Use of digital
healthcare technology, like a recently developed trauma care app, reduces variation in patient care and can improve outcome, according to a paper presented at the 2014 RACS/ANZCA Annual Scientific Congress in Singapore.
The research, presented by J.M. Hsu, MBBS, FRACS, of Westmead Hospital in New South Wales, described the process of developing the app which was based on standardized trauma algorithms. The app was designed to allow providers real-time, instant access to important trauma algorithms in an effort to reduce omissions and errors in care.
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Hsu and colleagues stated that prior to 2012, individual clinicians determined trauma care at the study center, Westmead Hospital.
“In 2012, a set of clinical algorithms for trauma was developed. These algorithms described diagnostic and management pathways from initial reception of the trauma patient, through the critical care and ward episodes of care,” Hsu and team wrote. “Existing guidelines and key papers in the trauma literature formed the basis of the algorithms.”
Thirty-two distinct algorithms were developed and each featured the following:
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Single page
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Simple flow diagram with readily identifiable critical decision nodes
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Minimum explanatory text
Researchers with the hospital began designing the app in May of 2013 and it was released on the iTunes App Store in January 2014. It featured the following:
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Landscape orientation for all algorithms
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Rotational orientation, i.e. always displays an upright orientation
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Pinch to zoom
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Search capability
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Home button
In the four months after its release, the app was downloaded 733 times and rated 4 and a half stars.
“There is ample evidence to suggest that standardized practices improve trauma outcomes. Shafi et al. demonstrated that increasing compliance to specified processes of care reduced mortality for trauma patients,” the authors wrote.
The widespread and increasing use of digital health technology has provided opportunities to further enhance trauma care.
“The development of an app, containing trauma care algorithms with critical decision nodes, has allowed efficient access to a decision aid for clinical staff at the point-of-care,” Hsu and colleagues concluded.
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