By Jason S. Adelman, MD, MS, Chief Patient Safety Officer and Associate Chief Quality Officer; Executive Director, Center for Patient Safety Research; Director, Patient Safety Research Fellowship, Columbia University Irving Medical Center and NewYork-Presbyterian; Associate Professor of Medicine (in biomedical informatics) and Vice Chair for Quality and Patient Safety, Department of Medicine, Columbia University Vagelos College of Physicians and Surgeons
Editor’s Note: Dr. Adelman was recently honored with the 2022 John M. Eisenberg Patient Safety and Quality Award for Individual Achievement.
I began my career as a hospitalist and was motivated to pursue patient safety after witnessing the sometimes-catastrophic medical errors that occur in the hospital environment. In one case, an elderly woman admitted with an irregular heartbeat and bronchitis was accidentally given a dose of methadone intended for a 35-year-old male patient. A resident clicked on the wrong patient in the electronic health record (EHR), a pharmacist signed off on the order, and a nurse-in-training administered the medication. The patient was found unresponsive several hours later, intubated and transferred to the intensive care unit (ICU). It would be easy to blame the providers, but that wouldn’t prevent this type of error from happening again.
A basic principle of patient safety is to identify system failures that lead to errors, fix systems in order to protect patients from errors, and prevent clinicians from making errors. Toward this goal, I assembled a team of clinicians, patient safety leaders, and health information technology (health IT) specialists to develop two alerts to prevent wrong-patient errors:
- ID-verify alert that displays the patient’s identifiers on initiating orders requiring a single click to proceed
- ID-reentry alert that requires the clinician to enter the patient’s initials, gender and age
We posed the question, “How we would know if the interventions were effective?” While one in five Americans experience a medical error, there was no mechanism to detect errors in EHRs. The answer was developing the Wrong-Patient Retract-and-Reorder (RAR) measure, an electronic query that identifies orders that are placed for a patient, canceled within 10 minutes, then reordered for a different patient by the same clinician within the next 10 minutes.
Because these events can be captured soon after they occur, we contacted clinicians involved and confirmed that 76% of events were errors. Additionally, we found that, compared with no alert, wrong-patient orders were significantly reduced by 16% with the ID-verify alert and by 41% with the ID-reentry alert.
Success of Wrong-Patient RAR Measure
Based on these results, the Office of the National Coordinator for Health Information Technology (ONC) Patient Identification SAFER Guide recommends verifying patient identification at the time of ordering as a best practice and using the Wrong-Patient RAR measure for monitoring and surveillance. Following this recommendation, Epic, which owns one of the most used EHR systems in the United States, built a verification alert into its EHR system.
The Wrong-Patient RAR measure detected more than 7,000 events in one year at a large academic medical center, providing hard evidence of the scope of the problem. The Wrong-Patient RAR measure was the first and only health IT safety measure endorsed by National Quality Forum (NQF) and made possible a new field of research. It also has been used to answer research questions regarding patient identification in vulnerable populations, safety of EHR configurations, and benefits of safety interventions, with additional studies underway.
Addressing Wrong-Patient Errors for Newborns in NICU
In another area of this research, the risk of wrong-patient errors among the vulnerable population of newborns receiving care in neonatal intensive care units (NICUs) was suspected but, in the absence of standardized measures, could not be systematically quantified. Using the Wrong-Patient RAR measure, we demonstrated a significantly higher rate of wrong-patient orders in NICUs versus general pediatric units and a greater risk among multiple- versus singleton-birth infants.
The temporary naming convention typically used by hospitals (e.g., Babyboy/Babygirl) was thought to be a major contributing factor to wrong-patient errors in the NICU. To prevent these errors, we conducted a study using a more distinct naming convention that incorporated the mother’s first name (e.g., Judysboy/Judysgirl). Use of the distinct naming convention significantly reduced wrong-patient orders in the NICU by 36.3%. Citing these results, The Joint Commission now requires hospitals to use distinct methods of newborn identification in its National Patient Safety Goals (NPSGs), and Joint Commission International issued a standard in its International Patient Safety Goals (IPSGs) using the example “Anupam Girl Patel” instead of “Girl Patel.”
Future Expansion of RAR Method
Expanding the innovative RAR method, researchers will be able to study medication errors, radiology errors and more. In my current research, I am leading a research team to develop additional order error measures using the novel RAR method. These measures make it possible, as never before, to:
- understand the epidemiology and root causes of orders errors
- design targeted prevention strategies
- utilize a systematic outcome measure to test the strategies
In my dual roles as Patient Safety Researcher and Chief Patient Safety Officer for a large healthcare system, I have also addressed falls prevention, diagnostic errors, safety culture, and COVID-19 safety through my work. I am currently leading safety culture transformation throughout the NewYork-Presbytarian enterprise where I designed and conducted an interactive safety culture training program for senior leadership, management, and staff.
I am honored to be the recipient of the John M. Eisenberg Patient Safety and Quality Award for Individual Achievement from The Joint Commission and NQF— two organizations that define the standards and measures used to evaluate the nation’s performance in quality and patient safety.
Jason S. Adelman, MD, MS, is Chief Patient Safety Officer and Associate Chief Quality Officer; Executive Director, Center for Patient Safety Research; Director, Patient Safety Research Fellowship, Columbia University Irving Medical Center and NewYork-Presbyterian; Associate Professor of Medicine (in biomedical informatics) and Vice Chair for Quality and Patient Safety, Department of Medicine, Columbia University Vagelos College of Physicians and Surgeons.
The Eisenberg Award honored Dr. Adelman, an internationally recognized expert and researcher in patient safety, whose research developing and validating automated measures of medical errors using electronic health record (EHR) data, examining the epidemiology of medical errors in healthcare systems, and testing system-level approaches to prevent these errors using health information technology (IT), has had a significant impact in the field of patient safety.