Mind the Gap: Putting Evidence into Practice in the Era of Learning Health Systems

Transforming the Effectiveness and Equity of a Psychological Therapy Service: A Case Study in the English NHS Talking Therapies Program

To work with a psychological therapies service to implement a recovery plan, as required by a government body, aimed at improving patient outcomes (effectiveness) and decreasing practitioner variability (equity). A case-study utilizing components of a learning health system, including nationally mandated patient outcome data, comprising three 18-month phases: (1) retrospective baseline; (2) improving patient outcomes (management-led); and (3) reducing practitioner variability (clinician-led). Primary analyses focused on 35 practitioners (NPR = 35) who were constant across the three phases and their patients in each phase (NPA = 930, 1226, 1217, respectively). Reliable improvement rates determined patient outcomes and multilevel modeling yielded practitioner effects. To test generalizability, results were compared to the whole practitioner sample for each phase: (1) NPR = 81, NPA = 1982; (2) NPR = 80, NPA = 2227; (3) NPR = 74, NPA = 2267. Ethical approval was granted by the Health Research Authority. Patient outcomes improved in successive phases for both the core and whole practitioner samples with the largest impact occurring in the management-led intervention. Practitioner variability decreased in successive phases in both the core and whole practitioner samples except in the management-led intervention of the whole sample. Compared with the management-led intervention, the practitioner-led intervention yielded a decrease in practitioner effect exceeding 60% in the core sample and approaching 50% in the whole sample. The implementation of multiple components of a learning health system can lead to improvements in both the effectiveness and equity of a psychological therapy service.

Identifying factors influencing emerging innovations in hospital discharge decision making in response to system stress: a qualitative study

BACKGROUND

The purpose of this qualitative study was to identify emergent rehabilitation innovations and clinician perceptions influencing their implementation and outcomes related to hospital discharge decision-making during the Coronavirus 2019 pandemic.

METHODS

Rehabilitation clinicians were recruited from the Veterans Affairs Health Care System and participated in individual semi-structured interviews guided by the integrated Promoting Action on Research Implementation in Health Services (i-PARIHS) framework. Data were analyzed using a rapid qualitative, deductive team-based approach informed by directed content analysis.

RESULTS

Twenty-three rehabilitation clinicians representing physical (N = 11) and occupational therapy (N = 12) participated in the study. Three primary themes were generated: (1) Innovation: emerging innovations in discharge processes included perceived increases in team collaboration, shifts in caseload prioritization, and alternative options for post-acute care. (2) Recipients: innovations emerged as approaches to communicating discharge recommendations changed (in-person to virtual) and strong patient/family preferences to discharge to the home challenged collaborative goal setting; and (3) Context: the ability of rehabilitation clinicians to innovate and the form of innovations were influenced by the broader hospital system, interdisciplinary team dynamics, and policy fluctuations. Innovations described by participants included (1) use of technological modalities for interdisciplinary collaboration, (2) expansion of telehealth modalities to deliver care in the home, (3) changes in acute care case prioritization, and (4) alternative options for discharge directly to home.

CONCLUSIONS

Our findings reinforce that rehabilitation clinicians developed innovative strategies to quickly adapt to multiple systems-level factors that were changing in the face of the COVID-19 pandemic. Future research is needed to assess the impact of innovations, remediate unintended consequences, and evaluate the implementation of promising innovations to respond to emerging healthcare delivery needs more rapidly.

Integrating Patients Into Programmes to Address the Allergy Knowledge Practice Gap

There is a wide gap between the first publication of new treatments with efficacy and their successful application in clinical practice. In many respects, the management of allergic diseases is a good exemplar of the knowledge/practice gap. It was assumed that systematic reviews and publication of guidelines would ensure timely delivery of effective care, but this has not proved to be the case. While there are many reasons to explain shortcomings in healthcare delivery, the lack of patient and carer involvement in the planning of research, evidence review, guideline development and guideline implementation is most compelling. To achieve adherence to evidence-based guidelines consistently across all levels of the health service requires the implementation of integrated care with clear pathways through which patients can navigate. Quality improvement methodology could be employed to plan and implement integrated care pathways (ICPs). There is evidence that ICPs achieve improved outcomes for acute hospital-based interventions, but less work has focussed on long-term conditions where more diverse agencies are involved. At all stages, stakeholder representation from the full range of healthcare professionals, patients, their families, social services, education, local government and employers must be involved. In this article we review the step-wise and iterative process by which knowledge is implemented into practice to improve patient experience and outcomes We argue how this process can benefit from the involvement of patients and their carers as equal partners, and we discuss how different initiatives have involved patients with allergic diseases. There currently is a gap in evidence that links patient involvement to improved outcomes. We recommend the use of the Core Outcome Sets (COS) and Patient Reported Experience Measures (PREMS) which have been developed for allergic diseases to monitor the effects of implementation research and the impact of patient and carer involvement on outcomes.

How to use communities of practice to support change in learning health systems: A landscape of roles and guidance for management

Background

Communities of practice support evidence-based practice and can be, in and of themselves, applied learning spaces in organizations. However, the variety of ways that communities of practice can support learning health systems are poorly characterized. Furthermore, health system leaders have little guidance on designing and resourcing communities of practice to effectively serve learning health systems.

Methods

We conducted a collective case study, examining a cross-section of Canadian-based communities of practice dedicated to supporting evidence-based practice. We held semi-structured interviews with 21 participants representing 16 communities of practice and 5 community of practice facilitation platforms that provide administration support, tools, and oversight for multiple communities of practice. Using the Conceptual Framework for Value-Creating Learning Health Systems, we characterized the numerous roles that communities of practice can take to support learning health systems. We also pulled insights from the interviews on properly resourcing and managing communities of practice.

Results

Communities of practice can advance learning health systems across learning cycles (ie, identifying learning priorities, generating data and knowledge, and implementing and evaluating change). They also act as important infrastructure required to share and coordinate across learning health systems. Community of practice facilitation platforms reduce staff members' workload, in turn, creating greater efficiency and effectiveness across community of practice lifespans. Furthermore, these platforms can be a mechanism to coordinate critical activities (e.g., priority alignment, knowledge brokerage/sharing across the broader system).

Conclusion

To the authors' knowledge, this is the first study to characterize communities of practice across the learning health system landscape. With these results, learning health system leaders have a catalog that clarifies the potential communities of practice roles in knowledge generation, implementation, and uptake of new evidence. Furthermore, the results provide evidence that organizational investment in overarching community of practice facilitation platforms will strengthen and accelerate community of practice supports in learning health systems.

Learning from data in dentistry: Summary of the third annual OpenWide conference

The overarching goal of the third scientific oral health symposium was to introduce the concept of a learning health system to the dental community and to identify and discuss cutting-edge research and strategies using data for improving the quality of dental care and patient safety. Conference participants included clinically active dentists, dental researchers, quality improvement experts, informaticians, insurers, EHR vendors/developers, and members of dental professional organizations and dental service organizations. This report summarizes the main outputs of the third annual OpenWide conference held in Houston, Texas, on October 12, 2022, as an affiliated meeting of the American Dental Association (ADA) 2022 annual conference.

