Cardiovascular Disease, Heart Failure: Patient Outcomes

Summary

There is strong evidence that significant short-term improvements in functional status are achievable through home telehealth. Evidence of long-term improvement is insufficient.  Our review retrieved only one intervention that lasted longer than four months, and there is some evidence to suggest that improvements in functional status lessen over time.  Further research into long-term outcomes is warranted.

While there is also strong evidence that home telehealth has the potential to reduce mortality significantly more than usual care, extreme caution must be used in interpreting this finding.  Although several strongly designed studies reported this outcome, many others found that home telehealth had no significant effect on mortality rates.  We advise those who are seeking to reduce mortality through home telehealth to examine the interventions that were successful in doing so and to give careful consideration to the transferability of these findings to their own environment.

There is strong evidence that home telehealth interventions can be significantly more effective than usual care in improving disease-related knowledge and symptom distress.  There is also strong evidence that quality of life tends to improve significantly with use of home telehealth.  However, this improvement is greater than that seen with usual care in only one-fourth of reported studies.

There is moderate evidence that home telehealth can improve self-efficacy in some patient populations. Evidence that it can improve mental health is weak.

Home telehealth interventions for heart failure achieve uptake rates upward of 90% with apparent regularity, although the general bias towards reporting positive results makes it difficult to determine whether this is truly representative of the average.  One study reported a sharp decline in system use over time, suggesting that future researchers should be careful to measure uptake at multiple points rather than taking an average.

The majority of patients using home telehealth report positive experiences with the technology and/or the program as a whole. There is not complete agreement on this point. Privacy concerns and an uncomfortable sense of being observed have been reported by some patients, and those with arthritis or other mobility limitations may have difficulty using equipment that requires fine motor control.  However, most of the evidence points towards high levels of acceptance or at least tolerance of home telehealth.  There is evidence that this is true of older patient populations (75+) as well as younger users. 

No information on patient cost and time savings was found.

Details

Uptake and Use of Technology

Summary: Uptake and use of technology outcomes were reported in 14 studies. In many cases, these were measured as secondary outcomes. Patient satisfaction was generally high, and problems using technology appeared rare. Rates of adherence were also high, often exceeding 90%. There appears to be little evidence to support concerns about patient uptake and use of technology, although the possibility of reporting bias must be taken into account.

Study Details: Studies used a range of indicators to measure uptake and use of technology outcomes. Study details have been grouped into several categories for ease of reading.

Adherence

The percentage of the intervention group deemed ‘adherent’ ranged up to 97% (Soran et al., 2008). In Chaudhry et al. (2009), adherence – defined as using the system at least once per week – was found to be highest in the first week of the study period, with over 90% adherence. However, adherence dropped dramatically by week 29, at which point only 55% of participants were using the system according to schedule. Wakefield et al. (2009) also found high rates of adherence, and report that no significant differences were found between rates of adherence to scheduled telephone contacts (94%) and videoconferencing visits (96%). Dar et al. (2009), while not using the label ‘adherence’, report that 95% of the study participants used the monitoring equipment at least 90% of the study duration.

Rates of Use

In Schwarz et al. (2008), over 90% of patients reported using the telehealth system on a daily basis. Readers should be aware, however, that nurses in the same study found that the system was not used for an average of 16 (range 0-66) out of 118 days (Schwarz et al., 2008). This discrepancy in patient- and provider-reported rates of use provokes both interest and caution.

Over 80% of the intervention group in Cleland et al. (2005) submitted at least 1 measurement daily (weight or blood pressure). 55% sent twice daily measurements over 80% of the time. Bowles et al. (2009) found that the study group sent an average of 34 data transmissions to providers over the 2-month study. The range was 1-123, suggesting that use of the system varied considerably. In Kashem et al. (2008), the study group sent a total of 1,887 online messages to their care providers, or nearly 40 messages per patient over 12 months.

Although frequency of use is largely dependent on the study design and type of telehealth intervention, this information provides some insight into the impact of technology on patients’ self-management regimens and on their daily lives. It can also be taken as an indicator of patient satisfaction, albeit an indirect and imperfect one.

Satisfaction

Average patient satisfaction with home monitoring was “generally high” in Wakefield et al. (2008b) and ranged from approximately 92 to 97 on a 100 point scale in Woodend et al. (2008). However, some patients in Woodend et al. (2008), particular those with arthritis, reported that they had difficulty using some of the telehealth equipment. The 12-lead electrocardiogram was the most common source of problems.

