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<p>Patient portals are widely available to facilitate self-service interactions, including appointment booking, offering convenience to users. Promoting clinically appropriate care pathways, however, is complex; portals must recognize patient intent while striving for an intuitive experience. In October 2024, the Southern California Permanente Medical Group, which serves 4.9 M patients, deployed the Kaiser Permanente Intelligent Navigator (KPIN), a system that augments the patient portal to enhance care navigation and the patient experience. It applies natural language processing to generate alerts for high-acuity cases, and it recommends suitable care offerings. Early findings are promising, with the AUC for clinical alerts and clinical navigation at 0.977 and 0.889, respectively. KPIN’s adjusted successful booking rate was 53.68%, with an abandonment rate of 2.94% (IQR: 2.77–3.11%), aligning with patient survey results showing an 8.63 percentage point increase for positive sentiment. These results highlight the success of KPIN in an integrated value-based care delivery model.</p>

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Digital transformation with clinical alerts and personalized care systems in an integrated value based model

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年7月8日

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  • Dinh Nguyen,
  • Sinjin Lee,
  • Ronil Synghal,
  • Leon Chan,
  • Ferdinand Justus,
  • Mark Moromisato,
  • Tianyuan Shao,
  • Caleb Wang,
  • Mason Kellogg,
  • Brett Anwar,
  • Julie Creech,
  • Kari Ochoa,
  • Danette Gigliotti,
  • Omar Ortiz,
  • Kien La,
  • Khang Nguyen

摘要

Patient portals are widely available to facilitate self-service interactions, including appointment booking, offering convenience to users. Promoting clinically appropriate care pathways, however, is complex; portals must recognize patient intent while striving for an intuitive experience. In October 2024, the Southern California Permanente Medical Group, which serves 4.9 M patients, deployed the Kaiser Permanente Intelligent Navigator (KPIN), a system that augments the patient portal to enhance care navigation and the patient experience. It applies natural language processing to generate alerts for high-acuity cases, and it recommends suitable care offerings. Early findings are promising, with the AUC for clinical alerts and clinical navigation at 0.977 and 0.889, respectively. KPIN’s adjusted successful booking rate was 53.68%, with an abandonment rate of 2.94% (IQR: 2.77–3.11%), aligning with patient survey results showing an 8.63 percentage point increase for positive sentiment. These results highlight the success of KPIN in an integrated value-based care delivery model.