Mortality prediction models, causal effects, and end-of-life decision making in the intensive care unit

Jason H Maley^{1

2}, Kerollos N Wanis³, Jessica G Young^{3

4}, Leo A Celi^{2

5}

Affiliations

¹ Center for Healthcare Delivery Science, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA jmaley@bidmc.harvard.edu.
² Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
³ Department of Epidemiology, Harvard University T H Chan School of Public Health, Boston, Massachusetts, USA.
⁴ Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA.
⁵ Division of Pulmonary, Critical Care, and Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA.

Jason H Maley et al. BMJ Health Care Inform. 2020 Oct.

. 2020 Oct;27(3):e100220.

doi: 10.1136/bmjhci-2020-100220.

Jason H Maley^{1

2}, Kerollos N Wanis³, Jessica G Young^{3

4}, Leo A Celi^{2

5}

¹ Center for Healthcare Delivery Science, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA jmaley@bidmc.harvard.edu.
² Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
³ Department of Epidemiology, Harvard University T H Chan School of Public Health, Boston, Massachusetts, USA.
⁴ Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA.
⁵ Division of Pulmonary, Critical Care, and Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA.

No abstract available

Keywords: information science; medical informatics; patient care.

Conflict of interest statement

Competing interests: None declared.

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