Predicting the need for institutional care shortly after admission to rehabilitation: Rasch analysis and predictive validity of the BRASS index

European Journal of Physical and Rehabilitation Medicine

Volumn 48, Issue 3, 2012, Pages 443-454

  Panella, L ^a   La Porta, F ^b   Caselli, S ^b   Marchisio, S ^a   Tennant, A ^c  

^a Vercelli Hospital   (Italy)

^b AUSL Modena   (Italy)

^c UNIVERSITY OF LEEDS   (United Kingdom)

Author keywords

Aged; Come assessment (health care); Out; Patient discharge; Psychometrics; Rehabilitation

Indexed keywords

AGED; ARTICLE; COMPARATIVE STUDY; DISABILITY; DISABLED PERSON; FEMALE; FORECASTING; HOSPITAL DISCHARGE; HUMAN; MALE; METHODOLOGY; MIDDLE AGED; PROSPECTIVE STUDY; PSYCHOMETRY; REPRODUCIBILITY; RETROSPECTIVE STUDY; RISK ASSESSMENT; SEVERITY OF ILLNESS INDEX;

AGED; AGED, 80 AND OVER; DISABILITY EVALUATION; DISABLED PERSONS; FEMALE; FORECASTING; HUMANS; MALE; MIDDLE AGED; PATIENT DISCHARGE; PROSPECTIVE STUDIES; PSYCHOMETRICS; REPRODUCIBILITY OF RESULTS; RETROSPECTIVE STUDIES; RISK ASSESSMENT; SEVERITY OF ILLNESS INDEX;

EID: 84871744887     PISSN: 19739087     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (43)

