Phoenix Children's CIO says big data tactics reduce medical errors

David Higginson explains how tapping into big data enabled it to reduce dosing mistakes among pediatric patients.
By David Higginson
08:24 AM
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big data reduce medical errors

While dosing errors are a major issue for hospitals and health systems, the concern is even greater for pediatric providers. Our patients vary dramatically in weight, from 10-ounce premature babies to 200-pound adolescents. Because medication dosing is based on weight, this variability among patients increases the likelihood of mistakes, creating a significant safety hazard. Even more important, there is very little room for error when giving medications to small patients.

To protect the safety of our young patients, Phoenix Children’s Chief Medical Information Officer Vinay Vaidya, MD, led a team to develop a “zero-tolerance” dose range checking system. The goal was a lofty one: to eliminate 100 percent of overdosing errors at the prescribing stage.

The team used the power of technology to develop and implement the system, a process that included three key steps.

The first was an extensive analysis of more than 750,000 prescription orders from Phoenix Children’s across an eight-year period. 

[Also: Healthcare IT News names Phoenix Children's #1 Large Best Hospital IT Department 2016]

Second, the hospital conducted a study of drug dosage reference information and feedback from pharmacists and physicians to define thresholds for “very high” and “dangerously high” doses.

The third step was to create a two-tiered alert system within the electronic health record that would return a “soft stop” or “hard stop” at the time of order entry, requiring the prescriber to consult a pharmacist and/or amend the dose to an appropriate range

Since the rollout of the Pediatric Dose Range Checking System in 2011, there has been no overdosing at the prescribing stage at Phoenix Children’s.

The success of this effort has led to dozens of other clinical intelligence solutions that harness the power of data and provide clinical decision support at the point of care to improve quality and safety. Other notable examples include automated isolation orders for patients returning to the hospital who are known to harbor multidrug-resistant organisms, and automated urine pregnancy screening orders for eligible adolescent female patients presenting to the ER.

All told, these efforts illustrate the power of innovation and technology in producing tangible results and improving patient care.


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