| has abstract
| - Learning health systems (LHS) are healthcare systems in which knowledge generation processes are embedded in daily practice to improve healthcare. At its most fundamental level, a learning health system applies a conceptual approach wherein science, informatics, incentives, and culture are aligned to support continuous improvement, innovation, and equity, and seamlessly embed knowledge and best practices into care delivery The idea was first conceptualized in a 2006 workshop organized by the US Institute of Medicine (now the National Academy of Medicine (NAM)), building on ideas around evidence-based medicine and "practice-based evidence". and around recognition of the persistent gap between evidence generated in the context of biomedical research and the application of that evidence in the provision of care. The need to close this gap was further underscored by the growth of electronic health records (EHR) and other innovations in health information technology and computational power, and the resulting ability to generate data that can lead to better evidence and better outcomes. There has since been increasing interest in the topic, including the creation of the Wiley journal Learning Health Systems. Cornerstone elements of the LHS include: 1.
* generation, application, and improvement of scientific knowledge; 2.
* an organizational infrastructure that supports the engagement of communities of patients, healthcare professionals and researchers who collaborate to identify evidence gaps that could be addressed through research in routine healthcare settings; 3.
* deployment of computational technologies and informatics approaches that organize and leverage large electronic health data sets, i.e. "big data" for use in research; 4.
* quality improvement at the point of care for each patient using new knowledge generated by research. Other compatible ways of describing the LHS co-exist alongside the NAM definition, including the definition used by AHRQ, the Agency for Healthcare Research and Quality. AHRQ defines a learning health system as "a health system in which internal data and experience are systematically integrated with external evidence, and that knowledge is put into practice. As a result, patients get higher quality, safer, more efficient care, and health care delivery organizations become better places to work.” HISTORYThe NAM’s early efforts to develop the ideas underpinning the LHS began in 2006, via a series of workshops held over several years from 2006-2013. Among several early publications to express the need for a rapid learning health system was a commentary in Health Affairs in 2007 where Lynn Etheredge applied the term “rapid learning health system” in recognition of the opportunity to leverage electronic health records (EHR) to “learn” what works in health care. The series of NAM workshops generated several summary publications on topics under the mantle of the LHS, including publications focused on the digital infrastructure as well as on ethical considerations. In 2013, the workshops culminated in a seminal report, “Best Care at Lower Cost: the Path to Continuously Learning Health Care in America.”. Summarizing the heretofore efforts, McGinnis and colleagues enumerate key milestones in the evolution of the LHS that include these reports as well as decades-old efforts to generate evidence from routine health care delivery. Nomenclature may vary in reference to the LHS concept. Some refer to a learning healthcare system, others refer to learning systems or collaborative learning health networks. The architecture and objectives are similar, irrespective of the label—addressing evidence gaps, harnessing data, and effectively utilizing the best evidence at the point of need. Related concepts include the use of real-world data to generate real-world evidence, and mobilizing computable biomedical knowledge. Given that the LHS has an expansive definition and scope, many of the early adopters of this approach were health systems that also had embedded research capabilities, such as a formal department or institute. The Veterans Administration Health System, Group Health Cooperative, Kaiser Permanente and Geisinger Health System were among the vanguard organizations who also published insights from their experience of launching formal learning health system activities. Increasingly, academic health systems have taken up the principles and practices espoused by the earliest adopters. A large proportion of LHS research relies on the use of electronic health records (EHRs) and must navigate the inherent challenges of EHRs. LHS entails a clinical lifecycle. Patient data is collected, it is amalgamated across multiple patients and a problem is defined. These are activities largely driven by healthcare professionals. With the support of technology, an analysis is performed, which returns evidence, from which knowledge is generated, which leads to changed clinical practice, and thus to new patient data being collected. McLachlan and colleagues (2018) suggest a taxonomy of nine LHS classification types: 1.
* Cohort identification looks for patients with similar attributes. 2.
* Positive deviance finds examples of better care against a benchmark. 3.
* Negative deviance finds examples of sub-optimal care. 4.
* Predictive patient risk modeling uses patterns in data to find groups at greater risk of adverse events. 5.
* Predictive care risk and outcome models identify situations that are at greater risk of poor care. 6.
* Clinical decision support systems use patient algorithms applied to patient data to make specific treatment recommendations. 7.
* Comparative effectiveness research determines the most effective treatments. 8.
* Intelligent assistance use data to automate routine processes. 9.
* Surveillance monitors data for disease outbreaks or other treatment issues. Next Generation of Learning Health Systems Researchers:The Agency for Healthcare Research and Quality (AHRQ) and the Patient-Centered Outcomes Research Institute (PCORI) have awarded $40 million in grants over 5 years to 11 institutions to support the training of clinician and research scientists to conduct patient-centered outcomes research within LHS. The LHS Centers of Excellence are: 1.
* A Chicago Center of Excellence in Learning Health Systems Research Training (ACCELERAT), Northwestern University, Chicago, Ill. 2.
* CATALyST: Consortium for Applied Training to Advance the Learning Health System with Scholars/Trainees, Kaiser Permanente Washington Research Institute, Seattle, WA. 3.
* Learning Health System Scholar Program at Vanderbilt, Vanderbilt University, Nashville, Tenn. 4.
* Leveraging Infrastructure to Train Investigators in Patient-Centered Outcomes Research in Learning Health System (LITI- PCORLHS), Indiana University School of Medicine, Indianapolis, Ind. 5.
* Minnesota Learning Health System Mentored Career Development Program (MN-LHS), University of Minnesota, Minneapolis, Minnesota. 6.
* Northwest Center of Excellence & K12 in Patient Centered Learning Health Systems Science, Oregon Health and Science University, Portland, Oregon. 7.
* PEDSnet Scholars: A Training Program for Pediatric Learning Health System Researchers, Children’s Hospital of Philadelphia, Philadelphia, PA 8.
* Stakeholder-Partnered Implementation Research and Innovation Translation (SPIRIT) program, University of California Los Angeles, Los Angeles, California. 9.
* The Center of Excellence in Promoting LHS Operations and Research at Einstein/Montefiore (EXPLORE), Albert Einstein College of Medicine, Bronx, N.Y. 10.
* Transforming the Generation and Adoption of PCOR into Practice (T-GAPP), University of Pennsylvania, Philadelphia, PA. 11.
* University of California-San Francisco Learning Health System K12 Career Development Program, University of California San Francisco, San Francisco, California. (en)
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