1. Rhoads C, Dean J, Cason C, Blaylock A. Comprehensive discharge planning: a hospital-home healthcare partnership. Home Healthc Nurse 1992;10:13-8.
2. Mistiaen P, Duijnhouwer E, Wijkel D, de Bont M, Veeger A. The problems of elderly people at home one week after discharge fromt an acute care setting. J Adv Nurs 1997;25:1233-40. (Pubitemid 127452292)
3. United Nations. Report of the Second World Assembly on Ageing, Madrid, 8-12 April 2002. New York; 2002.
4. Mamon J, Steinwachs D, Fahey M, Bone L, Oktay K, Klein L. Impact of hospital discharge planning on meeting patient needs after returning home. Health Serv Res 1992;27:155-75.
5. Holland DE, Harris MR, Pankratz S, S. C. C, Matt-Hensrud NN, Severson MA. Prospective evaluation of a screen for complex discharge planning in hospitalized adults. JAGS 2003:51:678-82. (Pubitemid 36541433)
6. Grimmer K, May E, Dawson A, Peoples C. Informing discharge plans - assessments of elderly patients in Australian public hospitals: a field study. The Internet Journal of Allied Health Sciences and Practice 2004;2:3-10.
7. Denti L, Agosti M, Franceschini M, On behalf of ICR2 Study Group. Outcome predictors for first stroke in the elderly. Eur J Phys Rehabil Med 2008;44:3-11.
8. Italian Ministry of Health. Essential levels of health care-LEA, DPCM, November 29. 2001.
9. Conferenza Stato-Regioni. Documento preliminare informativo sui contenuti del nuovo piano sanitario nazionale 2010-2012. 2009.
10. Slade A, Fear J, Tennant A. Identifying patients at risk of nursing home admission: The Leeds Elderly Assessment Dependency Screening tool (LEADS). BMC Health Serv Res 2006;6:31.
11. Blaylock A, Canon CL. Discharge planning predicting patients' needs. J Gerontol Nurs 1992;18:5-10.
12. Mistiaen P, Duijnhouwer E, Prins-Hoekstra A, Ros W, Blaylock A. Predictive validity of the BRASS index in screening patients with post-discharge problems. Blaylock Risk Assessment Screening Score. J Adv Nurs 1999;30:1050-6.
13. Chaboyer W, Kendall E, Foster M. Use of the "BRASS" to identify ICU patients who may have complex hospital discharge planning needs. Nursing Critical Care 2002;7:171-5.
14. World Medical Association. Declaration of Helsinki: ethical principles for medical research involving human subjects. Fer-ney-Voltaire: WMA; 2002.
15. Saiani L, Zanolin ME, Dalponte A, Palese A, Viviani D. Valutazi-one della sensibilità e specificità di uno strumento di screening dei pazienti a rischio di dimissione difficile. Assistenza infer-mieristica e ricerca 2008;27:184-93.
16. Reeve BB, Hays RD, Bjorner JB, Cook KF, Crane PK, Teresi JA et al. Psychometric evaluation and calibration of health-related quality of life item banks: plans for the Patient-Reported Outcomes Measurement Information System (PROMIS). Med Care 2007;45(5 Suppl 1):S22-31.
17. Elhan AH, Öztuna D, Kutlay S, Küçükdeveci AA, Tennant A. An initial application of computerized adaptive testing (CAT) for measuring disability in patients with low back pain. BMC Musculoskelet Disord 2008;9:166.
18. Franchignoni F, Horak FB, Godi M, Nardone A, Giordano A. Using pyschometric techniques to improve the balance evaluation systems test: the mini-Bestest. J Rehab Med 2010;42:316-24.
19. La Porta F, Franceschini M, Caselli S, Cavallini P, Susassi S, Tennant A. Unified Balance Scale: an activity-based, bed to community, and aetiology-independent measure of balance calibrated with rasch analysis. J Rehabil Med 2011;43:435-44
20. Horn JL. A rationale and test for the numbers of factors in factor analysis. Psychometrika 1965;30:179-85.
21. Andrich D. Rasch models for measurement. London: Sage Publications.; 1988.
22. Tennant A, Penta M, Tesio L, Grimby G, Thonnard JL, Slade A et al. Assessing and adjusting for cross-cultural validity of impairment and activity limitation scales through differential item functioning within the framework of the Rasch model: the PRO-ESOR project. Med Care 2004;42(1 Suppl):I37-48.
23. Pallant JF, Tennant A. An introduction to the Rasch measurement model: an example using the Hospital Anxiety and Depression Scale (HADS). Br J Clin Psychol 2007;46(Pt 1):1-18. (Pubitemid 46332274)
24. Hobart J, Cano S. Improving the evaluation of therapeutic interventions in multiple sclerosis: the role of new psychometric methods. Health Technol Assess 2009;13:iii, ix-x, l-177.
25. Scientific Advisory Committee of the Medical Outcome Trust. Assessing health status and quality-of-life instruments: attributes and review criteria. Qual Life Res 2002;11:193-205.
26. Hinderer SR, Hinderer KA. Principles and applications of measurement methods. In: De Lisa JA, Gans BM, Walsh NE, Boc-kenek WL, Frontera WR, Geiringer SR et al., editors. Physical medicine and rehabilitation: Principles and practice (4th ed). Philadelphia: Lippincott, Williams & Wilkins; 2005. p. 1139-62.
27. La Porta F, Franceschini M, Caselli S, Cavallini P, Susassi S, Tennant A. Unified Balance Scale: classic psychometric and clinical properties. J Rehabil Med 2011;43:445-53.
28. U. S. Department of Health and Human Services, Centers for Disease Control and Prevention (CDC), Office of Workforce and Career Development (OWCD), (CDD) CDD. Principles of Epidemiology in Public Health Practice - An Introduction to Applied Epidemiology and Biostatistics. 3rd edition. [Internet]. Available at http://www.cdc.gov/training/products/ssl000/ssl000-ol.pdf [cited 2012, Mar. 8].
29. Tabachnick BG, Fidell LS. Using multivariate statistics (4th edition). New York: HarperCollins; 2001.
30. Linacre JM. Sample size and item calibration stability. Rasch Measurement Trasactions 1994;7:328.
31. Bland J, Altman D. Multiple significance tests: the Bonferroni method. Br Med J 1995;310:170.
32. Wainer H, Kiely G. Item clusters and computer adaptive testing: A case for testlets. J Educ measurement 1987;24:185-202.
33. Wright BD, Masters GN. Rating Scale Analysis. Chicago: MESA Press; 1982.
34. nd edition. Maidenhead, UK: Open University Press; 2005.
35. Franchignoni F, Horak F, Godi M, Nardone A, Giordano A. Using psychometric techniques to improve the Balance Evaluation Systems Test: the mini-BESTest. J Rehabil Med 2010;42:323-31.
36. Franceschini M, La Porta F, Agosti M, Massucci M, Group obotl. Is health-related-quality of life of stroke patients influenced by neurological impairments at one year after stroke? Eur J Phys Rehabil Med 2010;46:1-11.
37. World Health Organization. International Classification of Functioning, Disability and Health: ICE Geneva; 2001.
38. Stucki G, Cieza A. The International Classification of Functioning, Disability and Health (ICF) in physical and rehabilitation medicine. Eur J Phys Rehabil Med 2008;44:299-302.
39. Stucki G, Melvin J. The International Classification of Functioning, Disability and Health: a unifying model for the conceptual description of physical and rehabilitation medicine. J Rehabil Med 2007;39:286-92.
40. Gutenbrunner C, Ward AB, Chamberlain MA, on behalf of Section of Physical and Rehabilitation Medicine Union Européenne des Médecins Specialistes (UEMS), European Board of Physical and Rehabilitation Medicine, Academie Europeenne de Mede-cine de Réadaptation et al. White book on physical and rehabilitation medicine in Europe. Eura Med Phys 2006;42:4:292-332.
41. Marais I, Andrich D. Formalizing dimension and response violations of local independence in the unidimensional Rasch model. J Appl Meas 2008;9:200-15.
42. Tennant A, Conaghan PG. The Rasch measurement model in rheumatology: What is it and why use it? When should it be applied, and what should one look for in a Rasch paper? Arthritis Care & Research 2007;57:1358-62. (Pubitemid 350308830)
43. Svensson E. Guidelines to statistical evaluation of data from rating scales and questionnaire. J Rehabil Med 2001;33.