Bondmass (2007) found that patients receiving the telehealth intervention reported significantly higher levels of satisfaction with their care compared to patients receiving usual care.

In Cleland et al. (2005), 96% of the patients in the study group expressed ‘good’ or ‘very good’ satisfaction with the technology, while in Hudson et al. (2005), “most patients were satisfied” with the program. Of the participants who completed the post-study patient satisfaction survey in Kulshreshtha et al. (2010), 100% reported that the system was easy to use and increased their feelings of control over their health. Note that only 40% of patients completed the satisfaction survey, creating high potential for self-selection bias.

Wakefield et al. (2009) were atypical in reporting no significant differences in perception or satisfaction with care resulting from the telehealth intervention. In Whitten et al. (2009), some patients expressed concerns over privacy, a preference to see healthcare providers in person rather than using telehealth, and a belief that telehealth should be an option only in circumstances when health care cannot be provided in person.

Acceptability of the intervention technology was captured in some studies as perceived ease of use, which was rated as “good” or “very good” by 80% of participants in Balk et al. (2008) and Schmidt et al. (2008). Woodend et al. (2008) and Whitten et al. (2009) had similar results, with patients generally reporting high ease of use. A gender difference was reported in 1 study: male patients in Schmidt et al. (2008) had significantly higher acceptance of the technology (t=4.21, p<.05). Age, however, was not significantly associated with acceptance.

In Kulshreshtha et al. (2010), 80% of participants believed that the telehealth program should continue. Half of participants in Schmidt et al. (2008) stated that they would like to continue using the device in the future while the other half preferred it only for interim use. The most common reason for preferring to discontinue use of the telehealth device was that patients ”felt observed in their daily activities” (Schmidt et al., 2008). In Dar et al. (2009), acceptance, or at least tolerance, appeared to be high; only 1 of 182 participants requested the removal of the telehealth equipment.

In contrast to the general findings, Myers et al. (2006) reported that 13.5% of patients withdrew from their study due to “feeling anxious” or “not liking” the telemonitoring procedure or equipment.

Recent Developments: A scan of material from 2011-2012, a time period not covered by our initial searches, found 1 additional article that addressed patient uptake and use of technology (Lemay et al., 2011). In this study, researchers reported that the elderly patients of their study sample (75+) were comfortable and competent users of home telehealth technology. 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 Lemay et al. (2011) for more details.

Self-Management, Self-Efficacy, and Behaviour Change

Self-management, self-efficacy and behaviour change outcomes were measured in 7 studies (Balk et al., 2008; Bondmass, 2007; Bowles et al., 2009; Gambetta et al., 2007; Hudson et al., 2005; Ramaekers et al., 2009; Wakefield et al., 2009).

Disease-Related Knowledge

Summary: Disease-related knowledge, an important component of self-management, was measured in four Level 2 studies. There is strong evidence that home telehealth interventions can result in significantly greater increases in disease knowledge than those seen with usual care. Though the factors essential to success cannot be identified with any certainty at this point, one might speculate that intervention length influenced this result: the studies that found no change treated patients for 3 months or less, whereas those that did find change lasted 6 months or more. The content of the intervention, the technology used to deliver it, and the characteristics of the patient population can also be assumed to have had a significant role. An intervention with carefully tailored content but challenging technical components is unlikely to be appropriate for a population with low levels of technical literacy. A straightforward interface that offers substandard content is equally likely to be unsuccessful.

Study Details: Balk et al. (2008) and Ramaekers et al. (2009), both Level 2 studies, found significantly greater increases in disease knowledge in intervention group patients than in control group patients. However, 2 other studies – also with Level 2 ratings – found no significant differences between study groups in diet or medication knowledge following the intervention (Bowles et al., 2009; Wakefield et al., 2009).

Self-Efficacy

Summary: Patient self-efficacy was reported in 3 studies: two Level 2 and one Level 4. There is moderate evidence of association between home telehealth and improvements in self-efficacy. However, one Level 2 study did not find any improvement, despite the fact that this outcome was targeted in the intervention.

Study Details: A Level 2 study by Wakefield et al. (2009) measured self-efficacy using 2 validated scales and found neither significant improvements in self-efficacy across time nor any significant differences in self-efficacy scores between the telehealth and usual care groups at the end of the study. Authors of the study speculated that a more intensive intervention may be necessary in order to bring about changes in self-efficacy. Another Level 2 study, in contrast, found that participants in the intervention group had significantly higher self-efficacy scores at the end of the study than the control group (Bondmass, 2007). In a Level 4 study by Hudson et al. (2005), 97% of participants reported improvements in self-efficacy. It is not clear whether a validated tool was used to measure this, or whether this result achieved statistical significance. 

