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Hands-On Guidance for Data Integration in Health: The CancerLinQ Story

Posted on June 15, 2017 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.

Institutions throughout the health care field are talking about data sharing and integration. Everyone knows that improved care, cost controls, and expanded research requires institutions who hold patient data to safely share it. The American Society of Clinical Oncology’s CancerLinQ, one of the leading projects analyzing data analysis to find new cures, has tackled data sharing with a large number of health providers and discovered just how labor-intensive it is.

CancerLinQ fosters deep relationships and collaborations with the clinicians from whom it takes data. The platform turns around results from analyzing the data quickly and to give the clinicians insights they can put to immediate use to improve the care of cancer patients. Issues in collecting, storing, and transmitting data intertwine with other discussion items around cancer care. Currently, CancerLinQ isolates the data from each institution, and de-identifies patient information in order to let it be shared among participating clinicians. CancerLinQ LLC is a wholly-owned nonprofit subsidiary of ASCO, which has registered CancerLinQ as a trademark.

CancerLinQ logo

Help from Jitterbit

In 2015, CancerLinQ began collaborating with Jitterbit, a company devoted to integrating data from different sources. According to Michele Hazard, Director of Healthcare Solutions, and George Gallegos, CEO, their company can recognize data from 300 different sources, including electronic health records. At the beginning, the diversity and incompatibility of EHRs was a real barrier. It took them several months to figure out each of the first EHRs they tackled, but now they can integrate a new one quickly. Oncology care, the key data needed by CancerLinQ, is a Jitterbit specialty.

Jitterbit logo

One of the barriers raised by EHRs is licensing. The vendor has to “bless” direct access to EHR and data imported from external sources. HIPAA and licensing agreements also make tight security a priority.

Another challenge to processing data is to find records in different institutions and accurately match data for the correct patient.

Although the health care industry is moving toward the FHIR standard, and a few EHRs already expose data through FHIR, others have idiosyncratic formats and support older HL7 standards in different ways. Many don’t even have an API yet. In some cases, Jitterbit has to export the EHR data to a file, transfer it, and unpack it to discover the patient data.

Lack of structure

Jitterbit had become accustomed to looking in different databases to find patient information, even when EHRs claimed to support the same standard. One doctor may put key information under “diagnosis” while another enters it under “patient problems,” and doctors in the same practice may choose different locations.

Worse still, doctors often ignore the structured fields that were meant to hold important patient details and just dictate or type it into a free-text note. CancerLinQ anticipated this, unpacking the free text through optical character recognition (OCR) and natural language processing (NLP), a branch of artificial intelligence.

It’s understandable that a doctor would evade the use of structured fields. Just think of the position she is in, trying to keep a complex cancer case in mind while half a dozen other patients sit in the waiting room for their turn. In order to use the structured field dedicated to each item of information, she would have to first remember which field to use–and if she has privileges at several different institutions, that means keeping the different fields for each hospital in mind.

Then she has to get access to the right field, which may take several clicks and require movement through several screens. The exact information she wants to enter may or may not be available through a drop-down menu. The exact abbreviation or wording may differ from EHR to EHR as well. And to carry through a commitment to using structured fields, she would have to go through this thought process many times per patient. (CancerLinQ itself looks at 18 Quality eMeasures today, with the plan to release additional measures each year.)

Finally, what is the point of all this? Up until recently, the information would never come back in a useful form. To retrieve it, she would have to retrace the same steps she used to enter the structured data in the first place. Simpler to dump what she knows into a free-text note and move on.

It’s worth mentioning that this Babyl of health care information imposes negative impacts on the billing and reimbursement process, even though the EHRs were designed to support those very processes from the start. Insurers have to deal with the same unstructured data that CancerLinQ and Jitterbit have learned to read. The intensive manual process of extracting information adds to the cost of insurance, and ultimately the entire health care system. The recent eClinicalWorks scandal, which resembles Volkswagon’s cheating on auto emissions and will probably spill out to other EHR vendors as well, highlights the failings of health data.

Making data useful

The clue to unblocking this information logjam is deriving insights from data that clinicians can immediately see will improve their interventions with patients. This is what the CancerLinQ team has been doing. They run analytics that suggest what works for different categories of patients, then return the information to oncologists. The CancerLinQ platform also explains which items of data were input to these insights, and urges the doctors to be more disciplined about collecting and storing the data. This is a human-centered, labor-intensive process that can take six to twelve months to set up for each institution. Richard Ross, Chief Operating Officer of CancerLinQ calls the process “trench warfare,” not because its contentious but because it is slow and requires determination.

Of the 18 measures currently requested by CancerLinQ, one of the most critical data elements driving the calculation of multiple measures is staging information: where the cancerous tumors are and how far it has progressed. Family history, treatment plan, and treatment recommendations are other examples of measures gathered.

