007; Waldmann et al., 2008) and 1 was Level 4 (Gialluria et al., 2006).MortalitySummary: Mortality was measured in 2 studies, both Level 2 evidence (Al-Khatib et al., 2010; Waldmann et al., 2008). There is moderate evidence that home telehealth can reduce cardiac-related deaths in patients with coronary artery disease. However, results from the study from which this finding is derived (Waldmann et al., 2008) merit close examination.Study Details: Waldmann et al. (2008) treated mortality as part of a composite endpoint of all-cause mortality, myocardial infarction, re-hospitalization, and re-vascularization. There was no significant difference between groups in patients reaching the composite endpoint. However, cardiac-related deaths were significantly higher in the control group (3% vs. 1%, p-0.21), despite the fact that users of the telehealth systemwere significantly more likely to reach the composite endpoint (57% vs. 35%, p<.001). This may have been due to increased hospitalizations in telehealth users, which the study’s authors attribute to changes in clinical pathways.Al-Khatib et al. (2010), examining mortality alone, found no significant difference between groups.
Summary: Measures of functional health were used in 2 studies: one Level 2 and one Level 4 (Barnason et al., 2006, and Gialluria et al., 2006, respectively). There is moderate evidence associating home telehealth interventions with significant improvements in functional health status. In the studies retrieved, these improvements were equal to or superior to those seen in usual care.
Study Details: General health functioning scores, measured using selected sub-scales of the Medical Outcomes Study Short Form-36 (MOS SF-36), improved significantly in both the intervention and the control group in Barnason et al. (2006). However, improvements were significantly greater (p<.01) in intervention group patients. Postoperative problems did not differ significantly between groups.
Gialluria et al. (2006) used a 3-arm study design. Control Group 1 took part in a hospital-based exercise program, Control Group 2 in a home-based exercise program, and the intervention group in a home-based program supplemented by telehealth. Significant improvements in cardiovascular functional capacity were seen in both Control Group 1 and the intervention group, with no significant change in Control Group 2. In this study, an exercise program using home telehealth appeared to be no less effective than standard hospital-based care, and significantly more effective than a home exercise program without telehealth support.
Summary: Measures of mental health were used in two Level 2 studies and one Level 4 study (Lindsay et al., 2008, and Miller et al., 2007; Gialluria et al., 2006, respectively). There is moderate evidence that home telehealth interventions can lead to improvements in mental health. Evidence of significantly greater improvement than that seen with usual care is insufficient.
Study Details: Miller et al. (2007) noted significant improvement in both intervention and control groups in scores on the mental subscale of the Medical Outcomes Survey Short Form-36. No significant difference between groups was found.
Patients in Lindsay et al. (2008) were surveyed on mental health. There was no significant difference between groups at the study endpoint and no significant change over time in the intervention group. However, scores in the control group declined significantly over the course of the 6-month study.
In Gialluria et al. (2006), mean scores on state anxiety and depression scales were significantly reduced in the intervention group (STAI-YI (State Anxiety): 37±5.33 to 33.8±7.52; Beck Depression Inventory Scores: 16.2±4.5 to 15.8±2.2). No significant changes were seen in either control group of this 3-arm study. This study had several limitations, including small sample size and non-randomized enrollment methods.
Recent Developments: A scan of material from 2011-2012, a time period not covered by our initial searches, found 2 additional articles that addressed clinical outcomes, symptoms, and health status (Dalleck et al., 2011; Zimmerman et al., 2011). In Dalleck et al. (2011), a 3-month cardiac rehabilitation program delivered through home telehealth appeared as effective as usual care. Zimmerman et al. (2011) report on a secondary analysis that suggested that females might be more responsive to a telehealth intervention aimed at relieving symptoms. Both studies had limitations. As these studies were not subject to the same level of analysis as the other studies included in this review, we will not attempt further analysis. See Dalleck et al. (2011) and Zimmerman et al. (2011) for more details.
Quality of Life
Summary: Quality of life was reported in 4 studies. Three received Level 2 evidence ratings (Al-Khatib et al., 2010; Barnason et al., 2009; Miller et al., 2007), and one a Level 4 rating (Giallauria et al., 2006). There is moderate evidence that home telehealth has the potential to significantly improve quality of life, but no evidence that this improvement has long-term persistence or is significantly greater than that seen with usual care.
Study Details: Barnason et al. (2009), and Miller et al. (2007) found no significant group effect for scores on the Medical Outcomes Survey Short Form-36. Al-Khatib et al. (2010), using the European Quality of Life thermometer, found that quality of life was significantly better in the intervention group at 6 months (average score 83 vs. 75; p=.002), but that the difference was no longer significant at 12 months.
Giallauria et al. (2006) found no improvement in the intervention group of a 3-arm study.
Cost and Time Savings
Summary: Cost and time savings were reported in 1 study. Patients using home telehealth saved appointment time and travel time. This general applicability of this study’s findings cannot be determined from the evidence available.
Study Details: Raatikainen et al. (2008) stated that intervention group patients saved an average of approximately 3 hours. Mean patient time needed to transmit the necessary data for the intervention was significantly shorter than that needed for outpatient appointments: 9.9±3.7 minutes (range 2.3-17.5) vs. 391±282 minutes (range 41-1346); p<.001. These numbers included 1-way travel time to hospital, which averaged 182±148 minutes (range 10-670).
 It is unclear whether this figure refers to the number of instances of eating these foods or the number of days on which these foods were eaten.
 This analysis controlled for uptake by breaking the intervention group into users and non-users.
 Although Miller et al. (2007) note significant improvement in both groups over time for the mental health subscale.