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.

Optimization of Care Pathways Through Technological, Clinical, Organizational and Social Innovations: A Qualitative Study

Numerous calls at national and international level are leading some countries to seek to redesign the provision of healthcare and services. Care pathways have the potential to improve outcomes by providing a mechanism to coordinate care and reduce fragmentation and ultimately costs. However, their implementation still shows variable results, resulting in them being considered as complex interventions in complex systems. By mobilizing an emerging approach combining action research and grounded theory methodology, we conducted a pilot project on care pathways. We used a strongly inductive process, to mobilize comparison and continuous theoretical sampling to produce theories. Forty-two interviews were conducted, and participant observations were made throughout the project, including 60 participant observations at meetings, workshops and field observations. The investigators kept logbooks and recorded field notes. Thematic analysis was used with an inductive approach. The present model explains the factors that positively or negatively influence the implementation of innovations in care pathways. The model represents interactions between facilitating factors, favourable conditions for the emergence of innovation adoption, implementation process enablers and challenges or barriers including those related specifically to the local context. What seems to be totally new is the embodiment of the mobilizing shared objective of active patient-partner participation in decision-making, data collection and analysis and solution building. This allows, in our opinion, to transcend professional perspectives for the benefit of patient-oriented results. Finally, the pilot project has created expectations in terms of spread and scaling. Future research on care pathway implementation should go further in the evaluation of the multifactorial impacts and develop a methodological framework of care pathway implementation, as the only existing proposition seems limited. Furthermore, from a social science perspective, it would be interesting to analyse the modes of social valuation of the different actors to understand what allows the transformation of collective action.

Implementation model for a national learning health system (IMPLEMENT-National LHS): a concept analysis and systematic review protocol

INTRODUCTION

Despite efforts and repeated calls to improve the organisation and quality of healthcare and services, and in view of the many challenges facing health systems, the results and capacity to adapt and integrate innovations and new knowledge remain suboptimal. Learning health systems (LHS) may be an effective model to accelerate the application of research for real quality improvement in healthcare. However, while recognising the enormous potential of LHS, the literature suggests the model remains more of an aspiration than a reality.

METHODS AND ANALYSIS

To reach a fine understanding of the implementation of the concepts involved in LHS, we will use a hybrid method which combines concept analyses with systematic review methodology. We will use a two-step analysis, a content analysis to analyse the definitions, uses and attributes of the concept and a systematic review to analyse the concept's implementation mechanisms. We will search eight databases and grey literature and present a broad synthesis of the available evidence regarding design, implementation and evaluation of LHS in a multilevel perspective. We will follow the latest Preferred Reporting Items for Systematic Review and Meta-Analysis statement for conducting and reporting a systematic review. Two reviewers will independently screen the titles and abstracts against the eligibility criteria followed by full-text screening of potentially relevant articles for final inclusion decision. Conflicts will be resolved with a senior author. We will include published primary studies that use qualitative, quantitative or mixed methods. The assessment of risk of bias will be made using the Mixed-Methods Appraisal Tool.

ETHICS AND DISSEMINATION

This systematic review is exempt from ethics approval. The results formulated will highlight evidence-based interventions that support the implementation of a national LHS. They will be of particular interest to decision makers, researchers, managers, clinicians and patients allowing finally to implement the promising proposal of LHSs at national scale.

PROSPERO REGISTRATION NUMBER

CRD42023393565.

My 28 Days - a global digital women's health initiative for evaluation and management of secondary amenorrhea: case report and literature review

There is a need to close the gap between knowledge and action in health care. Effective care requires a convenient and reliable distribution process. As global internet and mobile communication increase capacity, innovative approaches to digital health education platforms and care delivery are feasible. We report the case of a young African woman who developed acute secondary amenorrhea at age 18. Subsequently, she experienced a 10-year delay in the diagnosis of the underlying cause. A global digital medical hub focused on women's health and secondary amenorrhea could reduce the chance of such mismanagement. Such a hub would establish more efficient information integration and exchange processes to better serve patients, family caregivers, health care providers, and investigators. Here, we show proof of concept for a global digital medical hub for women's health. First, we describe the physiological control systems that govern the normal menstrual cycle, and review the pathophysiology and management of secondary amenorrhea. The symptom may lead to broad and profound health implications for the patient and extended family members. In specific situations, there may be significant morbidity related to estradiol deficiency: (1) reduced bone mineral density, 2) cardiovascular disease, and 3) cognitive decline. Using primary ovarian insufficiency (POI) as the paradigm condition, the Mary Elizabeth Conover Foundation has been able to address the specific global educational needs of these women. The Foundation did this by creating a professionally managed Facebook group specifically for these women. POI most commonly presents with secondary amenorrhea. Here we demonstrate the feasibility of conducting a natural history study on secondary amenorrhea with international reach to be coordinated by a global digital medical hub. Such an approach takes full advantage of internet and mobile device communication systems. We refer to this global digital women's health initiative as My 28 Days®.

Gathering speed and countering tensions in the rapid learning health system

The vision of the learning health system (LHS), conceptualized 15 years ago, is for the rapid generation, use, and spread of high-quality evidence that yields better health experiences, outcomes, efficiencies, and equity in everyday practice settings across communities. However, despite the emergence of many useful LHS frameworks and examples to guide adoption, large gaps remain in the speed and consistency with which evidence is generated and used across the range of settings from the bedside to the policy table. Gaps in progress are not surprising, however, given the tensions that predictably arise when key stakeholders-researchers, health systems, and funders-comingle in these efforts. This commentary examines eight core tensions that naturally arise and offers practical actions that stakeholders can take to address these tensions and speed LHS adoption. The urgency for attenuating these tensions and accelerating health system improvements has never been higher. Timeliness, rigor, and prioritization can be aligned across stakeholders, but only if all partners are intentional about the operational and cultural challenges that exist.

Guiding principles for technical infrastructure to support computable biomedical knowledge

Over the past 4 years, the authors have participated as members of the Mobilizing Computable Biomedical Knowledge Technical Infrastructure working group and focused on conceptualizing the infrastructure required to use computable biomedical knowledge. Here, we summarize our thoughts and lay the foundation for future work in the development of CBK infrastructure, including: explaining the difference between computable knowledge and data, and contextualizing the conversation with the Learning Health Systems and the FAIR principles. Specifically, we provide three guiding principles to advance the development of CBK infrastructure: (a) Promote interoperable systems for data and knowledge to be findable, accessible, interoperable, and reusable. (b) Enable stable, trustworthy knowledge representations that are human and machine readable. (c) Computable knowledge resources should, when possible, be open. Standards supporting computable knowledge infrastructures must be open.

