Swiss Learning Health System: A national initiative to establish learning cycles for continuous health system improvement

Implementing the learning health system paradigm within academic health centers

Introduction

The learning health system (LHS) concept represents a bold innovation that combines organizational learning, strategic analysis of patient data, stakeholder engagement and the systematic translation of research into practice - all in service of improving the quality of health care delivered across the organization. This innovation has been diffused and widely adopted by healthcare organizations over the past 15 years, but academic health centers (AHCs) have been slower on the uptake. The irony is that AHCs have the resources (e.g., trained researchers, sophisticated clinical data systems, informatics infrastructure) that are necessary to do the highest-quality and most impactful LHS work.

Methods

Based on a review of publications describing how AHCs have implemented LHS work, as well as the authors' direct experience promoting the adoption of the LHS paradigm at Atrium Health Wake Forest Baptist (AHWFB), we:identify a set of factors that have inhibited broader adoption of the LHS paradigm among AHCs; distinguish between the forms of LHS work that are consistent and inconsistent with the mission of AHCs; and offer recommendations for broader adoption and fuller implementation of the LHS paradigm.

Results

The LHS paradigm represents an expansion of the scientific paradigm which serves as the foundation of research enterprise within AHCs. Both paradigms value rigorous studies of new treatments and practices, including pragmatic clinical trials. The LHS paradigm also places a high value on quality improvement studies, organizational learning, and the translation of research findings into improved patient care and operations within the local health system. The two paradigms differ on the origin of the research question, i.e., a pressing patient-care issue facing the health system versus the investigator's own research interests. Academic researchers have been disincentivized from pursuing at least some forms of LHS research. However, a growing number of AHCs are finding ways to integrate the LHS paradigm into their research enterprise, either by providing research faculty with institutional funding to cover their effort on studies that address the health system's priority issues, or by establishing an institute dedicated to LHS research.

Conclusions

The LHS paradigm is a disruptive intervention for AHCs, one that was initially resisted but is increasingly being embraced. AHCs are developing strategies for conducting LHS research, typically in parallel to the more traditional biomedical science that is core to academic medicine. Full implementation of the LHS paradigm will require further alignment between LHS and science, including a shift in the criteria for promotion and tenure to support those researchers who choose to focus on the pressing issues facing the health system.

Implementation strategies and outcome measures for advancing learning health systems: a mixed methods systematic review

BACKGROUND

Learning health systems strive to continuously integrate data and evidence into practice to improve patient outcomes and ensure value-based healthcare. While the LHS concept is gaining traction, the operationalization of LHSs is underexplored.

OBJECTIVE

To identify and synthesize the existing evidence on the implementation and evaluation of advancing learning health systems across international health care settings.

METHODS

A mixed methods systematic review was conducted. Six databases (CINAHL, Embase, Medline, PAIS, Scopus and Nursing at Allied Health Database) were searched up to July 2022 for terms related to learning health systems, implementation, and evaluation measures. Any study design, health care setting and population were considered for inclusion. No limitations were placed on language or date of publication. Two reviewers independently screened the titles, abstracts, and full texts of identified articles. Data were extracted and synthesized using a convergent integrated approach. Studies were critically appraised using relevant JBI critical appraisal checklists.

RESULTS

Thirty-five studies were included in the review. Most studies were conducted in the United States (n = 21) and published between 2019 and 2022 (n = 24). Digital data capture was the most common LHS characteristic reported across studies, while patient engagement, aligned governance and a culture of rapid learning and improvement were reported least often. We identified 33 unique strategies for implementing LHSs including: change record systems, conduct local consensus discussions and audit & provide feedback. A triangulation of quantitative and qualitative data revealed three integrated findings related to the implementation of LHSs: (1) The digital infrastructure of LHSs optimizes health service delivery; (2) LHSs have a positive impact on patient care and health outcomes; and (3) LHSs can influence health care providers and the health system.

CONCLUSION

This paper provides a comprehensive overview of the implementation of LHSs in various healthcare settings. While this review identified key implementation strategies, potential outcome measures, and components of functioning LHSs, further research is needed to better understand the impact of LHSs on patient, provider and population outcomes, and health system costs. Health systems researchers should continue to apply the LHS concept in practice, with a stronger focus on evaluation.

