Evidence map›Paper›PMID 23938600›Full record

SynthesisMedical care2013

Collaborative chronic care models for mental health conditions: cumulative meta-analysis and metaregression to guide future research and implementation.

Christopher J Miller, Andrew Grogan-Kaylor, Brian E Perron, Amy M Kilbourne, Emily Woltmann, Mark S Bauer

Registry-linked trialOpen access · greenAbstract readMeta-Analysis
In one paragraph

Synthesis in Medical care, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02543840 (Hybrid Controlled Trial to Implement Collaborative Care in General Mental Health), which is not on this map. Cited by 68 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
68citing papers in PubMed, 3 pooled it
3.3field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT02543840 nacompletednot on this mapstarted 2016, after this paper: background citation

Hybrid Controlled Trial to Implement Collaborative Care in General Mental Health

TypeinterventionalSponsorVA Boston Healthcare SystemRan2016 to 2018Enrolled1,112ConditionsMental Health DisordersArmsReplicating Effective Programs plus External Facilitation, Educational Materials
3 · Its place in the literature

Who cites it

68 citing papers in PubMed, 3 syntheses or guidelines pooled it, 132 citations in OpenAlex.

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  6. Matching depression management to severity prognosis in primary care: results of the Target-D randomised controlled trial.The British journal of general practice : the journal of the Royal College of General Practitioners · 2021
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8 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 4 institutions in 1 country.

Christopher J Miller*Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System †Department of Psychiatry, Harvard Medical School, Boston, MA ‡School of Social Work, University of Michigan §VA Ann Arbor Center for Clinical Management Research ∥Department of Psychiatry, University of Michigan Medical School, Ann Arbor, MI ¶The Brown School, Washington University, St Louis, MO.
Andrew Grogan-Kaylor
Brian E Perron
Amy M Kilbourne
Emily Woltmann
Mark S Bauer
University of Michigan–Ann Arbor · USVA Boston Healthcare System · USVA Center for Clinical Management Research · USWashington University in St. Louis · US

Funding

Implementing Chronic Care Management for Bipolar DisorderR01MH079994 · NIMH · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI KILBOURNE, AMY M · 2008 to 2012
$3.3M
NIMH NIH HHS R01 MH079994
6 · The paper itself

Abstract

objectivePrior meta-analysis indicates that collaborative chronic care models (CCMs) improve mental and physical health outcomes for individuals with mental disorders. This study aimed to investigate the stability of evidence over time and identify patient and intervention factors associated with CCM effects to facilitate implementation and sustainability of CCMs in clinical practice.

methodsWe reviewed 53 CCM trials that analyzed depression, mental quality of life (QOL), or physical QOL outcomes. Cumulative meta-analysis and metaregression were supplemented by descriptive investigations across and within trials.

resultsMost trials targeted depression in the primary care setting, and cumulative meta-analysis indicated that effect sizes favoring CCM quickly achieved significance for depression outcomes, and more recently achieved significance for mental and physical QOL. Four of 6 CCM elements (patient self-management support, clinical information systems, system redesign, and provider decision support) were common among reviewed trials, whereas 2 elements (health care organization support and linkages to community resources) were rare. No single CCM element was statistically associated with the success of the model. Similarly, metaregression did not identify specific factors associated with CCM effectiveness. Nonetheless, results within individual trials suggest that increased illness severity predicts CCM outcomes.

conclusionsSignificant CCM trials have been derived primarily from 4 original CCM elements. Nonetheless, implementing and sustaining this established model will require health care organization support. Although CCMs have typically been tested as population-based interventions, evidence supports stepped care application to more severely ill individuals. Future priorities include developing implementation strategies to support adoption and sustainability of the model in clinical settings while maximizing fit of this multicomponent framework to local contextual factors.

Indexed as

Models, OrganizationalBehavioral ResearchChronic DiseaseComparative Effectiveness ResearchCooperative BehaviorFemaleForecastingHumansMaleMental DisordersMental Health ServicesRegression Analysis

Identifiers

PMID23938600
PMCPMC3800198
OpenAlexW1980234429

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.