Purpose The significant individual and societal burden of work disability could be reduced if supportive workplace strategies could be added to evidence-based clinical treatment and rehabilitation to improve return-to-work (RTW) and other disability outcomes. The goal of this article is to summarize existing research on workplace interventions to prevent disability, relate these to employer disability management practices, and recommend future research priorities. Methods The authors participated in a year-long collaboration that ultimately led to an invited 3-day conference, Improving Research of Employer Practices to Prevent Disability, held October 14–16, 2015, in Hopkinton, Massachusetts, USA. The collaboration included a topical review of the literature, group conference calls to identify key areas and challenges, drafting of initial documents, review of industry publications, and a conference presentation that included feedback from peer researchers and a question/answer session with an expert panel with direct employer experience. Results Evidence from randomized trials and other research designs has shown general support for job modification, RTW coordination, and organizational support, but evidence is still lacking for interventions at a more granular level. Grey literature reports focused mainly on job re-design and work organization. Panel feedback focused on organizational readiness and the beliefs and values of senior managers as critical factors in facilitating changes to disability management practices. While the scientific literature is focused on facilitating improved coping and reducing discomforts for individual workers, the employer-directed grey literature is focused on making group-level changes to policies and procedures. Conclusions Future research might better target employer practices by tying interventions to positive workplace influences and determinants, by developing more participatory interventions and research designs, and by designing interventions that address factors of organizational change.Electronic supplementary materialThe online version of this article (doi:10.1007/s10926-016-9664-z) contains supplementary material, which is available to authorized users.
Purpose We aimed to identify and inventory clinical decision support (CDS) tools for helping front-line staff select interventions for patients with musculoskeletal (MSK) disorders. Methods We used Arksey and O’Malley’s scoping review framework which progresses through five stages: (1) identifying the research question; (2) identifying relevant studies; (3) selecting studies for analysis; (4) charting the data; and (5) collating, summarizing and reporting results. We considered computer-based, and other available tools, such as algorithms, care pathways, rules and models. Since this research crosses multiple disciplines, we searched health care, computing science and business databases. Results Our search resulted in 4605 manuscripts. Titles and abstracts were screened for relevance. The reliability of the screening process was high with an average percentage of agreement of 92.3 %. Of the located articles, 123 were considered relevant. Within this literature, there were 43 CDS tools located. These were classified into 3 main areas: computer-based tools/questionnaires (n = 8, 19 %), treatment algorithms/models (n = 14, 33 %), and clinical prediction rules/classification systems (n = 21, 49 %). Each of these areas and the associated evidence are described. The state of evidentiary support for CDS tools is still preliminary and lacks external validation, head-to-head comparisons, or evidence of generalizability across different populations and settings. Conclusions CDS tools, especially those employing rapidly advancing computer technologies, are under development and of potential interest to health care providers, case management organizations and funders of care. Based on the results of this scoping review, we conclude that these tools, models and systems should be subjected to further validation before they can be recommended for large-scale implementation for managing patients with MSK disorders.
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