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Journal Article

Citation

Domensino AF, van Haastregt JCM, Winkens I, van Bennekom CAM, van Heugten CM. PLoS One 2020; 15(6): e0235085.

Copyright

(Copyright © 2020, Public Library of Science)

DOI

10.1371/journal.pone.0235085

PMID

32569269

Abstract

OBJECTIVE: Data collection in the field of acquired brain injury (ABI) lacks uniformity due to the broad spectrum of available measurement instruments, leading to incomparability of data and the need for patients to 'repeat their story'. To pursue uniform data collection, an ABI-specific minimal dataset (MDS-ABI) is currently under development. The current study aimed to assess the feasibility (performance according to protocol, user opinion, potential implementation barriers, and suggested improvements) of the MDS-ABI in clinical settings.

METHODS: A mixed-methods approach was used in a range of healthcare sectors for persons with ABI. Clinicians of several relevant disciplines within these sectors were asked to administer the MDS-ABI to five patients. Subsequently, feasibility according to clinicians was assessed by means of a paper questionnaire about every administration and an online questionnaire about the feasibility in general. Feasibility according to patients was assessed with a paper questionnaire and think aloud interviews.

RESULTS: Thirteen clinicians and 50 patients were included. In general, the MDS-ABI performed according to protocol. Both clinicians and patients were overall satisfied with the content of the MDS-ABI. The Cumulative Illness Rating Scale was regarded incomprehensible, leading to missing data. Further, clinicians indicated that the MDS-ABI would not be suitable for all ABI-patients, as some are incapable of self-report due to potential cognitive problems, communicative problems, fatigue, perceptual problems, or impaired awareness of deficits.

CONCLUSION: The MDS-ABI is a promising tool for obtaining core information on ABI-patients. The MDS-ABI will be adjusted according to the suggestions. For patients who are incapable of self-report, a proxy-reported version of the self-reported part was developed.


Language: en

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