A secondary analysis of the moderating effects of depression and multimorbidity on the effectiveness of a chronic disease self-management programme

Abstract

Objective

Patients accessing the chronic disease self-management programme (CDSMP) often report multiple long-term conditions (multimorbidity). Although multimorbidity often predicts poor outcomes, CDSMP effectiveness may be enhanced in multimorbidity via synergies between self-management for different conditions. This study assessed whether CDSMP benefits varied by patterns of multimorbidity.

Methods

The study was based on a secondary analysis of an RCT. Patients with long-term conditions (n = 629) were randomised to CDSMP or wait-list and completed baseline and 6 month assessments. We identified four multimorbidity groups: (1) single physical condition; (2) multiple physical conditions; (3) single physical condition plus ‘probable depression’; (4) multiple physical conditions plus ‘probable depression’.

Results

Multimorbidity group significantly moderated the effect of CDSMP on vitality, health-related quality of life, and mental well-being, with the greatest benefit found for patients with multiple physical conditions plus ‘probable depression’.

Conclusion

The coexistence of depression and multiple physical conditions is associated with increased illness burden, but such patients benefit more from the CDSMP. The mechanisms underlying this effect are unclear, but it does not appear to be through self-management or self-efficacy.

Practice implications

The presence of multimorbidity in combination with depression may be a useful criteria for referral to the CDSMP.

Introduction

An ageing population and improvements in health care means that the global burden of disease is shifting to long-term conditions [1], and there is increasing interest in improving health by changing patient behaviour through self-management support [2]. Partly this derives from concerns about the costs of health care utilisation, and partly from data suggesting that self-management is a core driver of improved outcomes in long-term conditions [3]. In the United Kingdom, self-management is defined as:

‘the care taken by individuals towards their own health and well being: it comprises the actions they take to lead a healthy lifestyle; to meet their social, emotional and psychological needs; to care for their long-term condition; and to prevent further illness or accidents’ [4]

Group-based interventions such as the chronic disease self-management programme (CDSMP) are a key source of self-management support [5], [6], [7]. These interventions are designed to teach a range of self-management skills and techniques, and to enhance patient self-efficacy in the management of long-term conditions and their functional and emotional sequelae. The CDSMP can be used with patients with a variety of conditions. Secondary analyses have identified patient characteristics that predict benefit (i.e. moderators of treatment effect) [8], [9]. Our recent analysis found that patients reporting lower baseline self-efficacy and quality of life demonstrated more positive health outcomes following the CDSMP [10].

Many patients seeking support for self-management have more than one condition (so-called multimorbidity) [11] and this is associated with poor outcomes [12], [13]. However, key questions about the impact of multimorbidity remain.

First, what is the mechanism? There are a variety of plausible theories of the mechanisms that might cause patients with multimorbidity to have poor outcomes, including biological interactions between disorders [14], [15], but self-management remains a potential candidate. Patients with multimorbidity have to deal with multiple self-management activities with limited resources of energy, time, attention and motivation [16], [17] and potentially face complex decisions about priorities among self-management tasks [18], [19]. This may reduce their ability to conduct effective self-management and lead to poor outcomes.

The second key question concerns the types of multimorbidity and the combinations of conditions that are particularly associated with poor outcomes. For many long-term conditions (such as diabetes and coronary heart disease), there are potential synergies, where several conditions benefit from the same self-management (e.g. exercise). A recent study found that patients with multimorbidity who took part in a disease management programme reported significant improvements [20]. However, depression is a common disorder which is often co-morbid with long-term conditions such as diabetes [21]. The co-existence of depression and diabetes may lead to underregulation of diabetes (i.e. where depression lowers patient self-efficacy to undertake self-management) or mis-regulation (i.e. where improvements in depression lead to changes in diet which in turn have a negative effect on diabetes management) [22]. However, even here the evidence is unclear. Although depression is often associated with reduced self-management in observational studies [23], patients with long-term conditions who report comorbid depression have been reported as demonstrating greater benefits after attending the CDSMP [24].

At present, the mechanisms by which multimorbidity impacts on patient outcomes are unclear. We have previously demonstrated that patients with high baseline levels of illness severity are more likely to report favourable outcomes from the CDSMP [10]. However, in this previous study, severity was assessed through specific research assessments and not through routine data. Therefore, this finding is less useful in everyday practice, because such severity data are not routinely collected, and practitioners would not be able to access such information easily to inform their clinical decision making. This new analysis extends our previous work by identifying whether assessments of multimorbidity based on numbers of conditions are predictive of patient benefit in the CDSMP in the same way as research assessments of severity. Data on number of conditions are routinely available in practice, and thus the present analysis will determine whether measures of multimorbidity provide a more clinically useful and practical aid to clinical decision making about referral to CDSMP.

In summary, we used secondary analysis of data from our published CDSMP trial to test whether multimorbidity moderated outcomes from the CDSMP, to determine whether multimorbidity predicted level of benefit from the course and could be used in routine clinical decision making about referral to the CDSMP.