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The Pain of Recording Patient Risk Factors as Illuminated by Apixio (Part 2 of 2)

Posted on October 28, 2016 I Written By

Andy Oram is an editor at O'Reilly Media, a highly respected book publisher and technology information provider. An employee of the company since 1992, Andy currently specializes in open source, software engineering, and health IT, but his editorial output has ranged from a legal guide covering intellectual property to a graphic novel about teenage hackers. His articles have appeared often on EMR & EHR and other blogs in the health IT space. Andy also writes often for O'Reilly's Radar site (http://oreilly.com/) and other publications on policy issues related to the Internet and on trends affecting technical innovation and its effects on society. Print publications where his work has appeared include The Economist, Communications of the ACM, Copyright World, the Journal of Information Technology & Politics, Vanguardia Dossier, and Internet Law and Business. Conferences where he has presented talks include O'Reilly's Open Source Convention, FISL (Brazil), FOSDEM, and DebConf.

The previous section of this article introduced Apixio’s analytics for payers in the Medicare Advantage program. Now we’ll step through how Apixio extracts relevant diagnostic data.

The technology of PDF scraping
Providers usually submit SOAP notes to the Apixio web site in the form of PDFs. This comes to me as a surprise, after hearing about the extravagant efforts that have gone into new CCDs and other formats such as the Blue Button project launched by the VA. Normally provided in an XML format, these documents claim to adhere to standards and offer a relatively gentle face to a computer program. In contrast, a PDF is one of the most challenging formats to parse: words and other characters are reduced to graphical symbols, while layout bears little relation to the human meaning of the data.

Structured documents such as CCDs contain only about 20% of what CMS requires, and often are formatted in idiosyncratic ways so that even the best CCDs would be no more informative than a Word document or PDF. But the main barrier to getting information, according to Schneider, is that Medicare Advantage works through the payers, and providers can be reluctant to give payers direct access to their EHR data. This reluctance springs from a variety of reasons, including worries about security, the feeling of being deluged by requests from payers, and a belief that the providers’ IT infrastructure cannot handle the burden of data extraction. Their stance has nothing to do with protecting patient privacy, because HIPAA explicitly allows providers to share patient data for treatment, payment, and operations, and that is what they are doing giving sensitive data to Apixio in PDF form. Thus, Apixio had to master OCR and text processing to serve that market.

Processing a PDF requires several steps, integrated within Apixio’s platform:

  1. Optical character recognition to re-create the text from a photo of the PDF.

  2. Further structuring to recognize, for instance, when the PDF contains a table that needs to be broken up horizontally into columns, or constructs such the field name “Diagnosis” followed by the desired data.

  3. Natural language processing to find the grammatical patterns in the text. This processing naturally must understand medical terminology, common abbreviations such as CHF, and codings.

  4. Analytics that pull out the data relevant to risk and presents it in a usable format to a human coder.

Apixio can accept dozens of notes covering the patient’s history. It often turns up diagnoses that “fell through the cracks,” as Schneider puts it. The diagnostic information Apixio returns can be used by medical professionals to generate reports for Medicare, but it has other uses as well. Apixio tells providers when they are treating a patient for an illness that does not appear in their master database. Providers can use that information to deduce when patients are left out of key care programs that can help them. In this way, the information can improve patient care. One coder they followed could triple her rate of reviewing patient charts with Apixio’s service.

Caught between past and future
If the Apixio approach to culling risk factors appears round-about and overwrought, like bringing in a bulldozer to plant a rosebush, think back to the role of historical factors in health care. Given the ways doctors have been taught to record medical conditions, and available tools, Apixio does a small part in promoting the progressive role of accountable care.

Hopefully, changes to the health care field will permit more direct ways to deliver accountable care in the future. Medical schools will convey the requirements of accountable care to their students and teach them how to record data that satisfies these requirements. Technologies will make it easier to record risk factors the first time around. Quality measures and the data needed by policy-makers will be clarified. And most of all, the advantages of collaboration will lead providers and payers to form business agreements or even merge, at which point the EHR data will be opened to the payer. The contortions providers currently need to go through, in trying to achieve 21st-century quality, reminds us of where the field needs to go.

The Pain of Recording Patient Risk Factors as Illuminated by Apixio (Part 1 of 2)

Posted on October 27, 2016 I Written By

Andy Oram is an editor at O'Reilly Media, a highly respected book publisher and technology information provider. An employee of the company since 1992, Andy currently specializes in open source, software engineering, and health IT, but his editorial output has ranged from a legal guide covering intellectual property to a graphic novel about teenage hackers. His articles have appeared often on EMR & EHR and other blogs in the health IT space. Andy also writes often for O'Reilly's Radar site (http://oreilly.com/) and other publications on policy issues related to the Internet and on trends affecting technical innovation and its effects on society. Print publications where his work has appeared include The Economist, Communications of the ACM, Copyright World, the Journal of Information Technology & Politics, Vanguardia Dossier, and Internet Law and Business. Conferences where he has presented talks include O'Reilly's Open Source Convention, FISL (Brazil), FOSDEM, and DebConf.

