Using existing data to identify candidate items for a health state classification system in multiple sclerosis.

Purpose: In multiple sclerosis (MS), the use of preference-based measures is limited to generic measures such as Health Utilities Index Mark 2 and 3, the EQ-5D and the SF-6D. However, the challenge of using such generic preference-based measures in people with MS is that they may not capture all dom...

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Publicado en:Quality of Life Research Vol. 23; no. 5; pp. 1445 - 1458
Autores principales: Kuspinar, Ayse, Finch, Lois, Pickard, Simon, Mayo, Nancy E
Formato: research Journal Article
Publicado: Springer Nature Jun2014
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Jun2014
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s11136-013-0604-5
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        atl: Using existing data to identify candidate items for a health state classification system in multiple sclerosis.
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        au:
          Kuspinar, Ayse
          Finch, Lois
          Pickard, Simon
          Mayo, Nancy E
        affil: Faculty of Medicine, School of Physical and Occupational Therapy, McGill University, 3654 Prom Sir William Osler, Montreal, QC, H3G 1Y5, Canada, ayse.kuspinar@mail.mcgill.ca.
      sug:
        subj:
          Multiple Sclerosis Psychosocial Factors
          Outcomes (Health Care) Methods
          Quality of Life
          Questionnaires Standards
          Sickness Impact Profile
          Activities of Daily Living Classification
          Activities of Daily Living Psychosocial Factors
          Adult
          Algorithms
          Female
          Human
          Linear Regression
          Male
          Multiple Sclerosis
          Multiple Sclerosis Classification
          Patient Satisfaction
          Quality-Adjusted Life Years
          Quebec
          Questionnaires
          Reproducibility of Results Utilization
          Severity of Illness Indices
          Visual Analog Scaling
          Adult: 19-44 years
          Female
          Male
      ab: Purpose: In multiple sclerosis (MS), the use of preference-based measures is limited to generic measures such as Health Utilities Index Mark 2 and 3, the EQ-5D and the SF-6D. However, the challenge of using such generic preference-based measures in people with MS is that they may not capture all domains of health relevant to the disease. Therefore, the main aim of this paper is to describe the development of a health state classification system for MS patients. The specific objectives are: (1) to identify items best reflecting the domains of quality of life important to people with MS and (2) to provide evidence for the discriminative capacity of the response options by cross-walking onto a visual analog scale of health rating.Methods: The data come from an epidemiologically sampled population of people with MS diagnosed post-1994. The dataset consisted of 206 items relating to impairments, activity limitations, participation restrictions, health perception and quality of life. Important domains were identified from the responses to the Patient Generated Index, an individualized measure of quality of life. The extent to which the items formed a uni-dimensional, linear construct was estimated using Rasch analysis, and the best item was selected using the threshold map.Results: The sample was young (mean age 43) and predominantly female (n = 140/189; 74%). The P-PBMSI classification system consisted of five items, with three response levels per item, producing a total of 243 possible health states. Regression coefficient values consistently decreased between response levels and the linear test for trend were statistically significant for all items. The linear test for trend indicated that for each item the response options provided the same discriminative ability within the magnitude of their capacity. A scoring algorithm was estimated using a simple additive formula. The classification system demonstrated convergent validity against other measures of similar constructs and known-groups validity between different clinical subgroups.Conclusion: This study produced a health state classifier system based on items impacted upon by MS, and demonstrated the potential to discriminate the health impact of the disease.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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