Effectiveness and efficiency of primary care based case management for chronic diseases: rationale and design of a systematic review and meta-analysis of randomized and non-randomized trials [CRD32009100316]

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Abstract

Background

Case management is an important component of structured and evidence-based primary care for chronically ill patients. Its effectiveness and efficiency has been evaluated in numerous clinical trials. This protocol describes aims and methods of a systematic review of research on the effectiveness and efficiency of case management in primary care.

Methods/Design

According to this protocol Medline, Embase, CINAHL, PsychInfo, the Cochrane Central Register of Controlled trials, DARE, NHS EED, Science Citation Index, The Royal College of Nursing Database, Dissertation Abstracts, registers of clinical trials and the reference lists of retrieved articles will be searched to identify reports on randomized and non-randomized controlled trials of case management interventions in a primary care setting without limitations on language or publication date. We will further ask experts in the field to avoid missing relevant evidence. Study inclusion and data extraction will be performed independently by two reviewers. After assessing risk of bias according to predefined standards, included studies will be described qualitatively. Subgroup analyses are planned for different chronic diseases and intervention strategies. If appropriate, a quantitative synthesis of data will be performed to provide conclusive evidence about the effectiveness and efficiency of primary care based case management in chronic care.

Review registration

Centre for Reviews and Dissemination (University of York): CRD32009100316.

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Most cited references 7

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Improving chronic illness care: translating evidence into action.

E Wagner, B. Austin, Jasmine Davis … (2015)

The growing number of persons suffering from major chronic illnesses face many obstacles in coping with their condition, not least of which is medical care that often does not meet their needs for effective clinical management, psychological support, and information. The primary reason for this may be the mismatch between their needs and care delivery systems largely designed for acute illness. Evidence of effective system changes that improve chronic care is mounting. We have tried to summarize this evidence in the Chronic Care Model (CCM) to guide quality improvement. In this paper we describe the CCM, its use in intensive quality improvement activities with more than 100 health care organizations, and insights gained in the process.

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Risk of bias versus quality assessment of randomised controlled trials: cross sectional study

Lisa Hartling, María Ospina, Yuanyuan Liang … (2009)

Objectives To evaluate the risk of bias tool, introduced by the Cochrane Collaboration for assessing the internal validity of randomised trials, for inter-rater agreement, concurrent validity compared with the Jadad scale and Schulz approach to allocation concealment, and the relation between risk of bias and effect estimates. Design Cross sectional study. Study sample 163 trials in children. Main outcome measures Inter-rater agreement between reviewers assessing trials using the risk of bias tool (weighted κ), time to apply the risk of bias tool compared with other approaches to quality assessment (paired t test), degree of correlation for overall risk compared with overall quality scores (Kendall’s τ statistic), and magnitude of effect estimates for studies classified as being at high, unclear, or low risk of bias (metaregression). Results Inter-rater agreement on individual domains of the risk of bias tool ranged from slight (κ=0.13) to substantial (κ=0.74). The mean time to complete the risk of bias tool was significantly longer than for the Jadad scale and Schulz approach, individually or combined (8.8 minutes (SD 2.2) per study v 2.0 (SD 0.8), P<0.001). There was low correlation between risk of bias overall compared with the Jadad scores (P=0.395) and Schulz approach (P=0.064). Effect sizes differed between studies assessed as being at high or unclear risk of bias (0.52) compared with those at low risk (0.23). Conclusions Inter-rater agreement varied across domains of the risk of bias tool. Generally, agreement was poorer for those items that required more judgment. There was low correlation between assessments of overall risk of bias and two common approaches to quality assessment: the Jadad scale and Schulz approach to allocation concealment. Overall risk of bias as assessed by the risk of bias tool differentiated effect estimates, with more conservative estimates for studies at low risk.

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A taxonomy for disease management: a scientific statement from the American Heart Association Disease Management Taxonomy Writing Group.

