Understanding the Components of Quality Improvement Collaboratives: A Systematic Literature Review
Open accessAbstract
Context: In response to national efforts to improve quality of care, policymakers and health care leaders have increasingly turned to quality improvement collaboratives (QICs) as an efficient approach to improving provider practices and patient outcomes through the dissemination of evidence‐based practices. This article presents findings from a systematic review of the literature on QICs, focusing on the identification of common components of QICs in health care and exploring, when possible, relations between QIC components and outcomes at the patient or provider level. Methods: A systematic search of five major health care databases generated 294 unique articles, twenty‐four of which met our criteria for inclusion in our final analysis. These articles pertained to either randomized controlled trials or quasi‐experimental studies with comparison groups, and they reported the findings from twenty different studies of QICs in health care. We coded the articles to identify the components reported for each collaborative. Findings: We found fourteen crosscutting components as common ingredients in health care QICs (e.g., in‐person learning sessions, phone meetings, data reporting, leadership involvement, and training in QI methods). The collaboratives reported included, on average, six to seven of these components. The most common were in‐person learning sessions, plan‐do‐study‐act (PDSA) cycles, multidisciplinary QI teams, and data collection for QI. The outcomes data from these studies indicate the greatest impact of QICs at the provider level; patient‐level findings were less robust. Conclusions: Reporting on specific components of the collaborative was imprecise across articles, rendering it impossible to identify active QIC ingredients linked to improved care. Although QICs appear to have some promise in improving the process of care, there is great need for further controlled research examining the core components of these collaboratives related to patient‐ and provider‐level outcomes.
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Active research agendas have focused on determining the essential components of many discrete implementation strategies such as audit and feedback, learning collaboratives, and supervision.
“In fact, active research agendas have focused on determining the essential components of many of these “discrete” implementation strategies, such as audit and feedback [44], learning collaboratives [45], and supervision [46].”
From A refined compilation of implementation strategies: results from the Expert Recommendations for Implementing Change (ERIC) project (2015) · cites this paper as [45]
Nadeem et al.'s review of learning collaboratives concluded that reporting on specific components of the collaborative was imprecise across articles, rendering it impossible to identify active quality improvement collaborative ingredients linked to improved care.
“For example, Nadeem et al. (95) review of learning collaboratives concluded that, “reporting on specific components of the collaborative was imprecise across articles, rendering it impossible to identify active quality improvement collaborative ingredients linked to improved care.””
From Enhancing the Impact of Implementation Strategies in Healthcare: A Research Agenda (2019) · cites this paper as [95]
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- Authors
- NADEEM, E., OLIN, S. S., HILL, L. C., HOAGWOOD, K. E., & HORWITZ, S. M.
- Affiliations
- New York University (US)
- New York University
- Columbia University (US)
- Corresponding author
- NADEEM, ERUM
- Venue
- The Milbank Quarterly
- Publisher
- Wiley
- Published
- 2013-06
- Volume
- 91
- Issue
- 2
- Pages
- 354-394
- ISSN
- 0887-378X (ISSN-L)
- 1468-0009
- PMC
- PMC3696201
- OpenAlex
- W2169510653
- Cited by
- 332
- References
- 73
- Citations by year
- 2026: 12 · 2025: 10 · 2024: 27 · 2023: 36 · 2022: 27 · 2021: 25 · 2020: 25 · 2019: 32 · 2018: 26 · 2017: 29 · 2016: 33 · 2015: 28 · 2014: 19 · 2013: 3
- FWCI
- 4.65
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Milbank Quarterly (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health
- National Institute of Mental Health (K01MH083694, P30MH090322)
- Topics
- Health Sciences › Health Professions › Health Information Management › Healthcare Quality and Management
- Health Sciences › Health Professions › General Health Professions › Health Policy Implementation Science
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Clinical practice guidelines implementation
- Keywords
- quality improvement collaborative, quality improvement, evidence-based practice dissemination, PDSA cycle, leadership engagement, process of care
- MeSH terms
- Cooperative Behavior, Humans, Quality of Health Care, Outcome Assessment, Health Care, Quality Improvement
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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