Created an analytics dashboard and platform to help us collect copious decision support data and display it in a way that helps us manage clinical decision support. We can identify poorly performing alerts, rules, etc, and pick them out from the mass of CDS rules.
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Alert fatigue and poorly performing CDS results from underlying non-specific rules that can be hard to identify and mitigate efficiently. This solution uses visual analytics and formula to identify these rules, change them, and monitor the effects.
Improves safety, efficiency, and satisfaction by decreasing exposure of EHR users to bad alerts and CDS.
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Dexheimer JW, Kirkendall ES, Kouril M, Hagedorn PA, Minich T, Duan LL, Mahdi M, Szczesniak R, Spooner SA. The Effects of Medication Alerts on Prescriber Response in a Pediatric Hospital.Appl Clin Inform. 2017 May 10;8(2):491-501.
Kirkendall ES, Kouril M, Dexheimer JW, Courter JD, Hagedorn P, Szczesniak R, Li D, Damania R, Minich T, Spooner SA. Automated identification of antibiotic overdoses and adverse drug events via analysis of prescribing alerts and medication administration records. J Am Med Inform Assoc. 2017 Mar 1;24(2):295-302.
Kirkendall ES, Kouril M, Minich T, Spooner SA. Analysis of electronic medication orders with large overdoses: opportunities for mitigating dosing errors. Appl Clin Inform. 2014 Jan 8;5(1):25-45.
Kirkendall ES, Goldenhar LM, Simon JL, Wheeler DS, Andrew Spooner S. Transitioning from a computerized provider order entry and paper documentation system to an electronic health record: expectations and experiences of hospital staff. Int J Med Inform. 2013 Nov;82(11):1037-45.
Kirkendall ES, Spooner SA, Logan JR. Evaluating the accuracy of electronic pediatric drug dosing rules. J Am Med Inform Assoc. 2014 Feb;21(e1):e43-9.
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