Blog Posts on Patient Identification in Healthcare

Takeaways from the 2015 NE NAHAM Regional Conference – “Improving the Patient Experience”

October 27, 2015/5307 views / 0 Comments/in BLOG, Events/Conferences, Iris Recognition, Patient Identification, Patient Safety /by John Trader

David Cuberos, Enterprise Sales consultant with RightPatient®, poses with Bryan Marcotte from Baystate Health, winner of the gift card door prize at the 2015 NE NAHAM regional conference.

The following guest post was written by David Cuberos, Enterprise Sales Consultant with RightPatient®

The time that we spend meeting with patient access professionals in the field is important to us. It’s an opportunity for our team to better understand core patient access functions/workflow and how these critical front line staffers help mold the patient experience as a first point of contact in what can often be a long, complex journey through the healthcare system. Our strong support for the National Association of Healthcare Access Management (NAHAM) and their regional chapters is a key relationship — instrumental to our product and service design and the ability for us as healthcare software vendors to deliver a solution that meets the dynamic needs of these healthcare professionals and moves the patient safety needle in a positive direction.

Last week, we had the opportunity to meet with patient access professionals from the northeast region of the U.S. to discuss the patient access professionals’ impact on the patient experience. We learned a lot about challenges faced by patient access staff, how it impacts workflow, and what new technology solutions are available to help meet the shifting and often complex demands of this position.

We also had the opportunity to discuss the ongoing conundrum of achieving accurate patient identification with show attendees and display our biometric patient identification solution that helps to increase patient safety and eliminate duplicate medical records/overlays and prevent medical identity theft and healthcare fraud. This was an ideal environment for us to not only help educate attendees on the value of implementing a patient identification solution, but it also provided us the opportunity to clear up misunderstandings about how this technology operates in a healthcare setting. As we do at all events, we learned a great deal about what types of questions healthcare professionals have about this technology and walked away with some key takeaways:

1. Retinal scanning and iris recognition are two different biometric technologies: This is a recurring misunderstanding we consistently see wherever we go. Due to the fact that both retinal scanning and iris recognition use the human eye for identification, most people believe that the technology is the same. In fact, the two are very different – explained in this blog post we wrote that breaks down the differences between iris recognition and retinal scanning.

2. Patient acceptance of iris recognition is extremely high: Some believe that using the iris as a unique identification credential can invoke patient trepidation to register their biometrics as a way to protect their identity and ensure accurate treatment throughout the care continuum. However, when healthcare staff observes the iris camera in person, they realize that it is perhaps the least invasive biometric modality because it simply takes a high-resolution digital photograph of the patient and can identify them in less than three seconds. Our field research supports patient acceptance of iris recognition for identification, with over a 99% acceptance rate.

3. Proper due diligence of biometric patient ID vendors is critical: Did you know that not all biometric matching types support the elimination of duplicate medical records or have the ability to prevent medical identity theft and healthcare fraud in real-time? Are you concerned about implementing a contact dependent biometric modality for patient identification that may jeopardize hospital infection control policies or require additional investments in a cleaning solution or wipes after each use? Does a biometric identification system seamlessly integrate with your electronic health record system to accurately authenticate patients from any touchpoint along the care continuum? Does your biometric patient identification solution have the ability to secure remote access to protected health information (PHI) from patient portals and/or mHealth apps?

These are all important to ask when evaluating biometric patient identification vendors but our experience is that many hospitals aren’t asking the right questions.

4. Hospital resources to resolving duplicate medical records are staggering: We continue to be amazed at the number of hospital staff dedicated to resolving duplicate medical records. In fact we spoke with a few attendees who mentioned that they have “teams of people” dealing with duplicate medical record clean-up. Although we can’t understate enough the importance of maintaining clean data, we have longed believed that implementation of modern patient identification technologies that have the ability to not only clean a master patient index (MPI), but sustain the integrity of the data moving forward. The key to preventing duplicate medical records is implementation of technology that can accurately identify patients no matter where they are along the care continuum.

5. Patient experience can be boosted through the use of biometric patient identification technology: Patients pay close attention to their experience at a medical facility. Patient knowledge of the negative effects of duplicate medical records and medical identity theft has increased their empowerment to seek services at facilities where their identities are protected. Implementing a biometric patient identification solution to protect patient identities invokes the emotion that medical facilities care about safeguarding patient safety and privacy.

