Integrating clinicians, knowledge and data: expert-based cooperative analysis in healthcare decision support

Peer reviewed: Yes

Authors: Gibert, Karina and García-Alonso, Carlos and Salvador-Carulla, Luis

Publication: Health research policy and systems

Year: 2010

DOI: https://doi.org/10.1186/1478-4505-8-28

Method: Descriptive introduction of a new hybrid methodology Expert-based Cooperative Analysis (EbCA), which incorporates explicit prior expert knowledge in data analysis methods, and elicits implicit or tacit expert knowledge to improve decision support in healthcare systems. EbCA was compared to classical procedures using qualitative explicit prior knowledge in two case examples: 1) Bench-marking of small mental health areas based on technical efficiency estimated by EbCA-Data Envelopment Analysis (EbCA-DEA), and 2) Case-mix of schizophrenia based on functional dependency using Clustering Based on Rules (ClBR). Bayesian predictive validity measures were used for comparison with expert panels results. Overall agreement was tested by Intraclass Correlation Coefficient in case “1” and kappa in both cases.

Message: EbCA provides a convenient way of completing classical data analysis with Prior Expert Knowledge by extracting relevant knowledge in complex health domains. One of the major benefits of EbCA is iterative elicitation of implicit or tacit expert knowledge. Both explicit and tacit or implicit expert knowledge are critical to guide the scientific analysis of very complex decision problems such as those found in health system research.

BibTeX: @article{gibert2010integrating, title={Integrating clinicians, knowledge and data: expert-based cooperative analysis in healthcare decision support}, author={Gibert, Karina and Garc{'\i}a-Alonso, Carlos and Salvador-Carulla, Luis}, journal={Health research policy and systems}, volume={8}, number={1}, pages={1–16}, year={2010}, publisher={Springer} }