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It’s Time to Rethink Patient Matching

Posted on February 28, 2018 I Written By

The following is a guest blog post by Wes Rishel in partnership with Verato.

Henry Ford famously said, “If I’d asked them what they wanted, they would have said ‘faster horses.'” When it comes to patient matching – the cornerstone of health information interoperability – we seem to be asking for faster horses. But what we need is a totally new approach.

The “horse” here is probabilistic patient matching. Probabilistic algorithms match two patient records by comparing them directly to each other and determining the probability that the two records belong to the same patient. Basically, if the demographic data (like name, address, and birthdate) looks very similar across the two records, then a match is made.

These algorithms have been the preferred approach to resolving and matching patient identities since the 1980s. But today’s healthcare landscape is very different from that of the 1980s. Healthcare organizations are no longer simply providers or payers – there are now Health Information Exchanges (HIEs), Accountable Care Organizations (ACOs), care management companies, and even health systems with their own insurance plans.

There is now a larger push to share and exchange patient data between all of these organizations and with state and federal agencies and do analytics on a massive scale for research and population health. And we can anticipate an explosion of patient data coming from many new sources, including patient portals, patient engagement applications, telemedicine applications, personal health records, and Internet of Things (IoT) medical devices.

All of these factors make today’s patient matching challenges much more difficult than those of the 1980s, and yet we’re applying the same matching approach we used three decades ago. The consequences are drastic: up to one in five patient records are not accurately matched within the same health care system according to CHIME, and as many as half of patient records are mismatched when data is transferred between health care systems according to the ONC.

As a technology adviser over the years, I frequently advised governmental and private entities with over a million patient records that, as flawed as it was, probabilistic matching was their only choice. But probabilistic matching has clearly reached its limits. Even large and expensive efforts within healthcare organizations to improve and tune probabilistic algorithms achieve only incrementally better results. It is time to move on from the “horse.” We need a totally new approach.

A completely new approach in healthcare is a familiar approach elsewhere

It is time to emulate Henry Ford and find a completely new approach to patient matching. But it is also important to recognize that Ford didn’t actually invent the car. He didn’t even invent mass production, which had already been applied in other industries. His contribution was the vision that applying mass production to automobiles would open up a whole market, the gumption to gather the investment and execute, and the stubbornness to ignore naysayers.

So it is with patient matching. We simply need innovators that have the vision to apply proven identity matching approaches to the healthcare industry – as well as the gumption and stubbornness necessary to thrive in a crowded and often slow-moving healthcare IT market.

Many industries – including retail and financial services – already have viable and proven solutions to match and link their customer records, and these are the solutions we should look to as an industry to solve our own patient matching challenges.

Most proven solutions hinge on cross-correlating the demographic data from customer records with demographic data from third-party sources, including public records, credit agencies, or telephone companies. Importantly, this third-party demographic data includes not just current and correct attributes for a person, but also out-of-date and incorrect attributes – like previous addresses, maiden names, and common typing errors for birthdates or phone numbers.

By referencing these comprehensive sets of third-party demographic data during the matching process, these “Referential Matching” approaches can significantly outperform probabilistic matching algorithms. For example, Referential Matching can match one record that contains a maiden name, old address, and birthdate with another that contains a married name, new address, and phone number. Both of these records match to the same person in the third-party reference database, which has the entire set of demographic attributes for that person. In essence, this third-party reference database acts as an “answer key” for demographic data.

Results from this approach were recently published in Journal of AHIMA 88, “Applying Innovation to the Patient Identification Challenge” by Lorraine Fernandes, RHIA, Jim Burke, and Michele O’Connor, MPA, RHIA, FAHIMA. This article reviewed how Healthix, the largest public health information exchange (HIE) in the nation, used a vendor built on referential matching architecture to resolve 54.1 million MRNs down to 21.9 million unique identities. These 21.9 million unique individual records are now clear and available to meet key clinical and operational needs.

Referential Matching needs to make its way to the healthcare industry, and luckily it is already being used by many of the largest health systems, payers, and HIEs. But this is not enough. The costs of poor patient matching are too dramatic to keep pushing for faster horses: inaccurate matching decreases quality of care, has drastic implications for patient safety and privacy, costs millions of dollars of lost revenue each year to denied claims, and increases costs to our healthcare system due to systemic inefficiencies, redundant tests and procedures, and unnecessary IT and labor expenditures.

The healthcare industry should take a lesson from Henry Ford. The winning disruptive patient matching solution need not be created, but only adapted from other industries. As another wise man said, “discovery consists of seeing what everybody has seen, and thinking what nobody has thought.”

Health IT Q&A, Speciality EMRs, and Secure Messaging: Around Health Care Scene.

Posted on September 16, 2012 I Written By

Katie Clark is originally from Colorado and currently lives in Utah with her husband and son. She writes primarily for Smart Phone Health Care, but contributes to several Health Care Scene blogs, including EMR Thoughts, EMR and EHR, and EMR and HIPAA. She enjoys learning about Health IT and mHealth, and finding ways to improve her own health along the way.

EMR and HIPAA

Health IT Q&A With Scott Joslyn, CIO and Senior Vice President, MemorialCare Health System

This post features Scott Joslyn from MemorialCare Health System. He talks about a few different Health IT topics, including benefits and disadvantages to EHR and voice recognition. Joslyn is definitely an expert on Health IT, so this is a post you don’t want to miss.

