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      Context, mechanisms and outcomes of integrated care for diabetes mellitus type 2: a systematic review

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          Abstract

          Background

          Integrated care interventions for chronic conditions can lead to improved outcomes, but it is not clear when and why this is the case. This study aims to answer the following two research questions: First, what are the context, mechanisms and outcomes of integrated care for people with type 2 diabetes? Second, what are the relationships between context, mechanisms and outcomes of integrated care for people with type 2 diabetes?

          Methods

          A systematic literature search was conducted for the period 2003–2013 in Cochrane and PubMed. Articles were included when they focussed on integrated care and type 2 diabetes, and concerned empirical research analysing the implementation of an intervention. Data extraction was performed using a common data extraction table. The quality of the studies was assessed with the Mixed Methods Appraisal Tool. The CMO model (context + mechanism = outcome) was used to study the relationship between context factors (described by the barriers and facilitators encountered in the implementation process and categorised at the six levels of the Implementation Model), mechanisms (defined as intervention types and described by their number of Chronic Care Model (sub-)components) and outcomes (the intentional and unintentional effects triggered by mechanism and context).

          Results

          Thirty-two studies met the inclusion criteria. Most reported barriers to the implementation process were found at the organisational context level and most facilitators at the social context level. Due to the low number of articles reporting comparable quantitative outcome measures or in-depth qualitative information, it was not possible to make statements about the relationship between context, mechanisms and outcomes.

          Conclusions

          Efficient resource allocation should entail increased investments at the organisational context level where most barriers are expected to occur. It is likely that investments at the social context level will also help to decrease the development of barriers at the organisational context level, especially by increasing staff involvement and satisfaction. If future research is to adequately inform practice and policy regarding the impact of these efforts on health outcomes, focus on the actual relationships between context, mechanisms and outcomes should be actively incorporated into study designs.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12913-015-1231-3) contains supplementary material, which is available to authorized users.

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          Most cited references45

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          Effects of quality improvement strategies for type 2 diabetes on glycemic control: a meta-regression analysis.

          Kaveh Shojania, Sumant R. Ranji, Kathryn McDonald … (2006)
          There have been numerous reports of interventions designed to improve the care of patients with diabetes, but the effectiveness of such interventions is unclear. To assess the impact on glycemic control of 11 distinct strategies for quality improvement (QI) in adults with type 2 diabetes. MEDLINE (1966-April 2006) and the Cochrane Collaboration's Effective Practice and Organisation of Care Group database, which covers multiple bibliographic databases. Eligible studies included randomized or quasi-randomized controlled trials and controlled before-after studies that evaluated a QI intervention targeting some aspect of clinician behavior or organizational change and reported changes in glycosylated hemoglobin (HbA1c) values. Postintervention difference in HbA1c values were estimated using a meta-regression model that included baseline glycemic control and other key intervention and study features as predictors. Fifty randomized controlled trials, 3 quasi-randomized trials, and 13 controlled before-after trials met all inclusion criteria. Across these 66 trials, interventions reduced HbA(1c) values by a mean of 0.42% (95% confidence interval [CI], 0.29%-0.54%) over a median of 13 months of follow-up. Trials with fewer patients than the median for all included trials reported significantly greater effects than did larger trials (0.61% vs 0.27%, P = .004), strongly suggesting publication bias. Trials with mean baseline HbA1c values of 8.0% or greater also reported significantly larger effects (0.54% vs 0.20%, P = .005). Adjusting for these effects, 2 of the 11 categories of QI strategies were associated with reductions in HbA(1c) values of at least 0.50%: team changes (0.67%; 95% CI, 0.43%-0.91%; n = 26 trials) and case management (0.52%; 95% CI, 0.31%-0.73%; n = 26 trials); these also represented the only 2 strategies conferring significant incremental reductions in HbA1c values. Interventions involving team changes reduced values by 0.33% more (95% CI, 0.12%-0.54%; P = .004) than those without this strategy, and those involving case management reduced values by 0.22% more (95% CI, 0.00%-0.44%; P = .04) than those without case management. Interventions in which nurse or pharmacist case managers could make medication adjustments without awaiting physician authorization reduced values by 0.80% (95% CI, 0.51%-1.10%), vs only 0.32% (95% CI, 0.14%-0.49%) for all other interventions (P = .002). Most QI strategies produced small to modest improvements in glycemic control. Team changes and case management showed more robust improvements, especially for interventions in which case managers could adjust medications without awaiting physician approval. Estimates of the effectiveness of other specific QI strategies may have been limited by difficulty in classifying complex interventions, insufficient numbers of studies, and publication bias.
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            The effectiveness of disease and case management for people with diabetes. A systematic review.

