International journal of medical informatics
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Accurate and scalable surveillance methods are critical to understand widespread problems associated with misuse and abuse of prescription opioids and for implementing effective prevention and control measures. Traditional diagnostic coding incompletely documents problem use. Relevant information for each patient is often obscured in vast amounts of clinical text. ⋯ Scalable, semi-automated NLP methods can efficiently and accurately identify evidence of problem opioid use in vast amounts of EHR text. Incorporating such methods into surveillance efforts may increase prevalence estimates by as much as one-third relative to traditional methods.
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We examined the role of privacy in collaborative clinical work and how it is understood by hospital IT staff. The purpose of our study was to identify the gaps between hospital IT staff members' perceptions of how electronic health record (EHR) users' protect the privacy of patient information and how users actually protect patients' private information in their daily collaborative activities. Since the IT staff play an important role in implementing and maintaining the EHR, any gaps that exist between the IT staff's perceptions of user work practices and the users' actual work practices can result in a number of problems in the configuration, implementation, or customization of the EHR, which can lead to collaboration challenges, interrupted workflow, and privacy breaches. ⋯ A hospital's IT staff face a daunting task in ensuring users' collaborative work practices are supported by the system while providing effective privacy mechanisms. In order to achieve both goals, the IT staff must have a clear understanding of their users' practices. However, as this study highlights, there may be a mismatch between the IT staff's understandings of how users protect patient privacy and how users actually protect privacy.
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Computerized provider order entry systems commonly contain alerting mechanisms for patient allergies, incorrect doses, or drug-drug interactions when ordering medications. Providers have the option to override (bypass) these alerts and continue with the order unchanged. This study examines the effect of customizing medication alert override options on the appropriateness of override selection related to patient allergies, drug dosing, and drug-drug interactions when ordering medications in an electronic medical record. ⋯ There is a benefit realized by using a customized list for medication override reasons. Poor application design or configuration can negatively affect provider behavior when responding to important medication alerts.