Verizon Hopes To Be Secure Healthcare Network For All

Verizon is more than just switches, routers, and cables. Katherine Rourke discovered what the company has in store in the future with mHealth. She talked with Dr. Tippett from Verizon, who said Verizon’s Connected Health Division is “aiming to set the bar higher.” The company is hard at work, so expect some great things coming from Verizon.

Hospital EMR and EHR

Specialty EMRs: Behind the Curve? 

Are specialty EMRs worth investing in? There is debate on both sides of the issue, and a general consensus doesn’t appear to be developing anytime soon. Anne talks about assertions made in a statement recently about specialty EMRs, and offers her own two cents on the topic.

Study Suggests Most HIEs Aren’t Sustainable

HIEs are very expensive. Unfortunately, according to a recent study, the investment in them don’t seem to have any financial or clinical payback. There’s so much time and effort being put toward HIEs — would money be better spent elsewhere? Likely, but Anne Zieger doesn’t see things changing anytime soon.

Smart Phone Health Care

App Developers Urged to Consider Older Generations

There are apps developed that could make managing diseases like diabetes so much easier. However, these apps may not be designed with all age groups in mind. Researchers from North Carolina State are urging app developers to keep older generations in mind, who aren’t able to use certain apps as they are currently designed.

Happy EMR Doctor

EMRs’ Big Gaping Hole of Secure Messaging

This post is the first in a series from Dr. West, highlighting insights from his recent participating at a breakfast panel in Washington D.C. He talks about issues with secure messaging, including the lack of EMRs that have secure messaging included in their system. In the end, he discusses how secure messaging could impact patients and doctors positively.

Building — But Not Overbuilding — Next Gen HIEs

Posted on July 2, 2012 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

Today I’m delighted to bring you some thoughts from Micky Tripathi, founding president and CEO of the Massachusetts eHealth Collaborative.  In a write-up for the useful iHealthBeat.org blog, Tripathi argues that the HIT world is in danger of seriously overbuilding the next generation of HIEs.

As he notes, a generation of private HIEs (known as CHINs at the time) failed or struggled in the early to mid-1990s. He also reminds us that the failures — such as the demise of Tennessee’s CareSpark and the Minnesota Health Information Exchange — are far from over. In his mind, this is mostly because these groups tried to create over-architected HIEs.

Now, we’re at the heart of the matter. What is an over-architected HIE?  I’ll let Tripathi speak:

Put simply, it’s one that tries to do too much for too many with not enough money and time. It tries to establish an all-encompassing infrastructure and service to meet multiple, heterogeneous current and future requirements of multiple, heterogeneous current and future customers. It tries to do all of this with a shoestring budget and staff. And worst of all, it focuses more on long-term potential “big-bang” value at the expense of short-term, realizable, incremental value. Or as one HIE organization’s promotional material put it, the value proposition is to be a “one-stop shop for Clinical and Administrative Information.”  (Editor’s note: They actually made that claim? Wow.)

What’s wrong with trying to build a Holy Grail of HIEs that solves everyone’s problems?  His analysis:

1.   HIEs can only develop so fast no matter how much money and people you throw at them, given that moving clinical documents around, searching and retrieving clinical info and getting everything into a big database requires a lot of manual labor, legal and technical judgement, cultural and clinical change.

2. While HIEs can only move so fast, business and technology can move at breathtaking speed. Building out an infrastructure which is supposed to work five years from now may turn out to be a massive waste of resources. As he points out, remember that the game-changing iPad is only two years old.

3. CIOs are, let us say, a little overwhelmed at the moment. Asking them to build out a huge infrastructure for the HIE doesn’t exactly make things better. “Better to proceed with achievable steps that deliver incremental value along the way,” he says.

Well, all I can say is that I agree with him completely. Incremental moves and technologies like the Direct Project seem infinitely smarter than a “Big Bang” approach. HIEs are going to be part of our future like it or not, for many reasons, so why not get it right a little bit at a time?

Are EMRs As Great For ACOs As People Say?

Posted on March 13, 2012 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

For quite some time, talking heads have noted that EMRs will be an essential part of ACOs, so much so that most doubt you can have a successful ACO organization without one.  What I don’t see asked as often, however, is whether EMRs are shaping the future of the ACO movement, both negatively and positively.

What would an ACO look like, if it could exist at all, without an electronic record or HIE in place?

* There would even more mistakes and delays in sharing patient records, as one can hardly expect a larger group of institutions to make *less* mistakes

*  ACOs could launch without having to spend millions of dollars on EMR software, hardware, training and support

*  Clinical workflow would remain the same, generally, even if doctors were forced to include larger numbers of co-workers in their network

And how are ACOs working with EMRs in place?

*  Aside from limited case studies in individual institutions , it’s not clear whether EMRs are turning large, newly assembled care organizations into safer places to get care.

*  ACOs are forming more slowly than they might be, arguably, because a comprehensive EMR is part of t he cost of doing business

* New clinical workflow patterns are being forced upon clinicians, cutting across multiple institutions. While this might ultimately increase efficiency, it’s hard to ignore how many human hours are being invested (or wasted, depending on your position) on new technology.

As you can see, I come down on the “EMRs may not be all they’re cracked up to be for ACOs” side of things. Now, I’d concede that I haven’t been completely fair — I know EMRs have yielded great benefits for some groups of institutions– but I’d say the jury’s still out overall.