Participation in quality improvement (QI) collaboratives has helped hospitals improve outcomes and decrease costs.1,2 As such, state-level surgical QI collaboratives have become increasingly common. However, the optimal design of an effective collaborative and its key drivers of success remain unclear. Our objective was to create a conceptual model of a surgical QI collaborative to facilitate the development, implementation, and systematic evaluation of the Illinois Surgical Quality Improvement Collaborative (ISQIC).
A multidisciplinary, multi-institutional team of ISQIC researchers conducted a literature review and expanded and adapted key components of existing models of health care QI to create a conceptual model for a surgical QI collaborative.3,4 Feedback from QI leaders, hospital administrators, clinical frontline staff, and quality researchers guided the evolution of the model through multiple iterations until final consensus was reached. Institutional review board approval was not required, as this research did not involve human participants.
The conceptual model’s foundation consists of surgical QI needs that stimulate system and process changes that, in turn, result in improved outcomes. The model is cyclical to account for the iterative nature of the system and process changes made in response to QI needs. Surgical QI collaboratives can facilitate QI through initiatives that support 3 key levels of surgical QI: the hospital, the QI team, and the perioperative microsystem (eg, operating room and inpatient unit). Interrelated domains contain the key components of surgical QI that may benefit from collaborative support (Figure).
At the hospital level, institutional leadership, QI support and capacity, QI characteristics, and hospital culture are essential for success. At the QI team level, the dynamics, attributes, and composition of the team are paramount. Last, within the perioperative microsystem level, environment, culture, and staff leadership are similarly fundamental to QI success. Components of each domain and examples of collaborative support are provided in the Table.
This conceptual model provides a formal framework for the development and systematic evaluation of surgical QI collaboratives. Previous QI collaboratives have had success in improving quality, yet the mechanisms underlying this success remain unclear. Surgical QI is complex with many interrelated components and processes, impeding assessment of individual collaborative support mechanisms. By depicting the key drivers of surgical QI and their interrelatedness, this model provides a framework for collaborative QI that facilitates the generation, implementation, and evaluation of collaborative interventions.
Conceptual models of health care QI have been previously described, but most models do not integrate QI collaborative influence on institutional drivers of success.3,5,6 Although this model was created explicitly for ISQIC, the underlying components and relationships can be applied to other QI collaboratives. As a result, this model may serve as a valuable tool for implementing and evaluating interventions in new or well-established collaboratives.
Of note, this model is adapted from existing models for health care QI, with modifications made by consensus expert opinion.3,4 Given the paucity of data regarding the interactions between QI collaboratives and institutional QI, the individual components and relationships of this conceptual model are still in need of validation. Additionally, this model may fail to capture all inherent complexities of surgical QI at diverse hospitals. However, this model can provide an organized conceptual framework that facilitates the systematic evaluation of QI collaborative interventions.
The success of QI collaboratives is contingent on the ability to facilitate QI within hospitals beyond what could be accomplished in the absence of collaborative support. It is imperative for QI collaboratives to evaluate the efficacy of each component to prevent resources from being allocated to ineffective support mechanisms. This conceptual model has facilitated the ongoing evaluation of ISQIC and can be similarly used by others. Such evaluations can provide valuable insight into the mechanisms underlying successful collaborative QI and help to optimize the efficacy of QI collaboratives in health care.
Corresponding Author: Karl Y. Bilimoria, MD, MS, Surgical Outcomes and Quality Improvement Center, Department of Surgery and Center for Healthcare Studies, Feinberg School of Medicine, Northwestern University, 633 N St Clair, 20th Floor, Chicago, IL 60611 (k-bilimoria@northwestern.edu).
Published Online: September 7, 2016. doi:10.1001/jamasurg.2016.2817
Author Contributions: Drs Wandling and Minami had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Concept and design: All Authors.
Acquisition, analysis, or interpretation of data: Wandling, Minami, Holl, Bilimoria.
Drafting of the manuscript: Wandling, Minami, Holl.
Critical revision of the manuscript for important intellectual content: All Authors.
Statistical analysis: Wandling.
Obtaining funding: Bilimoria.
Administrative, technical, or material support: Wandling, Minami, Yang, Holl.
Study supervision: O'Leary, Yang, Holl, Bilimoria.
No additional contributions: Johnson.
Conflict of Interest Disclosures: None reported.
Funding/Support: This research was supported by Blue Cross Blue Shield of Illinois, Health Care Service Corp, and grant R01HS024516-01 from the Agency for Healthcare Research and Quality (principal investigator: Dr Bilimoria). Dr Wandling was supported by grant 1F32GM113513-01 from the National Institute of General Medical Sciences of the National Institutes of Health (principal investigator: Dr Wandling), and Dr Minami was supported by grant T-32 HS 000078 from the Agency for Healthcare Research and Quality (principal investigator: Dr Holl).
Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
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