{"id":243,"date":"2025-03-26T11:30:46","date_gmt":"2025-03-26T10:30:46","guid":{"rendered":"https:\/\/datalchemy.net\/nos-prestations\/targeting-beneficiaries\/"},"modified":"2025-08-19T10:18:37","modified_gmt":"2025-08-19T08:18:37","slug":"targeting-beneficiaries","status":"publish","type":"projet","link":"https:\/\/datalchemy.net\/en\/our-services\/targeting-beneficiaries\/","title":{"rendered":"Prioritizing cancer screening calls"},"content":{"rendered":"\n

Context<\/strong><\/h2>\n\n

The Caisse Primaire d’Assurance Maladie (CPAM) de Meurthe-et-Moselle is setting up a call center to encourage its beneficiaries to undergo free cancer screenings<\/strong>.<\/p>\n\n

Need<\/strong><\/h2>\n\n
    \n
  • Optimizing prevention campaigns<\/strong>: The Meurthe-et-Moselle CPAM wants to give priority to contacting beneficiaries eligible for free cancer screenings <\/strong>who are most likely to participate.<\/strong><\/li>\n\n\n\n
  • Data-driven prioritization<\/strong>: This prioritization of calls will be based on the use of data available to the CPAM concerning its beneficiaries.<\/li>\n\n\n\n
  • Basic project requirements<\/strong>:\n
      \n
    • Absolute protection of personal data<\/strong>: The confidentiality of beneficiaries’ information must be guaranteed, excluding any access to Datalchemy. <\/li>\n\n\n\n
    • Methodological robustness<\/strong>: The algorithmic methods used must be statistically robust, in line with current scientific research.<\/li>\n\n\n\n
    • Project reversibility<\/strong>: Ensure that the project is passed on to internal teams so that they can take ownership of it.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n

      Completed work<\/strong> <\/h2>\n\n

      To meet this need, Datalchemy was commissioned to help the CPAM de Meurthe-et-Moselle. We were involved in : <\/p>\n\n

        \n
      • Identification of relevant data<\/strong>: Relevant beneficiary data was identified through extensive discussions with CPAM’s business and IT teams, in order to understand and target the data essential to the project.<\/li>\n\n\n\n
      • Processing real data using synthetic data.<\/strong> For the cleaning and preparation of relevant beneficiary data, an innovative approach was employed, involving the construction of a synthetic dataset,<\/strong> reproducing the characteristics of real data. This method made it possible to develop and validate a data processing code, directly applicable to CPAM confidential real data. <\/li>\n\n\n\n
      • Training and prediction of an ML model for targeting<\/strong>: Beneficiaries most likely to undergo screening are identified using an ML model trained for this purpose on cleaned real data, enabling a list of people to be prioritized for contact by the CPAM call center.<\/li>\n\n\n\n
      • Documentation and handover to CPAM teams to ensure project reversibility<\/strong>.<\/li>\n<\/ul>\n\n

        Results <\/h2>\n\n
          \n
        • The project demonstrated strong predictive performance<\/strong>, with model recall of 70%<\/strong>. <\/li>\n\n\n\n
        • A list of beneficiaries to contact has been drawn up<\/strong> for the call center. <\/li>\n\n\n\n
        • The project was carried out entirely without access to actual data<\/strong>, thus ensuring total confidentiality of personal<\/strong> CPAM<\/strong> data<\/strong>. <\/li>\n\n\n\n
        • The project was successfully passed on to the CPAM teams. <\/li>\n<\/ul>\n\n

          <\/p>\n","protected":false},"featured_media":3711,"template":"","meta":{"_acf_changed":false,"inline_featured_image":false},"tags":[189,193,186,183,191],"class_list":["post-243","projet","type-projet","status-publish","has-post-thumbnail","hentry","tag-model-training-en","tag-notebook-en","tag-pandas-en","tag-python-en","tag-xgboost-en"],"acf":[],"yoast_head":"\nPrioritizing cancer screening calls - Datalchemy<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/datalchemy.net\/en\/our-services\/targeting-beneficiaries\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Prioritizing cancer screening calls - Datalchemy\" \/>\n<meta property=\"og:description\" content=\"Context The Caisse Primaire d’Assurance Maladie (CPAM) de Meurthe-et-Moselle is setting up a call center to encourage its beneficiaries to undergo free cancer screenings. 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