The data collection process has to start by determining how each practice defines a cancer patient. The CancerLinQ team builds this definition into its request for data. Sometimes they submit “pull” requests at regular intervals to the hospital or clinic, whereas other times the health care provider submits the data to them at a time of its choosing.

Some institutions enforce workflows more rigorously than others. So in some hospitals, CancerLinQ can persuade the doctors to record important information at a certain point during the patient’s visit. In other hospitals, doctors may enter data at times of their own choosing. But if they understand the value that comes from this data, they are more likely to make sure it gets entered, and that it conforms to standards. Many EHRs provide templates that make it easier to use structured fields properly.

When accepting information from each provider, the team goes through a series of steps and does a check-in with the provider at each step. The team evaluates the data in a different stage for each criterion: completeness, accuracy of coding, the number of patients reported, and so on. By providing quick feedback, they can help the practice improve its reporting.

The CancerLinQ/Jitterbit story reveals how difficult it is to apply analytics to health care data. Few organizations can afford the expertise they apply to extracting and curating patient data. On the other hand, CancerLinQ and Jitterbit show that effective data analysis can be done, even in the current messy conditions of electronic data storage. As the next wave of technology standards, such as FHIR, fall into place, more institutions should be able to carry out analytics that save lives.

IBM Watson Partners With FDA On Blockchain-Driven Health Sharing

Posted on January 16, 2017 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she’s served as editor in chief of several healthcare B2B sites.

IBM Watson Health has partnered with the FDA in an effort to create scalable exchange of health data using blockchain technology. The two will research the exchange of owner-mediated data from a variety of clinical data sources, including EMRs, clinical trial data and genomic health data. The researchers will also incorporate data from mobiles, wearables and the Internet of Things.

The initial project planned for IBM Watson and the FDA will focus on oncology-related data. This makes sense, given that cancer treatment involves complex communication between multispecialty care teams, transitions between treatment phases, and potentially, the need to access research and genomic data for personalized drug therapy. In other words, managing the communication of oncology data is a task fit for Watson’s big brain, which can read 200 million pages of text in 3 seconds.

Under the partnership, IBM and the FDA plan to explore how the blockchain framework can benefit public health by supporting information exchange use cases across varied data types, including both clinical trials and real-world data. They also plan to look at new ways to leverage the massive volumes of diverse data generated by biomedical and healthcare organizations. IBM and the FDA have signed a two-year agreement, but they expect to share initial findings this year.

The partnership comes as IBM works to expand its commercial blockchain efforts, including initiatives not only in healthcare, but also in financial services, supply chains, IoT, risk management and digital rights management. Big Blue argues that blockchain networks will spur “dramatic change” for all of these industries, but clearly has a special interest in healthcare.  According to IBM, Watson Health’s technology can access the 80% of unstructured health data invisible to most systems, which is clearly a revolution in the making if the tech giant can follow through on its potential.

According to Scott Lundstrom, group vice president and general manager of IDC Government and Health Insights, blockchain may solve some of the healthcare industry’s biggest data management challenges, including a distributed, immutable patient record which can be secured and shared, s. In fact, this idea – building a distributed, blockchain-based EMR — seems to be gaining traction among most health IT thinkers.

As readers may know, I’m neither an engineer nor a software developer, so I’m not qualified to judge how mature blockchain technologies are today, but I have to say I’m a bit concerned about the rush to adopt it nonetheless.  Even companies with a lot at stake  — like this one, which sells a cloud platform backed by blockchain tech — suggest that the race to adopt it may be a bit premature.

I’ve been watching tech fashions come and go for 25 years, and they follow a predictable pattern. Or rather, they usually follow two paths. Go down one, and the players who are hot for a technology put so much time and money into it that they force-bake it into success. (Think, for example, the ERP revolution.) Go down the other road, however, and the new technology crumbles in a haze of bad results and lost investments. Let’s hope we go down the former, for everyone’s sake.

HIEs and Patient Engagement – Why and Why Now?

Posted on June 20, 2013 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.

The following is a guest post by Jeff Donnell, President of NoMoreClipboard.
Jeff Donnell - NoMoreClipboard PHR
Health information exchanges have become quite adept at moving medical data from provider to provider on behalf of patients, but making that data available to those same patients has rarely been attempted – until recently.

Not including patients at the HIE exchange table is understandable, but ironic. Understandable for reasons ranging from policy challenges to a lack of standards to technical limitations. Ironic because HIEs are ideally positioned to aggregate data from multiple providers – leveraging the interfaces already in place with provider applications – and deliver that data to consumers, overcoming several of the major barriers to patient adoption and use of tools like PHRs and patient portals.

