Wednesday 22 March 2023
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More Insights on Duplicate Medical Records and National Patient ID

Duplicate Medical Records; The Unintended Consequence of Implementing EMRs

More Insights on Duplicate Medical Records and National Patient ID

The Velocity Interoperability Blog and Velocity Interoperability Podcast are sponsored by Velocity Health Informatics. Velocity provides both data quality and data integration as a service offerings to ensure that healthcare providers access the correct patient record with the right data for each patient they serve.  See the introductory blog post. Visit Velocity on the Web and follow them on Twitter, LinkedIN and Facebook!

More Insights on Duplicate Medical Records and National Patient ID

TODAYS GUEST Lorraine Fernandes, Principal, Fernandes Healthcare Insights

Lorraine joined us to provide More Insights on Duplicate Medical Records and National Patient ID! Specifically, we discuss the following with Lorraine:

  1. Will you please get us started by giving our audience a 10,000 foot overview how you help your clients at Fernandes Healthcare Insights?
  2. What is patient matching and why is this such a hot topic in today’s healthcare market?
  3. What is the state of patient matching in today’s healthcare ecosystem?
  4. What has traditionally been used to match patient records and is this enough?
  5. Why is this so important in today’s healthcare environment?
  6. What about a national healthcare identifier as the solution, as many nations use this approach?
  7. What innovation is being applied to this ongoing challenge?
  8. If you had to guess, what does the future hold for patient identification? How will we progress in the next 3 years?

About Lorraine Fernandes

Lorraine Fernandes is an international and domestic thought leader, accomplished author and respected public speaker on topics related to technology’s role in healthcare transformation. Lorraine is President-Elect for the International Federation of Health Information Management Associations (IFHIMA) and serves as editor for the IFHIMA Global News. Lorraine is recipient of the American Health Information Management Association (AHIMA) 2013 Pioneer Award and 1998 Discovery Award and California Health Information Association (CHIA) 2002 Distinguished Member Award.

She has published numerous articles and blogs, and presented domestically and internationally on using information technology for the improvement of individual and population health, and creating a single view of citizen records for health and social services. Connect with Lorraine on LinkedIN!

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The Velocity Interoperability Blog and Velocity Interoperability Podcast are sponsored by Velocity Health Informatics. Velocity provides both data quality and data integration as a service offerings to ensure that healthcare providers access the correct patient record with the right data for each patient they serve.  Visit Velocity on the Web and follow them on Twitter, LinkedIN and Facebook!


Joe Lavelle 00:55 Welcome to the Velocity Interoperability Podcast brought to us by the gurus at Velocity, I am your host, Joe Lavelle and I am really looking forward to another thought provoking discussion where we further investigate data quality, interoperability and medical record remediation.

We’re going to get right to it. Today, we are joined by Lorraine Fernandes, Principal of Fernandes Healthcare Insights. Lorraine, welcome to the show!

Lorraine Fernandes 01:17 Thank you Joe.

Joe Lavelle 01:19 Well, thanks so much for making the time today. Before we start our discussion, could you take a minute or two and tell the audience about you and your background.

Lorraine Fernandes 01:26 Oh, I’ll be delighted to Joe. So I hail from Northern California right now, as you’ve heard Joe my name is Lorraine Fernandes. I am the founder and principal of Fernandes Healthcare Insights, but many of you listening to this podcast will know me for my days of patient and provider identification consulting services, and industry insight when I worked with IBM, when I worked in Initiate Systems and when I was a consultant earlier on in my career, so I’ve spent sad to say probably the last 20 plus years focusing more and more on the challenges of interoperability as it relates to patient and provider identification, and really building the governance around those two foundational issues.

Joe Lavelle 02:21 Great! Lorraine, let’s start here with kind of foundational element. What is patient matching, and why is this such a hot topic in today’s healthcare market?

Lorraine Fernandes 02:30 Good question Joe, and it’s kind of like its back to the basic, let’s start at the beginning or however you want to coin that. As I said in my intro I spent over 20 years focusing more and more on this issue, so obviously it’s still an issue. And it’s an issue that’s even more important today than it was 20 years ago, because we are trying to discern in patient matching, who is Lorraine Fernandes? My name ends in an S. Who is Lorraine Fernandes? Thinking my name may end in a Z. Or my maiden name of Lorraine Grunwaldt, I’m a good German from the Midwest, have lots of variation in the demographics that describe me and obviously across healthcare system in the US, where I’ve been a patient or a consumer. I have different demographics. So it’s the bottom line challenge of who is Lorraine? As I’ve been known across health systems, and the challenge of connecting all of my data in order to serve my care needs today, and perhaps tied to reimbursement, tied to research, tied to care coordination.