Stakeholder-engaged co-design and implementation of web-based tools to enhance the dissemination and implementation of AHRQ EPC reports

Introduction

A mission-critical aspect of learning health systems (LHSs) is the provision of evidence-based practice. One source of such evidence is provided by the Agency for Healthcare Research and Quality (AHRQ) through rigorous systematic reviews, termed evidence reports that synthesize available evidence on nominated topics of interest. However, the AHRQ Evidence-based Practice Center (EPC) program recognizes that the production of high-quality evidence reviews does not guarantee or promote their use and usability in practice.

Methods

To make these reports more relevant to LHSs and promote evidence dissemination, AHRQ awarded a contract to the American Institutes for Research (AIR) and its Kaiser Permanente ACTION (KPNW ACTION) partner to design and implement web-based tools to meet the gap in dissemination and implementation of EPC reports in LHSs. We used a co-production approach to accomplish this work across three phases of activity: planning, co-design, and implementation between 2018 and 2021. We describe the methods and results and discuss implications for future efforts.

Results

Web-based information tools that provide clinically relevant summaries with clear visual representations from the AHRQ EPC systematic evidence reports may be used by LHSs to increase awareness and accessibility of EPC reports, formalize and enhance LHSs' evidence review infrastructure, develop system-specific protocols and care pathways, improve practice at the point of care, and train and educate.

Conclusions

The co-design of these tools and facilitated implementation generated an approach to making EPC reports more accessible and allows for more widespread application of systematic review results in supporting evidence-based practices in LHSs.

Exploring Patient Journey Mapping and the Learning Health System: Scoping Review

BACKGROUND

Journey maps are visualization tools that can facilitate the diagrammatical representation of stakeholder groups by interest or function for comparative visual analysis. Therefore, journey maps can illustrate intersections and relationships between organizations and consumers using products or services. We propose that some synergies may exist between journey maps and the concept of a learning health system (LHS). The overarching goal of an LHS is to use health care data to inform clinical practice and improve service delivery processes and patient outcomes.

OBJECTIVE

The purpose of this review was to assess the literature and establish a relationship between journey mapping techniques and LHSs. Specifically, in this study, we explored the current state of the literature to answer the following research questions: (1) Is there a relationship between journey mapping techniques and an LHS in the literature? (2) Is there a way to integrate the data from journey mapping activities into an LHS? (3) How can the data gleaned from journey map activities be used to inform an LHS?

METHODS

A scoping review was conducted by querying the following electronic databases: Cochrane Database of Systematic Reviews (Ovid), IEEE Xplore, PubMed, Web of Science, Academic Search Complete (EBSCOhost), APA PsycInfo (EBSCOhost), CINAHL (EBSCOhost), and MEDLINE (EBSCOhost). Two researchers applied the inclusion criteria and assessed all articles by title and abstract in the first screen, using Covidence. Following this, a full-text review of included articles was done, with relevant data extracted, tabulated, and assessed thematically.

RESULTS

The initial search yielded 694 studies. Of those, 179 duplicates were removed. Following this, 515 articles were assessed during the first screening phase, and 412 were excluded, as they did not meet the inclusion criteria. Next, 103 articles were read in full, and 95 were excluded, resulting in a final sample of 8 articles that satisfied the inclusion criteria. The article sample can be subsumed into 2 overarching themes: (1) the need to evolve service delivery models in health care, and (2) the potential value of using patient journey data in an LHS.

CONCLUSIONS

This scoping review demonstrated the gap in knowledge regarding integrating the data from journey mapping activities into an LHS. Our findings highlighted the importance of using the data from patient experiences to enrich an LHS and provide holistic care. To satisfy this gap, the authors intend to continue this investigation to establish the relationship between journey mapping and the concept of LHSs. This scoping review will serve as phase 1 of an investigative series. Phase 2 will entail the creation of a holistic framework to guide and streamline data integration from journey mapping activities into an LHS. Lastly, phase 3 will provide a proof of concept to demonstrate how patient journey mapping activities could be integrated into an LHS.

Use of clinical pathways integrated into the electronic health record to address the coronavirus disease 2019 (COVID-19) pandemic

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic has required healthcare systems to meet new demands for rapid information dissemination, resource allocation, and data reporting. To help address these challenges, our institution leveraged electronic health record (EHR)-integrated clinical pathways (E-ICPs), which are easily understood care algorithms accessible at the point of care.

OBJECTIVE

To describe our institution's creation of E-ICPs to address the COVID-19 pandemic, and to assess the use and impact of these tools.

SETTING

Urban academic medical center with adult and pediatric hospitals, emergency departments, and ambulatory practices.

METHODS

Using the E-ICP processes and infrastructure established at our institution as a foundation, we developed a suite of COVID-19-specific E-ICPs along with a process for frequent reassessment and updating. We examined the development and use of our COVID-19-specific pathways for a 6-month period (March 1-September 1, 2020), and we have described their impact using case studies.

RESULTS

In total, 45 COVID-19-specific pathways were developed, pertaining to triage, diagnosis, and management of COVID-19 in diverse patient settings. Orders available in E-ICPs included those for isolation precautions, testing, treatments, admissions, and transfers. Pathways were accessed 86,400 times, with 99,081 individual orders were placed. Case studies demonstrate the impact of COVID-19 E-ICPs on stewardship of resources, testing optimization, and data reporting.

CONCLUSIONS

E-ICPs provide a flexible and unified mechanism to meet the evolving demands of the COVID-19 pandemic, and they continue to be a critical tool leveraged by clinicians and hospital administrators alike for the management of COVID-19. Lessons learned may be generalizable to other urgent and nonurgent clinical conditions.

Conceptualizing learning health systems: A mapping review

Introduction

Health systems worldwide face the challenge of increasing population health with high-quality care and reducing health care expenditure growth. In pursuit for a solution, regional cross-sectoral partnerships aim to reorganize and integrate services across public health, health care and social care. Although the complexity of regional partnerships demands an incremental strategy, it is yet not known how learning works within these partnerships. To understand learning in regional cross-sectoral partnerships for health, this study aims to map the concept Learning Health System (LHS).

Methods

This mapping review used a qualitative text analysis approach. A literature search was conducted in Embase and was limited to English-language papers published in the period 2015-2020. Title-abstract screening was performed using established exclusion criteria. During full-text screening, we combined deductive and inductive coding. The concept LHS was disentangled into aims, design elements, and process of learning. Data extraction and analysis were performed in MAX QDA 2020.

Results

In total, 155 articles were included. All articles used the LHS definition of the Institute of Medicine. The interpretation of the concept LHS varied widely. The description of LHS contained 25 highly connected aims. In addition, we identified nine design elements. Most elements were described similarly, only the interpretation of stakeholders, data infrastructure and data varied. Furthermore, we identified three types of learning: learning as 1) interaction between clinical practice and research; 2) a circular process of converting routine care data to knowledge, knowledge to performance; and performance to data; and 3) recurrent interaction between stakeholders to identify opportunities for change, to reveal underlying values, and to evaluate processes. Typology 3 was underrepresented, and the three types of learning rarely occurred simultaneously.

