. 2021 Jan 5;28(3):653–663. doi: 10.1093/jamia/ocaa296

Table 2.

Summary of study characteristics

Characteristic	Variable	Results
Study Design	Retrospective cohort	66 (82.5)⁵^,^28–92
	Prospective cohort	5 (6.3)^93–97
	Case-control	3 (3.8)^98–100
	Qualitative	3 (3.8)¹²^,¹⁰¹^,¹⁰²
	Retrospective + prospective cohort	3 (3.8)^103–105
Location^a	United States	55 (68.8)⁵^,²⁸^,²⁹^,³¹^,³²^,³⁴^,³⁶^,^40–44^,^47–50^,⁵²^,^54–60^,⁶²^,⁶³^,^65–70^,^73–80^,⁸²^,⁸³^,⁸⁵^,^90–93^,⁹⁵^,^97–100^,¹⁰²^,¹⁰⁴^,¹⁰⁵
	United Kingdom	7 (8.8)³⁹^,⁵³^,⁵⁵^,⁶¹^,⁶³^,⁶⁷^,⁷⁷
	Taiwan	5 (6.3)³⁸^,³⁹^,⁴⁵^,⁶⁷^,⁸⁸
	Canada	4 (5)¹²^,³³^,⁸¹^,⁸⁷
	China	4 (5)³⁷^,³⁹^,⁷¹^,¹⁰³
	Australia	3 (3.8)⁸⁶^,⁹⁴^,⁹⁶
	Germany	2 (2.5)⁵¹^,¹⁰¹
	India	2 (2.5)⁶⁴^,⁸⁹
	Switzerland	2 (2.5)³⁵^,⁷²
	South Korea	1 (1.3)³⁰
	Saudi Arabia	1 (1.3)⁴⁶
	Spain	1 (1.3)⁸⁴
	France	1 (1.3)⁷⁶
	Portugal	1 (1.3)⁷⁵
Year	2019	23 (28.8)¹²^,⁴²^,⁴³^,⁶⁰^,⁶⁴^,⁶⁵^,⁶⁷^,⁶⁸^,⁷⁰^,⁷²^,⁷⁹^,⁸²^,⁸³^,⁹²^,^95–99^,^101–103^,¹⁰⁵
	2018	18 (22.5)³⁰^,³⁶^,³⁹^,⁴¹^,⁴⁶^,⁶¹^,⁶³^,⁶⁶^,⁶⁹^,⁷¹^,⁷⁴^,⁷⁸^,⁸¹^,⁸⁸^,⁸⁹^,⁹¹^,⁹⁴^,¹⁰⁴
	2017	15 (18.8)⁵^,²⁹^,³¹^,⁴⁴^,^51–53^,⁵⁷^,⁵⁸^,⁷⁵^,⁷⁷^,⁸⁰^,⁸⁵^,⁸⁷^,¹⁰⁰
	2016	12 (15)²⁸^,³²^,³⁷^,⁴⁰^,⁴⁷^,⁴⁹^,⁵⁰^,⁶²^,⁷³^,⁸⁴^,⁸⁶^,⁹³
	2015	12 (15)^33–35^,³⁸^,⁴⁵^,⁴⁸^,^54–56^,⁵⁹^,⁷⁶^,⁹⁰
Machine learning methods^a	Neural networks	34 (42.5)^28–33^,³⁵^,³⁹^,⁴¹^,⁴³^,⁴⁵^,^47–51^,⁵⁴^,⁶⁰^,⁶⁶^,⁶⁸^,⁷⁰^,⁷²^,⁷⁶^,^79–84^,⁸⁹^,⁹⁴^,⁹⁶^,⁹⁹^,¹⁰⁰
	Random forests	32 (40)³⁰^,^35–38^,⁴⁰^,^42–44^,^49–51^,⁵⁴^,⁵⁷^,^63–66^,⁷¹^,⁷⁶^,⁷⁹^,⁸³^,⁸⁸^,⁹⁰^,⁹¹^,⁹⁴^,⁹⁵^,⁹⁷^,⁹⁸^,^103–105
	Regression^b	27 (33.8)³⁰^,³²^,³⁵^,^39–41^,⁴³^,⁴⁷^,⁴⁸^,⁵⁰^,⁵⁴^,⁵⁶^,⁶¹^,⁶²^,⁶⁵^,⁷⁰^,⁷⁶^,⁷⁹^,⁸³^,⁸⁴^,⁸⁷^,⁸⁸^,^90–92^,⁹⁴^,⁹⁵
	Support vector machines	24 (30)³²^,³⁴^,³⁵^,^37–39^,⁴⁴^,^46–48^,⁵⁰^,⁵¹^,^55–57^,⁵⁹^,⁶¹^,⁶²^,⁶⁶^,⁷⁵^,⁷⁹^,⁹⁴^,⁹⁸^,¹⁰³
	Boosting	17 (21.3)³²^,⁴⁷^,⁴⁹^,⁵⁰^,⁵²^,⁵³^,^65–67^,⁶⁹^,⁷⁶^,⁷⁸^,⁹⁰^,⁹¹^,⁹⁴^,⁹⁸^,¹⁰³
	Decision trees	15 (18.8)³²^,³⁵^,^38–40^,⁴⁷^,⁴⁸^,⁵⁰^,⁵²^,⁵³^,⁵⁶^,⁶²^,⁷⁶^,⁷⁸^,⁸⁸
	Penalized regression^c	13 (16.3)⁵^,³⁵^,³⁷^,⁴⁴^,⁵⁵^,⁵⁷^,⁶⁵^,⁶⁶^,⁹¹^,⁹⁵^,⁹⁸^,¹⁰⁰^,¹⁰³
	Bayesian	13 (16.3)⁵^,³⁵^,³⁷^,³⁹^,⁴⁴^,⁵⁷^,⁶²^,⁶⁶^,⁷⁶^,⁷⁹^,⁸⁶^,⁹³^,⁹⁸
	Topic modeling	9 (11.3)⁵⁵^,⁵⁷^,⁵⁹^,⁶⁶^,⁷⁹^,⁸⁰^,⁸⁵^,⁹¹^,⁹⁹
