Funding Learning Health System Research: Challenges and Strategies.

PURPOSE: A growing number of health systems are establishing learning health system (LHS) programs, where research focuses on rapidly improving the health system's internal operations and performance. The authors examine funding challenges facing such initiatives and identify strategies for managing tensions between reliance on external research funding and directly contributing to improvement and learning within the researchers' own system. METHOD: Qualitative case studies of LHS research programs in 5 health systems were performed via 38 semistructured interviews (October 2019-April 2021) with 35 diverse respondents. Inductive and deductive rapid qualitative analysis supported interview, system-level, and cross-system summaries and analysis. RESULTS: External funding awards to LHS researchers facilitated some internal improvement and learning, scientific advancements, and the reputation of researchers and their systems, but reliance on external funding also challenged researchers' responsiveness to concerns of system leaders, managers, practitioners, and system needs. Gaps between external funding requirements and internally focused projects arose in objectives, practical applicability, audiences, timetables, routines, skill sets, and researchers' careers. To contribute more directly to system improvement, LHS researchers needed to collaborate with clinicians and other nonresearchers and pivot between long research studies and shorter, dynamic improvement, evaluation, and data analysis projects. With support from system executives, LHS program leaders employed several strategies to enhance researchers' internal contributions. They aligned funded-research topics with long-term system needs, obtained internal funding for implementing and sustaining practice change, and diversified funding sources. CONCLUSIONS: To foster LHS research contributions to internal system learning and improvement, LHS program leaders need to manage tensions between concentrating on externally funded research and fulfilling their mission of providing research-based services to their own system. Health system executives can support LHS programs by setting clear goals for them; appropriately staffing, budgeting, and incentivizing LHS researchers; and developing supportive, system-wide teamwork, skill development programs, and data infrastructures.

The Role of a Resilient Information Infrastructure in COVID-19 Vaccine Uptake in Ontario.

The COVID-19 pandemic has highlighted the need for a robust and nimble public health data infrastructure. ICES - a government-sponsored, independent, non-profit research institute in Ontario, Canada - functions as a key component of a resilient information infrastructure and an enabler of data co-production, contributing to Ontario's response to the COVID-19 pandemic as part of a learning health system. Linked data on the cumulative incidence of infection and vaccination at the neighbourhood level revealed disparate uptake between areas with low versus high risk of COVID-19. These data were leveraged by the government, service providers, media and the public to inform a more efficient and equitable vaccination strategy.

Learning networks in pediatric heart failure and transplantation.

BACKGROUND: Learning networks have emerged in medicine as a novel organizational structure that contains elements of quality improvement, education, and research with the goal of effecting rapid improvements in clinical care. In this article, the concept of a learning network is defined and highlighted in the field of pediatric heart failure and transplantation. METHODS: Learning networks are defined, with particular attention paid to the recent creation of the Advanced Cardiac Therapies Improving Outcomes Network (ACTION) for children with heart failure and those being supported with ventricular assist devices (VAD). RESULTS: The mission, goals, and organizational structure of ACTION are described, and recent initiatives promoted by ACTION are highlighted, such as stroke reduction initiatives, practice harmonization protocols, and use of ACTION data to support the recent US Food and Drug Administration approval of newer VAD for pediatric patients. CONCLUSIONS: The learning network, exemplified by ACTION, is distinguished from traditional clinical research collaboratives by contributions in research, quality improvement, patient-reported outcomes, and education, and serves as an effective vehicle to drive clinical improvement in the care of children with advanced heart failure.

Learning health systems from an academic perspective: establishing a collaboratory within a school of medicine and health sciences.

