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European Journal of Heart Failure 2005 7(7):1133-1144; doi:10.1016/j.ejheart.2005.08.005
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© 2005 European Society of Cardiology

Effectiveness of comprehensive disease management programmes in improving clinical outcomes in heart failure patients. A meta-analysis

Rosa Roccafortea,b,*, Catherine Demersa,c, Fulvia Baldassarred, Koon K.Teoa,c and Salim Yusufa,c

a Population Health Research Institute, McMaster University, and Hamilton Health Sciences Hamilton, Ontario, Canada
b Cardiology Department, S. Raffaele Hospital Milan, Italy
c Division of Cardiology, McMaster University Hamilton, Ontario, Canada
d Department of Epidemiology and Biostatistics, McMaster University Hamilton, Ontario, Canada

* Corresponding author. Viale Abruzzi, 90, 20131 Milan, Italy. Tel./fax: +39 02 29512491. E-mail address: rosaroccaforte{at}hotmail.com


   Abstract
Top
 Abstract
1. Introduction
 2. Methods
 3. Results
 4. Discussion
 5. Conclusions
 References
 
Background: Disease management programmes (DMP) have been advocated to improve long term outcomes of heart failure (HF) patients.

Aims: To summarise the evidence supporting DMP effectiveness in improving HF clinical outcomes.

Methods: Eligible studies were located through a systematic literature search. Only randomised controlled trials (RCTs), enrolling HF patients, and allocating them to DMP or usual care (UC), were included. Information on study setting and design, participants' characteristics and interventions tested were collected. A study quality assessment was performed. Main clinical outcomes assessed were: all-cause mortality and (re)hospitalisations, HF-related (re)hospitalisations and mortality. Meta-analysis was performed according to both Yusuf–Peto method and random effects model.

Results: Thirty-three RCTs were included. Mortality was significantly reduced by DMP compared to UC: OR = 0.80 (CI 0.69–0.93, p=0.003). All-cause and HF-related hospitalisation rates were also significantly reduced: OR=0.76 (CI 0.69–0.94, p<0.00001) and OR=0.58 (CI 0.50–0.67, p<0.00001), respectively. Different DMP approaches appeared to be equally effective (sensitivity analyses).

Conclusion: DMP reduce mortality and hospitalisations in HF patients. Because various types of DMP appear to be similarly effective, the choice of a specific programme depends on local health services characteristics, patient population, and resources available.

Key Words: Disease management programme • Heart failure • Hospitalisation • Mortality • Meta-analysis

Received June 15, 2005; Accepted August 22, 2005


   1. Introduction
Top
 Abstract
 1. Introduction
2. Methods
 3. Results
 4. Discussion
 5. Conclusions
 References
 
Heart failure (HF) is the leading cause of hospitalisation in many countries, and represents a huge economic burden [1]. About 40% of patients are readmitted within one year following their first hospital admission for HF [2–4] Despite effective therapies, mortality for HF is still high, with 40% of patients dying within 4 years [3–5]. HF is predominantly a disease of the elderly: two thirds of patients admitted to hospital for HF are older than 65 years of age: Patients frequently experience acute, recurrent episodes of decompensation, and are often affected by other significant co-morbidities [4,5], which lead to long, repeated hospitalisations [3,4].

The complexity of HF treatment has prompted the development and implementation of various disease management programmes (DMP) [6–8] in order to improve patients' long term outcomes. Several randomised controlled trials (RCTs) have compared DMP for HF to usual care. The results have been summarised in two previous meta-analyses, but these included a limited number of studies [9,10]. All-cause (re)hospitalisation rate was substantially reduced in patients allocated to DMP compared to usual care, but there appeared to be no effect on mortality, HF-related (re)hospitalisation, or length of hospital stay.

We aimed to re-evaluate the evidence supporting the effectiveness of HF DM programmes in improving relevant clinical outcomes – mortality first – in a much larger sample of studies and patient populations. We also explored whether specific types of DMP, or different components, timing and duration of the programme, were likely to be most beneficial.


   2. Methods
Top
 Abstract
 1. Introduction
 2. Methods
3. Results
 4. Discussion
 5. Conclusions
 References
 
2.1. Literature search
RCTs were included if: (1) patients were enrolled with a diagnosis of HF, and were followed in an outpatient setting; (2) a comprehensive DMP was compared to usual care; (3) all-cause mortality and/or (re)hospitalisation rates, and HF-related (re)hospitalisation rates and/or HF-related mortality, were the outcomes assessed. Studies were excluded if the study population included patients with conditions other than HF, and if the data for those with HF could not be separated; the intervention tested was not a comprehensive programme; the comparison was between two "active" interventions without an usual care group; the study was performed in an inpatient setting only.