Joe Lavelle 03:47 Outstanding. And so we’ve got the baseline. What is the state of patient matching in today’s healthcare ecosystem?

Lorraine Fernandes 03:56 So today I would say, well we are doing somewhat better in patient matching than what we did 10 or 20 years ago. It is still a significant challenge with some very dismal areas in some parts of the healthcare ecosystem for matching up Lorraine’s data. And whether the organization is attempting to match data based upon a byte for byte character match, which sadly some organizations still are. Many organizations are using sophisticated probabilistic likelihood ratio, different types of patient matching and complex computer algorithms. But despite all of that effort and the human effort the state today is that we probably still have, in any given health care organization, if not tens of thousands of records that can’t be matched, in many organizations you will see hundreds of thousands, I’ve even heard of millions of records that can’t be matched because the organization doesn’t have a comprehensive strategy to address the issue.

Joe Lavelle 05:16 That creates problems, lots of problems. I’m sure we’ll talk about them. What has traditionally been used to solve those problems, to match those records and are those traditional methods enough?

Lorraine Fernandes 05:29 So traditionally what you saw, let’s say 20 years ago, because as I said I’ve been addressing this for longer than 20 years. You saw that character by character, byte by byte match, which probably only linked 40 maybe 50% of the records that are out there. Then organizations moved to using the algorithms to do the matching which improved it significantly, probably in 80 to 90% world. Along that way when you talk about what’s traditionally been done, in most organizations of multi hospital systems, let’s say. There will be individuals or teams responsible for resolving those tens of thousands or hundreds of thousands of records that can’t be linked. So I think to sum it up Joe, you’d say, there’s some computer science involved, human labor involved and traditionally what’s lacked, sadly. But you are seeing a lot more of today, is really tying the governance around this and understanding it’s not just one thing or the other, it’s the classic people process and technology. Back to school Joe, back to school.

Joe Lavelle 06:50 Lorraine, why is this so important in today’s healthcare environment?

Lorraine Fernandes 06:54 So Joe we live in an era now very different than 10 or 20 years ago. 10 or 20 years ago data sat in silos sadly, and you didn’t see data freely exchanged across health systems, across health information exchanges, across from payer to provider. So some of the key initiatives that used this patient identifier data and those matched records, are going to include initiatives like value based reimbursement and being able to link Lorraine Fernandes data across the systems where I’ve had care. It’s going to impact reimbursement today and probably even to a greater extent tomorrow. Being able to share my records for care coordination has a much greater emphasis than what it did in the past, and you’re going to have to be able to match my records, so that the care team has access to all of my records.

There’s things like disease registries that maybe stands alone or maybe part of a population health strategy. So again being able to link my records within a healthcare system or across health care systems maybe important to that disease registry, obviously to population health and targeting who needs extra time and attention and resources to ensure better care and more cost effective care you might say. And then I think the last point I drive home there, is that consumer engagement strategy, that patient engagement strategy, we’re exposing a lot of data to the patient themselves today, and to the clinical analytics around that patient. So from a privacy and security perspective as well as a consumer engagement and a member engagement strategy, we want to make sure that when Lorraine Fernandes logs on to the patient portal, I’m truly seeing all of Lorraine Fernandes data and only Lorraine Fernandes data.

So that’s just a few examples of why it’s so important today to put some time and attention and energy to truly developing a strategy and then executing a solution approach to patient matching.

Joe Lavelle 09:33 We’ve talked a little bit on our show about a national healthcare identifier, is it possible that that would help with this problem?

Lorraine Fernandes 09:40 I think I remind everyone that it might be one component of moving forward, but what’s really needed is a solution approach not just a national healthcare identifier, but a solution. Because even if you said tomorrow or two years from tomorrow, you’re going to have a national healthcare identifier. there will be a tremendous amount of retrofitting that would have to be done to log that into a patient record, to ensure the accuracy of it, to build the fields. You probably won’t be able to link it to historical data because of the cost of retrofitting, so it more likely be at this date forward approach I think.

But there is certainly is a lot of dialogue going on around that and it could be a part of the future solution and the strategy, but I don’t think it’s the silver bullet and that’s why I will always remind people, you want a strategy that includes people, process and technology.

Joe Lavelle 10:46 Outstanding, there’s many parts of the problem that the identifier may not be the total solution for as well. What innovation can be applied to this ongoing challenge of eliminating duplicates?

