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. 2018 Jul 6;13(7):e0197484.
doi: 10.1371/journal.pone.0197484. eCollection 2018.

Measuring interdisciplinarity in clinical practice with IPC59, a modified and improved version of IPC65

Thomas G Poder  1   2 , Nathalie Carrier  2 , Suzanne K Bédard  2
Affiliations

Measuring interdisciplinarity in clinical practice with IPC59, a modified and improved version of IPC65

Thomas G Poder et al. PLoS One. .

Abstract

Rationale: Interdisciplinarity is considered a key concept in the management of complex cases in healthcare. However, working in interdisciplinary teams requires the integration of many concepts and a large amount of effort. To help healthcare managers and professionals identify the strengths and weaknesses of their interdisciplinary team and to ensure its continuous improvement, we developed a tool called the IPC65.

Objective: The purpose of this study was to test the reliability and validity of the IPC65.

Methods: Based on a comprehensive review of the literature and qualitative and quantitative assessments, the IPC65 was developed. In this study, the analysis was based on 392 healthcare professionals and managers from short-term care settings who provided valid responses throughout the province of Quebec in Canada. Descriptive statistics, Cronbach's alpha values, and inter-item correlations were measured, and a principal component analysis (PCA) was conducted. Item discrimination was used to provide an improved version of the IPC65.

Results: The IPC65 showed good statistical results. The discriminant procedure provided the basis for shortening and improving the IPC65 to form the IPC59. Cronbach's alpha values ranged from 0.857 to 0.967 in IPC59, demonstrating very good reliability for all four dimensions. The PCA showed good validity.

Conclusion: The IPC59 can be used to assess the degree of integration of key concepts leading to interdisciplinarity.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Conceptual framework for the analysis of integration implementation in the healthcare process, taken from Roberge et al. [15] and adapted from the model by Contandriopoulos et al. [14].
Fig 2
Fig 2. Graphical representation of principal component analysis for each dimension of integration.
Fig 3
Fig 3. Graphical representation of principal component analysis for new sub-dimensions of clinical integration and integration of care.
See this image and copyright information in PMC

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