Conclusion

To understand learning within regional cross-sectoral partnerships for health, we suggest to specify LHS-aim(s), operationalize design elements, and choose deliberately appropriate learning type(s).

Computer clinical decision support that automates personalized clinical care: a challenging but needed healthcare delivery strategy

How to deliver best care in various clinical settings remains a vexing problem. All pertinent healthcare-related questions have not, cannot, and will not be addressable with costly time- and resource-consuming controlled clinical trials. At present, evidence-based guidelines can address only a small fraction of the types of care that clinicians deliver. Furthermore, underserved areas rarely can access state-of-the-art evidence-based guidelines in real-time, and often lack the wherewithal to implement advanced guidelines. Care providers in such settings frequently do not have sufficient training to undertake advanced guideline implementation. Nevertheless, in advanced modern healthcare delivery environments, use of eActions (validated clinical decision support systems) could help overcome the cognitive limitations of overburdened clinicians. Widespread use of eActions will require surmounting current healthcare technical and cultural barriers and installing clinical evidence/data curation systems. The authors expect that increased numbers of evidence-based guidelines will result from future comparative effectiveness clinical research carried out during routine healthcare delivery within learning healthcare systems.

A study protocol for improving the delivery of acute kidney replacement therapy (KRT) to critically ill patients in Alberta – DIALYZING WISELY

Background

Acute kidney replacement therapy (KRT) is delivered to acutely ill patients to support organ function and life in the Intensive Care Unit (ICU). Implementing standardized acute KRT pathways can ensure its safe and effective management. At present, there is no standardized approach to the management of acute KRT in Alberta ICUs.

Methods

Dialyzing Wisely is a registry embedded, stepped-wedge, interrupted time-series evaluation of the implementation of a standardized, stakeholder-informed, and evidence-based acute KRT pathway into Alberta ICUs. The acute KRT pathway will consist of two distinct phases. First, we will implement routine monitoring of evidence-informed key performance indicators (KPIs) of acute KRT. Second, we will provide prescriber and program reports for acute KRT initiation patterns. After the implementation of both phases of the pathway, we will evaluate acute KRT performance quarterly and implement a customized suite of interventions aimed at improving performance. We will compare this with baseline and evaluate iterative post implementation effects of the care pathway.

Discussion

Dialyzing Wisely will implement, monitor, and report a suite of KPIs of acute KRT, coupled with a care pathway that will transform the quality of acute KRT across ICUs in Alberta. This program will provide a framework for scaling evidence-informed approaches to monitoring and management of acute KRT in other jurisdictions. We anticipate improvements in acute KRT performance, decreased healthcare system costs and improved patient quality of life by decreasing patient dependence on maintenance dialysis.

Trial registration

Clinicaltrials.gov, NCT05186636. Registered 11, January, 2022.

Informatics education for translational research teams: An unrealized opportunity to strengthen the national research infrastructure

Objective

To identify the informatics educational needs of clinical and translational research professionals whose primary focus is not informatics.

Introduction

Informatics and data science skills are essential for the full spectrum of translational research, and an increased understanding of informatics issues on the part of translational researchers can alleviate the demand for informaticians and enable more productive collaborations when informaticians are involved. Identifying the level of interest in different topics among various types of of translational researchers will help set priorities for development and dissemination of informatics education.

Methods

We surveyed clinical and translational science researchers in Clinical and Translational Science Award (CTSA) programs about their educational needs and preferences.

Results

Researchers from 23 out of the 62 CTSA hubs responded to the survey. 67% of respondents across roles and topics expressed interest in learning about informatics topics. There was high interest in all 30 topics included in the survey, with some variation in interest depending on the role of the respondents.

Discussion

Our data support the need to advance training in clinical and biomedical informatics. As the complexity and use of information technology and data science in research studies grows, informaticians will continue to be a limited resource for research collaboration, education, and training. An increased understanding of informatics issues across translational research teams can alleviate this burden and allow for more productive collaborations. To inform a roadmap for informatics education for research professionals, we suggest strategies to use the results of this needs assessment to develop future informatics education.

Training the next generation of learning health system scientists

Introduction

The learning health system (LHS) aligns science, informatics, incentives, stakeholders, and culture for continuous improvement and innovation. The Agency for Healthcare Research and Quality and the Patient-Centered Outcomes Research Institute designed a K12 initiative to grow the number of LHS scientists. We describe approaches developed by 11 funded centers of excellence (COEs) to promote partnerships between scholars and health system leaders and to provide mentored research training.

Methods

Since 2018, the COEs have enlisted faculty, secured institutional resources, partnered with health systems, developed and implemented curricula, recruited scholars, and provided mentored training. Program directors for each COE provided descriptive data on program context, scholar characteristics, stakeholder engagement, scholar experiences with health system partnerships, roles following program completion, and key training challenges.

Results

To date, the 11 COEs have partnered with health systems to train 110 scholars. Nine (82%) programs partner with a Veterans Affairs health system and 9 (82%) partner with safety net providers. Clinically trained scholars (n = 87; 79%) include 70 physicians and 17 scholars in other clinical disciplines. Non-clinicians (n = 29; 26%) represent diverse fields, dominated by population health sciences. Stakeholder engagement helps scholars understand health system and patient/family needs and priorities, enabling opportunities to conduct embedded research, improve outcomes, and grow skills in translating research methods and findings into practice. Challenges include supporting scholars through roadblocks that threaten to derail projects during their limited program time, ranging from delays in access to data to COVID-19-related impediments and shifts in organizational priorities.

Conclusions

Four years into this novel training program, there is evidence of scholars' accomplishments, both in traditional academic terms and in terms of moving along career trajectories that hold the potential to lead and accelerate transformational health system change. Future LHS training efforts should focus on sustainability, including organizational support for scholar activities.

Development of an Australia and New Zealand Lung Cancer Clinical Quality Registry: a protocol paper

INTRODUCTION

Lung cancer is the leading cause of cancer mortality, comprising the largest national cancer disease burden in Australia and New Zealand. Regional reports identify substantial evidence-practice gaps, unwarranted variation from best practice, and variation in processes and outcomes of care between treating centres. The Australia and New Zealand Lung Cancer Registry (ANZLCR) will be developed as a Clinical Quality Registry to monitor the safety, quality and effectiveness of lung cancer care in Australia and New Zealand.

METHODS AND ANALYSIS

Patient participants will include all adults >18 years of age with a new diagnosis of non-small-cell lung cancer (NSCLC), SCLC, thymoma or mesothelioma. The ANZLCR will register confirmed diagnoses using opt-out consent. Data will address key patient, disease, management processes and outcomes reported as clinical quality indicators. Electronic data collection facilitated by local data collectors and local, state and federal data linkage will enhance completeness and accuracy. Data will be stored and maintained in a secure web-based data platform overseen by registry management. Central governance with binational representation from consumers, patients and carers, governance, administration, health department, health policy bodies, university research and healthcare workers will provide project oversight.

