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Developing a Prognostic Information System for Personalized Care in Real Time.
Lieu, Tracy A; Herrinton, Lisa J; Buzkov, Dimitri E; Liu, Liyan; Lyons, Deborah; Neugebauer, Romain; Needham, Tami; Ng, Daniel; Prausnitz, Stephanie; Stewart, Kam; Van Den Eeden, Stephen K; Baer, David M.
Affiliation
  • Lieu TA; The Permanente Medical Group, Kaiser Permanente Northern California, US.
  • Herrinton LJ; Division of Research, Kaiser Permanente Northern California, US.
  • Buzkov DE; The Permanente Medical Group, Kaiser Permanente Northern California, US.
  • Liu L; Division of Research, Kaiser Permanente Northern California, US.
  • Lyons D; The Permanente Medical Group, Kaiser Permanente Northern California, US.
  • Neugebauer R; Division of Research, Kaiser Permanente Northern California, US.
  • Needham T; The Permanente Medical Group, Kaiser Permanente Northern California, US.
  • Ng D; Division of Research, Kaiser Permanente Northern California, US.
  • Prausnitz S; The Permanente Medical Group, Kaiser Permanente Northern California, US.
  • Stewart K; TPMG Technology Group, Kaiser Permanente Northern California, US.
  • Van Den Eeden SK; The Permanente Medical Group, Kaiser Permanente Northern California, US.
  • Baer DM; Division of Research, Kaiser Permanente Northern California, US.
EGEMS (Wash DC) ; 7(1): 2, 2019 Mar 25.
Article in En | MEDLINE | ID: mdl-30937324
ABSTRACT
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.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: EGEMS (Wash DC) Year: 2019 Document type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: EGEMS (Wash DC) Year: 2019 Document type: Article Affiliation country: United States