Development and validation of a short version of the Assessment of Chronic Illness Care (ACIC) in Dutch Disease Management Programs
Abstract Background In the Netherlands the extent to which chronically ill patients receive care congruent with the Chronic Care Model is unknown. The main objectives of this study were to (1) validate the Assessment of Chronic Illness Care (ACIC) in the Netherlands in various Disease Management Programmes (DMPs) and (2) shorten the 34-item ACIC while maintaining adequate validity, reliability, and sensitivity to change. Methods The Dutch version of the ACIC was tested in 22 DMPs with 218 professionals. We tested the instrument by means of structural equation modelling, and examined its validi... Mehr ...
Verfasser: | |
---|---|
Dokumenttyp: | Artikel |
Erscheinungsdatum: | 2011 |
Reihe/Periodikum: | Health and Quality of Life Outcomes, Vol 9, Iss 1, p 49 (2011) |
Verlag/Hrsg.: |
BMC
|
Schlagwörter: | chronic care / measurement / quality / chronic illness / disease management / Computer applications to medicine. Medical informatics / R858-859.7 |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-28986221 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | https://doi.org/10.1186/1477-7525-9-49 |
Abstract Background In the Netherlands the extent to which chronically ill patients receive care congruent with the Chronic Care Model is unknown. The main objectives of this study were to (1) validate the Assessment of Chronic Illness Care (ACIC) in the Netherlands in various Disease Management Programmes (DMPs) and (2) shorten the 34-item ACIC while maintaining adequate validity, reliability, and sensitivity to change. Methods The Dutch version of the ACIC was tested in 22 DMPs with 218 professionals. We tested the instrument by means of structural equation modelling, and examined its validity, reliability and sensitivity to change. Results After eliminating 13 items, the confirmatory factor analyses revealed good indices of fit with the resulting 21-item ACIC (ACIC-S). Internal consistency as represented by Cronbach's alpha ranged from 'acceptable' for the 'clinical information systems' subscale to 'excellent' for the 'organization of the healthcare delivery system' subscale. Correlations between the ACIC and ACIC-S subscales were also good, ranging from .87 to 1.00, indicating acceptable coverage of the core areas of the CCM. The seven subscales were significantly and positively correlated, indicating that the subscales were conceptually related but also distinct. Paired t-tests results show that the ACIC scores of the original instrument all improved significantly over time in regions that were in the process of implementing DMPs (all components at p < 0.0001). Conclusion We conclude that the psychometric properties of the ACIC and the ACIC-S are good and the ACIC-S is a promising alternate instrument to assess chronic illness care.