ETHICS AND DISSEMINATION

The ANZLCR has received national ethics approval under the National Mutual Acceptance scheme. Data will be routinely reported to participating sites describing performance against measures of agreed best practice and nationally to stakeholders including federal, state and territory departments of health. Local, regional and (bi)national benchmarks, augmented with online dashboard indicator reporting will enable local targeting of quality improvement efforts.

National learning systems to sustain and scale up delivery of quality healthcare: a conceptual framework

All around the world, health systems fail to provide good quality of care (QoC). By developing learning systems, health systems are able to better identify good practices and to explain how to sustain and scale these good practices. To facilitate the operationalisation of national learning systems, the Network for Improving Quality of Care for Maternal Newborn and Child Health (the Network) developed a conceptual framework for national learning systems to support QoC at scale. The Network facilitated an iterative process to reach consensus on a conceptual framework for national learning systems to sustain and scale up delivery of quality healthcare. Following a landscape analysis, the Network Secretariat and WHO convened two consultative meetings with country partners, technical experts and stakeholders. Based on these inputs, we developed a conceptual framework for national learning systems to support QoC at scale. National learning systems use a variety of approaches to identify practices that have improved QoC at the patient and provider levels. They also facilitate scale up and sustain strategies used successfully to support quality improvement. Despite growing consensus on the importance of learning for QoC, no one has yet detailed how this learning should be operationalised nationally. Our conceptual framework is the first to facilitate the operationalisation of national learning systems so that health systems can begin to develop, adapt and implement mechanisms to learn about what works or fails and to scale up and sustain this learning for QoC.

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.

WITHDRAWN: Designing a professional development online short course to foster Learning Healthcare Systems

This article has been withdrawn: please see Elsevier Policy on Article Withdrawal (http://www.elsevier.com/locate/withdrawalpolicy). This article has been withdrawn at the request of the editor and publisher. The publisher regrets that an error occurred which led to the premature publication of this paper. This error bears no reflection on the article or its authors. The publisher apologizes to the authors and the readers for this unfortunate error.

Learning Health Systems Can Promote and Sustain High-Value Occupational Therapy

In the current policy context, the occupational therapy profession must act to promote and sustain high-value care. Stakeholders have delineated efforts, such as defining and measuring high-quality care processes or promoting the adoption of evidence into practice, that can enhance the value of occupational therapy services. There is a growing recognition, however, that low-value care is the product of deficiencies within health care systems and is therefore most amenable to system-level solutions. To date, the specific nature of system-level changes capable of identifying and rectifying low-value occupational therapy has yet to be elucidated. In this "The Issue Is. . ." column, we introduce occupational therapy to the Learning Health System concept and its essential functions. Moreover, we discuss action steps for occupational therapy stakeholders to lay the foundation for Learning Health Systems in their own professional contexts. What This Article Adds: This article is the first to outline concrete action steps needed to transform occupational therapy practice contexts into Learning Health Systems. Such a transformation would represent a system-level change capable of fostering the delivery of high-value occupational therapy services to clients in a variety of practice settings.

The role of co-production in Learning Health Systems

Background

Co-production of health is defined as ‘the interdependent work of users and professionals who are creating, designing, producing, delivering, assessing, and evaluating the relationships and actions that contribute to the health of individuals and populations’. It can assume many forms and include multiple stakeholders in pursuit of continuous improvement, as in Learning Health Systems (LHSs). There is increasing interest in how the LHS concept allows integration of different knowledge domains to support and achieve better health. Even if definitions of LHSs include engaging users and their family as active participants in aspects of enabling better health for individuals and populations, LHS descriptions emphasize technological solutions, such as the use of information systems. Fewer LHS texts address how interpersonal interactions contribute to the design and improvement of healthcare services.

Objective

We examined the literature on LHS to clarify the role and contributions of co-production in LHS conceptualizations and applications.

Method

First, we undertook a scoping review of LHS conceptualizations. Second, we compared those conceptualizations to the characteristics of LHSs first described by the US Institute of Medicine. Third, we examined the LHS conceptualizations to assess how they bring four types of value co-creation in public services into play: co-production, co-design, co-construction and co-innovation. These were used to describe core ideas, as principles, to guide development.

Result

Among 17 identified LHS conceptualizations, 3 qualified as most comprehensive regarding fidelity to LHS characteristics and their use in multiple settings: (i) the Cincinnati Collaborative LHS Model, (ii) the Dartmouth Coproduction LHS Model and (iii) the Michigan Learning Cycle Model. These conceptualizations exhibit all four types of value co-creation, provide examples of how LHSs can harness co-production and are used to identify principles that can enhance value co-creation: (i) use a shared aim, (ii) navigate towards improved outcomes, (iii) tailor feedback with and for users, (iv) distribute leadership, (v) facilitate interactions, (vi) co-design services and (vii) support self-organization.

Conclusions

The LHS conceptualizations have common features and harness co-production to generate value for individual patients as well as for health systems. They facilitate learning and improvement by integrating supportive technologies into the sociotechnical systems that make up healthcare. Further research on LHS applications in real-world complex settings is needed to unpack how LHSs are grown through coproduction and other types of value co-creation.

A roadmap to operationalize and evaluate impact in a learning health system

BACKGROUND

Many health systems invest in initiatives to accelerate translation of knowledge into practice. However, organizations lack guidance on how to develop and operationalize such Learning Health System (LHS) programs and evaluate their impact. Kaiser Permanente Washington (KPWA) launched our LHS program in June 2017 and developed a logic model as a foundation to evaluate the program's impact.

OBJECTIVE

To develop a roadmap for organizations that want to establish an LHS program, understand how LHS core components relate to one another when operationalized in practice, and evaluate and improve their progress.

METHODS

We conducted a narrative review on LHS models, key model components, and measurement approaches.

RESULTS

The KPWA LHS Logic Model provides a broad set of constructs relevant to LHS programs, depicts their relationship to LHS operations, harmonizes terms across models, and offers measurable operationalizations of each construct to guide other health systems. The model identifies essential LHS inputs, provides transparency into LHS activities, and defines key outcomes to evaluate LHS processes and impact. We provide reflections on the most helpful components of the model and identify areas that need further improvement using illustrative examples from deployment of the LHS model during the COVID-19 pandemic.

CONCLUSION

The KPWA LHS Logic Model is a starting point for future LHS implementation research and a practical guide for healthcare organizations that are building, operationalizing, and evaluating LHS initiatives.

Embedding Learning in a Learning Health Care System to Improve Clinical Practice

PROBLEM

In an ideal learning health care system (LHS), clinicians learn from what they do and do what they learn, closing the evidence-to-practice gap. In operationalizing an LHS, great strides have been made in knowledge generation. Yet, considerable challenges remain to the broad uptake of identified best practices. To bridge the gap from generating actionable knowledge to applying that knowledge in clinical practice, and ultimately to improving outcomes, new information must be disseminated to and implemented by frontline clinicians. To date, the dissemination of this knowledge through traditional avenues has not achieved meaningful practice change quickly.