David Faxon, Barbara Riegel, Kevin Currie … (2006)

Disease management has shown great promise as a means of reorganizing chronic care and optimizing patient outcomes. Nevertheless, disease management programs are widely heterogeneous and lack a shared definition of disease management, which limits our ability to compare and evaluate different programs. To address this problem, the American Heart Association's Disease Management Taxonomy Writing Group developed a system of classification that can be used both to categorize and compare disease management programs and to inform efforts to identify specific factors associated with effectiveness. The AHA Writing Group began with a conceptual model of disease management and its components and subsequently validated this model over a wide range of disease management programs. A systematic MEDLINE search was performed on the terms heart failure, diabetes, and depression, together with disease management, case management, and care management. The search encompassed articles published in English between 1987 and 2005. We then selected studies that incorporated (1) interventions designed to improve outcomes and/or reduce medical resource utilization in patients with heart failure, diabetes, or depression and (2) clearly defined protocols with at least 2 prespecified components traditionally associated with disease management. We analyzed the study protocols and used qualitative research methods to develop a disease management taxonomy with our conceptual model as the organizing framework. The final taxonomy includes the following 8 domains: (1) Patient population is characterized by risk status, demographic profile, and level of comorbidity. (2) Intervention recipient describes the primary targets of disease management intervention and includes patients and caregivers, physicians and allied healthcare providers, and healthcare delivery systems. (3) Intervention content delineates individual components, such as patient education, medication management, peer support, or some form of postacute care, that are included in disease management. (4) Delivery personnel describes the network of healthcare providers involved in the delivery of disease management interventions, including nurses, case managers, physicians, pharmacists, case workers, dietitians, physical therapists, psychologists, and information systems specialists. (5) Method of communication identifies a broad range of disease management delivery systems that may include in-person visitation, audiovisual information packets, and some form of electronic or telecommunication technology. (6) Intensity and complexity distinguish between the frequency and duration of exposure, as well as the mix of program components, with respect to the target for disease management. (7) Environment defines the context in which disease management interventions are typically delivered and includes inpatient or hospital-affiliated outpatient programs, community or home-based programs, or some combination of these factors. (8) Clinical outcomes include traditional, frequently assessed primary and secondary outcomes, as well as patient-centered measures, such as adherence to medication, self-management, and caregiver burden. This statement presents a taxonomy for disease management that describes critical program attributes and allows for comparisons across interventions. Routine application of the taxonomy may facilitate better comparisons of structure, process, and outcome measures across a range of disease management programs and should promote uniformity in the design and conduct of studies that seek to validate disease management strategies.

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Author and article information

Journal

Journal ID (nlm-ta): BMC Health Serv Res

Title: BMC Health Services Research

Publisher: BioMed Central

ISSN (Electronic): 1472-6963

Publication date Collection: 2010

Publication date (Electronic): 7 May 2010

Volume: 10

Page: 112

Affiliations

[1 ]Competence Centre of General Practice, University Hospital Heidelberg, Department of General Practice and Health Services Research, Voßstrasse 2, 69115 Heidelberg, Germany

[2 ]Radboud University Nijmegen Medical Centre, Scientific Institute for Quality of Healthcare, P.O. Box 9101, 6500HB Nijmegen, Netherlands

Article

Publisher ID: 1472-6963-10-112

DOI: 10.1186/1472-6963-10-112

PMC ID: 2907755

PubMed ID: 20459654

SO-VID: ff86c808-3faa-4cfa-b003-4cee4eb1b28f

License:

This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Effectiveness and efficiency of primary care based case management for chronic diseases: rationale and design of a systematic review and meta-analysis of randomized and non-randomized trials [CRD32009100316]

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Abstract

Background

Methods/Design

Review registration

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International Journal of Applied Technology in Medical Sciences

Most cited references 7

Improving chronic illness care: translating evidence into action.

Risk of bias versus quality assessment of randomised controlled trials: cross sectional study

A taxonomy for disease management: a scientific statement from the American Heart Association Disease Management Taxonomy Writing Group.

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