Table 1.

Strategies to reduce errors and their consequences, with examples of application to healthcare and research work.

Strategy description	Example of how it has been applied to healthcare	Example of how it can be applied to research work
Prevent Error
Establish a reliable process (standardize whenever possible)	Consistent use of a checklist that details steps for safe insertion of central lines prevented catheter-related blood stream infections [10].	Create a study data management plan that details how data elements will be handled and adequately train research team members performing data handling tasks. For example, describe how missing values will be exported and coded distinguishing the handling of zero values, codes for missing values (like 999), and out of range/impossible values. Also, specify the type of data (dates, text, numbers) and pre-define a value range to identify out of range/impossible values.
Change process (or device) so that it is impossible to make the error anymore	A safety system was incorporated in the design of the anesthesia machine that safeguarded against the possibility of delivering the wrong gas supply. The system included a specific pin configuration for the Oxygen and Nitrous Oxide gas cylinders which made the user unable to connect the cylinder to the incorrect plug [11].	Use statistical software that allows for programming and direct export of tables and any associated text instead of copying/pasting values from analytic output. This eliminates possibility of errors from copying the wrong values or pasting them incorrectly into the table.
Eliminate unneeded tasks or parts	The concentrated injection solution of esmolol HCl (250 mg/mL) used to treat cardiac arrythmias was discontinued to prevent medication overdoses that resulted from failure to dilute it. Currently, this medication is available in ready-to-use 10-mg/mL vial (does not require dilution) [12].	Use direct data entry into computer devices (e.g use tablets or laptops to directly enter data as you collect it) rather than writing on paper forms and then reentering the data into computer. The data entry programs should include checks for inconsistencies or out-of-range responses. Avoid variable recoding as much as possible (if needed, clearly name and label the recoded variable for audit).
Facilitate the work, reducing complexity and ambiguity, so that it is less likely to make a mistake (e.g. use checklists and well documented procedure manuals)	Use of electronic medical record systems with built in algorithms facilitated decision-making and prescribing of venous thromboembolism (VTE) prophylaxis medications [13]. Tall-man lettering on medication vials is used to prevent mixing up look-alike drugs [14].	Create a process for data managers and analysts to become familiar with research study background, design, and all input forms and instruments, before proceeding to data preparation and analysis. ( E.g. hold dedicated meetings for this purpose prior to starting any data preparation for analysis) Maintain a single electronically-locked master data file from which data can then be exported for specific analytic purposes. Any version of a master data file should be annotated with a datetime stamp to confirm the latest version to be used. Documentation should note the reasons for subsequent master data files.
Create work environment that strives to prevent errors and supports teamwork	In response to high rates of preventable adverse events post hospital discharge, interventions have been implemented to facilitate coordination between inpatient and outpatient providers, including adding dedicated case managers and transition coaches on healthcare teams to help with discharge planning, and addressing patients' needs [15].	Consider handoffs of information and responsibilities (e.g. with team member turnover) as high risk/error-prone periods. Ensure sufficient communication and clarity on who is doing what at such times, and how any questions will be resolved.
Detect error
Make errors more visible/discoverable	Patient identification bands are used to avoid patient misidentification errors [16]. Electronic prescribing system alerts to prevent medication errors [17].	Use variable names that refer to specific forms so that they can be audited back to their source document, making errors more visible/discoverable. (Use industry standards and best practices as applicable) Run range checks and challenges for improbable and impossible values. Check consistency of values across study visits.
Create redundancy (i.e. multiple checks}	Independent double check of medication doses for high-alert medications [18].	Have critical and error-prone tasks performed by two independent individuals. This includes checks if summary tables and values have been copied/pasted. (Have this checking plan specified ahead of time so the two independent individuals apply the same rules).
Mitigate the effect of errors
Minimize direct effects of the errors	Rapid resuscitation measures for victims of medication overdose.	Report corrections for all published work that is affected by errors.
Learn from mistakes to prevent similar future events	Promoting safety culture and use of voluntary error- reporting systems to learn from errors and institute measures to prevent their recurrence [19].	Promote a culture that encourages admission of errors, discussion of underlying causes, and learning from them. This would require a collective ongoing effort from research leaders and funders to acknowledge that errors do occur in well conducted research, encourage reporting of those errors, and support those who report them.