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In Patients Admitted to a Home Rehabilitation Service, Is Remote Completion of the Patient-Generated Subjective Global Assessment Physical Examination Using Still Images Captured by Allied Health Assistants a Valid Alternative to an In-Person Physical Examination?

      Abstract

      Background

      There is increasing provision of telehealth services, including nutrition services. However, remote nutrition assessments are challenging due to difficulties in conducting physical assessments remotely, a crucial component of assessing nutritional status.

      Objective

      The aim of this study was to evaluate whether remote completion of the Patient-Generated Subjective Global Assessment physical examination using still images captured by allied health assistants (AHAs) is a valid alternative to an in-person physical examination in patients admitted to a home rehabilitation service.

      Design

      This study was cross-sectional in design.

      Participants/setting

      This study involved 104 adults admitted to the home rehabilitation service at Southern Adelaide Local Health Network, Adelaide, Australia, over 2 sampling periods in 2019 and 2020 who were receiving home visits by an AHA and were engaged in rehabilitation activities.

      Main outcome measures

      Validity of the still image-based physical assessment was determined using still images collected by an AHA and an in-person physical assessment completed by a dietitian from each participant. A dietitian blinded to the in-person results later assessed the de-identified still images to determine the presence and extent of deficit at each anatomical site and overall physical examination component of the Patient-Generated Subjective Global Assessment.

      Statistical analyses performed

      Percentage agreement, weighted κ, sensitivity, and specificity between the still image based and in-person physical examinations were determined to assess agreement between the 2 methods of assessment.

      Results

      The still image based physical examination achieved a percentage agreement of 75% against the in-person examination, with a weighted κ of 0.662 (95% confidence interval 0.516-0.808) and a sensitivity-specificity pair of 76.6% and 89.1%.

      Conclusions

      Physical examination using still images collected by AHAs achieved percentage agreement, κ, and sensitivity and specificity compared with an in-person physical examination that is consistent with or superior to commonly adopted nutrition screening and assessment tools. There is potential for implementation of this method to facilitate remote nutritional assessments by dietitians; however, further work is needed to ensure dietitians are able to assess still images reliably.

      Keywords

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      References

        • Fisk M.
        • Livingstone A.
        • Pit S.
        Telehealth in the context of COVID-19: Changing perspectives in Australia, the United Kingdom, and the United States.
        J Med Internet Res. 2020; 22e19264https://doi.org/10.2196/19264
      1. Bashshur RL, Shannon GW, Smith BR, et al. The empirical foundations of telemedicine interventions for chronic disease management. Telemed J E Health. Sep 2014;20(9):769-800. https://doi.org/10.1089/tmj.2014.9981

