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Healthcare | Forms Processing

athenahealth drives faster patient care by digitizing 20,000,000 pages per week with ABBYY

Healthcare | Forms Processing

Customer Overview

Name	athenahealth
Industry	Healthcare
Web	www.athenahealth.com

CHALLENGE

Convert 250,000 faxed medical records per day via the cloud into Electronic Health Records (EHRs) — by replacing old and inaccurate OCR technology with an advanced, flexible and fully-automated solution.

SOLUTION

ABBYY FineReader Engine

RESULTS

athenahealth increased the speed and accuracy of converting medical records into EHRs, enabling a broader range of data to be captured in real-time and processed more efficiently — ensuring that vital patient information reaches doctors faster.

athenahealth cloud-based EHR enables over 85,000 providers to deliver better care to more than 83 million patients. This requires over 20 million faxed patient documents to be captured and converted into EHRs every week — a task that athenahealth accomplishes quickly, accurately and automatically with ABBYY FineReader Engine.

“We’re capturing more data in less time than ever and getting it to healthcare providers far faster,” said Alison Lo, Senior Developer, athenahealth

Helping providers focus on providing patient care instead of managing health records

In 1997, Jonathan Bush and Todd Park created a software solution for dealing with the frustrating volume of paper records that their birthing practice generated — founding athenahealth in the process. Now a leader in cloud-based EHR management, athenahealth enables over 85,000 healthcare providers to focus on their patients instead of paperwork — improving EHR workflow efficiency and quality of care, without adding to headcount or budget.

Needed: A better solution for recognizing and converting millions of medical document pages a week

By 2012, clients were faxing millions of medical documents every month to athenahealth’s service — which captures and converts the data into EHRs and integrates them into clients’ workflows. “Essentially,” say Alison Lo, Senior Developer, athenahealth, “we handle the healthcare record workflow for providers. Our cloud-based EHR receives clinical documents via fax, automatically recognizes and converts them into EHRs, populates the medical records and then takes over the entire workflow, routing relevant information to the right people.”

However, the company’s fast-growing customer base and the increasing complexity of health records had pushed athenahealth’s capture solution to its limits. “There were quality issues,” explains Lo.

“The speed and accuracy of our old OCR software were drags on efficiency. And we anticipated big year-on-year increases in the number of faxes and their mix of data: demographic information, medical charts, X-rays, records featuring text with embedded images, you name it. We needed something that could handle it all.”

In looking for a solution, the athenahealth team counted flexibility, scalability and ease of integration as key requirements — as well as speed and accuracy. “We were looking to the long term,” says Fuchang Yin, Staff Developer, athenahealth. “And tight integration with our systems was key. That’s why, after testing OCR SDKs from a variety of vendors, we chose ABBYY FineReader Engine.”

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ABBYY FineReader Engine: The leading solution for seamlessly-integrated

OCR athenahealth handles all kinds of documents and serves every size of client: from single practitioners and clinics to large hospitals. So, Yin explains, “It was vital that the new solution accommodate a wide range of document types with equal accuracy. And in head-to-head comparisons, FineReader was more accurate every time. In fact,” Yin states, “FineReader was twice as accurate as its nearest competitor.”

“FineReader was twice as accurate as the nearest competitor and easily scaled to meet our needs. Its adaptability was remarkable.”

Fuchang Yin, Staff Developer, athenahealth

As Yin describes, implementing athenahealth’s new FineReader-based solution went smoothly: “FineReader’s adaptability was remarkable. It was straightforward to integrate the engine into our Perl-based modules running on Linux. The software is called directly, recognizes text and layout types, extracts the data, and then converts the results into text formats accordingly.”

Yin also states that thanks to FineReader’s accuracy, human intervention is minimized. Review by verification and QA staff goes quickly, and the results are available to clients much faster than before.

The results

Four years after implementation, FineReader continues to yield superior results for athenahealth, helping to support the company’s rapid growth and fast-expanding network of care providers.

“Today, we process 250,000 documents every day, with an average length of two to three pages each. That works out to around four million pages processed every week using FineReader. Over the last four years, FineReader has easily scaled up to meet our needs. And it’s allowing us to capture demographic data now, too. That’s very important to the healthcare providers we serve.”

Fuchang Yin, Staff Developer, athenahealth

Plus, as Lo describes, FineReader brings important benefits to patients, too: “ABBYY FineReader Engine enabled us to increase our EHR processing power. We’re capturing more data in less time than ever and getting it to healthcare providers far faster. This enables them to put much-needed information to work on behalf of their patients sooner, increasing the likelihood of better outcomes.”

And as Yin concludes, FineReader brings a host of additional benefits: “ABBYY FineReader’s speed, accuracy and flexibility makes a critical difference to our service to providers. It improves their EHR workflow efficiency — which helps them improve care without the need to hire additional staff, adopt more outcome-focused models, ensure regulatory compliance and raise patient satisfaction.”

ABBYY FineReader Engine