	Ensemble	7 (8.8)⁵²^,⁵³^,⁶²^,⁷⁶^,⁷⁸^,⁸¹^,⁹⁵
	Nearest neighbors	6 (7.5)³⁵^,⁵⁰^,⁵⁴^,⁷²^,⁹⁸^,¹⁰³
	Gaussian process	5 (6.3)⁵^,²⁹^,³¹^,⁵⁵^,⁹⁸
	Clustering	5 (6.3)⁵¹^,⁶¹^,⁸⁷^,⁸⁹^,⁹²
	Reinforcement learning	4 (5)³⁴^,⁶³^,⁷³^,⁷⁷
	Generalized additive models	3 (3.8)⁷⁶^,⁹⁰^,⁹⁵
	Bagging	3 (3.8)³⁵^,⁵⁰^,⁷⁶
	Discriminant analysis	2 (2.5)³⁵^,⁶¹
	Word vectorization	2 (2.5)⁶⁴^,⁸⁹
	Other methods^d	10 (12.5)³²^,³⁵^,³⁷^,⁴⁴^,⁵⁴^,⁵⁸^,⁷²^,^74–76
Sample size	Qualitative	10-19 clinicians
Sample size	Model development	127 patients to 296,724 hospital admissions
Clinical specialty^a	Intensive care (adult)	37 (46.3)⁵^,¹²^,²⁸^,³⁰^,³⁴^,⁴³^,⁴⁴^,^51–53^,⁵⁵^,⁵⁶^,^58–61^,⁶³^,⁶⁴^,^66–69^,^71–77^,⁷⁹^,⁸⁰^,⁸³^,⁸⁶^,⁸⁷^,⁸⁹^,⁹¹^,¹⁰¹
	In-hospital, acute care/not further specified	14 (17.5)³⁰^,³¹^,³⁴^,⁴⁶^,⁵⁰^,⁵⁴^,⁶⁹^,⁸²^,⁸⁵^,⁹⁰^,⁹⁷^,^103–105
	Emergency medicine	14 (17.5 )¹²^,³⁵^,³⁶^,⁴⁰^,⁴²^,⁵⁷^,⁶⁹^,⁸⁴^,⁸⁶^,⁸⁸^,⁹⁰^,⁹³^,⁹⁵^,⁹⁹
	Cardiology	7 (8.8)³⁷^,⁷¹^,⁸¹^,⁸⁶^,⁸⁸^,⁹²^,¹⁰²
	Pediatric (acute and intensive care)	6 (7.5)³²^,⁵⁸^,⁷⁰^,⁷⁸^,⁸¹^,¹⁰⁰
	Nephrology	5 (6.3)⁶²^,⁶⁶^,⁷⁵^,⁷⁹^,⁸³
	Neonatal intensive care	4 (5)³³^,⁹⁴^,⁹⁶^,⁹⁸
	Stroke	4 (5)^47–49^,⁸⁶
	Surgery	3 (3.8)³⁸^,⁴¹^,⁸⁶
	Diabetes	2 (2.5)³⁹^,⁶⁵
	Pulmonology/respiratory	2 (2.5)⁴²^,⁹⁰
	Nursing	1 (1.3)⁴⁵
	Trauma	1 (1.3)⁹⁵
	In-hospital, specifically: emergency medicine, intensive care, cardiothoracic surgery/transplant, neurology/vascular/stroke, gastrointestinal, oncology/hematology/immunology/pharmacology	1 (1.3)⁸⁶

Values are n (%) or range.

Studies may fall into more than 1 category.

Does not meet our definition of machine learning but included for purposes of reporting all methods authors compared.

Including LASSO, Ridge, and Elastic Net.

Generalized linear models, conditional inference recursive partition, conditional random fields, Weibull-Cox proportional hazards, lazy learner, piecewise-constant conditional intensity model, analysis of covariance (see footnote b), analysis of variance (see footnote b), fuzzy modeling (see footnote b), switching-state autoregressive model, mimic learning, nearest shrunken centroids, J48 algorithm, PART rule.