We developed a specific search strategy using a combination of keyword and free-text terms. The following text word terms and Medicine Subjects Headings (MeSH) were used: heart failure, congestive; disease management; case management; comprehensive health care; health services research; health services costs; home care services; clinical protocols; quality of health care; nurse-led clinics. Other key and text words were retrieved through the relevant articles. No language restriction was applied.

We searched the following databases in duplicate (R.R. and F.B.): PubMed — Medline and Pre-Medline (1980 — December 2004), EMBASE (1980 — December 2004); CINAHL (1982 — December 2004), the Cochrane Controlled Trial Registry (the "Central", issue III 2004), and the Cochrane Effective Practice and Organisation of Care Study Registry. Internal medicine, cardiology and nursing journals from January 1990 to December 2004 were searched in printed or online editions by R.R. and F.B. All retrieved studies were carefully examined for references and related articles. We also used other sources, such as personal files on HF; contacts with experts of the disease and with the authors of retrieved articles, if deemed necessary to obtain study details. The authors of registered, but not yet published studies, or trials presented during scientific meetings as abstracts, were also contacted.

Study screening and assessment for eligibility was done in duplicate (by R.R. and F.B.), using standard forms. Agreement between the two screeners was calculated as percentage agreement and Cohen's kappa, and disagreements were resolved by consensus.

Information on study setting and design, characteristics of trial participants, programme characteristics: time of initiation (in hospital, at discharge, after discharge, or in outpatient setting), type of intervention (educational, phone contacts, nurse visits, nurse and physician visits, nurse and pharmacist check-ups, multidisciplinary teams), duration of the intervention, patients' compliance to intervention, were collected.

2.2. Study quality assessment
The quality of each study was evaluated according to the "component approach" [11], examining: (a) randomisation procedure (random sequence generation and allocation concealment) adequacy, (b) blinding of outcome assessors, (c) follow up completeness, and (d) intention-to-treat analysis. A sensitivity analysis [11] was performed, stratifying trials for the quality components considered: if all of them were present in a study, the study was deemed of "high" quality; otherwise, it was judged as being "not high".

2.3. Statistical analysis
Our main outcomes were all-cause mortality and all-cause (re)hospitalisation rate, measured as number of patients (n) allocated to intervention or usual care arms experiencing the outcome of interest at least once, over the total number of patients randomised to that arm (N). Similarly, HF-related (re)hospitalisation rate and HF-related mortality (secondary outcomes) were measured as n of patients in the intervention or usual care groups experiencing the outcome at least once, over total N of patients allocated to that group. Hence, each patient could contribute to one event only for all these outcomes.

The pooled effect estimates for binary variables were expressed as odds ratio (OR) and risk ratio (RR); 95% confidence intervals (CI) were calculated, and the analysis was performed according to the Yusuf–Peto's method and random effects model (DerSimonian and Laird). For continuous variables, such as length of hospital stay and total number of days spent in hospital, we calculated means and standard deviations, and combined them in a weighted mean difference (WMD) [12].

We used the software RevMan 4.2.7 statistical package (Review Manager version 4.2.7, May 2004; www.cochrane.org).

Statistical heterogeneity in each outcome considered was evaluated applying the Cochran Q test [12], considering a p value <0.05 as statistically significant. Sensitivity analyses were performed to test differences in interventions, duration of follow up, year of publication and study country, as possible source of heterogeneity.

The presence of publication and other biases was assessed by means of funnel plots [13].


   3. Results
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
4. Discussion
 5. Conclusions
 References
 
3.1. Literature search
Our search strategy located 804 titles, of which 750 were deemed ineligible on the basis of title and abstract, and 54 were retrieved as full text (Fig. 1). Thirty-three out of 54 met the eligibility criteria, and were included in the analysis [14–46]. The remaining 21 trials (list available on request) were excluded for various reasons: they were not original papers (1 study), were sub-study reports (n=7); failed to provide separate data for HF patients (n=4); the intervention was not a comprehensive DMP (n=2), the study compared two active interventions (n=2), or they did not measure outcomes we were interested in (n=2). One study was completed in the 1960s, and was excluded because the study population, co-interventions and the patient characteristics are likely to have been very different from recent trials. Another study was excluded because it utilised a cluster randomisation design, with hospitals as the units of randomisation, and the intervention was mostly delivered in an inpatient setting. A third study randomised nurses to provide DMP or usual care to HF patients: nurses were therefore the units of randomisation.


