A practical model for research with learning health systems: Building and implementing effective complex case management
Introduction
In the United States, health systems are groups of hospital and physician providers that organize around the delivery of healthcare services. While the structure of these health systems varies widely across the country, in the face of widespread challenges of rising costs and rapid changes in care delivery, health systems of all types have begun focusing on the triple aim to improve the value of healthcare, the health of populations, and the experience of the individual patient (Berwick et al., 2008). To achieve these goals requires transformative actions to rapidly generate and apply knowledge—in essence, a “rapid-learning health system” (Etheredge, 2007). Learning health systems depend on accessing and applying evidence from research while simultaneously learning from their own care delivery processes. The value of co-producing research in supporting a learning health system has been articulated (Greene et al., 2012), but there has been limited success in embedding researchers into health systems (Reid, 2016).
There are multiple useful frameworks conceptualizing a learning health system, but each framework has used a different perspective and these frameworks typically lack practical tools to guide research with learning health systems. For example, the Institute of Medicine (IOM) has identified a series of foundational elements for achieving a learning health system including a digital infrastructure, data utility, and a supportive policy environment, along with key care improvement targets (Smith et al., 2013). The Veterans Health Administration refined the IOM foundational elements based on a dynamic sustainability framework that focuses on testing interventions in real-world settings (Atkins et al., 2017). Greene et al. described learning health system activities at Group Health Cooperative using a six-phase model that encompassed scanning, design, implementation, evaluation, adjustment, and dissemination, with supporting roles for research at each phase (Greene et al., 2012). Psek et al. extended Greene's model to learning at the institutional level at Geisinger, adopting an operational perspective rather than a research perspective (Psek et al., 2015). These models provide highly valuable framing of work with learning health systems, but are limited in identifying the specific steps to incorporate research as a co-equal partner in achieving health system learning.
For researchers to contribute meaningfully to the creation of learning health systems, practical tools are required to operationalize existing conceptual frameworks. We describe a model currently in use by the University of Wisconsin (UW) Health Innovation Program (HIP). The HIP model expands beyond Greene's concept of research in a supporting role to the health system (Greene et al., 2012) to conceptualize research as a co-equal partner (Sibbald et al., 2014). The concept of a co-equal partner builds on Ovretveit's research-practice partnerships, which are defined by the intent to produce actionable findings, involvement of researchers and practitioners in defining questions and interpreting findings, and significant amounts of time or other contributions from both researchers and practitioners (Ovretveit et al., 2014). The HIP model adds the concept of sustainable change based on research conducted within the health system as a key component of research with learning health systems. This focus on health system learning and sustainable change distinguish the model from those focused primarily on research production (Martin, 2010). Because sustainable change often requires health system redesign, it highlights the importance of collaboration with human factors and systems engineering, recognizing the important role of IT, systems engineering tools, and related organizational innovations (Reid et al., 2005). The HIP model consolidates and enhances existing learning health system frameworks by defining specific practical steps needed to create sustainable change based on research conducted within the health system. As an example of the model's application, we describe the use of the model to improve patient identification for the UW health system's (UW Health) case management program.
Section snippets
Conceptual model
Launched in 2006, HIP has more than a decade of experience integrating research into clinical practice. In partnership with UW Health and UW faculty, HIP developed an approach to operationalizing the learning health system that links externally-funded research projects to health system change. Based on priorities identified by the health system, HIP identifies researchers interested in relevant topics and then facilitates communication with the health system to design and implement projects
Case study
As an example of the model's application, we describe the use of the HIP model to improve patient identification, increase program effectiveness, and achieve cost savings for the UW Health case management program.
Discussion
We have developed a model for researchers to contribute meaningfully to the creation of learning health systems, including practical tools to operationalize key concepts. Our model focuses on the specific steps needed to support a research partnership with a learning health system. Our case study shows the importance of culture, infrastructure, and strong leadership support in realizing this vision for any given project. Through development of an infrastructure and process to support learning
Declaration of competing interest
None.
Acknowledgements
Funding/Support
Research reported in this article was partially funded through two Patient-Centered Outcomes Research Institute (PCORI) Awards (HSD-1603-35039; Principal Investigator: Maureen A. Smith and ME-1409-21219; Principal Investigator: Menggang Yu). The views in this publication are solely the responsibility of the authors and do not necessarily represent the views of the PCORI, its Board of Governors or Methodology Committee. This project was also supported by the UW Health Innovation
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