How Dissemination and Implementation Science Can Contribute to the Advancement of Learning Health Systems

Many health systems are working to become learning health systems (LHSs), which aim to improve the value of health care by rapidly, continuously generating evidence to apply to practice. However, challenges remain to advance toward the aspirational goal of becoming a fully mature LHS. While some important challenges have been well described (i.e., building system-level supporting infrastructure and the accessibility of inclusive, integrated, and actionable data), other key challenges are underrecognized, including balancing evaluation rapidity with rigor, applying principles of health equity and classic ethics, focusing on external validity and reproducibility (generalizability), and designing for sustainability. Many LHSs focus on continuous learning cycles, but with limited consideration of issues related to the rapidity of these learning cycles, as well as the sustainability or generalizability of solutions. Some types of data have been consistently underrepresented, including patient-reported outcomes and preferences, social determinants, and behavioral and environmental data, the absence of which can exacerbate health disparities. A promising approach to addressing many challenges that LHSs face may be found in dissemination and implementation (D&I) science. With an emphasis on multilevel dynamic contextual factors, representation of implementation partner engagement, pragmatic research, sustainability, and generalizability, D&I science methods can assist in overcoming many of the challenges facing LHSs. In this article, the authors describe the current state of LHSs and challenges to becoming a mature LHS, propose solutions to current challenges, focusing on the contributions of D&I science with other methods, and propose key components and characteristics of a mature LHS model that others can use to plan and develop their LHSs.

Clarifying the concept of a learning health system for healthcare delivery organizations: Implications from a qualitative analysis of the scientific literature

The “learning health system” (LHS) concept has been defined in broad terms, which makes it challenging for health system leaders to determine exactly what is required to transform their organization into an LHS. This study provides a conceptual map of the LHS landscape by identifying the activities, principles, tools, and conditions that LHS researchers have associated with the concept. Through a multi‐step screening process, two researchers identified 79 publications from PubMed (published before January 2020) that contained information relevant to the question, “What work is required of a healthcare organization that is operating as an LHS?” Those publications were coded as to whether or not they referenced each of 94 LHS elements in the taxonomy developed by the study team. This taxonomy, named the Learning Health Systems Consolidated Framework (LHS‐CF), organizes the elements into five “bodies of work” (organizational learning, translation of evidence into practice, building knowledge, analyzing clinical data, and engaging stakeholders) and four “enabling conditions” (workforce skilled for LHS work, data systems and informatics technology in place, organization invests resources in LHS work, and supportive organizational culture). We report the frequency that each of the 94 elements was referenced across the 79 publications. The four most referenced elements were: “organization builds knowledge or evidence,” “quality improvement practices are standard practice,” “patients and family members are actively engaged,” and “organizational culture emphasizes and supports learning.” By dissecting the LHS construct into its component elements, the LHS‐CF taxonomy can serve as a useful tool for LHS researchers and practitioners in defining the aspects of LHS they are addressing. By assessing how often each element is referenced in the literature, the study provides guidance to health system leaders as to how their organization needs to evolve in order to become an LHS ‐ while also recognizing that each organization should emphasize elements that are most aligned with their mission and goals.

The Indiana Learning Health System Initiative: Early experience developing a collaborative, regional learning health system

INTRODUCTION

Learning health systems (LHSs) are usually created and maintained by single institutions or healthcare systems. The Indiana Learning Health System Initiative (ILHSI) is a new multi-institutional, collaborative regional LHS initiative led by the Regenstrief Institute (RI) and developed in partnership with five additional organizations: two Indiana-based health systems, two schools at Indiana University, and our state-wide health information exchange. We report our experiences and lessons learned during the initial 2-year phase of developing and implementing the ILHSI.

METHODS

The initial goals of the ILHSI were to instantiate the concept, establish partnerships, and perform LHS pilot projects to inform expansion. We established shared governance and technical capabilities, conducted a literature review-based and regional environmental scan, and convened key stakeholders to iteratively identify focus areas, and select and implement six initial joint projects.

RESULTS

The ILHSI successfully collaborated with its partner organizations to establish a foundational governance structure, set goals and strategies, and prioritize projects and training activities. We developed and deployed strategies to effectively use health system and regional HIE infrastructure and minimize information silos, a frequent challenge for multi-organizational LHSs. Successful projects were diverse and included deploying a Fast Healthcare Interoperability Standards (FHIR)-based tool across emergency departments state-wide, analyzing free-text elements of cross-hospital surveys, and developing models to provide clinical decision support based on clinical and social determinants of health. We also experienced organizational challenges, including changes in key leadership personnel and varying levels of engagement with health system partners, which impacted initial ILHSI efforts and structures. Reflecting on these early experiences, we identified lessons learned and next steps.

CONCLUSIONS

Multi-organizational LHSs can be challenging to develop but present the opportunity to leverage learning across multiple organizations and systems to benefit the general population. Attention to governance decisions, shared goal setting and monitoring, and careful selection of projects are important for early success.

