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      Reliability and validity of the Veterans Administration Mobility Screening and Solutions Tool

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          Abstract

          Objectives

          The Veterans Administration (VA) Mobility Screening and Solutions Tool (VA MSST) was developed to screen a patient’s safe mobility level ‘in the moment’ and provide clinical decision support related to the use of safe patient handling and mobility (SPHM) equipment. This evidence-based flowchart tool is a common language tool that enables any healthcare worker at any time to accurately measure and communicate patient mobility and transfer equipment needs across disciplines and settings.

          Methods

          The VA MSST has four levels and differentiates between the need for powered and non-powered equipment depending on the patient’s independence. Subject matter experts wrote scenarios for interrater reliability and validity testing. The initial VA MSST draft iteration was reviewed by 163 VA staff (mostly physical therapists and occupational therapists) amongst simulation scenarios and provided content validity, and additional insight and suggestions. Revisions were made to create the final VA MSST which was evaluated by over 200 healthcare workers from varied disciplines (including medical doctors, advanced practice registered nurses, registered nurses, licensed practical nurses, certified nursing assistants, occupational therapists, physical therapists, speech therapists, radiology and ultrasound technicians, etc.). An instruction video and eighteen scenario videos were embedded in an online survey. The survey intended to demonstrate the interrater reliability and validity (concurrent and construct) of the VA MSST. Over 500 VA staff (raters) received a survey invitation via email.

          Results

          Raters ( N = 230) from multiple disciplines and healthcare settings independently screened patient mobility status for each of 18 scenarios using the VA MSST. The raters were diverse in their age and years of experience. The estimated interrater reliability (IRR) for VA MSST was excellent and statistically significant with an estimated Krippendorff’s alpha (ICC (C, k)) of 0.998 [ 95% CI: 0.996–0.999]. Eighty-two percent of raters reported that overall VA MSST instructions were clear or very clear and understandable. VA MSST ratings made by technicians and nursing assistants group correlated strongly (r = 0.99, p < 0.001) with the ‘gold standard’ (experienced physical therapists), suggesting a high concurrent validity of the tool. The VA MSST significantly discriminated between the different levels of patient mobility required for safe mobilization as intended (each difference, p < 0.0001); this suggests a good construct validity.

          Conclusions

          The VA MSST is an evidence-based flowchart screening and decision support tool that demonstrates excellent interrater reliability across disciplines and settings. VA MSST has strong face and content validity, as well as good concurrent and construct validity.

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          Most cited references12

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          Answering the Call for a Standard Reliability Measure for Coding Data

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            Measuring inter-rater reliability for nominal data – which coefficients and confidence intervals are appropriate?

            Background Reliability of measurements is a prerequisite of medical research. For nominal data, Fleiss’ kappa (in the following labelled as Fleiss’ K) and Krippendorff’s alpha provide the highest flexibility of the available reliability measures with respect to number of raters and categories. Our aim was to investigate which measures and which confidence intervals provide the best statistical properties for the assessment of inter-rater reliability in different situations. Methods We performed a large simulation study to investigate the precision of the estimates for Fleiss’ K and Krippendorff’s alpha and to determine the empirical coverage probability of the corresponding confidence intervals (asymptotic for Fleiss’ K and bootstrap for both measures). Furthermore, we compared measures and confidence intervals in a real world case study. Results Point estimates of Fleiss’ K and Krippendorff’s alpha did not differ from each other in all scenarios. In the case of missing data (completely at random), Krippendorff’s alpha provided stable estimates, while the complete case analysis approach for Fleiss’ K led to biased estimates. For shifted null hypotheses, the coverage probability of the asymptotic confidence interval for Fleiss’ K was low, while the bootstrap confidence intervals for both measures provided a coverage probability close to the theoretical one. Conclusions Fleiss’ K and Krippendorff’s alpha with bootstrap confidence intervals are equally suitable for the analysis of reliability of complete nominal data. The asymptotic confidence interval for Fleiss’ K should not be used. In the case of missing data or data or higher than nominal order, Krippendorff’s alpha is recommended. Together with this article, we provide an R-script for calculating Fleiss’ K and Krippendorff’s alpha and their corresponding bootstrap confidence intervals. Electronic supplementary material The online version of this article (doi:10.1186/s12874-016-0200-9) contains supplementary material, which is available to authorized users.
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              The National League for Nursing Project to Explore the Use of Simulation for High-Stakes Assessment: Process, Outcomes, and Recommendations.

              This project was designed to explore the feasibility of using simulation for high-stakes assessment in pre-licensure RN programs.
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                Author and article information

                Contributors
                Christine.Melillo@va.gov
                Journal
                BMC Health Serv Res
                BMC Health Serv Res
                BMC Health Services Research
                BioMed Central (London )
                1472-6963
                5 November 2022
                5 November 2022
                2022
                : 22
                : 1323
                Affiliations
                [1 ]GRID grid.281075.9, ISNI 0000 0001 0624 9286, Nursing Innovations Center for Evaluation (NICE), , Research and Development Service, James A. Haley Veterans’ Hospital and Clinics, ; Tampa, FL USA
                [2 ]GRID grid.416818.2, ISNI 0000 0004 0419 1967, VA Phoenix Healthcare System, ; Phoenix, AZ USA
                [3 ]CEO, EarlyMobility.com, Plantation, FL USA
                [4 ]GRID grid.239186.7, ISNI 0000 0004 0481 9574, Department of Occupational Health and Safety, Veterans Health Administration, ; Washington DC, USA
                [5 ]GRID grid.422201.7, ISNI 0000 0004 0420 5441, VA North Texas Health Care System, ; Dallas, TX USA
                [6 ]Western North Carolina VA Health Care System, Asheville, NC USA
                [7 ]GRID grid.239186.7, ISNI 0000 0004 0481 9574, Office of Nursing Services, Veterans Health Administration, Department of Veterans Affairs, ; Washington, DC USA
                Article
                8745
                10.1186/s12913-022-08745-1
                9637301
                36335334
                792048cd-d1cd-4a05-aa49-8ac22048d4e6
                © This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2022

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 20 April 2022
                : 27 October 2022
                Categories
                Research
                Custom metadata
                © The Author(s) 2022

                Health & Social care
                patient mobility,screening,patient safety,staff safety
                Health & Social care
                patient mobility, screening, patient safety, staff safety

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