APPROACH

Vanderbilt University Medical Center (VUMC) developed QuizTime, a smartphone application learning platform, to provide a mechanism for embedding workplace-based clinician learning in the LHS. QuizTime leverages spaced education and retrieval-based practice to facilitate practice change. Beginning in January 2020, clinician-researchers and educators at VUMC designed a randomized, controlled trial to test whether the QuizTime learning system influenced clinician behavior in the context of recent evidence supporting the use of balanced crystalloids rather than saline for intravenous fluid management and new regulations around opioid prescribing.

OUTCOMES

Whether spaced education and retrieval-based practice influence clinician behavior and patient outcomes at the VUMC system level will be tested using the data currently being collected.

NEXT STEPS

These findings will inform future directions for developing and deploying learning approaches at scale in an LHS, with the goal of closing the evidence-to-practice gap.

Learning health systems: Driving real-world impact in mental health and substance use disorder research

The Veterans Health Administration (VHA), under the U.S. Department of Veterans Affairs (VA), is one of the largest single providers of health care in the U.S. VA supports an embedded research program that addresses VA clinical priorities in close partnership with operations leaders, which is a hallmark of a Learning Health System (LHS). Using the LHS framework, we describe current VA research initiatives in mental health and substance use disorders that rigorously evaluate national programs and policies designed to reduce the risk of suicide and opioid use disorder (data to knowledge); test implementation strategies to improve the spread of effective programs for Veterans at risk of suicide or opioid use disorder (knowledge to performance); and identify novel research directions in suicide prevention and opioid/pain treatments emanating from implementation and quality improvement research (performance to data). Lessons learned are encapsulated into best practices for building and sustaining an LHS within health systems, including the need for early engagement with clinical leaders; pragmatic research questions that focus on continuous improvement; multi-level, ongoing input from regional and local stakeholders, and business case analyses to inform ongoing investment in sustainable infrastructure to maintain the research-health system partnership. Essential ingredients for supporting VA as an LHS include data and information sharing capacity, protected time for researchers and leaders, and governance structures to enhance health system ownership of research findings. For researchers, incentives to work with health systems operations (e.g., retainer funding) are vital for LHS research to be recognized and valued by academic promotion committees.

Recommendations for strengthening the role of embedded researchers to accelerate implementation in health systems: Findings from a state-of-the-art (SOTA) conference workgroup

BACKGROUND

Traditional research approaches do not promote timely implementation of evidence-based innovations (EBIs) to benefit patients. Embedding research within health systems can accelerate EBI implementation by blending rigorous methods with practical considerations in real-world settings. A state-of-the-art (SOTA) conference was convened in February 2019 with five workgroups that addressed five facets of embedded research and its potential to impact healthcare. This article reports on results from the workgroup focused on how embedded research programs can be implemented into heath systems for greatest impact.

METHODS

Based on a pre-conference survey, participants indicating interest in accelerating implementation were invited to participate in the SOTA workgroup. Workgroup participants (N = 26) developed recommendations using consensus-building methods. Ideas were grouped by thematic clusters and voted on to identify top recommendations. A summary was presented to the full SOTA membership. Following the conference, the workgroup facilitators (LJD, CDH, NR) summarized workgroup findings, member-checked with workgroup members, and were used to develop recommendations.

RESULTS

The workgroup developed 12 recommendations to optimize impact of embedded researchers within health systems. The group highlighted the tension between "ROI vs. R01" goals-where health systems focus on achieving return on their investments (ROI) while embedded researchers focus on obtaining research funding (R01). Recommendations are targeted to three key stakeholder groups: researchers, funders, and health systems. Consensus for an ideal foundation to support optimal embedded research is one that (1) maximizes learning; (2) aligns goals across all 3 stakeholders; and (3) implements EBIs in a consistent and timely fashion.

CONCLUSIONS

Four cases illustrate a variety of ways that embedded research can be structured and conducted within systems, by demonstrating key embedded research values to enable collaborations with academic affiliates to generate actionable knowledge and meaningfully accelerate implementation of EBIs to benefit patients.

IMPLICATIONS

Embedded research approaches have potential for transforming health systems and impacting patient health. Accelerating embedded research should be a focused priority for funding agencies to maximize a collective return on investment.

Opportunities and challenges for the computational interpretation of rare variation in clinically important genes

Genome sequencing is enabling precision medicine-tailoring treatment to the unique constellation of variants in an individual's genome. The impact of recurrent pathogenic variants is often understood, however there is a long tail of rare genetic variants that are uncharacterized. The problem of uncharacterized rare variation is especially acute when it occurs in genes of known clinical importance with functionally consequential variants and associated mechanisms. Variants of uncertain significance (VUSs) in these genes are discovered at a rate that outpaces current ability to classify them with databases of previous cases, experimental evaluation, and computational predictors. Clinicians are thus left without guidance about the significance of variants that may have actionable consequences. Computational prediction of the impact of rare genetic variation is increasingly becoming an important capability. In this paper, we review the technical and ethical challenges of interpreting the function of rare variants in two settings: inborn errors of metabolism in newborns and pharmacogenomics. We propose a framework for a genomic learning healthcare system with an initial focus on early-onset treatable disease in newborns and actionable pharmacogenomics. We argue that (1) a genomic learning healthcare system must allow for continuous collection and assessment of rare variants, (2) emerging machine learning methods will enable algorithms to predict the clinical impact of rare variants on protein function, and (3) ethical considerations must inform the construction and deployment of all rare-variation triage strategies, particularly with respect to health disparities arising from unbalanced ancestry representation.

Implementation and Impact of a Risk-Stratified Prostate Cancer Screening Algorithm as a Clinical Decision Support Tool in a Primary Care Network

BACKGROUND

Implementation methods of risk-stratified cancer screening guidance throughout a health care system remains understudied.

OBJECTIVE

Conduct a preliminary analysis of the implementation of a risk-stratified prostate cancer screening algorithm in a single health care system.

DESIGN

Comparison of men seen pre-implementation (2/1/2016-2/1/2017) vs. post-implementation (2/2/2017-2/21/2018).

PARTICIPANTS

Men, aged 40-75 years, without a history of prostate cancer, who were seen by a primary care provider.

INTERVENTIONS

The algorithm was integrated into two components in the electronic health record (EHR): in Health Maintenance as a personalized screening reminder and in tailored messages to providers that accompanied prostate-specific antigen (PSA) results.

MAIN MEASURES

Primary outcomes: percent of men who met screening algorithm criteria; percent of men with a PSA result. Logistic repeated measures mixed models were used to test for differences in the proportion of individuals that met screening criteria in the pre- and post-implementation periods with age, race, family history, and PSA level included as covariates.