            S Norris, P. Nichols, C Caspersen … (2002)
            This report presents the results of a systematic review of the effectiveness and economic efficiency of disease management and case management for people with diabetes and forms the basis for recommendations by the Task Force on Community Preventive Services on the use of these two interventions. Evidence supports the effectiveness of disease management on glycemic control; on screening for diabetic retinopathy, foot lesions and peripheral neuropathy, and proteinuria; and on the monitoring of lipid concentrations. This evidence is applicable to adults with diabetes in managed care organizations and community clinics in the United States and Europe. Case management is effective in improving both glycemic control and provider monitoring of glycemic control. This evidence is applicable primarily in the U.S. managed care setting for adults with type 2 diabetes. Case management is effective both when delivered in conjunction with disease management and when delivered with one or more additional educational, reminder, or support interventions.
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              Effectiveness of disease-management programs for improving diabetes care: a meta-analysis.

              Rodolphe Thiébaut, C Pimouguet, Catherine Helmer … (2011)
              We conducted a meta-analysis of randomized controlled trials to assess the effectiveness of disease-management programs for improving glycemic control in adults with diabetes mellitus and to study which components of programs are associated with their effectiveness. We searched several databases for studies published up to December 2009. We included randomized controlled trials involving adults with type 1 or 2 diabetes that evaluated the effect of disease-management programs on glycated hemoglobin (hemoglobin A₁(C)) concentrations. We performed a meta-regression analysis to determine the effective components of the programs. We included 41 randomized controlled trials in our review. Across these trials, disease-management programs resulted in a significant reduction in hemoglobin A₁(C) levels (pooled standardized mean difference between intervention and control groups -0.38 [95% confidence interval -0.47 to -0.29], which corresponds to an absolute mean difference of 0.51%). The finding was robust in the sensitivity analyses based on quality assessment. Programs in which the disease manager was able to start or modify treatment with or without prior approval from the primary care physician resulted in a greater improvement in hemoglobin A₁(C) levels (standardized mean difference -0.60 v. -0.28 in trials with no approval to do so; p < 0.001). Programs with a moderate or high frequency of contact reported a significant reduction in hemoglobin A₁(C) levels compared with usual care; nevertheless, only programs with a high frequency of contact led to a significantly greater reduction compared with low-frequency contact programs (standardized mean difference -0.56 v. -0.30, p = 0.03). Disease-management programs had a clinically moderate but significant impact on hemoglobin A₁(C) levels among adults with diabetes. Effective components of programs were a high frequency of patient contact and the ability for disease managers to adjust treatment with or without prior physician approval.
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                Author and article information

                Contributors
                Loraine Busetto: 0031-134664160 , l.busetto@tilburguniversity.edu
                Katrien Ger Luijkx: k.g.luijkx@tilburguniversity.edu
                Arianne Mathilda Josephus Elissen: a.elissen@maastrichtuniversity.nl
                Hubertus Johannes Maria Vrijhoef: h.j.m.vrijhoef@tilburguniversity.edu
                Journal
                Journal ID (nlm-ta): BMC Health Serv Res
                Journal ID (iso-abbrev): BMC Health Serv Res
                Title: BMC Health Services Research
                Publisher: BioMed Central (London )
                ISSN (Electronic): 1472-6963
                Publication date (Electronic): 15 January 2016
                Publication date PMC-release: 15 January 2016
                Publication date Collection: 2015
                Volume: 16
                Electronic Location Identifier: 18
                Affiliations
                [ ]Department of TRANZO, Faculty of Social and Behavioural Sciences, Tilburg University, PO Box 90153, 5000 LE Tilburg, The Netherlands
                [ ]Department of Health Services Research, CAPHRI School for Public Health and Primary Care, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands
                [ ]Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
                Article
                Publisher ID: 1231
                DOI: 10.1186/s12913-015-1231-3
                PMC ID: 4715325
                PubMed ID: 26772769
                SO-VID: 9d61d059-836a-43fd-a6aa-3efce71ed004
                Copyright © © Busetto et al. 2016
                License:

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                Date received : 13 January 2015
                Date accepted : 11 December 2015
                Categories
                Subject: Research Article
                Custom metadata
                issue-copyright-statement © The Author(s) 2016

                ScienceOpen disciplines: Health & Social care
                Keywords: integrated care,chronic care model,cmo model,implementation model,diabetes type 2,chronic conditions
                Data availability:
                ScienceOpen disciplines: Health & Social care
                Keywords: integrated care, chronic care model, cmo model, implementation model, diabetes type 2, chronic conditions

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