Understanding how to improve the patient experience in healthcare requires careful examination of processes and workflow that bring convenience and demonstrate a genuine interest in protecting patient identities. We continue in our mission to provide the most comprehensive and holistic patient identification solutions available to help improve the patient experience in healthcare.

A special shout out to Bryan Marcotte from Baystate Health as the winner of the gift card door prize. Congratulations Bryan!

How can we help you to improve the patient experience at your medical facility?

David Cuberos is an Enterprise Sales Consultant with RightPatient® helping hospitals and healthcare organizations realize the benefits of implementing biometrics for patient identification to; increase patient safety, eliminate duplicate medical records and overlays, and prevent medical identity theft and healthcare fraud.

Improving Mobile Patient Identification with Wireless Technology

October 21, 2015/6262 views / 0 Comments/in Biometric Hardware, BLOG, Data Integrity, Future of Biometrics, Health Care, Mobile, Patient Identification, Patient Matching, Patient Safety /by John Trader

Patient Identification isn’t Cookie Cutter

You know the drill. A trauma patient is whisked into the emergency room bypassing the normal registration process to receive immediate care. Despite the patient’s condition, you as a patient registration representative are still responsible for establishing the patient’s identity, verifying their insurance eligibility, and ensuring that services rendered are allocated to the proper electronic medical record so the hospital can maintain high levels of data integrity and secure accurate revenue cycle compensation. Or, perhaps a handicap or disabled patient arrives at your facility and you may have to adjust normal registration procedures to compensate for their condition which may involve approaching the patient in the waiting room instead of asking them to approach you.

Particularly in emergency situations, wireless biometric patient identification devices offer convenience and portability to ensure patient safety.

The following post was submitted by Brad Marshall, Enterprise Development Consultant with RightPatient®

Whatever the case may be, some hospitals that have implemented biometrics for patient identification now have the ability to use a wireless camera to identify a patient at bedside or in-person, adding registration flexibility and removing the need to deal with the often cumbersome tangle of wires, USB cables, and devices on computers on wheels (COWs) or workstation on wheels (WOWs). These hospitals understand that wireless, portable patient identification offers distinct advantages to quickly identify patients with special conditions without the restrictions of a USB connection that may limit mobility and waste valuable time.

The Flexibility of Free Standing Patient Identification in ED or Bedside

The ability to quickly, easily, and accurately identify patients in emergency situations can often be the difference between life and death. Think about identifying an unconscious or unknown patient who arrives in the Emergency Department (ED) with a long medical history that includes medication allergies or important pre-existing conditions. Treating a patient in the absence of this critical health data not only endangers their health, but it presents a huge liability to the hospital should something go wrong based on missing or incomplete information. Not to mention that fact that in healthcare, especially in emergency situations, seconds matter.

Patient registration staff and clinicians both need the convenience and portability of a wireless biometric patient identification device that can be used to quickly determine a patient’s identity at any physical touchpoint along the care continuum. Think for a moment about the importance of verifying a patient’s identity at bedside. Accurate patient identification is not only an important safety protocol, but it also offers a variety of other benefits including:

Cost reductions by eliminating unnecessary or repetitive diagnostic testing or procedures
Reduction of mistakes during treatment that could result in hospital liability
Efficient organization of supplies, medications, and specimens

Innovative wireless patient identification devices increase productivity by saving time without compensating accuracy during the registration process. Characterized by their mobility and efficiency, these devices are configured to seamlessly communicate with biometric patient identification systems integrated with electronic health record (EHR) platforms to ensure 100% accuracy.

Conclusion

Wireless devices are revolutionizing patient identification in healthcare by combining the speed and accuracy of biometrics with a convenient and portable design that eliminates the frustration of maneuvering cumbersome COWs and WOWs and the restrictions of USB connected devices. Specifically designed to ensure patient safety, lower hospital liability, and strengthen and sustain patient data integrity, wireless patient identification devices almost seem to be a “must have” for any hospital that is vested in ensuring the highest quality care, especially amid challenging conditions.

Interested in learning more? Drop us a note and we will be happy to set up a no obligation demo to show you firsthand how these devices operate, and provide more details about the advantages.

