Table 3.

Overview of the automated trigger tool methodology.

Study		Description of the method
Diagnostic test accuracy studies
	Gerdes and Hardahl, 2013 [44]	(1) Extraction and preparation of all texts from the EHRsa; (2) Use of SAS Text Miner and the SAS Enterprise Content Categorization software to build query models (natural language processing algorithms)
	O’Leary et al, 201 3[41]	(1) Leveraging of various information systems in the EDWb; (2) Write Structured Query Language queries to mimic work of a reviewer to identify potential AEsc based on trigger tool; (3) Two reviewers review the positive EDW screens; (4) Another reviewer reviews narrative summaries and determines presence of AEs
Prevalence studies
	Call et al, 2014 [36]	(1) Software program conducts an extensive search of patient records for any type of order containing specific medications and laboratory values; (2) Information generated into a report with patient-specific information; (3) Review by two reviewers
	Dickermann et al, 2011 [37]	(1) Trigger reports automatically generated on a daily basis from the EHR by querying the Sunquest Laboratory Information System for laboratory results; (2) Reviewer examined every trigger by reading the EHRs and interviewing care providers
	Lim et al, 2016 [42]	(1) Administration of a trigger drug to a patient automatically sent an electronic trigger-detection message to two reviewers; (2) Trigger-detection messages were evaluated immediately after or during the day by both reviewers (consensus if disagreement); (3) Event reviewed by a medication safety pharmacist and then by a physician for validation.
	Moore et al, 2009 [38]	(1) The laboratory results and administered medications of each adult hospital patient were continuously monitored by the computerized trigger alert system; (2) If any of the conditions defined was satisfied (trigger algorithm), an alert was triggered, and data were collected by study investigators on the patient for a period of 72 hours after the initial trigger firing to determine whether an adverse drug event had occurred.
	Muething et al, 2010 [39]	(1) Combination of trigger tool approach with the clinical information system; (2) Every evening, automatic detection of triggers are sent to the project manager (detection of event within 24 h); (3) Summary of the incident automatically generated and sent to the appropriate staff on the unit involved
	Nwulu et al, 2013 [45]	(1) The triggers identified electronically were linked to the electronic prescription records; (2) Two or more positive triggers generated for the same patient, within a 24- or 72-hour interval (trigger-dependent) were treated as one trigger; (3) The paper-based case notes were reviewed to identify any documentation of interest
	Patregnani et al, 2015 [43]	(1) Generation of a trigger report by querying the Laboratory Information System (2) Reviewer investigated the event by reading the patient’s EHRs and interviewing the clinical care team
	Shea et al, 2013 [40]	(1) Generation of a trigger report by querying the Laboratory Information System (2) Reviewer investigated the event by reading the patient’s EHRs and interviewing the clinical care team
	Stockwell et al, 2013 [25]	(1) Automated trigger reports are generated from hospital information systems on a nightly basis; (2) Each trigger report is examined by a reviewer and interviews conducted with care providers.

^aEHRs: electronic health records.

^bEDW: Enterprise Data Warehouse.

^cAEs: adverse events.