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      Capturing the patient voice: implementing patient-reported outcomes across the health system

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          Abstract

          Purpose

          Supporting the capture and use of patient-reported outcomes (PROs) at the point-of-care enriches information about important clinical and quality of life outcomes. Yet the ability to scale PROs across healthcare systems has been limited by knowledge gaps around how to manage the diversity of PRO uses and leverage health information technology. In this study, we report learnings and practice insights from UW Medicine’s practice transformation efforts to incorporate patient voice into multiple areas of care.

          Methods

          Using a participatory, action research approach, we engaged with UW Medicine clinical and administrative stakeholders experienced with PRO implementation to inventory PRO implementations across the health system, characterize common clinical uses for PROs, and develop recommendations for system-wide governance and implementation of PROs.

          Results

          We identified a wide breadth of PRO implementations ( n = 14) in practice and found that nearly half (47%) of employed PRO measures captured shared clinical domains (e.g., depression). We developed three vignettes (use cases) that illustrate how users interact with PROs, characterize common ways PRO implementations support clinical care across the health system (1) Preventive care, (2) Chronic/Specialty care, and (3) Surgical/Interventional care), and elucidate opportunities to enhance efficient PRO implementations through system-level standards and governance.

          Conclusions

          Practice transformation efforts increasingly require integration of the patient voice into clinical care, often through the use of PROs. Learnings from our work highlight the importance of proactively considering how PROs will be used across the layers of healthcare organizations to optimize the design and governance of PROs.

          Electronic supplementary material

          The online version of this article (10.1007/s11136-019-02320-8) contains supplementary material, which is available to authorized users.

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          Most cited references22

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          Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations

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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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              Patient-Reported Outcomes - Harnessing Patients' Voices to Improve Clinical Care.

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                Author and article information

                Contributors
                austie@uw.edu
                clerouge@fiu.edu
                andreah@uw.edu
                segalc@uw.edu
                lavallee@uw.edu
                Journal
                Qual Life Res
                Qual Life Res
                Quality of Life Research
                Springer International Publishing (Cham )
                0962-9343
                1573-2649
                12 October 2019
                12 October 2019
                2020
                : 29
                : 2
                : 347-355
                Affiliations
                [1 ]GRID grid.34477.33, ISNI 0000000122986657, Surgical Outcomes Research Center, , University of Washington, ; 1107 NE 45th Street, Suite 502, Box 354808, Seattle, WA 98105 USA
                [2 ]GRID grid.65456.34, ISNI 0000 0001 2110 1845, Information Systems and Business Analytics, , Florida International University, ; Miami, FL USA
                [3 ]GRID grid.34477.33, ISNI 0000000122986657, Department of Health Services, , University of Washington, ; Seattle, WA USA
                [4 ]GRID grid.34477.33, ISNI 0000000122986657, Department of Biomedical Informatics and Medical Education, , University of Washington, ; Seattle, WA USA
                Author information
                http://orcid.org/0000-0002-4221-1362
                Article
                2320
                10.1007/s11136-019-02320-8
                6995985
                31606809
                b25cf40e-bab9-4971-a2a7-f3dc791f3f2e
                © The Author(s) 2019

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

                History
                : 26 September 2019
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000133, Agency for Healthcare Research and Quality;
                Award ID: R01HS023785
                Award Recipient :
                Categories
                Article
                Custom metadata
                © Springer Nature Switzerland AG 2020

                Public health
                patient-reported outcomes,patient engagement,depression,care transformation,action research,implementation

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