Brad Marshall is an Enterprise Development Consultant with RightPatient®. With several years of experience implementing both large and small scale biometric patient identification projects in healthcare, Brad works closely with key hospital executives and front line staff to ensure project success.

Bethesda Health Implements Iris Biometrics for Patient Identification

October 13, 2015/5035 views / 0 Comments/in BLOG, Comments On Recent Biometric News Stories, Health Care, Iris Recognition, Patient Identification, Patient Safety /by John Trader

Excited to announce that another hospital system has implemented our biometric patient identification solution using iris biometrics to help raise patient safety standards, safeguard patients from medical identity theft and fraud at the point of service, and prevent the creation of duplicate medical records.

Bethesda Health becomes the latest hospital system to implement the RightPatient® biometric patient identification solution using iris recognition.

After carefully evaluating several biometric patient identification solutions, Bethesda Health chose to deploy iris biometrics due to it’s non-contact, hygienic form factor which supports hospital infection control initiatives plus, implementation of RightPatient® poises Bethesda Health to eventually extend the use of the technology to any patient touchpoint along the care continuum that requires patient identification accuracy to ensure optimal outcomes. This is critical foresight by Bethesda staff who recognized that accurate patient identification in the new healthcare paradigm extends far beyond in or outpatient registration within their facilities and should now be addressed holistically by providing secure and accurate patient ID at any point along the care continuum where patients have access to medical care or sensitive personal health information (e.g. patient portals, mHealth apps, home health, etc.).

We welcome Bethesda Health as a trusted partner in the effort to increase patient safety, reduce duplicate medical record rates, eliminate medical identity theft, improve revenue cycle efficiency through the use of our biometric patient identification platform using iris recognition.

For more information on the deployment, please visit the news release section of our Web site.

Learn more about the advantages of using biometrics for patient identification by visiting the Resources section of our Web site.

New Podcast Shines Spotlight on The Patient Safety Movement in Healthcare

October 12, 2015/4268 views / 0 Comments/in BLOG, Patient Safety, Podcasts /by John Trader

We interviewed Jim Bialick, President of The Patient Safety Movement to discuss the topic of patient safety in healthcare.

Patient safety is a topic intertwined with so many policies and procedures in healthcare, many considering it to be the “cornerstone” to deliver quality care. After all, any healthcare organization can be equipped with the latest and most cutting edge care delivery technologies and staff with deep experience in healthcare delivery, but easily fail to recognize the impact on providing holistic patient safety, no matter where a patient falls along the continuum.

Many organizations have materialized with the sole purpose of advancing patient safety in healthcare, but none perhaps more impactful or relevant than The Patient Safety Movement, a Foundation focused on collaborating and breaking down information silos that exist between hospitals, medical technology companies, the government, and other stakeholders that enourages the sharing of data that can identify at-risk patients before they’re in danger and provides specific, actionable solutions that healthcare professionals can implement today to help realize the goal of zero preventable deaths by the year 2020.

We had the pleasure of interview Jim Bialick, President of the Patient Safety Movement for first hand insight on their goals and mission, information about their forthcoming Patient Safety Summit in January 2016. Plus, we had the chance to ask Jim his opinion on the use of biometrics for patient identification in healthcare, the state of patient data integrity in healthcare, and insight into the impact of duplicate medical records. Here is a list of questions covered during our podcast with Jim Bialick and The Patient Safety Movement:

1. What can you tell us about The Patient Safety Movement mission and goals? What steps are you taking and what accomplishments have been realized since you began the movement?
2. I noticed that the Patient Safety Movement is sponsoring the “Patient Safety Movement Foundation Innovation Competition” to encourage advocates to submit innovations to advance the goal of zero preventable deaths by 2020. What can you tell us about the motivation behind creating this award and how you feel it will advance the patient safety initiative?
3. Talk to me for a minute about the upcoming Patient Safety, Science, and Technology Summit in January 2016. What is the significance of this event, why should people attend, and what one message do you hope attendees walk away with?
4. Improving and sustaining patient data integrity in healthcare has gained strong momentum due to its effect on the ability of clinicians to provide accurate, cost effective care to a patient. Due to the increase in patient touchpoints (portals, mHealth apps, kiosks, smartphones) from the rapid digitization of healthcare that provide new ways to access personal health information and receive services, what additional patient safety concerns have you worried that could potentially undermine patient data integrity?
5. It’s often said that accurate patient identification in healthcare is one of the key pillars of protecting patient safety throughout the care continuum. Considering the fact that many healthcare organizations still rely on outdated and ineffective patient matching methodologies, what new patient identification technologies do you see as promising to improve patient identification accuracy and patient data integrity?
6. The growth of biometrics for patient identification presents an opportunity for healthcare organizations to modernize authentication protocols to improve patient safety, eliminate duplicate medical records, and prevent medical identity theft and fraud at the point of service. We recently conducted a survey of 1,067 patients about infection control policies in healthcare and preferences regarding biometric technology and found that 70% prefer a non-contact device. Based on your experience, why do you think this is the case? If evaluating a contact dependent device for patient ID, what would providers need to consider in terms of hygiene and infection control? What are the patient safety risks of using a contact dependent vs. non-contact biometric modality (e.g. palm vein vs. iris recognition) for patient ID in healthcare from an infection control perspective?
7. In The Patient Safety Movement mission statement, you talk about “breaking down the silos” in healthcare. Can you please explain your interpretation of “breaking down the silos” and why do you feel this is an important component to advance the initiative? What distinct advantage does coalescing the fragmented and disparate entities in healthcare have to advance patient safety in healthcare?
8. Why are hospitals allowed to operate under the radar with issues such as duplicates and overlays that pose such a significant risk to patient safety? Who governs this and why isn’t such an industry-wide epidemic made more public so that patients and regulators are made aware? Should there be an industry level of transparency where it is mandated that a hospital’s exposure to such issues is made public, constantly monitored, penalized and regulated?

For a full version of the podcast, please click here.

Our thanks to Jim for his time and wisdom on the topic of patient safety in healthcare! Follow The Patient Safety Movement on Twitter, and please “like” their Facebook page.

Have an idea for a podcast? Drop us an email at: jtrader@rightpatient.com! For a full list of our podcast library, please visit our podcast page.

In Your Face: The Future of Federated Patient Identification

October 7, 2015/5888 views / 0 Comments/in BLOG, Facial Reciognition, Future of Biometrics, Health Care, Patient Identification /by John Trader

The following guest post was written by Michael Trader, Co-Founder and President of RightPatient®

The Patient ID Problem

The recurring and complex issue of how to establish and maintain accurate patient identification in healthcare and how to establish a federated patient identity is getting a lot of attention these days. Accurate patient identification in healthcare is a topic that has always garnered attention and concern, but perhaps it has gained momentum and urgency due to the rapid digitization of the industry and the concerted push for interoperability and national health information exchange to improve individual and population health. The push for increased interoperability could make patient data matching errors and mismatches exponentially more problematic and dangerous and it is widely believed that inadequate patient identification continues to jeopardize patient safety and artificially inflate the cost of care.

Can the use of facial recognition biometrics help establish a federated patient identity credential in healthcare?

Opinions on the most effective patient identification and patient matching strategies run the gamut. Some say standardizing patient demographic data will help, others feel that establishing a national patient identifier is the answer to the problem. What’s clear is that in the absence of any broad improvements to patient identification, the goal of establishing longitudinal patient records reflecting a patient’s experience across the care continuum, payers, geographic locations, and stages of life, will remain elusive.

One idea that is catching on with healthcare providers to help improve patient identification in healthcare is capturing a photo during registration that is linked to a unique electronic medical record.

Use of Patient Photos Increasing

Nearly 2.3 million people were victims of medical identity theft in 2014, according to the “Fifth Annual Study on Medical Identity Theft” released earlier this year by the Medical Identity Fraud Alliance (MIFA), an industry trade association of healthcare providers, payers and service providers – a 21% increase over the 2013 number of 1.8 million. Medical identity theft and healthcare fraud continue to be a pervasive problem throughout the industry and in the absence of a solution, the problem is only going to get worse as millions more Americans are brought into the healthcare fold through Obamacare.