Figure 1
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  		Fig. 1 Flow diagram of study inclusion and exclusion process.

 
The percentage agreement for study screening and eligibility between two reviewers (R.R. and F.B.) was 80%; kappa was 0.83 (CI 0.61–1.00).

The possible presence of publication and other biases in the literature search was explored with funnel plots constructed around the combined effect estimate for all- cause mortality (main outcome). The graph showed a fairly symmetrical distribution of the included studies around the pooled effect estimate, indicating little evidence of publication bias (Fig. 2).


Figure 2
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  		Fig. 2 Funnel plot of included studies, constructed around the common effect estimate of all-cause mortality. OR calculated with the Yusuf–Peto method. The individual data points represent the included studies; the vertical line indicates the common effect estimate.

 
3.2. Study characteristics
Table 1 summarises the characteristics of the included studies. They were published between 1993 and 2004; 15 trials were performed in the US, 12 in Europe, 2 in Australia, two in Canada and one each in New Zealand and Argentina. Most studies were performed in academic centres or tertiary referral hospitals; several, however, involved community hospitals or primary care physicians [17,26,29,34,37–40,42,44–46].


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  		Table 1 Characteristics of included studies

 
The majority of patients were older than 65 years (73 years on average), women were well represented (58%), and 75% of patients were whites. The diagnosis of HF was usually based on typical symptoms and clinical and radiological signs of pulmonary congestion. Only in the most recent trials was the presence of left ventricular systolic dysfunction on echocardiography required for a patient to be included in the study [16,20,22,23,30–32,34–36,41,44,46]. Many trials enrolled patients with New York Heart Association (NYHA) functional class III and IV symptoms [19–24,26,27,29,31–33,36–38,41], who were at high risk for re-hospitalisation for HF or other chronic conditions. However, only two studies [14,16] explicitly excluded low risk patients.

DMP interventions varied widely: (1) multidisciplinary approach (No. of trials=7) [14,16,31,32,34,35,41], as defined by the primary investigators, always started during the index hospitalisation, carried out for 2–12 weeks up to one year after discharge, and delivered by various health professionals, (2) interventions centred on specific health professionals, usually HF specialist nurses (but also case managers, or pharmacists), focused on some components of care, such as patient and family education [20,21,30,33,46], or improvement in patient adherence to drug therapy [21,24,25,38,46]. The intervention could be initiated in hospital, at discharge, or immediately afterwards. It could last from a few weeks to one year, and could consist of a series of planned home/outpatient clinic visits supplemented by regular phone contacts [19,20,22,26–30,33,36,37,39,45,46], or 1–2 home/outpatient visits by the specialist nurse or pharmacist, and, in case of need, phone calls [15,17,18,21,23–25,38,44].

Usual care (UC) was less defined and only briefly described, or not described at all, by the investigators. Patients allocated to usual care were generally referred to their family physicians and home care nurses, or other home care services, after discharge following the index hospitalisation.

Patients were followed for 3 to 22 months (average of 6 months).

3.3. Quality assessment
Twelve out of 33 study reports [17–20,24,25,30,33,34,39,41,45] provided enough details on randomisation procedure to be judged as adequate. As expected, due to the nature of intervention, blinding was not feasible. Patients were masked regarding which group they had been allocated to in 3 studies only [17,22,37]; care providers and outcome assessors were blinded in 8 trials [17,23,24,28,31,33,41,45]. All but one [23] studies achieved more than 75% complete follow up. Eighteen studies [17–20,24,25,28,29,31–35,39–42,45] performed an intention-to-treat analysis, as stated by the investigators. According to the quality criteria chosen, 10 out of 33 trials were deemed to be of "high" quality [17,19,23,24,28,29,33,39,41,45].

3.4. Main analysis
3.4.1. All-cause mortality rate
Twenty eight studies [16–23,25–46] provided data on mortality (total No. of patients 5308, total No. of events 881) (Fig. 3). Only 3 studies [35,38,41] found a statistically significant reduction in death rate in patients allocated to the intervention group compared to usual care. The pooled OR (Yusuf–Peto method) was 0.80 (CI 0.69–0.93, p=0.003) with some degree of heterogeneity ({chi}227=43.86, p=0.02), which was totally accounted for by one study only [35]. It did not appear to be different from the other trials with respect to design, patients enrolled, type of intervention.


