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Patient generated health data and electronic health record integration in oncologic surgery: A call for artificial intelligence and machine learning
Author(s) -
Melstrom Laleh G.,
Rodin Andrei S.,
Rossi Lorenzo A.,
Fu Paul,
Fong Yuman,
Sun Virginia
Publication year - 2021
Publication title -
journal of surgical oncology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.201
H-Index - 111
eISSN - 1096-9098
pISSN - 0022-4790
DOI - 10.1002/jso.26232
Subject(s) - medicine , electronic health record , artificial intelligence , focus (optics) , health care , oncologic surgery , patient care , relation (database) , patient data , surgery , nursing , computer science , database , physics , optics , economics , economic growth
Abstract In this review, we aim to assess the current state of science in relation to the integration of patient‐generated health data (PGHD) and patient‐reported outcomes (PROs) into routine clinical care with a focus on surgical oncology populations. We will also describe the critical role of artificial intelligence and machine‐learning methodology in the efficient translation of PGHD, PROs, and traditional outcome measures into meaningful patient care models.