Decision Support

Studies of what goes wrong behind the scenes in clinical software are somewhat rare. More commonly, reports address issues as they affect end users, not how those issues arise from programming errors or architectural missteps. Analysis of Clinical Decision Support System Malfunctions: A Case Series and Survey, by Wright and colleagues, provides information about how […]

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Drug Alert Fatigue and Software Design

by Jerome Carter on April 4, 2016 · 0 comments

The rise in EHR adoption has brought with it a 21st-century headache–alert fatigue.   Every day clinicians deal with numerous medication-related alerts, such as allergies, drug interactions, and duplicate medications.   Making matters worse is the fact that many alerts are clinically insignificant, causing cognitive overload and workflow disruptions, which could result in lower quality care.   Faced […]

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Pre/post-implementation studies typically use a few standard measures. Business metrics (e.g., total cost of ownership, return on investment, revenue changes) and clinical metrics (e.g., patient visit levels, visit duration) are employed to get an understanding of how the EHR’s presence has impacted the organization (1,2,3).   Unfortunately, clinical metrics often assess the post-implementation state from too […]

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Current EHR and HIT thinking places significant value on immediate and downstream use of EHR data.   The expected benefits of interoperability, clinical decision support, and data analytics all depend on accurate EHR data.  Yet, somehow, data quality has not gotten the attention that it should.   While clinical researchers are increasingly focused on improving phenotyping algorithms […]

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Those of you who follow along regularly know the importance I place on workflow for everything from EHR design to practice optimization.    Workflow technology is rapidly maturing and deserves consideration for clinical applications.   Clinical decision support is an obvious way to introduce workflow technology into healthcare systems.   However, computerization of guidelines has a long history […]

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EHR Data Accuracy—Should You Be Concerned?

by Jerome Carter on April 9, 2012 · 0 comments

When creating the EHR at UAB, I spent months working on the data model.   Much of that effort went into making sure that the data captured would be suitable for outcomes research.   Of course, the data model can only do so much to ensure data quality–what users choose to enter also plays a role. Anyone […]

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