Figure 3
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  		Fig. 3 All-cause mortality. OR calculated with the Yusuf–Peto method. n: number of patients experiencing the outcome of interest in the DMP (treatment) group or in the usual care (control) group. N: total number of patients allocated to treatment (DMP) or to control (usual care) group.

 
The combined RR was 0.84 (CI 0.74–0.94; p=0.003, no heterogeneity); the pooled OR calculated with the random effect was 0. 81 (CI 0. 67–0.98, p=0.03, test for heterogeneity: {chi}227=40.20, p=0.05).

3.4.2. All-cause (re)hospitalisation rates
In 32 studies [14–38,40–45], which reported all-cause (re)hospitalisation rates in 7387 patients, there were 3220 events (Fig. 4). Seven trials [20,29,30,34,38,39,41] found a significant reduction in (re)hospitalisation rates in patients allocated to the intervention group compared to usual care. Only one study [17], which was directed at facilitating patients' access to primary care, found an increased rate of hospital (re)admissions following the intervention. The combined OR (Yusuf–Peto method) was 0.76 (CI 0.69–0.94, p<0.00001) with a significant degree of heterogeneity ({chi}231=71.01, p<0.0001); the pooled RR was 0.86 (CI 0.82–0.91, p<0.00001); the random effect OR was 0.70 (CI 0.60–0.82, p<0.00001), both highly heterogeneous. Most of the observed heterogeneity was attributable to a single study [17]: when excluded, heterogeneity was substantially reduced (p<0.04).


Figure 4
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  		Fig. 4 All-cause (re)hospitalisation rate. OR calculated with the Yusuf–Peto method. n: number of patients experiencing the outcome of interest in the treatment (DMP) or in the control (usual care) group. N: total number of patients allocated to DMP (treatment) or usual care (control).

 
HF-specific (re)hospitalisation rates were assessed in 20 studies [19–33,36–38,41,43,45,46] (No. of patients=3817, No. of events=1060). Eight trials [22,23,27,30,34,36,43] showed a statistically significant reduction in the intervention group compared to usual care; none demonstrated an increase. The combined OR (Yusuf–Peto method) was 0.58 (CI 0.50–0.67, p<0.00001). Again the test for heterogeneity was statistically significant ({chi}219=39.82, p<0.003), without identifying any study as the likely source of heterogeneity. The combined RR was 0.69 (CI 0.63–0.77, p<0.00001, no heterogeneity) and the random effect OR was 0.56 (CI 0.45–0.71, p<0.00001, with some degree of heterogeneity).

Seven studies [16,22,28,37,40,41,45] reported data on (re)hospitalisation rates for conditions other than HF. None demonstrated a statistically significant reduction in this outcome in the intervention group compared to usual care. The combined OR was 1.06 (CI 0.84–1.34).

Data on HF-specific mortality rate as available in 4 trials only [21,22,35,38]. There was a statistically significant reduction in the intervention group compared to usual care (No. of patients=700; OR 0.37, CI 0.21–0.73, p<0.0002) with no heterogeneity. This OR value was much lower than the pooled OR computed on all studies reporting mortality data (see above). However the data were so sparse that the combined results should be deemed unreliable.

3.5. Other outcomes
The total number of days spent in hospital for any cause during the follow up after the index hospitalisation (measured as mean±standard deviation) was significantly reduced in the intervention group compared to usual care: WMD=–1.49, CI –2.03 to –0.95, p<0.00001 (12 studies, No. of patients=2356) (Fig. 5, Table 2). The number of days in hospital for worsening HF, the length of hospital stay during hospital re-admissions (for any cause and for worsening HF), the total number of all-cause and HF-related multiple re-admissions were similarly reduced in the intervention arm compared to usual care (Table 2). The data, i.e. number of patients and number of events, were however relatively few, and any combined analysis results may be somewhat unreliable.


Figure 5
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  		Fig. 5 Total number of days spent in hospital for any reason during follow up. WMD, weight mean difference, calculated with the fixed method. n and N: see legend of previous figures.