Lorraine Fernandes 10:59 Well I think the innovation that’s happening today in what I’m seeing particularly in the last 2 or 3 years, is I see what the CHIME challenges trying to do for example and saying you know, let’s think about the importance of this and let’s put a different lens on it and see what comes of that process and we don’t know what that process is. It’s overdo now in coming to us, but we’ll see what that’s says by the middle of 2017 is what I now understand. So probably more importantly what I see happening is people addressing this in an innovative fashion with governance wrapped around it, that multi stakeholder documented approach, is thinking about how do I improve the quality of my data or how do I apply learning technology to these tens or hundreds of thousands of records that aren’t resolved.

So in the first case, how do I enhance data quality so that my records will more apt to match on that first pass when there’s a patient encounter? People are using data services out there from a variety of sources to improve that quality of healthcare data with data you find in public databases, in credit bureaus, in other public domain files. And I’ve seen a number of case studies out there that have remarkably improved the quality and therefore the data can automatically link.

Then on the technology side, what I’ve seen in the last couple of years a lot more, is the use of learning algorithms, neural networks, artificial intelligence, whatever you want to use for your term there. But really teaching a computer system to think like the human and I have someone that I talked to a couple of weeks ago and they were talking about how they improved their resolution so that they taught the algorithm to automatically resolve these records that weren’t matching, you might call them ambiguous linkages or records below a clerical review threshold.

So you teach the algorithm to think like a human, obviously through a lot of work sampling, and then the algorithm can quickly and cheaply resolve those rather simple records that couldn’t be matched to begin with, and then you leave the very difficult stuff for the stewardship team that really have to apply a lot more discerning power I guess you’d say to that. So lots of innovation happening, I see every few months a new vendor coming up with a new approach, and people using the technology and the data that is certainly beyond healthcare to apply innovation.

Joe Lavelle 14:05 Good deal and I forget to send you my crystal ball, but just imagine you have it there in front of you. What do you see the future holding in the next couple of years? How are things going to evolve?

Lorraine Fernandes 14:16 I think people are going to become more aware of some work that ONC has done in this area in the last couple of years. We all know that in 2014, if you spent time on this topic, ONC released a report that reviewed the state of this particular challenge patient matching, and they talked about how to enhance data, how to standardized fields, how to work interoperability in this. And so I think one of the things we’ll see is ONC’s interoperability roadmap that was published about a year and a half ago now, people are going to begin using some of the metrics that are in that. And if you were not familiar with it, there’s actually a component of this nationwide interoperability roadmap that says by 2017, obviously we are there. You have to be able to measure your error rate and it must be less than 2%.

We hope people are there today, the reality is many many organizations aren’t. But I think what really gets people to pause and to accelerate you know what they’re going to do in this crystal ball area, is the fact that this ONC interoperability roadmap says you must be able to measure and demonstrate that you’re less than one half of 1% in an error rate by 2020. So 2020 is only three years away, and you have to be at one half of 1%. That’s I think where people are need to start to focus in order to get to that, and I think the other thing I’ll add to that Joe, because I’ve had people say to me, well, Lorraine this is ONC and their interoperability roadmap, and we all know we’ve had an election and the politics has changed, does this really matter?

I think it does, because this is a national benchmark that organizations can use large, small, multidisciplinary, university, I think any organizations can grab on to this and say, I need to march to this beat to be able to meet this one half of 1%. Because there are other organizations, there will be health plans I suspect that are going to hold this up as an element that you must meet. There is the chance that other components of the federal health system could begin to really embrace this and say you’ve got to be at this one half of 1%. So even though it’s ONC saying this about a little over a year ago, I see the commercial world picking up this baton and I see public and private collaborative picking up these types of metrics and say, okay, let’s build the solution because it really does require a solution, let’s build the solution to get to this one half of 1% by 2020.

Joe Lavelle 17:34 Outstanding. Lorraine, it was so great to have you on the show, thanks for stopping by and sharing your great wisdom with us today.

Lorraine Fernandes 17:40 Thank you much Joe!

Joe Lavelle 17:42 Oh, well thank you. Before we wrap our conversation, we want to thank the great folks at Velocity for sponsoring the show once again. Please go to to find out more about the innovative ways that they are solving data quality and interoperability needs for their clients. And now on behalf of our guest, Lorraine Fernandes, I am Joe Lavelle, we’ll be back soon with another informative episode of the Velocity Interoperability Podcast. See you then.


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JOE LAVELLE is a Healthcare Management and Technology Consultant with a record of successfully meeting the business and technology challenges of diverse organizations including health plans, health delivery networks, and health care companies for 25 years. Joe worked his way up through Cap Gemini and Andersen Consulting to the partner/VP level of at First Consulting Group, Technology Solutions Group and Santa Rosa Consulting. After running his own company, Results First Consulting, for 12 years Joe Co-Founded intrepidNow with Todd Schnick to create incredible content to dramatically improve the sales and marketing efforts of their clients.