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      A learning health systems approach to integrating electronic patient‐reported outcomes across the health care organization

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          Abstract

          Introduction

          Foundational to a learning health system (LHS) is the presence of a data infrastructure that can support continuous learning and improve patient outcomes. To advance their capacity to drive patient‐centered care, health systems are increasingly looking to expand the electronic capture of patient data, such as electronic patient‐reported outcome (ePRO) measures. Yet ePROs bring unique considerations around workflow, measurement, and technology that health systems may not be poised to navigate. We report on our effort to develop generalizable learnings that can support the integration of ePROs into clinical practice within an LHS framework.

          Methods

          Guided by action research methodology, we engaged in iterative cycles of planning, acting, observing, and reflecting around ePRO use with two primary goals: (1) mobilize an ePRO community of practice to facilitate knowledge sharing, and (2) establish guidelines for ePRO use in the context of LHS practice. Multiple, emergent data collection activities generated generalizable guidelines that document the tangible best practices for ePRO use in clinical care. We organized guidelines around thematic areas that reflect LHS structures and stakeholders.

          Results

          Three core thematic areas (and 24 guidelines) emerged. The theme of governance reflects the importance of leadership, knowledge management, and facilitating organizational learning around best practice models for ePRO use. The theme of integration considers the intersection of workflow, technology, and human factors for ePROs across areas of care delivery. Lastly, the theme of reporting reflects critical considerations for curating data and information, designing system functions and interactions, and presentation of ePRO data to support the translation of knowledge to action.

          Conclusions

          The guidelines produced from this work highlight the complex, multidisciplinary nature of implementing change within LHS contexts, and the value of action research approaches to enable rapid, iterative learning that leverages the knowledge and experience of communities of practice.

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          Most cited references26

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          The values and value of patient-centered care.

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            A new sociotechnical model for studying health information technology in complex adaptive healthcare systems.

            Conceptual models have been developed to address challenges inherent in studying health information technology (HIT). This manuscript introduces an eight-dimensional model specifically designed to address the sociotechnical challenges involved in design, development, implementation, use and evaluation of HIT within complex adaptive healthcare systems. The eight dimensions are not independent, sequential or hierarchical, but rather are interdependent and inter-related concepts similar to compositions of other complex adaptive systems. Hardware and software computing infrastructure refers to equipment and software used to power, support and operate clinical applications and devices. Clinical content refers to textual or numeric data and images that constitute the 'language' of clinical applications. The human--computer interface includes all aspects of the computer that users can see, touch or hear as they interact with it. People refers to everyone who interacts in some way with the system, from developer to end user, including potential patient-users. Workflow and communication are the processes or steps involved in ensuring that patient care tasks are carried out effectively. Two additional dimensions of the model are internal organisational features (eg, policies, procedures and culture) and external rules and regulations, both of which may facilitate or constrain many aspects of the preceding dimensions. The final dimension is measurement and monitoring, which refers to the process of measuring and evaluating both intended and unintended consequences of HIT implementation and use. We illustrate how our model has been successfully applied in real-world complex adaptive settings to understand and improve HIT applications at various stages of development and implementation.
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              Toward a science of learning systems: a research agenda for the high-functioning Learning Health System

              Objective The capability to share data, and harness its potential to generate knowledge rapidly and inform decisions, can have transformative effects that improve health. The infrastructure to achieve this goal at scale—marrying technology, process, and policy—is commonly referred to as the Learning Health System (LHS). Achieving an LHS raises numerous scientific challenges. Materials and methods The National Science Foundation convened an invitational workshop to identify the fundamental scientific and engineering research challenges to achieving a national-scale LHS. The workshop was planned by a 12-member committee and ultimately engaged 45 prominent researchers spanning multiple disciplines over 2 days in Washington, DC on 11–12 April 2013. Results The workshop participants collectively identified 106 research questions organized around four system-level requirements that a high-functioning LHS must satisfy. The workshop participants also identified a new cross-disciplinary integrative science of cyber-social ecosystems that will be required to address these challenges. Conclusions The intellectual merit and potential broad impacts of the innovations that will be driven by investments in an LHS are of great potential significance. The specific research questions that emerged from the workshop, alongside the potential for diverse communities to assemble to address them through a ‘new science of learning systems’, create an important agenda for informatics and related disciplines.
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                Author and article information

                Contributors
                austie@uw.edu
                Journal
                Learn Health Syst
                Learn Health Syst
                10.1002/(ISSN)2379-6146
                LRH2
                Learning Health Systems
                John Wiley and Sons Inc. (Hoboken )
                2379-6146
                01 March 2021
                October 2021
                : 5
                : 4 ( doiID: 10.1002/lrh2.v5.4 )
                : e10263
                Affiliations
                [ 1 ] Surgical Outcomes Research Center, Department of Surgery University of Washington Seattle Washington USA
                [ 2 ] Department of Health Services University of Washington Seattle Washington USA
                [ 3 ] Information Systems and Business Analytics Florida International University Miami Florida USA
                [ 4 ] Department of Biomedical Informatics and Medical Education University of Washington Seattle Washington USA
                [ 5 ] Department of Industrial & Systems Engineering, College of Engineering University of Washington Seattle Washington USA
                [ 6 ] Biobehavioral Nursing and Health Informatics University of Washington Seattle Washington USA
                Author notes
                [*] [* ] Correspondence

                Elizabeth J. Austin, Research Scientist, University of Washington, 1107 NE 45th Street, Suite 502, Box 354808, Seattle, WA 98105.

                Email: austie@ 123456uw.edu

                Author information
                https://orcid.org/0000-0002-4221-1362
                Article
                LRH210263
                10.1002/lrh2.10263
                8512814
                34667879
                16408051-4007-42f7-9fa4-8795475a9534
                © 2021 The Authors. Learning Health Systems published by Wiley Periodicals LLC on behalf of University of Michigan.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                History
                : 20 January 2021
                : 02 November 2020
                : 15 February 2021
                Page count
                Figures: 1, Tables: 4, Pages: 10, Words: 7269
                Funding
                Funded by: Agency for Healthcare Research and Quality , doi 10.13039/100000133;
                Award ID: R01HS023785
                Categories
                Experience Report
                Experience Reports
                Custom metadata
                2.0
                October 2021
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.0.8 mode:remove_FC converted:13.10.2021

                learning health system,patient‐facing technologies,patient‐reported outcomes,stakeholder engagement

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