Learning health systems in primary care: a systematic scoping review

BACKGROUND

Learning health systems have been gaining traction over the past decade. The purpose of this study was to understand the spread of learning health systems in primary care, including where they have been implemented, how they are operating, and potential challenges and solutions.

METHODS

We completed a scoping review by systematically searching OVID Medline®, Embase®, IEEE Xplore®, and reviewing specific journals from 2007 to 2020. We also completed a Google search to identify gray literature.

RESULTS

We reviewed 1924 articles through our database search and 51 articles from other sources, from which we identified 21 unique learning health systems based on 62 data sources. Only one of these learning health systems was implemented exclusively in a primary care setting, where all others were integrated health systems or networks that also included other care settings. Eighteen of the 21 were in the United States. Examples of how these learning health systems were being used included real-time clinical surveillance, quality improvement initiatives, pragmatic trials at the point of care, and decision support. Many challenges and potential solutions were identified regarding data, sustainability, promoting a learning culture, prioritization processes, involvement of community, and balancing quality improvement versus research.

CONCLUSIONS

We identified 21 learning health systems, which all appear at an early stage of development, and only one was primary care only. We summarized and provided examples of integrated health systems and data networks that can be considered early models in the growing global movement to advance learning health systems in primary care.

Evolution or Revolution? Recommendations to Improve the Swiss Health Data Framework

Background: Facilitating access to health data for public health and research purposes is an important element in the health policy agenda of many countries. Improvements in this sense can only be achieved with the development of an appropriate data infrastructure and the implementations of policies that also respect societal preferences. Switzerland is a revealing example of a country that has been struggling to achieve this aim. The objective of the study is to reflect on stakeholders' recommendations on how to improve the health data framework of this country.

Methods: We analysed the recommendations collected as part of a qualitative study including 48 expert stakeholders from Switzerland that have been working principally with health databases. Recommendations were divided in themes and subthemes according to applied thematic analysis.

Results: Stakeholders recommended several potential improvements of the health data framework in Switzerland. At the general level of mind-set and attitude, they suggested to foster the development of an explicit health data strategy, better communication and the respect of societal preferences. In terms of infrastructure, there were calls for the creation of a national data center, the improvement of IT solutions and the use of a Unique Identifier for patient data. Lastly, they recommended harmonising procedures for data access and to clarify data protection and consent rules.

Conclusion: Recommendations show several potential improvements of the health data framework, but they have to be reconciled with existing policies, infrastructures and ethico-legal limitations. Achieving a gradual implementation of the recommended solutions is the preferable way forward for Switzerland and a lesson for other countries that are also seeking to improve health data access for public health and research purposes.

Establishing a learning healthcare system to improve health outcomes for people with epilepsy

OBJECTIVE

To describe the organization of the Epilepsy Learning Healthcare System (ELHS), a network that aims to improve care outcomes for people with epilepsy (PWE).

MATERIALS AND METHODS

Patients and family partners, providers, researchers, epidemiologists, and other leaders collaborated to recruit epilepsy centers and community services organizations into a novel learning network. A multidisciplinary Coordinating Committee developed ELHS governance and organizational structure, including four key planning Cores (Community, Clinical, Quality Improvement, and Data). Through Quality Improvement (QI) methodology grounded in the Institute for Healthcare Improvement (IHI) model, including iterative Plan-Do-Study-Act (PDSA) rapid learning cycles and other learning and sharing sessions, ELHS equipped epilepsy centers and community organizations with tools to standardize, measure, share, and improve key aspects of epilepsy care. The initial learning cycles addressed provider documentation of seizure frequency and type, and also screening for medication adherence barriers. Rapid learning cycles have been carried out on these initial measures in both clinical centers and community-based settings. Additional key measures have been defined for quality of life, screening, and treatment for mental health and behavioral comorbidities, transition from pediatric to adult care, counseling for women and girls living with epilepsy, referral for specialty care, and prevention and treatment of seizure clusters and status epilepticus.

RESULTS

It is feasible to adopt a learning healthcare system framework in epilepsy centers and community services organizations. Through structured collaboration between epilepsy care providers, community support organizations, PWE, and their families/caregivers we have identified new opportunities to improve outcomes that are not available in traditional care models.

Implementation of a "real-world" learning health system: Results from the evaluation of the Connected Health Cities programme

BACKGROUND

The "learning health system" has been proposed to deliver better outcomes for patients and communities by analyzing routinely captured health information and feeding back results to clinical staff. This approach has been piloted in the Connected Health Cities (CHC) programme in four regions in the North of England. This paper presents the results of the evaluation of this program conducted between February and December 2018.