KEY RESULTS

During the pre- and post-implementation periods, 49,053 and 49,980 men, respectively, were seen across 26 clinics (20.6% African American). The proportion of men who met screening algorithm criteria increased from 49.3% (pre-implementation) to 68.0% (post-implementation) (p < 0.001); this increase was observed across all races, age groups, and primary care clinics. Importantly, the percent of men who had a PSA did not change: 55.3% pre-implementation, 55.0% post-implementation. The adjusted odds of meeting algorithm-based screening was 6.5-times higher in the post-implementation period than in the pre-implementation period (95% confidence interval, 5.97 to 7.05).

CONCLUSIONS

In this preliminary analysis, following implementation of an EHR-based algorithm, we observed a rapid change in practice with an increase in screening in higher-risk groups balanced with a decrease in screening in low-risk groups. Future efforts will evaluate costs and downstream outcomes of this strategy.

Developing an Institute for Health Care Delivery Science: successes, challenges, and solutions in the first five years

Medical knowledge is increasing at an exponential rate. At the same time, unexplained variations in practice and patient outcomes and unacceptable rates of medical errors and inefficiencies in health care delivery have emerged. Our Institute for Health Care Delivery Science (I-HDS) began in 2014 as a novel platform to conduct multidisciplinary healthcare delivery research. We followed ten strategies to develop a successful institute with excellence in methodology and strong understanding of the value of team science. Our work was organized around five hubs: 1) Quality/Process Improvement and Systematic Review, 2) Comparative Effectiveness Research, Pragmatic Clinical Trials, and Predictive Analytics, 3) Health Economics and Decision Modeling, 4) Qualitative, Survey, and Mixed Methods, and 5) Training and Mentoring. In the first 5 years of the I-HDS, we have identified opportunities for change in clinical practice through research using our health system's electronic health record (EHR) data, and designed programs to educate clinicians in the value of research to improve patient care and recognize efficiencies in processes. Testing the value of several model interventions has guided prioritization of evidence-based quality improvements. Some of the changes in practice have already been embedded in the EHR workflow successfully. Development and sustainability of the I-HDS has been fostered by a mix of internal and external funding, including philanthropic foundations. Challenges remain due to the highly competitive funding environment and changes needed to adapt the EHR to healthcare delivery research. Further stakeholder engagement and culture change working with hospital leadership and I-HDS core and affiliate members continues.

Sequential implementation of the EQUIPPED geriatric medication safety program as a learning health system

OBJECTIVES

To present the three-site EQUIPPED academic health system research collaborative, which engaged in sequential implementation of the EQUIPPED medication safety program, as a learning health system; to understand how the organizations worked together to build resources for program scale-up.

DESIGN

Following the Replicating Effective Programs framework, we analyzed content from implementation teams' focus groups, local and cross-site meeting minutes and sites' organizational profiles to develop an implementation package.

SETTING

Three academic emergency departments that each implemented EQUIPPED over three successive years.

PARTICIPANTS

Implementation team members at each site participating in focus groups (n = 18), local meetings during implementation years, and cross-site meetings during all years of the projects.

INTERVENTION(S)

EQUIPPED provides Emergency Department providers with clinical decision support (education, order sets, and feedback) to reduce prescribing of potentially inappropriate medications to adults aged 65 years and older who received a prescription at time of discharge.

MAIN OUTCOME MEASURE(S)

Implementation process components assembled through successive implementation.

RESULTS

Each site had clinical and environmental characteristics to be addressed in implementing the EQUIPPED program. We identified 10 process elements and describe lessons for each. Lessons guided the compilation of the EQUIPPED intervention package or toolkit, including the EQUIPPED logic model.

CONCLUSIONS

Our academic health system research collaborative addressing medication safety through sequential implementation is a learning health system that can serve as a model for other quality improvement projects with multiple sites. The network produced an implementation package that can be vetted, piloted, evaluated, and finalized for large-scale dissemination in community-based settings.

Making NSCLC Crystal Clear: How Kinase Structures Revolutionized Lung Cancer Treatment

The parallel advances of different scientific fields provide a contemporary scenario where collaboration is not a differential, but actually a requirement. In this context, crystallography has had a major contribution on the medical sciences, providing a “face” for targets of diseases that previously were known solely by name or sequence. Worldwide, cancer still leads the number of annual deaths, with 9.6 million associated deaths, with a major contribution from lung cancer and its 1.7 million deaths. Since the relationship between cancer and kinases was unraveled, these proteins have been extensively explored and became associated with drugs that later attained blockbuster status. Crystallographic structures of kinases related to lung cancer and their developed and marketed drugs provided insight on their conformation in the absence or presence of small molecules. Notwithstanding, these structures were also of service once the initially highly successful drugs started to lose their effectiveness in the emergence of mutations. This review focuses on a subclassification of lung cancer, non-small cell lung cancer (NSCLC), and major oncogenic driver mutations in kinases, and how crystallographic structures can be used, not only to provide awareness of the function and inhibition of these mutations, but also how these structures can be used in further computational studies aiming at addressing these novel mutations in the field of personalized medicine.

Clinical decision trees support systematic evaluation of multidisciplinary team recommendations

Purpose

EUSOMA’s recommendation that “each patient has to be fully informed about each step in the diagnostic and therapeutic pathway” could be supported by guideline-based clinical decision trees (CDTs). The Dutch breast cancer guideline has been modeled into CDTs (www.oncoguide.nl). Prerequisites for adequate CDT usage are availability of necessary patient data at the time of decision-making and to consider all possible treatment alternatives provided in the CDT.

Methods

This retrospective single-center study evaluated 394 randomly selected female patients with non-metastatic breast cancer between 2012 and 2015. Four pivotal CDTs were selected. Two researchers analyzed patient records to determine to which degree patient data required per CDT were available at the time of multidisciplinary team (MDT) meeting and how often multiple alternatives were actually reported.

Results

The four selected CDTs were indication for magnetic resonance imaging (MRI) scan, preoperative and adjuvant systemic treatment, and immediate breast reconstruction. For 70%, 13%, 97% and 13% of patients, respectively, all necessary data were available. The two most frequent underreported data-items were “clinical M-stage” (87%) and “assessable mammography” (28%). Treatment alternatives were reported by MDTs in 32% of patients regarding primary treatment and in 28% regarding breast reconstruction.

Conclusion

Both the availability of data in patient records essential for guideline-based recommendations and the reporting of possible treatment alternatives of the investigated CDTs were low. To meet EUSOMA’s requirements, information that is supposed to be implicitly known must be explicated by MDTs. Moreover, MDTs have to adhere to clear definitions of data-items in their reporting.

Quality Enhancement Research Initiative Implementation Roadmap: Toward Sustainability of Evidence-based Practices in a Learning Health System

BACKGROUND

Learning Health Systems strive to continuously integrate innovations and evidence-based practices (EBPs) into routine care settings. Few models provide a specified pathway to accelerate adoption and spread of EBPs across diverse settings.

OBJECTIVE

The US Department of Veterans Affairs Quality Enhancement Research Initiative (QUERI) Implementation Roadmap facilitates uptake of EBPs in routine practice by aligning research and health system priorities.

