Abstract data connectivity pattern
HealthOctober 18, 2021

Can we achieve drug data unity?

Health information exchange is generally viewed as less than a smooth process. When it comes to drug data, we strive to set and enforce standards to unify our communications and data sharing. And yet, gaps remain in the type of data we are sharing, revealing key safety inputs that are often missing.

Idealistically, we have, right now, the data and the capabilities to achieve a fully interoperable healthcare ecosystem, informatics experts say. If every healthcare entity in a given region committed to adopting a set of standards for data sharing — including broadening what types of patient information is shared — and to implementing and developing a consistent interoperable technology, it could enable widespread data unity and information exchange.

Realistically, however, that doesn’t happen.

When it comes to setting standards for information exchange, generally, whichever body steps up to propose a standard becomes the standard bearer, says Steven Hart, MD, a clinical informatics expert, even if that standard is ambiguous or less well-defined than the industry may have hoped.

Once a standard has been set and starts to become implemented, it is complex and costly to change it, adds Sarah Smith, PharmD, Director of Harmonized Clinical Decision Support for Clinical Effectiveness at Wolters Kluwer, Health. The investment of time and money to undo or redo an established health data vocabulary or standard identifier that is implemented and entrenched throughout a major health system, retail chain, benefits provider, or national health organization’s information system — let alone thousands of such entities — would be substantial, and in some cases daunting enough to discourage the endeavor.

The clinical data input gap

Data unity is about more than how we share data, it’s about what data we share, according to Hart and informatics experts.

For example, in a hospital setting, healthcare professionals have access to a wealth of inputs from which to draw context for clinical drug safety screenings:

  • Diagnosis / indication
  • Age
  • Weight
  • Gender / sex assigned at birth
  • Any available and relevant labs (i.e., potassium, sodium)
  • Current drug levels
  • Renal function measurement (Serum creatinine/ Creatinine clearance/ eGFR)

But then, that patient and their prescription leave the hospital and head out into the wide world of retail pharmacies, clinics, outpatient care, and insurance counseling services. And usually, the only data that goes with them and their script are:

  • Age
  • Gender
  • Indication (sometimes)

More complete sharing of information — including sending retail pharmacies more complete problem lists, renal function estimates, and even basic patient weight — would lead to more precise drug safety screenings, and ultimately, fewer drug errors, according to Hart and Smith. However, the financial value of implementing a substantial change to information sharing standards would be difficult to quantify, and it would be challenging to draw a straight line from cause to effect.

So, what should we be sharing and how do we bridge the information gaps between healthcare entities?

Download the eBook, “Drug Data Unity: Realistic and Idealistic Futures for Information Exchange.”

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