Learning Health Systems (LHSs) seek continuous improvement through the translation and integration of internally and externally generated knowledge across stakeholders within and external to the organization, yet current approaches are primarily described from the healthcare delivery perspective, leaving teaching and research responsibilities underexposed. Academic medical centers offer a unique perspective on LHSs because their mission includes teaching, research, and healthcare. This introduces an opportunity to enact, educate, and study processes and outcomes of LHSs within a single system. Little information is available to describe these processes and outcomes, resulting in a knowledge gap regarding the role of education and research in the quality improvement cycles and learning of LHSs. To close this knowledge gap, The George Washington University School of Medicine and Health Sciences initiated the Health Research and Education Collaboratory (GW Collaboratory) in 2017. The GW Collaboratory was established to study mechanisms supporting continuous quality improvement and learning in health systems within an academic medical center. We envision the GW Collaboratory as interconnected knowledge nodes facilitating collaboration among clinicians, patients, researchers, and educators to study the knowledge generation, dissemination, application, and evaluation required for continuous quality improvement and learning. We employ a project-based approach to foster communities of learning focused on exploring specific health problems of interest. We propose the GW Collaboratory as one model by which academic medical centers can contribute to the science of LHS.

The essential role of population health during and beyond COVID-19.

The coronavirus disease 2019 (COVID-19) pandemic has fundamentally changed how health care systems deliver services and revealed the tenuousness of care delivery based on face-to-face office visits and fee-for-service reimbursement models. Robust population health management, fostered by value-based contract participation, integrates analytics and agile clinical programs and is adaptable to optimize outcomes and reduce risk during population-level crises. In this article, we describe how mature population health programs in a learning health system have been rapidly leveraged to address the challenges of the pandemic. Population-level data and care management have facilitated identification of demographic-based disparities and community outreach. Telemedicine and integrated behavioral health have ensured critical primary care and specialty access, and mobile health and postacute interventions have shifted site of care and optimized hospital utilization. Beyond the pandemic, population health can lead as a cornerstone of a resilient health system, better prepared to improve public health and mitigate risk in a value-based paradigm.

The influence of the learning health system to address the COVID-19 pandemic: An examination of early literature.

INTRODUCTION: The COVID-19 pandemic has demanded immediate response from healthcare systems around the world. The learning health system (LHS) was created with rapid uptake of the newest evidence in mind, making it essential in the face of a pandemic. The goal of this review is to gain knowledge on the initial impact of the LHS on addressing the COVID-19 pandemic. METHODS: PubMed, Scopus and the Duke University library search tool were used to identify current literature regarding the intersection of the LHS and the COIVD-19 pandemic. Articles were reviewed for their purpose, findings and relation to each component of the LHS. RESULTS: Twelve articles were included in the review. All stages of the LHS were addressed from this sample. Most articles addressed some component of interoperability. Articles that interpreted data unique to COVID-19 and demonstrated specific tools and interventions were least common. CONCLUSIONS: Gaps in interoperability are well known and unlikely to be solved in the coming months. Collaboration between health systems, researchers, governments and professional societies is needed to support a robust LHS which grants the ability to rapidly adapt to global emergencies.

A protocol for evaluating a multi-level implementation theory to scale-up obstetric triage in referral hospitals in Ghana.

BACKGROUND: Ghana significantly reduced maternal and newborn mortality between 1990 and 2015, largely through efforts focused on improving access to care. Yet achieving further progress requires improving the quality and timeliness of care. Beginning in 2013, Ghana Health Service and Kybele, a US-based non-governmental organization, developed an innovative obstetric triage system to help midwives assess, diagnosis, and determine appropriate care plans more quickly and accurately. In 2019, efforts began to scale this successful intervention into six additional hospitals. This protocol describes the theory-based implementation approach guiding scale-up and presents the proposed mixed-methods evaluation plan. METHODS: An implementation theory was developed to describe how complementary implementation strategies would be bundled into a multi-level implementation approach. Drawing on the Interactive Systems Framework and Evidenced Based System for Implementation Support, the proposed implementation approach is designed to help individual facilities develop implementation capacity and also build a learning network across facilities to support the implementation of evidence-based interventions. A convergent design mixed methods approach will be used to evaluate implementation with relevant data drawn from tailored assessments, routinely collected process and quality monitoring data, textual analysis of relevant documents and WhatsApp group messages, and key informant interviews. Implementation outcomes of interest are acceptability, adoption, and sustainability. DISCUSSION: The past decade has seen a rapid growth in the development of frameworks, models, and theories of implementation, yet there remains little guidance on how to use these to operationalize implementation practice. This study proposes one method for using implementation theory, paired with other kinds of mid-level and program theory, to guide the replication and evaluation of a clinical intervention in a complex, real-world setting. The results of this study should help to provide evidence of how implementation theory can be used to help close the "know-do" gap. Every woman and every newborn deserves a safe and positive birth experience. Yet in many parts of the world, this goal is often more aspiration than reality. In 2006, Kybele, a US-based non-governmental organization, began working with the Ghanaian government to improve the quality of obstetric and newborn care in a large hospital in Greater Accra. One successful program was the development of a triage system that would help midwives rapidly assess pregnant women to determine who needed what kind of care and develop risk-based care plans. The program was then replicated in another large hospital in the Greater Accra region, where a systematic theory to inform triage implementation was developed. This paper describes the extension of this approach to scale-up the triage program implementation in six additional hospitals. The scale-up is guided by a multi-level theory that extends the facility level theory to include cross-facility learning networks and oversight by the health system. We explain the process of theory development to implement interventions and demonstrate how these require the combination of local contextual knowledge with evidence from the implementation science literature. We also describe our approach for evaluating the theory to assess its effectiveness in achieving key implementation outcomes. This paper provides an example of how to use implementation theories to guide the development and evaluation of complex programs in real-world settings.