Diet and Self-Care

Summary: Changes in diet and self-care behaviours were reported in 4 studies: three Level 2 and one Level 4. At present, there is weak evidence of association between home telehealth and self-care behaviours. However, the findings of a Level 2 study by Ramaekers et al. (2009) suggest that further investigation is warranted.

Study Details: In a Level 4 study by Hudson et al. (2005), 81% of study participants reported making positive dietary changes due to the telehealth program and 100% reported having an action plan to address the weight change. Note that assistance in developing an action plan was a formalized component of the intervention. A Level 2 study by Ramaekers et al. (2009) also reported significant differences for 4 out of 8 items on the Heart Failure Compliance Scale at study endpoint: fluid restriction (87.1±15.1% v. 71.1±34.1%, p=.012); weighing (91.7±18.2 v. 67.4±38.6, p=.000); exercise (72.3±24.6% v. 57.2±34.0%, p=.034); and alcohol (96.9±9.6% v. 89.4±24.1%, p=.040). However, some of these differences were present at baseline. Furthermore, while the differences in the percentage change experienced by the groups are sizeable in some instances, p-values are not given.

The 2 remaining studies, both Level 2 evidence, found no significant differences in self-care or diet behavior between patients who received telehealth versus those who received usual care (Balk et al., 2008; Bowles et al., 2009).

Clinical Outcomes, Symptoms, and Health Status

Clinical outcomes, symptoms, and health status were reported in almost all studies. For full details, including p-values and effect size where available, see Table C.3.6.1: Patient Outcomes – Clinical Outcomes, Symptoms, and Health Status (below).

Clinical Variables

Summary: Changes in clinical variables were reported in 4 studies: two Level 2 and two Level 4. Evidence that telehealth can lead to significantly greater improvements in clinical variables than usual care is insufficient, although there is some indication that further research is warranted.

Study Details: A Level 2 study by Kashem et al. (2008) reported no significant changes in clinical status[1] in either the intervention or the control group over the course of a 1-year study. In Soran et al. (2008), also Level 2, researchers looked at changes in need for invasive procedures or intravenous inotrope use, which might be taken as an indirect measure of clinical status. No significant differences between groups were found.

The findings of the Level 4 studies, however, are suggestive. In a single-group study, Hudson et al. (2005) found a significant increase over the study period in the percentage of patients whose systolic or diastolic blood pressure measurements did not trigger any system alerts. Another study found sizeable reductions in clinical instability in the intervention group when compared to the control group. This study did not report p-values and it was unclear whether randomization was used (Scalvini et al., 2005a).

Symptoms and Self-Reported Health Status

Summary: Outcomes related to symptoms and self-reported health status were reported in 5 studies: three Level 2 and two Level 4. There is strong evidence of an association between home telehealth and significant improvements in self-reported symptoms. There is also strong evidence that this improvement can be significantly greater than that seen in usual care. This improvement was not seen in all cases: one of the three Level 2 studies found no significant intervention effect (Bowles et al., 2009).

Study Details: 

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A Level 2 study by Bondmass (2007) found significant improvements in  greater symptom distress in both groups in a randomized controlled study. However, these improvements were significantly greater in the intervention group. Dansky et al. (2008), also Level 2, used the Omaha System Problem Rating Scale to assess clinical outcomes of patients receiving usual care and those in 2 intervention groups. Intervention Group 1 used a 1-way, monitor-only telehealth system. Patients in Intervention Group 2 were given a 2-way monitor and video system. The study found significant improvements in both study intervention groups in symptoms related to sodium and fluid intake and in medication effectiveness. Furthermore, Intervention Group 1 showed significantly greater improvements than both the control group and Intervention Group 2. This study did suffer from several limitations, including small sample sizes at some measurement points and non-randomized group assignments. Nevertheless, it is interesting that patients in Intervention Group 1, who appeared to have less contact with providers than those in Intervention Group 2, experienced greater improvement.

Level 2 evidence from Bowles et al. (2009), in contrast, found no significant difference between control and intervention groups in self-rated health status as baseline, at 60 days, or at 90 days.

Whitten et al. (2009), using a single-group study design (Level 4 evidence), reported that patients had significant improvements in symptoms. Another Level 4 study by Hudson et al. (2005) found that 97% of patients rated their health status as remaining stable or improving after completing the telehealth program.

