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A Maturity Level Model (MLM) for the self-assessment of genomic medicine practices in healthcare systems

Authors :
Cardoso, maria Luis
Lopes, Fatima
Costa, Alexandra
Santos, Osvaldo
Konopko, Melissa
Merchant, Arshiya
Thorogood, Adrian
Saunders, Gary
Custers, Ilse
Bulcke, Marc Van Den
Schmitt, Tugce
Bogicevic, Ivana
Cividanes, Lene
Spalding, Dylan
Smith, Maeve
Bale, Mark
Pitini, Erica
Villari, Paolo
Baccolini, Valentina
Balciuniene, Anzelika
Ambrozaityte, Laima
Doménech, Elena
Martin-Sanchez, Fernando
Sobrón, Francisco
Saiz, Maria Luisa
Carracedo, Angel
Wedell, Anna
Thomsen, Anne Cambon
Veimer, Annika
Lundgren, Bettina
Solary, Eric
Birney, Ewan
Martins, Henrique
Klovins, Janis
Saarela, Janna
North, Kathryn
Caulfield, Mark
Piha, Tapani
Scollen, Serena
Vicente, Astrid
Publication Year :
2023
Publisher :
Zenodo, 2023.

Abstract

Genomic medicine implementation in healthcare systems can bring us one step closer to making personalised medicine a reality, with major socioeconomic benefits. Citizens and patients canwidely benefit from genomic data analysis for accurate and timely diagnosis, effective treatments with less adverse events, and accurate profiling for disease prevention. Implementation of genomics in healthcare is complex and requires adjustments in the governance, structure and organization of health services, as well as dedicated investments. Implementation is also dependent on the country context. In the context of the 1+Million Genomes (1+MG) initiative, we developed a Maturity Level Model (MLM) for health systems to self-evaluate the maturity of their genomic medicine practices, and define a path to optimization. MLM is a tool for healthcare systems to self-evaluate the level of maturity of their genomic medicine practices according to a common matrix, and to define a path to optimization. A MLM pilot in eight European countries provided important information regarding common strengths, weaknesses and asymmetries across Europe.

Details

Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....6e02b9d4208e86e73ecb43760a148ad6
Full Text :
https://doi.org/10.5281/zenodo.8135893