Working to Achieve the Quadruple Aim - Abstracts from the Kaiser Permanente 2020 National Quality Conference.

Quality improvement activities are essential to achieving the Institute for Healthcare Improvement's Quadruple Aim of improving the health of our patients and members, enhancing members' care experiences, reducing costs, and attaining joy and meaning for our physicians and care teams in the workplace. These activities are also essential in creating a learning health care system.

A qualitative study of design stakeholders' views of developing and implementing a registry-based learning health system.

BACKGROUND: New opportunities to record, collate, and analyze routine patient data have prompted optimism about the potential of learning health systems. However, real-life examples of such systems remain rare and few have been exposed to study. We aimed to examine the views of design stakeholders on designing and implementing a US-based registry-enabled care and learning system for cystic fibrosis (RCLS-CF). METHODS: We conducted a two-phase qualitative study with stakeholders involved in designing, implementing, and using the RCLS-CF. First, we conducted semi-structured interviews with 19 program personnels involved in design and delivery of the program. We then undertook 11 follow-up interviews. Analysis of interviews was based on the constant comparative method, supported by NVivo software. RESULTS: The organizing principle for the RCLS-CF was a shift to more partnership-based relationships between patients and clinicians, founded in values of co-production, and facilitated by technology-enabled data sharing. Participants proposed that, for the system to be successful, the data it collects must be both clinically useful and meaningful to patients and clinicians. They suggested that the prerequisites included a technological infrastructure capable of supporting data entry and joint decision-making in an accessible way, and a set of social conditions, including willingness from patients and clinicians alike to work together in new ways that build on the expertise of both parties. Follow-up interviews highlighted some of the obstacles, including technical challenges and practical constraints on refiguring relationships between clinicians and patients. CONCLUSIONS: The values and vision underlying the RCLS-CF were shared and clearly and consistently articulated by design stakeholders. The challenges to realization were often not at the level of principle, but were both practical and social in character. Lessons from this study may be useful to other systems looking to harness the power of "big data" registries, including patient-reported data, for care, research, and quality improvement.

Adapting rapid assessment procedures for implementation research using a team-based approach to analysis: a case example of patient quality and safety interventions in the ICU.