HIEs have recently grown interested in supporting electronic patient engagement, in large part based on provider inquiries regarding meaningful use stage two requirements. Many providers are looking for affordable alternatives to the tethered patient portals being offered by their EHR vendors, and they want to provide their patients with a solution that can be used across the care continuum. Increasingly, providers recognize that a patient who visits five different clinicians is not about to create five different patient portal accounts. Savvy providers realize that the HIE is well equipped to provide portable, interoperable solutions.

For HIEs interested in long-term sustainability, patient engagement makes perfect sense. The HIE can leverage its existing interfaces and aggregated data – making existing medical information available to patients from a single pipe, in a standardized format. The HIE can act as a conduit between consumers and clinicians – adding value for all parties. Providers can transmit data to patients, and recent CMS guidance indicates that all providers who contribute data to a shared portal (like that provided by an HIE) can count patients who use that portal toward their 5% patient participation requirement. Patients avoid having to collect data from every provider they see, and can populate a PHR or HIE portal account with existing electronic data. Everybody wins.

The value is evident, but what about those challenges? In the state of Indiana, we received an ONC Challenge Grant to figure out how to get HIE data in the hands of consumers with a PHR. We are fortunate to reside in a state with five well-established HIEs and a provider community eager to innovate, and we have spent the last two years working on those challenges (giving us a real appreciation for why the ONC affixed the challenge label to this grant program). We have addressed issues ranging from patient ID/Auth/Match to minor consent to provider skepticism to amended data use agreements. We have overcome any number of obstacles to get data flowing, and we are seeing increased levels of engagement and enhanced clinical outcomes.

We have learned any number of lessons to help other HIEs, state agencies and healthcare providers avoid pitfalls and make accelerated progress. We are eager to share what we have learned. Perhaps the most important lesson is to get started now – as crafting and implementing a patient engagement strategy takes time. As nobody appears to be manufacturing more time these days, HIEs and other organizations that envision sharing data with patients even a year or two down the road would be well advised to begin working in earnest, with an eye on making incremental progress.

Jeff Donnell is president of NoMoreClipboard, a web-based, Personal Health Record (PHR) management system designed to consolidate medical information in one convenient and secure location for easy retrieval and updates. NMC enables consumers to share personal or family member medical information with medical professionals electronically, reducing the need for repetitive medical paperwork.  Jeff and the company are committed to developing PHR applications that are consumer-friendly, interactive, secure, mobile and interoperable.  For more information, follow us on Twitter @NoMoreClipboard or visit www.NoMoreClipboard.com.

CCHIT Certification Thoughts

Posted on February 2, 2009 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 just came upon a blog post on the TempDev blog that talks about the expansion of CCHIT certification into a number of new specialty categories. It’s really interesting to look at the list of new categories:

  • Behavioral Health
  • Clinical Research
  • Dermatology
  • Oncology
  • Advanced Interoperability
  • Advanced Quality (in reference to Quality Measures)
  • Advanced Clinical Decision Support
  • Long Term Care
  • OB/GYN

As noted by Ben, these are in addition to the HIE and PHR categories added for 2009. Well, I never back away from a discussion about CCHIT. I just wonder why the Senate hasn’t called me up to a hearing to talk about CCHIT certification. Of course, my friend Al Borges would do much better than I, but I digress.

After reading through Ben’s post about the expansion of CCHIT I had to leave a few of my thoughts on the subject in the comments. I thought most of my readers would find it interesting and so here’s some off the cuff thoughts on CCHIT certification that I left in the comments:

You are dead on when you say that CCHIT is a powerful driver in the EHR marketplace. It’s a really tough decision for EMR companies to decide whether to spend money on CCHIT certification or not. Not because CCHIT certification will make their product any better. The biggest advantage CCHIT certification offers is in your ability to market/sale your EMR system. That fact can’t be argued. It’s just unfortunate that the public isn’t better informed about the meaning of CCHIT certification.

I do think that over time CCHIT certifications will be so old that EMR companies are going to have to avoid the discussion of with CCHIT certification year they have or something like that. This will lead to consumers being unhappy with the process and lead to more troubles in the future.

The problem is that CCHIT hasn’t create a sustainable certification model for most EHR companies. I even hear that CCHIT might not have a sustainable certification model themselves despite their incredibly high rates for certification. At least that was what I read when I heard that CCHIT was going back to the government for more funding.

I still think the biggest problem is that most people see certification as a strong indicator of whether the EMR is usable or not, but CCHIT doesn’t test that at all. I’m considering some options to measure that and even possibly pursuing a PhD in health informatics where I’d like to study the subject. We’ll see.

It will be interesting to see how many specialties actually certify in these categories. My guess is that it will be the same Jabba the Hut EMRs (my term) that did the original CCHIT certification.

I guess you know where I stand on this issue.

Watch for more discussion about CCHIT, because I think it’s important to share my views on the subject considering it could be a major part of what I call the Obama EMR stimulus package.