Enabling a learning healthcare system with automated computer protocols that produce replicable and personalized clinician actions

• Main Authors: Morris, AH, Stagg, B, Lanspa, M, Orme, J, Clemmer, TP, Weaver, LK, Thomas, F, Grissom, CK, Hirshberg, E, East, TD, Wallace, CJ, Young, MP, Sittig, DF, Pesenti, A, Bombino, M, Beck, E, Sward, KA, Weir, C, Phansalkar, SS, Bernard, GR, Taylor Thompson, B, Brower, R, Truwit, JD, Steingrub, J, Duncan Hite, R, Willson, DF, Zimmerman, JJ, Nadkarni, VM, Randolph, A, Curley, MAQ, Newth, CJL, Lacroix, J, Agus, MSD, Lee, KH, Deboisblanc, BP, Scott Evans, R, Sorenson, DK, Wong, A, Boland, MV, Grainger, DW, Dere, WH, Crandall, AS, Facelli, JC, Huff, SM, Haug, PJ, Pielmeier, U, Rees, SE, Karbing, DS, Andreassen, S, Fan, E, Goldring, RM, Berger, KI, Oppenheimer, BW, Wesley Ely, E, Gajic, O, Pickering, B, Schoenfeld, DA, Tocino, I, Gonnering, RS, Pronovost, PJ, Savitz, LA, Dreyfuss, D, Slutsky, AS, Crapo, JD, Angus, D, Pinsky, MR, James, B, Berwick, D
• Other Authors: DEAN'S OFFICE (MEDICINE)
• Format: Review
• Published: 2023
• Subjects: Clinical Decision-Making; Computers; Documentation; Electronic Health Records; Humans; Learning Health System
• Online Access: https://scholarbank.nus.edu.sg/handle/10635/246029
• Institution: National University of Singapore

10.1093/jamia/ocaa294