Many of us strain against the bonds of tradition in our workplace, harboring a secret dream that the industry could start afresh, streamlined and free of hampering traditions. But history weighs on nearly every field, including my own (publishing) and the one I cover in this blog (health care). Applying technology in such a field often involves the legerdemain of extracting new value from the imperfect records and processes with deep roots.

Along these lines, when Apixio aimed machine learning and data analytics at health care, they unveiled a business model based on measuring risk more accurately so that Medicare Advantage payments to health care payers and providers reflect their patient populations more appropriately. Apixio’s tools permit improvements to patient care, as we shall see. But the core of the platform they offer involves uploading SOAP notes, usually in PDF form, and extracting diagnostic codes that coders may have missed or that may not be supportable. Machine learning techniques extract the diagnostic codes for each patient over the entire history provided.

Many questions jostled in my mind as I talked to Apixio CTO John Schneider. Why are these particular notes so important to the Centers for Medicare & Medicaid Services (CMS)? Why don’t doctors keep track of relevant diagnoses as they go along in an easy-to-retrieve manner that could be pipelined straight to Medicare? Can’t modern EHRs, after seven years of Meaningful Use, provide better formats than PDFs? I asked him these things.

A mini-seminar ensued on the evolution of health care and its documentation. A combination of policy changes and persistent cultural habits have tangled up the various sources of information over many years. In the following sections, I’ll look at each aspect of the documentation bouillabaisse.

The financial role of diagnosis and risk
Accountable care, in varying degrees of sophistication, calculates the risk of patient populations in order to gradually replace fee-for-service with payments that reflect how adeptly the health care provider has treated the patient. Accountable care lay behind the Affordable Care Act and got an extra boost at the beginning of 2016 when CMS took on the “goal of tying 30 percent of traditional, or fee-for-service, Medicare payments to alternative payment models, such as ACOs, by the end of 2016 — and 50 percent by the end of 2018.

Although many accountable care contracts–like those of the much-maligned 1970s Managed Care era–ignore differences between patients, more thoughtful programs recognize that accurate and fair payments require measurement of how much risk the health care provider is taking on–that is, how sick their patients are. Thus, providers benefit from scrupulously complete documentation (having learned that upcoding and sloppiness will no longer be tolerated and will lead to significant fines, according to Schneider). And this would seem to provide an incentive for the provider to capture every nuance of a patient’s condition in a clearly code, structured way.

But this is not how doctors operate, according to Schneider. They rebel when presented with dozens of boxes to check off, as crude EHRs tend to present things. They stick to the free-text SOAP note (fields for subjective observations, objective observations, assessment, and plan) that has been taught for decades. It’s often up to post-processing tools to code exactly what’s wrong with the patient. Sometimes the SOAP notes don’t even distinguish the four parts in electronic form, but exist as free-flowing Word documents.

A number of key diagnoses come from doctors who have privileges at the hospital but come in only sporadically to do consultations, and who therefore don’t understand the layout of the EHR or make attempts to use what little structure it provides. Another reason codes get missed or don’t easily surface is that doctors are overwhelmed, so that accurately recording diagnostic information in a structured way is a significant extra burden, an essentially clerical function loaded onto these highly skilled healthcare professionals. Thus, extracting diagnostic information many times involves “reading between the lines,” as Schneider puts it.

For Medicare Advantage payments, CMS wants a precise delineation of properly coded diagnoses in order to discern the risk presented by each patient. This is where Apixio come in: by mining the free-text SOAP notes for information that can enhance such coding. We’ll see what they do in the next section of this article.

Recorded Video from Dell Healthcare Think Tank Event – #DoMoreHIT

Posted on March 20, 2015 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

I mentioned that I was going to be on the Dell Healthcare Think Tank event again this year. It was my 3rd time participating and it didn’t disappoint. In fact, this one dove into a number of insurance topics which we hadn’t ever covered before. I really learned a lot from the discussions and hopefully others learned from me.

Plus, in the first session I had the privilege to sit next to Dr. Eric Topol. He’s got such great insights into what’s happening in healthcare. Of course, I’m also always amazed by Mandi Bishop, who many of you may know from Twitter or her Eyes Wide Shut series here on EMR and HIPAA.

In case you missed the live stream of the event, you can find each of the three recorded sessions below. I also posted the 3 drawings that were created during the event on EMR and EHR. I look forward to hearing your thoughts on what was shared. Thanks Dell for hosting the conversation that brought together so many perspectives from across healthcare.

Session 1: Consumer Engagement & Social Media

Session 2: Bridging the Gap Between Providers, Payers and Patients

Session 3: Entrepreneurship & Innovation