Human Error and Privacy Breaches in Healthcare Organizations: Causes and Management Strategies

We apply Reason’s GEMS typology to study privacy breach incidents in healthcare organizations. An interpretive analysis of transcripts of interviews with privacy officers of healthcare organizations in the U.S. Midwest helps discern the underlying causes of human error and develop a framework for error management. The study finds that organizational factors causing human error constitute a greater impediment to HIPAA Privacy Rule compliance than do human factors

A cognitive taxonomy of medical errors

AbstractObjective. Propose a cognitive taxonomy of medical errors at the level of individuals and their interactions with technology.Design. Use cognitive theories of human error and human action to develop the theoretical foundations of the taxonomy, develop the structure of the taxonomy, populate the taxonomy with examples of medical error cases, identify cognitive mechanisms for each category of medical error under the taxonomy, and apply the taxonomy to practical problems.Measurements. Four criteria were used to evaluate the cognitive taxonomy. The taxonomy should be able (1) to categorize major types of errors at the individual level along cognitive dimensions, (2) to associate each type of error with a specific underlying cognitive mechanism, (3) to describe how and explain why a specific error occurs, and (4) to generate intervention strategies for each type of error.Results. The proposed cognitive taxonomy largely satisfies the four criteria at a theoretical and conceptual level.Conclusion. Theoretically, the proposed cognitive taxonomy provides a method to systematically categorize medical errors at the individual level along cognitive dimensions, leads to a better understanding of the underlying cognitive mechanisms of medical errors, and provides a framework that can guide future studies on medical errors. Practically, it provides guidelines for the development of cognitive interventions to decrease medical errors and foundation for the development of medical error reporting system that not only categorizes errors but also identifies problems and helps to generate solutions. To validate this model empirically, we will next be performing systematic experimental studies

Age, Performance and Retention Interval Effects on Acceptance of a Consumer Health Information Technology System

The older adult population will continue to place pressure on the financial and resource allocation of the healthcare industry as the over 65 population continues to grow. Health care expenditures to treat the aging population will continue to rise as older adults are more likely to have expensive chronic conditions. The future may lay with Consumer Health Information Technology which may allow the patients to have more control of their treatment schedule and self-management of their health and chronic conditions. However, older adults may exhibit cognitive declines that prohibit the learning and proper use of technology, and this assumption is a major inhibitor towards full implementation. This study used the Unified Theory of Acceptance and Use of Technology questionnaire to measure the acceptance of an over-the-counter blood pressure monitor. Twenty-six participants trained themselves to use the device and then measured their blood pressure and uploaded that data to a web software client for their potential healthcare givers for two sessions, one week apart. The results showed that older adults’ ability to perform tasks and limit errors after a retention period is worse when compared to younger adults. However, this performance decline after the retention interval did not result in a decline in the participants’ intention to use the device, showing that even with difficulty when using a novel medical device the older adults still rated that they would intend to use the device similarly to the younger cohort. These systems show the promise of ultimately relieving some of the cost burden and stress on the health industry by having more constant care and reducing hospital readmission rates but may require targeted training for older adults to better maintain task performance