The journey from data sharing to improved health outcomes is dependent on high-quality clinical data. Without it, it is difficult for providers to make the best clinical decisions possible, and the ability to optimize care processes and coordinated care becomes an impediment to improving health outcomes.

CommonWell Health Alliance, the Veterans Health Information Exchange, and CommonWell members have collaborated to create a new Data Quality Framework in order to evaluate real clinical data to establish improvement activities to incrementally improve the quality and consistency.

The framework strives to enhance clinicians' abilities to improve patient outcomes so that data exchanged can be easily ingested into receiving systems and used by clinicians for decision-making.

"As the CommonWell network continues to grow both in connected providers and in usage, so [do] providers' expectations for health data that offers a complete picture of a person's health history," explained Paul Wilder, executive director of the Commonwell Health Alliance.

Wilder, who will speak on the topic of improving healthcare outcomes through data quality enhancement at HIMSS21, said in the past, much of the data was read in document form – PDF or PDF-like.

Today, however, data is often in a fully coded form that can be processed by software systems.

"For the right data to be found efficiently by the user, and for the computer to extract information automatically, the data has to be in the right place and coded properly," he said.

"We know from the increase in usage that the data being exchanged is valuable, but data quality will always be important as we continue to fine-tune interoperability – especially as the quantity of data and users expands. The ultimate goal of data quality is simple: Better data, better outcomes."

Wilder said the first goal is to determine a baseline: You can't improve what you don't measure.

"What we expect to find is that most of the clinical documents shared by practices connected to CommonWell are valuable, but we also expect to find data that could be improved," he said.

With a baseline of knowledge, they can prioritize what to address and also increase confidence in the document content so vendors and HCOs can innovate on the data through things like clinical decision support and population health analytics.

Wilder noted the Data Quality Framework is meant to be a guide to aid in the process – adding a business value proposition to the traditional data quality process. He recalled that years ago, he worked with a cardiology practice that had no blood pressure measurements in their shared clinical documents.

"If there is one practice type that always measures blood pressure for a patient, it is cardiology," he said. "In fact, they often measure your pressure multiple times per visit using both your left arm and your right arm while most practices do one measurement and usually with your left arm."

Wilder explained this cardiology practice had added custom fields for left blood pressure and right pressure into their EHR, and didn't use the standard field at all.

"What they didn't know is these custom fields don't end up in their shared clinical documentation," he said. "It was an easy fix with their vendor once they discovered the problem."

Paul Wilder will discuss the ways in which enhanced data quality can improve healthcare outcomes at HIMSS21 in a session, "Improving Healthcare Outcomes by Enhancing Data Quality." It's scheduled for Wednesday, August 11, from 10:15-11:15 a.m., in room Venetian Murano 3201A.

Nathan Eddy is a healthcare and technology freelancer based in Berlin.
Email the writer: nathaneddy@gmail.com
Twitter: @dropdeaded209