 


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  		Table 2 Other clinically relevant outcomes

 
Several studies (No.=11; No. of patients=2038) [23,24,26,31,35,36,37,40,41,44–46] assessed the use of angiotensin converting enzyme inhibitors (ACE-I) at baseline and at the end of follow up, both in term of proportion of patients receiving these drugs, and of recommended doses. Pre- and post-intervention comparisons and between-group comparisons were performed. The adequacy of the drug regimen compared to that recommended by guidelines, or tested in RCTs, was evaluated in very different ways, so that it was not possible to identify a common effect measure to be combined in the analysis. As for the proportion of patients receiving any ACE-I at the end of follow up, all studies showed a significantly higher proportion of patients on ACE-I in the usual care group compared to the intervention group, with no heterogeneity: OR=1.48 (CI 1.20–1.83) (Fig. 6).


Figure 6
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  		Fig. 6 Proportion of patients on ACE-I therapy at the end of follow up in the two allocation groups. OR calculated with the Yusuf–Peto method. n and N: see legends of previous figures.

 
It was not possible to analyse beta-adrenoceptor blocker use in a reliable way, as data were only available in three studies [20,37,42].

3.6. Sensitivity analyses
Overall, similar results for the main outcomes of interest (mortality, all-cause and HF-related (re)hospitalisation rates) were observed across several sensitivity analyses performed according to pre-defined hypotheses (Table 3). In particular, "high quality" studies and programmes lasting 3–6 months were those most consistently associated with a significant reduction in all outcomes considered. Nurse-led interventions did not appear to affect all-cause mortality (21 trials, No. of patients=3757, OR=0.93, CI 0.77–1.11, no heterogeneity).


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  		Table 3 Sensitivity analysis results

 
3.7. Quality of life
Several investigators evaluated quality of life (QOL) as an outcome [14,15,17,18,21,23,26,28,29,31,32,35,39–41,44]. Different scales were used, principally The Minnesota Living With Heart Failure Questionnaire, and/or the Short Form-36 Questionnaire. In some studies the results were presented as mean scores with standard deviations, in others as median scores with range. It was therefore not possible to combine them in a summary measure. Eight studies [14,15,28,31,33,40,41] reported statistically significant differences (improvement) in QOL scores, both between the two allocation groups, and before and after the intervention. Four investigators found discordant results: QOL improvement in the short term (within 6 months), but not at the end of the follow up (one year) [23,26,40], or improvement in some QOL components (symptoms, distress), but not in others (functional and psychological components) [21]. Finally, 4 studies [17,29,39,44] did not report any statistically significant differences between the two groups of patients and/or between pre- and post-intervention period.


   4. Discussion
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
5. Conclusions
 References
 
4.1. Main findings
Our meta-analysis confirms, extends, and updates findings previously published [9,10] — that comprehensive DM programmes for HF are effective in reducing (re)hospitalisation rates for all causes and for worsening HF. Unlike previous analyses [9,10], which included fewer studies and patients, we have also demonstrated a statistically and clinically significant risk reduction of 16% in total mortality. This translates into one life saved for 34 patients treated, and compares quite favourably with those reported for various pharmacological treatments widely applied in clinical practice [47]. There was a high proportion of elderly patients (60% of the total sample), patients in NYHA class III–IV (45%), and patients with an ejection fraction <0.35 (39%). The observed control event rate (18%), however, was quite similar to that reported in less selected patient populations in several epidemiological studies [2,48,49]. In these types of patients, 90% of the deaths are attributable to cardiovascular causes, and about 30% to progressive heart failure [50]. Therefore, even if DMP were effective in reducing HF-related mortality only, this would be expected to translate into an overall benefit.

We found a substantial reduction in the rates of all-cause hospital re-admissions (14%), and HF-related (re)hospitalisations (31%), which was highly significant, and comparable in magnitude with those demonstrated with the use of ACE-inhibitors and beta-blockers in HF patients [51,52]. Other clinically important outcomes, which are considered useful markers of HF burden on health care systems [53,54] – cumulative number of days spent in hospital during follow up, length of hospital stay during subsequent re-admissions, and total number of multiple (re)hospitalisations – were all reduced by these strategies. Patients allocated to the intervention group were not only re-admitted less frequently, but spent less and less time in hospital.

The results on quality of life were less conclusive, partly because of the relatively small sample size of the trials evaluating this outcome, and partly because of the different measurement tools used. However, an improvement in at least some QOL components was observed by several investigators, and none reported a deterioration in the patients allocated to intervention compared to usual care.