        • Australia’s National Digital Health Strategy
        Safe, Seamless and Secure: Evolving Health and Care to Meet the Needs of Modern Australia.
        Australian Government, 2020
        • Marshall S.
        • Young A.
        • Bauer J.
        • Isenring E.
        Malnutrition in geriatric rehabilitation: Prevalence, patient outcomes, and criterion validity of the scored Patient-Generated Subjective Global Assessment and the Mini Nutritional Assessment.
        J Acad Nutr Diet. 2015; 116: 785-794https://doi.org/10.1016/j.jand.2015.06.013
        • Watterson C.
        • Fraser A.
        • Banks M.
        • et al.
        Evidence based practice guidelines for the nutritional management of malnutrition in adult patients across the continuum of care.
        Nutr Diet. 2009; 66: S1-S34https://doi.org/10.1111/j.1747-0080.2009.01383.x
        • Borkent J.W.
        • Naumann E.
        • Vasse E.
        • van der Heijden E.
        • de van der Schueren M.A.E.
        Prevalence and determinants of undernutrition in a sample of Dutch community-dwelling older adults: Results from two online screening tools.
        Int J Environ Res Public Health. 2019; 16: 1562
        • Borkent J.
        • Keller H.
        • Wham C.
        • Wijers F.
        • de van der Schueren M.
        Cross-country differences and similarities in undernutrition prevalence and risk as measured by SCREEN II in community-dwelling older adults.
        Healthcare (Basel). 2020; 8: 151https://doi.org/10.3390/healthcare8020151
        • Brunton C.
        • Arensberg M.
        • Drawert S.
        • Badaracco C.
        • Everett W.
        • McCauley S.
        Perspectives of registered dietitian nutritionists on adoption of telehealth for nutrition care during the COVID-19 pandemic.
        Healthcare (Basel). 2021; 9: 235https://doi.org/10.3390/healthcare9020235
        • Narva A.
        • Romancito G.
        • Faber T.
        • Steele M.
        • Kempner K.
        Managing CKD by telemedicine: The Zuni Telenephrology Clinic.
        Adv Chronic Kidney Dis. 2017; 24: 6-11https://doi.org/10.1053/j.ackd.2016.11.019
        • Charney P.
        • Peterson S.
        Practice paper of the Academy of Nutrition and Dietetics Abstract: Critical thinking skills in nutrition assessment and diagnosis.
        J Acad Nutr Diet. 2013; 113: 1545https://doi.org/10.1016/j.jand.2013.09.006
        • Ottery F.
        Patient-Generated Subjective Global Assessment.
        in: McCallum P. Polisena C. The Clinical Guide to Oncology Nutrition. The American Dietetic Association, 2000: 11-23
        • Miller M.
        • Thomas J.
        • Suen J.
        • Ong D.
        • Sharma Y.
        Evaluating photographs as a replacement for the in-person physical examination of the scored Patient-Generated Subjective Global Assessment in elderly hospital patients.
        J Acad Nutr Diet. 2018; 118: 896-903https://doi.org/10.1016/j.jand.2017.10.010
        • Sarigiovannis P.
        • Jowett S.
        • Saunders B.
        • Corp N.
        • Bishop A.
        Delegation by allied health professionals to allied health assistants: A mixed methods systematic review.
        Physiotherapy. 2021; 112: 16-30https://doi.org/10.1016/j.physio.2020.10.002
        • Wester P.
        • Angus R.
        • Easlea D.
        • Lin M.
        • Chen B.
        • Bisset L.
