AlloGraph: open-source web-based scalable platform for registry-driven monitoring of allogeneic hematopoietic cell transplant activity
Cousin, A.; Legrand, V.; Devillier, R.; Karam, M.; Forcade, E.; Jubert, C.; Villate, A.; Eloit, M.; Gyan, E.; Chevalier, P.; Labussiere-Wallet, H.; Castilla-Llorente, C.; Maertens, J.; Ceballos, P.; Rubio, M.-T.; Bruno, B.; Chalandon, Y.; Poire, X.; Mear, J.-B.; Gandemer, V.; Levy, J.; Malard, F.; Lewalle, P.; Paillard, C.; Loschi, M.; Dalle, J.-H.; Charbonnier, A.; Daguindau, E.; Bay, J.-O.; Prata De Lima, P.; Maillard, N.; Suarez, F.; Benakli, M.; Bazarbachi, A.; Thalhammer, J.; Nguyen, S.; Raus, N.; Huynh, A.; Michonneau, D.; Vallet, N.
Show abstract
Despite longitudinal and multidimensional collected data within registries, their routine exploitation for value-based care and outcome transparency remains limited by analytical complexity and heterogeneous expertise across centers. To address this gap, we developed an open-source and free web-based software which allows registry-based data analysis operational for evaluation of practices and quality system management applied to allogeneic hematopoietic cell transplant registry. It was built with Python and Dash framework to treat user formatted data. AlloGraph produces epidemiological summaries, survival analyses, and quality management indicators. Privacy protection is ensured by a Transport Layer Security protocol to a secure server where processing occurs in-memory, without data saving. AlloGraph was evaluated positively by 30 practitioners in 24 transplant centers, of whom 89% anticipated that AlloGraph would change their monitoring practice. AlloGraph represents a privacy-preserving and user-centered platform simplifying registry analysis for activity monitoring. This scalable model could be adapted to exploit real-world health databases.
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