Varying rates of patient identity verification when using computerized provider order entry

Duplicate Medication Order Errors: Safety Gaps and Recommendations for Improvement

Background: Duplicate medication orders are a prominent type of medication error that in some circumstances has increased after implementation of health information technology. Duplicate medication orders are commonly defined as two or more active orders for the same medication or medications within the same therapeutic class. While there have been several studies that have identified contributing factors and described potential solutions, duplicate medication order errors continue to impact patient safety. Methods: We analyzed 377 reports from 95 healthcare facilities to more granularly define the types of duplicate medication order errors and the context under which these errors occurred, as well as potential contributing factors. Results: Of the 377 reports reviewed, 304 (80.6%) met the criteria to be defined as a duplicate medication order error. The most frequent duplicate medication order error type was same order (n=131, 43.1%), followed by same therapeutic class (n=98, 32.2%) and same medication (n=70, 23.0%). Errors were identified during different medication process tasks and most commonly during medication reconciliation during the patient’s stay in the hospital (n=72, 23.7%) and during pharmacy verification (n=36, 11.8%). Factors contributing to these errors included health information technology issues (n=63, 20.7%), gaps in care coordination (n=44, 14.5%), and a prior dose or medication order not being discontinued (n=52, 17.1%). Conclusion: Our results highlight specific areas for practice improvement, and we make recommendations for how healthcare facilities can better address duplicate medication order errors.

Human Factors and Organizational Issues in Health Informatics: Innovations and Opportunities

OBJECTIVE

Human factors and ergonomics (HF/E) frameworks and methods are becoming embedded in the health informatics community. There is now broad recognition that health informatics tools must account for the diverse needs, characteristics, and abilities of end users, as well as their context of use. The objective of this review is to synthesize the current nature and scope of HF/E integration into the health informatics community.

METHODS

Because the focus of this synthesis is on understanding the current integration of the HF/E and health informatics research communities, we manually reviewed all manuscripts published in primary HF/E and health informatics journals during 2020.

RESULTS

HF/E-focused health informatics studies included in this synthesis focused heavily on EHR customizations, specifically clinical decision support customizations and customized data displays, and on mobile health innovations. While HF/E methods aimed to jointly improve end user safety, performance, and satisfaction, most HF/E-focused health informatics studies measured only end user satisfaction.

CONCLUSION

HF/E-focused health informatics researchers need to identify and communicate methodological standards specific to health informatics, to better synthesize findings across resource intensive HF/E-focused health informatics studies. Important gaps in the HF/E design and evaluation process should be addressed in future work, including support for technology development platforms and training programs so that health informatics designers are as diverse as end users.

Health Information Technology–Related Wrong-Patient Errors: Context is Critical

Health information technology (HIT) provides many benefits, but also facilitates certain types of errors, such as wrong-patient errors in which one patient is mistaken for another. These errors can have serious patient safety consequences and there has been significant effort to mitigate the risk of these errors through national patient safety goals, in-depth research, and the development of safety toolkits. Nonetheless, these errors persist. We analyzed 1,189 patient safety event reports using a safety science and resilience engineering approach, which focuses on identifying processes to discover errors before they reach the patient so these processes can be expanded. We analyzed the general care processes in which wrong-patient errors occurred, the clinical process step during which the error occurred and was discovered, and whether the error reached the patient. For those errors that reached the patient, we analyzed the impact on the patient, and for those that did not reach the patient, we analyzed how the error was caught. Our results demonstrate that errors occurred across multiple general care process areas, with 24.4% of wrong-patient error events reaching the patient. Analysis of clinical process steps indicated that most errors occurred during ordering/prescribing (n=498; 41.9%) and most errors were discovered during review of information (n=286; 24.1%). Patients were primarily impacted by inappropriate medication administration (n=110; 37.9%) and the wrong test or procedure being performed (n=65; 22.4%). When errors were caught before reaching the patient, this was primarily because of nurses, technicians, or other healthcare staff (n=303; 60.5%). The differences between the general care processes can inform wrong-patient error risk mitigation strategies. Based on these analyses and the broader literature, this study offers recommendations for addressing wrong-patient errors using safety science and resilience engineering, and it provides a unique lens for evaluating HIT wrong-patient errors.