        Use of the malnutrition screening tool by non-dietitians to identify at-risk patients in a rehabilitation setting: A validation study.
        Nutr Diet. 2018; 75: 324-330https://doi.org/10.1111/1747-0080.12416
        • Patel V.
        • Romano M.
        • Corkins M.
        • et al.
        Nutrition screening and assessment in hospitalized patients.
        Nutr Clin Pract. 2014; 29: 483-4901https://doi.org/10.1177/0884533614535446
        • Peat J.
        • Mellis C.
        • Williams K.
        • Xuan W.
        Health Science Research: A Handbook of Quantitative Methods.
        Allen & Unwin, 2001
        • Buderer N.
        Statistical methodology: I. Incorporating the prevalence of disease into the sample size calculation for sensitivity and specificity.
        Acad Emerg Med. 1996; 3: 895-900
        • Fischer M.
        • JeVenn A.
        • Hipskind P.
        Evaluation of muscle and far loss as diagnostic criteria for malnutrition.
        Nutr Clin Pract. 2015; 30: 239-248
        • Detsky A.
        • McLaughlin J.
        • Baker N.
        • Whittaker R.
        • Mendelson K.
        • Jeejeebhoy K.
        What is subjective global assessment of nutritional status?.
        JPEN J Parenter Enteral Nutr. 1987; 11: 8-13https://doi.org/10.1177/014860718701100108
        • White J.
        • Guenter P.
        • Jensen G.
        • Malone A.
        • Schofield M.
        Consensus statement of the Academy of Nutrition and Dietetics/American Society for Parenteral and Enteral Nutrition: Characteristics recommended for the identification and documentation of adult malnutrition (undernutrition).
        J Acad Nutr Diet. 2012; 112: 730-738https://doi.org/10.1016/j.jand.2012.03.012
        • Stemler S.
        A comparison of consensus, consistency, and measurement approaches to estimating interrater reliability.
        Pract Assess Res Eval. 2004; 9https://doi.org/10.7275/96jp-xz07
        • Hartmann D.
        Considerations in the choice of interobserver reliability measures.
        J Appl Behav Anal. 1977; 10: 103-116
        • Viera A.
        • Garrett J.
        Understanding the interobserver agreement: The kappa statistic.
        Fam Med. 2005; 37: 360-363
        • Arikbuka M.
        • Yucecan S.
        Assessment of nutritional status and its association with anthropometric measurements, blood results and body composition in elderly cardiovascular patients.
        Progress in Nutrition. 2016; 18: 344-351
        • Isenring E.
        • Banks M.
        • Ferguson M.
        • Bauer J.
        Beyond malnutrition screening: Appropriate methods to guide nutrition care for aged care residents.
        J Acad Nutr Diet. 2012; 112: 376-381https://doi.org/10.1016/j.jada.2011.09.038
        • Grunau G.
        • Linn S.
        Commentary: Sensitivity, Specificity, and Predictive Values: Foundations, Pliabilities, and Pitfalls in Research and Practice.
        Front Public Health. 2018; 5: 307https://doi.org/10.3389/fpubh.2018.00256
        • Van Bokhorst-de van Der Schueren M.
        • Guaitoli P.
        • Jansma E.
        • de Vet H.
        Nutrition screening tools: Does one size fit all? A systematic review of screening tools for the hospital setting.
        Clin Nutr. 2014; 33: 39-58https://doi.org/10.1016/j.clnu.2013.04.008
      2. SPSS Statistics for Windows. Version 27.0. IBM.

