Digitizing Healthcare Involves Grasping the Scope, Finding Value of EHR Data

As hospitals and physician practices continue to progress to electronic health record systems, challenges have been created by the sheer volume and quality of raw data that goes into EHRs. Advanced software and interoperability are helping to balance different aspects of electronic data, such as claims, coverage, delivery, patient history and treatments, but the large-scale availability of the information is still being analyzed.

With all of those different aspects of electronic healthcare, a hospital or physician practice has to try and interpret what all the data means — and how it could be used to improve patient safety, control costs, understand efficiency of treatments and other healthcare benchmarks. Three data specialists from information management consulting firm Earley & Associates — President and CEO Seth Earley, Vice President of Marketing Gary Kahn and Senior Consultant Christian Reich, MD — give three areas of focus that can make the vast world of EHR data easier to grasp for hospitals and healthcare providers.

Actual implementation of EHRs
Mr. Earley notes there are two ends of the spectrum in regard to adopting EHRs. One end is the institutional, academic viewpoint, which is very in-depth but also very slow-moving. The other end is the hype-driven, market-facing viewpoint, which focuses on the readiness of implementation but also lacks depth and patience. While information technology and EHRs in particular are becoming the new gold standard in hospitals, there has to be a middle ground, Mr. Earley says, because application of an EHR system without a plan for that data can lead to chaos.

"We're going to find high-quality care is going to be less costly, but it's more of an investment," Mr. Earley says. "Extracting meaning from that data is by being able to classify it and organize it; otherwise, it's just a big mess."

Mr. Earley stated there are actions hospitals and other healthcare organizations can do to ease implementation. Making sure procedures and practices can be codified and organized easily and establishing approaches to analyze data for trends in safety, cost reduction and efficacy are ways EHR data can be cleaned up and applied to ultimately make patients' lives better, he said.

Finding value in EHR data
Hospitals converting to EHRs know it is both time-consuming and overwhelming, Mr. Kahn says. While there are benefits of having patient data in digital form, addressing what patients' information actually means is one of the first hurdles any healthcare provider will have to consider. "As the industry transitions, there is going to be a development of standards," Mr. Kahn says. "One of challenges is how to map and harmonize data into new standards" to improve healthcare and patient experience.

Mr. Earley says there is the hope that EHRs will be able to adopt and in some cases create new healthcare standards and provide insight for improvements. For example, EHRs retain information on patient medication and effective treatments, but can that data improve future treatments and perhaps reduce costs for providers? Mr. Earley says EHRs need to be standardized in order for health data to be aggregated into meaningful trends. He also says data and healthcare terminologies need to be translated for laypeople in order to find true value. Healthcare is very complex, he states, and patient data becomes easier to understand if there is a common language. "There is still this confusion of languages," Mr. Earley says. "You need to be able process this information effectively, speak to one another, but also get the insights by extracting the data."

Billing, coding and EHRs: common medical data language
Something as rudimentary and foundational as defining patients' conditions and justifying billing and reimbursement can be complicated, Dr. Reich says. "ICD-9 is OK for billing, but they are very bad for other applications," such as coding and defining newer conditions, Dr. Reich says. "ICD-10 is going to fix some of the problems. But many systems are deeply entrenched in ICD-9, and it's going to be quite a mess for quite a while."

There are other systems, Dr. Reich notes, that attempt to make billing and coding as well as EHR data standards more efficient. One example of this type of system, which has been adopted for use by the U.S. federal government, is the Systematized Nomenclature of Medicine, or SNOMED. SNOMED has a tall hierarchy and very precise labeling for all diseases with hundreds of thousands of terms. However, it all comes back to being able to manage that data and making it useful, he says.

"The advantage, there is much more precision, but the problem is you have to find the right concepts and understand the nuances," Dr. Reich says. "The purpose of data standards for electronic health records is to make a definition of conditions and to make things generalized."

Related Articles on Health Information Technology:
10 Recent Survey Findings About ICD-10
CMS Awards $4.8M Contract to Help Develop EHR Quality Measures
Dr. David Bates: Framework for Using EMRs in Research May Take Several Years

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