BACKGROUND: Innovations to improve quality and safety in healthcare are increasingly complex, targeting multiple disciplines and organizational levels, and often requiring significant behavior change by those delivering care. Learning health systems must tackle the crucial task of understanding the implementation and effectiveness of complex interventions, but may be hampered in their efforts by limitations in study design imposed by business-cycle timelines and implementation into fast-paced clinical environments. Rapid assessment procedures are a pragmatic option for producing timely, contextually rich evaluative information about complex interventions implemented into dynamic clinical settings. METHODS: We describe our adaptation of rapid assessment procedures and introduce a rapid team-based analysis process using an example of an evaluation of an intensive care unit (ICU) redesign initiative aimed at improving patient safety in four academic medical centers across the USA. Steps in our approach included (1) iteratively working with stakeholders to develop evaluation questions; (2) integration of implementation science frameworks into field guides and analytic tools; (3) selecting and training a multidisciplinary site visit team; (4) preparation and trust building for 2-day site visits; (5) engaging sites in a participatory approach to data collection; (6) rapid team analysis and triangulation of data sources and methods using a priori charts derived from implementation frameworks; and (7) validation of findings with sites. RESULTS: We used the rapid assessment approach at each of the four ICU sites to evaluate the implementation of the sites' innovations. Though the ICU projects all included three common components, they were individually developed to suit the local context and had mixed implementation outcomes. We generated in-depth case summaries describing the overall implementation process for each site; implementation barriers and facilitators for all four sites are presented. One of the site case summaries is presented as an example of findings generated using the method. CONCLUSIONS: A rapid team-based approach to qualitative analysis using charts and team discussion using validation techniques, such as member-checking, can be included as part of rapid assessment procedures. Our work demonstrates the value of including rapid assessment procedures for implementation research when time and resources are limited.

A practical model for research with learning health systems: Building and implementing effective complex case management.

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 Health Innovation Program (HIP). The HIP model consolidates and enhances existing learning health system frameworks by defining specific steps needed to create sustainable change based on research conducted within the health system. As an example of the model's application, we describe its use to improve patient identification for the University of Wisconsin health system's case management program. Our case study shows the importance of culture, infrastructure, and strong leadership support in realizing a learning health systems research project and creating sustainable change within the health system. By articulating the foundational elements and steps to conduct research with learning health systems, our model supports researchers in achieving the challenge of moving learning health systems from concept to action.

Qualitative findings from a pilot stage implementation of a novel organizational learning tool toward operationalizing the Safety-II paradigm in health care.

'Safety-II' is a new approach to safety, which emphasizes learning proactively about how safety and efficacy are achieved in everyday frontline work. Previous research developed a new lesson-sharing tool designed based on the Safety-II approach: Resilience Engineering Tool to Improve Patient Safety (RETIPS). The tool comprises questions designed to elicit narratives of adaptations that have contributed to effectiveness in care delivery. The purpose of this study is to revise and validate the design of RETIPS. The tool was revised based on feedback of clinicians at a large multi-specialty hospital, resulting in a version customized for anesthesia residents, RETIPS-AnRes. RETIPS-AnRes was administered on a pilot-basis to anesthesia resident groups for a limited period of time. A review of the reports obtained shows a strong alignment of responses with the conceptual basis of the tool, i.e. learning about how things go well in everyday work. The exemplars include both, specific instances of successful patient care, as well as generic routines that contribute to safe and/or effective care delivery. These findings support RETIPS as a tool to operationalize the Safety-II paradigm in healthcare. Lessons and implications for implementation on a wider scale are discussed.

Novel tools for a learning health system: a combined difference-in-difference/regression discontinuity approach to evaluate effectiveness of a readmission reduction initiative.

Current methods used to evaluate the effects of healthcare improvement efforts have limitations. Designs with strong causal inference-such as individual patient or cluster randomisation-can be inappropriate and infeasible to use in single-centre settings. Simpler designs-such as prepost studies-are unable to infer causal relationships between improvement interventions and outcomes of interest, often leading to spurious conclusions regarding programme success. Other designs, such as regression discontinuity or difference-in-difference (DD) approaches alone, require multiple assumptions that are often unable to be met in real world improvement settings. We present a case study of a novel design in improvement and implementation research-a hybrid regression discontinuity/DD design-that leverages risk-targeted improvement interventions within a hospital readmission reduction programme. We demonstrate how the hybrid regression discontinuity-DD approach addresses many of the limitations of either method alone, and represents a useful method to evaluate the effects of multiple, simultaneous heath system improvement activities-a necessary capacity of a learning health system. Finally, we discuss some of the limitations of the hybrid regression discontinuity-DD approach, including the need to assign patients to interventions based upon a continuous measure, the need for large sample sizes, and potential susceptibility of risk-based intervention assignment to gaming.