METHODS

The Roadmap is based on earlier iterations of the QUERI translational research pipeline, incorporating recent advancements in quality improvement and implementation science. Progressive, dynamic phases were operationalized to form an implementation process that promoted a participatory approach which enables stakeholders (health care consumers, clinicians, administrators, and leaders) to systematically plan, deploy, evaluate, and sustain EBPs using implementation strategies within a Learning Health System framework.

RESULTS

The Roadmap consists of Preimplementation, Implementation, and Sustainment phases. Preimplementation identifies a high-priority need, selects EBPs to address the need, engages stakeholders to build implementation capacity, specifies needed EBP adaptions and evaluation goals, and activates leadership support. During Implementation, clinical and research leaders use implementation strategies to promote EBP technical competency and adaptive skills to motivate providers to own and sustain EBPs. Sustainment includes evaluation analyses that establish the EBP business case, and hand-off to system leadership to own EBP implementation maintenance over time.

CONCLUSIONS

The QUERI Implementation Roadmap systematically guides identification, implementation, and sustainment of EBPs, demystifying implementation science for stakeholders in a Learning Health System to ensure that EBPs are more rapidly implemented into practice to improve overall consumer health.

Accelerating implementation of research in Learning Health Systems: Lessons learned from VA Health Services Research and NCATS Clinical Science Translation Award programs

Translation of research to practice is challenging. In addition to the scientific challenges, there are additional hurdles in navigating the rapidly changing US health care system. There is a need for innovative health interventions that can be adopted in "real-world" settings. Barriers to translation involve misaligned timing of research funding and health system decision-making, lack of research questions aligned with health system and community priorities, and limited incentives in academia for health system and community-based research. We describe new programs from the US Department of Veterans Affairs Health Services Research and Development (HSR&D) and the National Center for Advancing Translational Sciences (NCATS) Clinical and Translational Science Award (CTSA) Programs that are building capacity for Learning Health System research. These programs help to incentivize adopting and adapting Learning Health System principles to ensure that, primarily in implementation science within academic/veterans affairs health systems, there is alignment of the research with the health system and community needs. Both HSR&D and NCATS CTSA Program encourage researchers to develop problem-focused research innovations in partnership with health systems and communities to ultimately facilitate design treatments that are feasible in "real-world" practice.

Cumulative network meta-analyses, practice guidelines, and actual prescriptions for postmenopausal osteoporosis: a meta-epidemiological study

We compared the cumulative network meta-analyses with the recommendations in postmenopausal osteoporosis practice guidelines and actual prescribing practices in the USA. There was no apparent discrepancy between guideline recommendations and drug prescribing rankings, with the exception of vitamin D and calcium, when we used cumulative NMAs as references.

PURPOSE

To compare the results of cumulative network meta-analyses (NMAs) with the recommendations in postmenopausal osteoporosis practice guidelines and actual prescribing practices in the USA.

METHODS

MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, Web of Science, and Scopus were searched to retrieve randomized controlled trials (RCTs) in July 2017. The Agency for Healthcare Research and Quality's National Guideline Clearinghouse and associated society websites were searched to retrieve guidelines in June 2018. We used the Medical Expenditure Panel Survey (MEPS) to analyze prescription data from 1996 to 2015. Two independent investigators selected eligible RCTs. One investigator selected potential eligible guidelines, which were confirmed by another investigator. Two independent investigators extracted data from included RCTs. One investigator extracted recommendations from guidelines, which were confirmed by another investigator. (Registration: UMIN000031894) RESULTS: We analyzed data from 1995, 2000, 2005, 2010, and 2015. We chose hip fracture as the primary outcome of cumulative NMAs. We included 51 trials, 17 guidelines, and 5099 postmenopausal osteoporosis patients from the MEPS. Bisphosphonate, including alendronate, and combination of vitamin D and calcium (vDCa) were consistently recommendable from an efficacy viewpoint in NMAs and recommended in guidelines. Alendronate was the most prescribed drug (more than 30% over the observation period); however, vDCa was seldom prescribed. The maximum proportion was 5.3% from 2011 to 2015.

CONCLUSIONS

In postmenopausal osteoporosis, there was no apparent discrepancy between guideline recommendations and drug prescribing rankings, with the exception of vDCa, when we used cumulative NMAs as references.

Understanding the roles of three academic communities in a prospective learning health ecosystem for diagnostic excellence

Inaccurate, untimely, and miscommunicated medical diagnoses represent a wicked problem requiring comprehensive and coordinated approaches, such as those demonstrated in the characteristics of learning health systems (LHSs). To appreciate a vision for how LHS methods can optimize processes and outcomes in medical diagnosis (diagnostic excellence), we interviewed 32 individuals with relevant expertise: 18 who have studied diagnostic processes using traditional behavioral science and health services research methods, six focused on machine learning (ML) and artificial intelligence (AI) approaches, and eight multidisciplinary researchers experienced in advocating for and incorporating LHS methods, ie, scalable continuous learning in health care. We report on barriers and facilitators, identified by these subjects, to applying their methods toward optimizing medical diagnosis. We then employ their insights to envision the emergence of a learning ecosystem that leverages the tools of each of the three research groups to advance diagnostic excellence. We found that these communities represent a natural fit forward, in which together, they can better measure diagnostic processes and close the loop of putting insights into practice. Members of the three academic communities will need to network and bring in additional stakeholders before they can design and implement the necessary infrastructure that would support ongoing learning of diagnostic processes at an economy of scale and scope.

The MEGNA Score and Preoperative Anemia are Major Prognostic Factors After Resection in the German Intrahepatic Cholangiocarcinoma Cohort

BACKGROUND

Surgical resection is associated with the best long-term results for intrahepatic cholangiocarcinoma (ICC); however, long-term outcomes are still poor.

OBJECTIVE

The primary aim of this study was to validate the recently proposed MEGNA score and to identify additional prognostic factors influencing short- and long-term survival.

PATIENTS AND METHODS

This was a retrospective analysis of a German multicenter cohort operated at 10 tertiary centers from 2004 to 2013. Patients were clustered using the MEGNA score and overall survival was analyzed. Cox regression analysis was used to identify prognostic factors for both overall and 90-day survival.

RESULTS

A total of 488 patients undergoing liver resection for ICC fulfilled the inclusion criteria and underwent analysis. Median age was 67 years, 72.5% of patients underwent major hepatic resection, and the lymphadenectomy rate was 86.9%. Median overall survival was 32.2 months. The MEGNA score significantly discriminated the long-term overall survival: 0 (68%), I (48%), II (32%), and III (19%) [p <0.001]. In addition, anemia was an independent prognostic factor for overall survival (hazard ratio 1.78, 95% confidence interval 1.29-2.45; p <0.01).

CONCLUSION

Hepatic resection provides the best long-term survival in all risk groups (19-65% overall survival). The MEGNA score is a good discriminator using histopathologic items and age for stratification. Correction of anemia should be attempted in every patient who responds to treatment. Perioperative liver failure remains a clinical challenge and contributes to a relevant number of perioperative deaths.