Eleven trials reported data on ACE-inhibitor therapy. The number of patients receiving these drugs at the end of follow up was surprisingly higher – and statistically different – in the usual care than in the intervention group. It should be noted that three studies [27,34,46] randomised patients to intervention or usual care only after optimisation of ACE-I treatment, hence no further increase in ACE-I use might be expected. In other trials, patients allocated to usual care might have been prescribed ACE-I by their own physicians, aware of their participation in a HF management trial and their allocation to the control group. In this regard, it was not possible to analyse beta-adrenoceptor blocker use in a reliable way, as data were only available in three studies [20,37,42].

4.2. Heterogeneity and sensitivity analyses
A certain degree of heterogeneity was present in the main analyses, depending on the summary measure or the pooling method used. It was expected because of the various types of interventions examined, and was explored through sensitivity analyses according to a priori defined hypotheses (differences in study quality, intervention main characteristics, length of follow up, year of publication, etc.). A relevant component of the observed heterogeneity was identified in the study quality, as "high quality" trials formed a homogeneous group of studies, which appeared to be significantly and consistently associated with a reduction in all outcomes considered. This finding stresses the importance of assessing primary study quality when performing a meta-analysis.

Multidisciplinary programmes and interventions of medium duration (3–6 months) appeared to be more consistently associated with a beneficial effect on mortality and HF-related (re)hospitalisation rates than nurse-led interventions and short (less than 3 months) or long (more than 6 months) duration programmes.

Usual care (the comparator) was poorly defined and described, or not described at all, by most investigators. This represents a limitation of the studies included in our analysis, and may be a source of heterogeneity: usual care varied from simple referral to specialist follow up in academic centres. In the first case, any type of structured disease management programme would appear more effective in improving HF clinical outcomes; in the latter, it might be quite difficult to observe a difference, if any.

Residual heterogeneity, if present, was difficult to explain on clinical grounds, and might be due to the play of chance.

4.3. Strengths and limitations
The use of multiple data bases, without any language restriction, and the development of a specific search strategy allowed for a large number of citations to be retrieved. Contacts with experts provided the opportunity to include studies not otherwise located, helping minimise publication and other biases. The literature search was continuously updated while the review was in progress.

The presence of publication and other biases was assessed with funnel plots [13]. Empirical studies [13,55] have demonstrated funnel plot results are fairly consistent with those derived from various statistical tests. In our meta-analysis, the funnel plot constructed around the common effect estimate for all-cause mortality was quite symmetric, indicating the likely absence of publication bias.

Some authors have raised concerns that these management strategies, while aimed to improve HF clinical course, may impair the provision of other medical care and necessary medications [9]. We chose all-cause mortality and all-cause (re)hospitalisation rate as our primary outcomes for this very reason.

It was not possible to demonstrate whether DM programmes for HF were effective in all clinical settings, because most studies included were performed in academic, tertiary, or urban hospital centres. We were unable to obtain individual patient data, which could have allowed us to identify which type of HF patients may benefit mostly from these strategies, regardless of the degree of disease severity, the presence of multiple co-morbidities, and a previous history of frequent hospital re-admissions.

While preparing our manuscript for submission, another meta-analysis on the same topic has been published by McAlister et al. [56]. Our results are relatively similar, although their analysis was performed grouping studies according to four different types of intervention. We identified only two types of intervention, broadly categorised as "multidisciplinary" and "nurse-led" interventions, according to the definition provided by the primary investigators themselves in their published reports. We preferred to perform sensitivity analyses based on some objective criteria differentiating the various types of programmes, such as intervention duration, or length of follow up. Overall, similar results for the main outcomes of interest (mortality, all-cause and HF-related (re)hospitalisation rates) were observed across the various groups of studies so identified.


   5. Conclusions
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
 5. Conclusions
References
 
Comprehensive DM programmes for HF patients reduce mortality and hospitalisations, may improve quality of life, and are potentially cost-saving, in moderate to high risk populations.

Ongoing [57] and future trials assessing the relative effectiveness of different types of intervention will provide answers about which programmes to adopt in practice. The final choice will rest on a careful evaluation of the characteristics of the local health services, patient population, barriers to the access to optimal medical care, human and financial resources.


   Acknowledgements
 
Financial support: Dr. Catherine Demers is the recipient of an Ontario Ministry of Health and Long Term Care Career Scientist Award; Dr. Salim Yusuf is the recipient of an endowed Chair of the Heart and Stroke Foundation of Ontario and a Senior Scientist Award from the Canadian Institutes of Health Research.


   References
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
 5. Conclusions
 References
 

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