Develop and Validate Health IT Safety Measures To Capture Violations of the Five Rights of Medication Safety (New York)

Project Details - Ongoing


The 2011 Institute of Medicine (IOM) report, Health IT and Patient Safety, raised awareness of new patient safety risks introduced by health information technology (IT) systems. However, it noted a lack of evidence quantifying the magnitude of these risks due to inadequate systems for capturing health IT safety events. As part of its recommendations, the IOM called for the Agency for Healthcare Research and Quality (AHRQ) to fund the development of “new measures for reliably assessing the current state of health IT safety and monitoring for improvements.”

This project will expand the use of a previously validated measure, the “Wrong-Patient Retract-and-Reorder (RAR) Measure,” to develop health IT measures needed for identifying violations of the “Five Rights of Medication Safety”: right patient, right dose, right medication, right route, and right frequency. For example, the “Wrong-Dose Retract-and-Reorder Measure” will identify an order placed on a patient that is retracted within 10 minutes and then placed by the same clinician on the same patient, but with a different dose within the next 10 minutes.

The specific aims of this project are as follows:

  • Develop and pilot effective and valid measures for detecting wrong-dose, wrong-medication, wrong-route, and wrong-frequency electronic orders in an acute care setting, by extending the wrong-patient Retract-and-Reorder automated detection method. 
  • Implement the automated measures developed in the first aim at a second hospital, using a different electronic health record, to evaluate the reliability of the measures. 
  • Conduct a multisite observational study describing the overall frequency of wrong-patient, wrong-dose, wrong-medication, wrong-route, and wrong-frequency electronic orders and describe the frequency in subgroups characterized by provider, patient, and system factors. 

An advisory panel of health IT and medication safety experts will develop measure specifications for each proposed measure to be implemented and validated. These specifications will be implemented to create a real-time list of RAR events for each measure. In order to assess each measure’s accuracy, 200 of the automatically identified RAR events per measure will be confirmed via telephone interviews. Refinements to the measure will be made until 75 percent of the time automated identification of an event is confirmed to be a true event. The final measures will be implemented and revalidated at two separate hospital settings to test if the measures are reliable and remain valid when implemented in different EHRs. The final measures will be applied to describe the overall frequency of wrong-patient, wrong-dose, wrong-medication, wrong-route, and wrong-frequency errors at both institutions and describe the frequency among specific subgroups characterized by provider, patient, and system factors.

Once developed, these new measures will be ready for endorsement by the National Quality Forum (NQF) and may be used to evaluate the effectiveness of interventions aimed at preventing some of health IT’s most serious and complicated safety issues.

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Leveraging Health IT to Test Solutions That Are Replicable, Scalable, and Improve Patient Safety


“Studies like that by Adelman and colleagues point the way to the creation of a digital learning health care system, in which the results of the interactions between clinicians (and, increasingly, patients and families) and the EHR are analyzed to help guide the strategies that lead to the highest value and most satisfying care. Having spent tens of billions of dollars digitating the health care system, it is essential to take advantage of the unique capacity of digital tools to allow clinicians and health care systems to learn from every click.” -editorial by Drs. Wachter, Murray, and Adler-Milstein4

Wrong-patient errors can affect any patient in any healthcare setting for a variety of reasons.

Dr. Jason Adelman, named as one of 50 experts leading the field of patient safety in 2018 by Becker’s Hospital Review,2 has led multiple AHRQ Health IT-funded research efforts centered on health IT safety. The research of Dr. Adelman, Executive Director of Patient Safety Research at Columbia University Irving Medical Center/NewYork-Presbyterian Hospital, is widespread and being replicated by other organizations. Dr. Adelman is part of the ECRI Patient Safety Collaborative, where he is advising several hospitals on how to implement the Wrong-Patient Retract-and-Reorder (RAR) Measure that he developed to evaluate the frequency of wrong-patient errors that occur through CPOE systems. When a clinician places an order, then cancels the order and places the same order for a different patient within the next 10 minutes, the measure flags it as a wrong-patient RAR event. While capturing the instance of retracting and reordering mistakes does not correct or prevent errors, it provides the facility with information to discover error trends along with opportunities to intercept processes that lead to such errors. Using such data as evidence of the CPOE’s potential impact on patient safety, decision makers can factor RAR measures in choosing one health IT design over another.

Having multiple EHRs open simultaneously does not increase wrong-patient orders.

“Placing orders on the wrong patient should never happen. Yet, human error is very common in the healthcare environment. Healthcare is inherently complex and heavily reliant on people rather than technology to protect patients from harm. It will likely take a multi-pronged health IT approach to prevent these types of errors.”
- Dr. Jason Adelman

Dr. Adelman’s AHRQ Health IT-funded research found that restricting clinicians to having one EHR record open at a time did not significantly reduce the rate of wrong-patient order errors compared with allowing up to four records to be open concurrently. His work did not support the ONC and Joint Commission recommendation that EHR systems should only allow one record to be displayed at a time. In the study, published in the May 14, 2019 issue of JAMA,3 using the RAR measure, Dr. Adelman and his team compared the risk of wrong-patient orders while accessing one versus four records open in a variety of clinical settings, including hospitals, EDs, and outpatient facilities. While no differences in wrong-patient orders were observed between those clinician groups, there was considerable variation in the frequency of errors in different clinical settings. The rate of wrong-patient order errors was lowest in outpatient settings, where physicians may care for one patient at a time. The highest rates, meanwhile, were seen in inpatient critical care and obstetrics units, which reflected differences in workflows and number of patients being cared for simultaneously, researchers noted. The research offers insights for healthcare systems that are trying to balance patient safety with the needs of busy clinicians who need tools for efficient workflow.

The right patient, right dose, right medication, right route, and right frequency.

The Health IT Program has also funded Dr. Adelman to extend research on RAR, to validate and evaluate the reliability of RAR using a different EHR system, so it can be implemented and may advance interventions to prevent these serious and complicated safety issues. The intent is to develop health IT measures that identify deviations from the Five Rights of Medication Safety: right patient, right dose, right medication, right route, and right frequency.

Use of photographs to prevent errors.

An additional Adelman-led, AHRQ-funded study is assessing the effectiveness of using patient photographs as an additional identifier in the EHR system to avoid wrong-patient errors when using CPOE systems. The research team will conduct a randomized controlled trial of wrong-patient error rates between systems with patient photos and without. Ultimately, the team plans to develop a toolkit with guidance to help other health systems in implementing patient photos in EHR systems.

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