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Developing a Prognostic Information System for Personalized Care in Real Time
Author(s) -
Tracy A. Lieu,
Lisa J. Herrinton,
Dimitri Buzkov,
Liyan Liu,
Deborah Lyons,
Romain Neugebauer,
Tami Needham,
Daniel B. Ng,
Stephanie Prausnitz,
Kam Stewart,
Stephen K. Van Den Eeden,
David Baer
Publication year - 2019
Publication title -
egems (generating evidence and methods to improve patient outcomes)
Language(s) - English
Resource type - Journals
ISSN - 2327-9214
DOI - 10.5334/egems.266
Subject(s) - champion , computer science , multidisciplinary approach , health care , medicine , data science , social science , sociology , political science , law , economics , economic growth
Context: Electronic medical records hold promise to transform clinical practice. However, technological and other barriers may preclude using them to guide care in real time. We used the Virtual Data Warehouse (VDW) to develop a tool that enables physicians to generate real-time, personalized prognostic information about survival after cancer. Case description: Patients with cancer often ask their oncologists, “Have you ever seen a patient like me?” To help oncologists answer this question, we developed a prototype Prognostic Information System (PRISM), a web-based tool that gathers data about the index patient from Kaiser Permanente’s clinical information systems, selects a historical cohort of similar patients, and displays the survival curve of the similar patients relative to key points in their treatment course. Findings and major themes: The prototype was developed by a multidisciplinary team with expertise in oncology, research, and technology. We have completed two rounds of user testing and refinement. Successful development rested on: (1) executive support and a clinical champion; (2) collaboration among experts from multiple disciplines; (3) starting with simple cases rather than ambitious ones; (4) extensive research experience with the Virtual Data Warehouse, related databases, and an existing query tool; and (5) following agile software development principles, especially iterative user testing. Conclusion: Clinical data stored in health care systems’ electronic medical records can be used to personalize clinical care in real time. Development of prognostic information systems can be accelerated by collaborations among researchers, technology specialists, and clinicians and by use of existing technology like the Virtual Data Warehouse.

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