Patients are the most important actors in clinical research. Therefore, patient preference information (PPI) could support the decision-making process, being indisputable for research value, quality, and integrity. However, there is a lack of clear guidance or consensus on the search for preference studies. In this blueprint, an openly available and regularly updated patient preference management system for an integrated database (PPMSDB) that contains the minimal set of data sufficient to provide detailed information for each study (the so-called evidence tables in systematic reviews) and a high-level overview of the findings of a review (summary tables) is described. These tables could help determine which studies, if any, are eligible for quantitative synthesis. Finally, a web platform would provide a graphical and user-friendly interface. On the other hand, a set of APIs (application programming interfaces) would also be developed and provided. The PPMSDB, aims to collect preference measures, characteristics, and meta-data, and allow researchers to obtain a quick overview of a research field, use the latest evidence, and identify research gaps. In conjunction with proper statistical analysis of quantitative preference measures, these aspects can facilitate formal evidence-based decisions and adequate consideration when conducting a structured decision-making process. Our objective is to outline the conceptual infrastructure necessary to build and maintain a successful network that can monitor the currentness and validity of evidence.

Building Infrastructure to Exploit Evidence from Patient Preference Information (PPI) Studies: A Conceptual Blueprint

Giordano, L;Francavilla, A;Lanera, C;Urru, S;Baldi, I
2022

Abstract

Patients are the most important actors in clinical research. Therefore, patient preference information (PPI) could support the decision-making process, being indisputable for research value, quality, and integrity. However, there is a lack of clear guidance or consensus on the search for preference studies. In this blueprint, an openly available and regularly updated patient preference management system for an integrated database (PPMSDB) that contains the minimal set of data sufficient to provide detailed information for each study (the so-called evidence tables in systematic reviews) and a high-level overview of the findings of a review (summary tables) is described. These tables could help determine which studies, if any, are eligible for quantitative synthesis. Finally, a web platform would provide a graphical and user-friendly interface. On the other hand, a set of APIs (application programming interfaces) would also be developed and provided. The PPMSDB, aims to collect preference measures, characteristics, and meta-data, and allow researchers to obtain a quick overview of a research field, use the latest evidence, and identify research gaps. In conjunction with proper statistical analysis of quantitative preference measures, these aspects can facilitate formal evidence-based decisions and adequate consideration when conducting a structured decision-making process. Our objective is to outline the conceptual infrastructure necessary to build and maintain a successful network that can monitor the currentness and validity of evidence.
2022
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3454909
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