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PLoS One ; 12(10): e0178453, 2017.
Article in English | MEDLINE | ID: mdl-29045409

ABSTRACT

In Italy, at present, a well-known problem is inhomogeneous provision of rehabilitative services, as stressed by MoH, requiring appropriate criteria and parameters to plan rehabilitation actions. According to the Italian National Rehabilitation Plan, Comorbidity, Disability and Clinical Complexity should be assessed to define the patient's real needs. However, to date, clinical complexity is still difficult to measure with shared and validated tools. The study aims to psychometrically validate the Italian Rehabilitation Complexity Scale-Extended v13 (RCS-E v13), in order to meet the guidelines requirements. An observational multicentre prospective cohort study, involving 8 intensive rehabilitation facilities of the Emilia-Romagna Region and 1712 in-patients, [823 male (48%) and 889 female (52%), mean age 68.34 years (95% CI 67.69-69.00 years)] showing neurological, orthopaedic and cardiological problems, was carried out. The construct and concurrent validity of the RCS-E v13 was confirmed through its correlation to Barthel Index (disability) and Cumulative Illness Rating Scale (comorbidity) and appropriate admission criteria (not yet published), respectively. Furthermore, the factor analysis indicated two different components ("Basic Care or Risk-Equipment" and "Medical-Nursing Needs and Therapy Disciplines") of the RCS-E v13. In conclusion, the Italian RCS-E v13 appears to be a useful tool to assess clinical complexity in the Italian rehab scenario case-mix and its psychometric validation may have an important clinical rehabilitation impact allowing the assessment of the rehabilitation needs considering all three dimensions (disability, comorbidity and clinical complexity) as required by the Guidelines and the inhomogeneity could be reduced.


Subject(s)
Psychometrics/methods , Rehabilitation , Surveys and Questionnaires , Aged , Demography , Factor Analysis, Statistical , Female , Humans , Italy , Male , Principal Component Analysis , Reproducibility of Results , Statistics, Nonparametric
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