METHODS

Fifty nine semistructured interviews were completed with a mix of CHC programme staff and external partners who had contributed to the delivery of the CHC programme. Interviews were audio recorded and transcribed verbatim. This also included the review of project documentation including project reports and minutes of project group meetings, in addition to a short online survey that was completed by 31 members of CHC programme staff. Data were analyzed thematically.

RESULTS

Two overarching themes emerged through the thematic analysis of participant interview: (a) challenges in the implementation of learning health system pathways, and (b) benefits to the CHC approach for both staff and patients. In particular, time constraints in delivering an ambitious program of work, data quality, and accessibility, as well as the long-term sustainability of the CHC programme were noted as key challenges in implementing a LHS at scale.

CONCLUSIONS

The findings from this evaluation provide valuable insight into creating learning health system at scale, including the potential benefits and likely challenges.

Change in environmental barriers experienced over a 5-year period by people living with spinal cord injury in Switzerland: a prospective cohort study

STUDY DESIGN

Cohort study with two measurement occasions.

OBJECTIVES

To investigate change in environmental barriers experienced by people living with spinal cord injury (SCI) over a 5-year period.

SETTING

Community, Switzerland.

METHODS

Data were from the Swiss spinal cord injury (SwiSCI) survey. Main outcome measure was the Nottwil Environmental Factors Inventory-Short Form. Random-effects Poisson regression featuring between-within estimation was used to examine predictors of the number of environmental barriers and of its change over time.

RESULTS

One thousand five hundred and forty-nine persons participated in Survey 2012 and 1530 participated in Survey 2017; 761 participated in both surveys. In both surveys most participants reported at least three barriers. Leading issues were unfavorable climate, inaccessibility of buildings and public spaces, and lack of or insufficiently adapted means of transportation. Reporting of barriers related to climate, finances, and state services declined over time. Between subjects, having more health problems, lesser physical independence, poorer mental health, and a lower household income were related to a higher number of barriers experienced. Within subjects, improvements in income, physical independence, and mental health over time were related to a reduction in barriers.

CONCLUSIONS

Inaccessibility of buildings and places and problems with transportation remained major barriers over a 5-year period and should be priorities of Swiss disability policy. People with reduced mental and physical health, and those with lower income are vulnerable groups deserving specific attention. Policies targeting income and life-long rehabilitation targeting health promotion and maintenance may be suitable means to reduce the experience of environmental barriers.

The International Spinal Cord Injury Survey: The Way Forward

As a community survey of individuals living with spinal cord injury in 22 countries, representing all 6 of the World Health Organization regions, the International Spinal Cord Injury (InSCI) community survey is one of the few surveys that highlights not only basic medical issues, but also the impact of spinal cord injury (SCI) on the everyday lives of people. The InSCI survey is part of a much larger project known as the Learning Health System for SCI Initiative (LHS-SCI). The objective of this article is to highlight some of the ongoing and planned next steps at the national and international levels. The implementation phase of the LHS-SCI initiative, beginning with the publication of primary results and extending until 2023, will use the results of the InSCI survey as evidence for implementation of recommendations for improving the societal response to the needs of individuals with SCI at the national level. To illustrate the variety of implementation activities currently underway, we provide country examples from Australia, Morocco, Malaysia, and Germany to demonstrate the diversity of approaches to the implementation of InSCI data. The implementation phase of the LHS-SCI initiative promises to usher in a new era of SCI research that will be seamlessly linked to ongoing and effective implementation actions, at both international and national levels and across settings from clinical practice, health systems management, and national policy.

Regulating the Secondary Use of Data for Research: Arguments Against Genetic Exceptionalism

As accessing, collecting, and storing personal information become increasingly easier, the secondary use of data has the potential to make healthcare research more cost and time effective. The widespread reuse of data, however, raises important ethical and policy issues, especially because of the sensitive nature of genetic and health-related information. Regulation is thus crucial to determine the conditions upon which data can be reused. In this respect, the question emerges whether it is appropriate to endorse genetic exceptionalism and grant genetic data an exceptional status with respect to secondary use requirements. Using Swiss law as a case study, it is argued that genetic exceptionalism in secondary use regulation is not justified for three reasons. First, although genetic data have particular features, also other non-genetic data can be extremely sensitive. Second, having different regulatory requirements depending on the nature of data hinders the creation of comprehensible consent forms. Third, empirical evidence about public preferences concerning data reuse suggests that exceptional protection for genetic data alone is not justified. In this sense, it is claimed that regulation concerning data reuse should treat genetic data as important, but not exceptional.