Our meta-analysis suggests that disease-management programs have a favourable effect on improving glycemic control, with a pooled standardized mean reduction of 0.38 (corresponding to a pooled absolute mean reduction of 0.51%) in hemoglobin A1C
levels compared with usual care. This finding was robust in sensitivity analyses based on quality assessment. The United Kingdom Prospective Diabetes Study showed that each 1% reduction in hemoglobin A1C
level was associated with a 37% decrease in the risk of microvascular complications and a 21% decrease in the risk of death related to diabetes, with no evidence of a threshold.63
Therefore, the absolute reduction of 0.51% in hemoglobin A1C
level in our study appears to be clinically significant. Moreover, this finding is probably largely underestimated, because the usual care provided in control groups in RCTs is often better than that provided in clinical practice. Indeed, there was a significant standardized mean reduction in hemoglobin A1C
levels of −0.25 in the control groups, which corresponds to an absolute mean reduction of 0.40%. Some studies included in our meta-analysis permitted patients in the control group to contact the medical team or be contacted by them during follow-up in addition to usual care.23,43,55
Also, patients received structured individual education before randomization in some trials.21,23
Our findings suggest that disease-management programs are more effective for patients who have poor glycemic control (mean hemoglobin A1C
≥ 8.0% at baseline) than for those with better glycemic control. This is concordant with results among patients starting insulin therapy.64
Thus, disease management could be particularly effective if targeted at patients with nonstabilized diabetes. Moreover, such patients have a higher risk of complications and so would probably derive greater long-term benefit from disease management.
We found that the ability of disease managers to start or modify medical treatment was an effective feature of disease-management programs. This confirms the findings of Shojania and colleagues, who evaluated the ability to adjust treatment without prior physician agreement.7
However, we found that the ability to adjust treatment was an effective feature both with and without prior physician agreement, which is more relevant for physicians, nurses and pharmacists in clinical practice. This has important implications, because nonadherence to medical treatment is a significant predictor of all-cause mortality and hospital admission among patients with diabetes.65
Despite its relevance for clinicians and policy-makers, the intensity of disease-management programs has not been investigated in previous reviews. Program intensity depends on the frequency of patient contacts, their duration and the length of the program. Because the duration of contact was not reported in most of the studies included in our review, we were not able to explore it. However, we explored frequency of contact and length of intervention. We did not find any significant difference associated with length of intervention, despite a nonsignificant improvement observed with shorter interventions. Frequency of contact proved to be a key feature of the effectiveness of disease-management programs. There was substantial discrepancy in frequency across trials, ranging from “counseling by telephone every week if necessary”22
to “at least five visits by the nurse within a study period of one year.”41
For our analysis, frequency of contact was estimated on the basis of the intervention protocol reported and, when available, the results. Although the reported intervention protocol probably overestimated the real frequency of contact, frequency was evaluated on the basis of results in 12 studies and was consequently found to be an effective measure. Our findings are consistent with those from a recent large controlled trial, although it showed a nonsignificant trend toward better glycemic control with more intensive intervention.20
The greater effectiveness associated with a high frequency of patient contact suggests that only disease-management programs with intensive interventions should be implemented, perhaps by targeting patients at high risk of diabetes complications.
Patient education is the cornerstone of diabetes care. An overall beneficial effect of education among patients with diabetes has already been shown in several studies.66,67
We did not find any difference in effectiveness between individual education and a combination of individual and group education. This finding suggests that a combination of group and individual education could be a solution to cope with the lack of medical providers and the time-consuming aspect of individual education. Surprisingly, neither the mode of contact nor feedback of the initial evaluation to the primary care physician were discriminatory components. However, we cannot rule out the possibility of incorrect classification of feedback as a program component, because it was taken for granted that such feedback would be provided systematically, so this step was not stipulated formally in the protocol.
Strengths and limitations
The strengths of the study include a comprehensive systematic review of the literature, with a large number of studies included. We used a broad search strategy to capture all relevant information. Our work confirms the findings of previous reviews, with a mean difference in hemoglobin A1C
level similar to that observed in previous studies.7,8,68,69
However, we included only RCTs and several more recent studies, with thus a larger sample size. Therefore, our estimate is probably more precise than that in previous studies.
Our study has limitations. Our analyses were based on results from randomized controlled trials, and adjustment was not done at an individual patient level. By including only studies published in English, we may have missed other relevant studies. The weak description of the intervention strategy in most studies precluded the analysis of some potentially relevant components. Notably, we were unable to study the effect of the degree of the primary care physician’s involvement in these programs, which is an essential aspect for implementation. For some components, such as frequency of patient contact, we contacted the authors for more details. However, because some trials were performed several years ago, no supplementary information was available. Another limitation was the short follow-up in many of the trials, even though we excluded trials with less than 12 weeks of follow-up. Because only five trials continued for more than 12 months, we were unable to capture the long-term effects of disease-management programs. However, outcomes such as long-term diabetes complications, especially vascular complications, have not yet been examined in studies of disease management for improved diabetes care. In some trials, the length of the intervention was very short (less than six months in six trials) and thus may have been too short to produce any clinical benefits.
We noted heterogeneity in the overall effect estimate and performed a meta-regression analysis to determine potential sources. The two components of disease-management programs that led to significantly greater improvements in glycemic control accounted for 6.1% (frequency of contact) and 39.2% (treatment adjustment) of the variance between studies. We did not identify all sources of variance among trials, but a meta-analysis of summary data from reported studies has little capacity to do so.
Although a recurrent problem in meta-analyses is publication bias, application of asymmetry tests seemed inappropriate owing to the presence of heterogeneity.70
A previous meta-analysis reported a larger effect estimate for small studies.7
Because a higher intensity of intervention appears to be an important feature underpinning the efficacy of disease-management programs, this “size trial effect” could be due to a higher intensity of intervention in small studies. Indeed, of the 16 studies with a high frequency of patient contact in our analysis, 11 (69%) were relatively small, with samples smaller than the median for the studies included (117 patients). This more intensive intervention in small studies, rather than publication bias, could explain the greater improvement in glycemic control.
Disease-management programs had a clinically moderate but significant impact on hemoglobin A1C levels among adults with diabetes. Effective components of the programs were a high frequency of patient contact and the ability for disease managers to adjust treatment with or without prior physician approval. Our findings have important implications for both the current policy on the delivery of diabetes care and the direction of future research. Our work delineates a general framework with core features for effective programs for disease management. Priority should be given to programs with intensive and proactive follow-up that target patients at high risk of diabetes complications rather than to programs with low frequency of contact that target the overall population of patients with diabetes. In addition, disease managers should be allowed to start or modify medical treatment proactively.
More research is needed concerning the long-term impact of disease-management programs on glycemic control, microvascular and macrovascular complications, admission to hospital and mortality. Further research should also determine whether, in addition to patients with nonstabilized diabetes, other groups of patients with diabetes would benefit from disease management. Lastly, high-quality cost-effectiveness studies of disease-management programs are needed to direct care providers and policy-makers in the allocation of health care resources.