Functional Status and Physical Activity

Summary: Changes in functional status and physical activity were reported in 5 studies. Three of these qualified for a Level 2 evidence rating, 1 for a Level 3 rating, and 1 for a Level 4 rating. There is strong evidence that home telehealth can lead to significant short-term improvements in functional status and physical health. Evidence of long-term improvements is insufficient.

Study Details: A Level 2 study by Piotrowicz et al. (2009) found significantly greater improvement in the intervention group in New York Heart Association functional class and in various physiological parameters. However, no significant differences between groups were found in improvement in exercise duration. Furthermore, the control group had significantly greater improvement in walking distance (418 (SD=92) to 462 (SD=91) metres in IG vs. 399 (SD=91) to 462 (SD=92) metres in CG; p=0.05).

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Both groups in a a Level 2 study by Woodend et al. (2008) had significantly better overall functional status and physical health post-intervention when tested with the Minnesota Living with Heart Failure Questionnaire. However, the telehealth group had significantly greater improvement. Note that this advantage was no longer present at the 1-year follow-up. Dansky et al. (2008), also Level 2, found no significant improvement in physical activity status.

A Level 3 study by Schmidt et al. (2008) reported significant improvement in the intervention group in physical health status from baseline to Month 1 and baseline to Month 2 – though not from Month 1 to Month 2, raising the possibility of a ceiling effect. A Level 4 study by Whitten et al. (2009) reported significant improvements following the intervention in 2 items of the 12-Item Short Form Health Survey (SF-12): energy levels and ability to engage in moderate activities.

Note that only 1 study retrieved lasted longer than 4 months. Authors reported a significant intervention effect at the 3-month measurement mark, but found that the difference between control and intervention groups was no longer present at the 1-year endpoint.

Mental Health

Summary: The effects of home telehealth on mental health of individuals were reported in 4 studies: three Level 2 and one Level 3. There is weak evidence that home telehealth can significantly improve mental health. The replicability of this result is questionable; 3 of 4 studies found no significant change in mental health status.

Study Details: A Level 3 study by Schmidt et al. (2008) reported significant improvements in mental health status in the intervention group. No significant differences between groups in depression scores or depressive symptoms were found in Level 2 studies by Bowles et al., (2009) or Schwarz et al. (2008). A Level 2 study by Ramaekers et al. (2009), though finding a non-significant decrease in depression in the intervention group over time, also reported no significant difference between groups.

Morbidity and Mortality

Summary: Morbidity and/or mortality were reported in 10 studies. Fully 9 of these merited Level 2 evidence ratings. The remaining study was classified as Level 3 evidence. The findings of some studies are strong evidence of the potential of telehealth to improve outcomes in this area, but it is clear that extreme caution should be used when assessing the generalizability of these findings. A large majority of studies reported no significant intervention effect.

Study Details: All studies are Level 2 evidence unless otherwise noted. Significant improvements in mortality rates were found in 2 studies. Cleland et al. (2005) report significantly higher mortality rates in the usual care group compared to the telehealth group. Wakefield et al. (2008a) describe a significantly higher crude mortality rate in the control group during the 3-month intervention: 6.1% in the control group versus 3.8% in the intervention group. However, this difference was not significant at 12 months.

Mortara et al. (2008) found no significant difference between groups in cardiac death plus heart failure hospitalization (combined measure) while Dansky et al. (2008) report no significant difference in likelihood of death at 120 days. An additional 6 studies found no significant differences between patients who received the telehealth intervention and those who received usual care in all-cause or cardiovascular related deaths (Chaudhry et al., 2009; Kashem et al., 2008; Soran et al., 2008; Wakefield et al., 2009), time to death (Chaudhry et al., 2009), number of days alive and out of the hospital (Balk et al., 2008), or number of days lost to death or acute hospitalization at 240 or 450 days (Cleland et al., 2005).

A Level 3 study by Gambetta et al. (2007) found a significantly higher risk of adverse events among patients in the usual care group than in the intervention group.

Recent Developments: A scan of material from 2011-2012, a time period not covered by our initial searches, found 2 additional studies that addressed mortality (Koehler et al., 2011; Sohn et al., 2012). Koehler et al. (2011), a randomized controlled trial with over 700 participants, reported no significant intervention effect. Sohn et al. (2012), a retrospective study, reported that mortality was 35% lower in the intervention group. 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 Koehler et al. (2011) and Sohn et al. (2012) for more details.