        • Dona E.
        • Olveira C.
        • Palenque F.
        • et al.
        Body composition measurement in bronchiectasis: Comparison between bioelectrical impedance analysis, skinfold thickness measurement, and dual-energy x-ray absorptiometry before and after pulmonary rehabilitation.
        J Acad Nutr Diet. 2018; 118: 1464-1473https://doi.org/10.1016/j.jand.2018.01.013
        • Jones D.
        • Lal S.
        • Strauss B.
        • Todd C.
        • Pilling M.
        • Burden S.
        Measurement of muscle mass and sarcopenia using anthropometry, bioelectrical impedance, and computed tomography in surgical patients with colorectal malignancy: Comparison of agreement between methods.
        Nutr Cancer. 2019; 72: 1-10
        • Souza N.
        • Gonzalez M.
        • Martucci R.
        • et al.
        Comparative analysis between computed tomography and surrogate methods to detect low muscle mass among colorectal cancer patients.
        JPEN J Parenter Enteral Nutr. 2020; 44: 1328-1337https://doi.org/10.1002/jpen.1741
        • Cereda E.
        Mini Nutritional Assessment.
        Curr Opin Clin Nutr Metab Care. 2012; 15: 29-41
        • Pt-Global
        The scored Patient-Generated Subjective Global Assessment.
        http://pt-global.org/?page_id=13
        Date accessed: September 15, 2021
        • Earthman C.
        Body composition tools for assessment of adult malnutrition at the bedside.
        JPEN J Parenter Enteral Nutr. 2015; 39: 787-822https://doi.org/10.1177/0148607115595227
        • Hoehler F.
        Bias and prevalence effects on kappa viewed in terms of sensitivity and specificity.
        J Clin Epidemiol. 2000; 53: 499-503
        • Feuerman M.
        • Miller A.
        Relationships between statistical measures of agreement: Sensitivity, specificity and kappa.
        J Eval Clin Pract. 2008; 14: 930-933
        • Ambagtsheer R.
        • Visvanathan R.
        • Cesari M.
        • et al.
        Feasibility, acceptability and diagnostic test accuracy of frailty screening instruments in community-dwelling older people within the Australian general practice setting: A study protocol for a cross-sectional study.
        BMJ Open. 2017; 7e016663https://doi.org/10.1136/bmjopen-2017-016663
        • Neelemaat F.
        • Meijers J.
        • Kruizenga H.
        • Van Ballegooijen H.
        • Van Bokhorst-de van Der Schueren M.
        Comparison of five malnutrition screening tools in one hospital inpatient sample.
        J Clin Nurs. 2011; 20: 2144-2152
        • Young A.
        • Kidston S.
        • Banks M.
        • Mudge A.
        • Isenring E.
        Malnutrition screening tools: Comparison against two validated nutrition assessment methods in older medical inpatients.
        Nutrition. 2013; 29: 101-106
        • Cederholm T.
        • Jensen G.
        • Correia M.
        • et al.
        GLIM criteria for the diagnosis of malnutrition—a consensus report from the global clinical nutrition community.
        Clin Nutr. 2019; 38: 1-9
        • Jensen G.
        • Compher C.
        • Sullivan S.
        • Mullin G.
        Recognizing malnutrition in adults: Definitions and characteristics, screening, assessment, and team approach.
        JPEN J Parenter Enteral Nutr. 2013; 37: 802-807
        • Platek M.
        • Hertroijs D.
        • Nicholson J.
        • Parekh N.
        Sensitivity and specificity of malnutrition screening tools used in the adult hospitalized patient setting: A systematic review.
        Top Clin Nutr. 2015; 30: 289-301
        • Salas E.
        • Cannon-Bowers J.
        Methods, tools and strategies for team training.
        in: Quinones M. Ehrenstein A. Training for a Rapidly Changing Workplace: Applications of Psychological Research. American Psychological Association, 1997: 249-279
        • Newman C.
        • Cornwell P.
        • Young A.
        • Ward E.
        • McErlain A.
        Accuracy and confidence of allied health assistants administering the subjective global assessment on inpatients in a rural setting: a preliminary feasibility study.
        Nutr Diet. 2018; 75: 129-136https://doi.org/10.1111/1747-0080.12370
        • Shaw J.
        • Agarwal P.
        • Desveaux L.
        • et al.
        Beyond “implementation”: digital health innovation and service design.
        NPJ Digit Med. 2018; 1: 48https://doi.org/10.1038/s41746-018-0059-8
        • Cimperman M.
        • Bren M.
        • Trkman P.
        • Stanonik M.
        Older adults’ perceptions of home telehealth services.
        Telemed J E Health. 2013; 19: 786-790https://doi.org/10.1089/tmj.2012.0272
        • Gallagher A.
        • Li S.
        • Wainwright P.
        Dignity in the care of older people: A review of the theoretical and empirical literature.
        BMC Nurs. 2008; 7: 11https://doi.org/10.1186/1472-6955-7-11
        • Cooper C.
        • Selwood A.
        • Livingston G.
        The prevalence of elder abuse and neglect: A systematic review.
        Age Ageing. 2008; 37: 151-160https://doi.org/10.1093/ageing/afm194
        • Willett W.
        Nutritional Epidemiology.
        2nd ed. Oxford University Press, 1998

      Biography

      J. Thomas is a lecturer, College of Nursing & Health Sciences, Flinders University, Bedford Park, Australia.

      Biography

      C. Lawless is a dietitian, Southern Adelaide Local Health Network, Bedford Park, Australia.

      Biography

      A. Christie is a dietitian at the Southern Adelaide Local Health Network, Bedford Park, Australia; at the time of the study, she was a student at the College of Nursing & Health Sciences, Flinders University, Bedford Park, Australia.

      Biography

      At the time of the study, O. Kuhr is a dietitian at the Central Adelaide Local Health Network, Adelaide; at the time of the study, he was a student at College of Nursing & Health Sciences, Flinders University, Bedford Park, Australia.

      Biography

      M. Miller is Professor, Nutrition and Dietetics, College of Nursing & Health Sciences, Flinders University, Bedford Park, Australia.