To help fight the increase in medical identity theft and to ensure a patient’s identity is accurately verified at each step along the care continuum, many healthcare facilities are capturing a patient’s photo at registration and linking that to a unique electronic medical record. The idea is an attempt to protect patient privacy, ensure accurate insurance benefits and subsequent reimbursement, and connect a face with a name, providing another option for identification besides date of birth. The idea is catching on quickly and many are embracing the use of patient photos to increase security and improve patient safety, but what often goes unrealized is the potential for a patient photo to be leveraged as a unique identification credential across the entire care continuum.

Leveraging Patient Photos for a Federated Identity Across the Care Continuum

Whenever we hear the words “patient identification” most of us envision sitting across a registration desk at a hospital or doctor’s office providing demographic data and our driver’s license and/or insurance card. However, patient identification in healthcare has evolved to now include accurate identification at each and every patient touchpoint along the care continuum including patient portals, mhealth apps, telehealth, and home health just to name a few. One of the smartest strategies to ensure accurate patient identification at any point along the care continuum is to capture a patient’s photo at registration and then leverage that photo along the care continuum through biometric facial recognition technology.

Let’s take patient portals for example. Most of us know that Meaningful Use Stage 2 mandates that healthcare providers provide patients the ability to electronically view, download, and transmit health information. The most popular means to that end is the increasing use of patient portals yet many providers rely on antiquated identification protocols such as user names and passwords to protect access to this personal health information (PHI). The problem is relying on user names, passwords, and/or personal identification numbers (PINs) is risky and could potentially open the door to third party data breaches which are decimating the industry and exposing millions of patients’ PHI.

As an alternative to using user names and passwords, consider a healthcare organization that captures a patient’s photo during registration. Not only is that photo visible to patient registration staff and clinicians at each episode along the care continuum as a second form of multi-factor authentication, but if a patient signs into a patient portal and the hospital has deployed facial recognition identification to authorize a patient’s identity prior to logging in, the hospital has just successfully leveraged that photo as an identification credential for access to their PHI. Same goes for mHealth apps. Biometric patient identification providers that offer the value and flexibility of facial recognition authentication can also help third party developers and healthcare providers add this technology to off-the-shelf (OTS) or custom mHealth apps as a more secure way of identifying patients with the ability to work with any standard camera.

Coupled with the fact that 80% of patients are open to healthcare interactions on smart devices but remain highly sensitive to sharing health data, facial recognition biometrics for accurate identification has already proven itself as a more secure alternative than user names and passwords not to mention the fact that 69% of 16 -24 year olds recently polled indicated they believe biometrics will be faster and easier than passwords and PINs and half foresee the death of passwords by the year 2020.

Writing on the Wall?

With predictions that 50% of smartphones sold by 2019 will have a fingerprint sensor and over a billion biometric mobile devices will ship worldwide by the year 2020 (all equipped with cameras sophisticated enough to use facial recognition), the evolution of patient identification in healthcare is tilting more towards the use of biometrics to replace user names, passwords, and PINs as the preferred method of authentication due to it’s increased security and the flexibility to apply the technology for accurate identification at more patient touchpoints borne from the rapid digitization of the industry. Considering the fact that 41% of consumers stress over smartphone mobile security and biometrics are already overtaking passwords as the de facto identification credential on smartphones, could this be the perfect storm for a rise in the use of facial recognition for accurate patient identification?

Responsible approaches to improving patient identification in healthcare must now include addressing accuracy at any touchpoint where a patient can now access PHI. The advent of facial recognition as a unique identifier in a singular or multi-factor environment is a smart answer to the challenge of ensuring a patient receives accurate care throughout the continuum no matter if they are physically present or accessing services from cyberspace.

Since more patients expect providers to ensure privacy and protect their PHI, is it time to more closely examine implementation of a patient identification solution that leverages biometric facial recognition?

Michael Trader is President and Co-Founder of RightPatient®. Michael is responsible for overseeing business development and marketing activities, government outreach, and for providing senior leadership on business and policy issues.

Improving Revenue Cycle Management with Accurate Patient ID

October 1, 2015/4941 views / 0 Comments/in BLOG, Data Integrity, Patient Identification, Patient Matching /by John Trader

The following post was submitted by Jeremy Floyd, Healthcare Director at RightPatient®.

The Dangers of Duplicate Medical Records

Most of us already know that duplicate medical records in healthcare pose a direct threat to patient safety. The concept is rather straightforward — if a duplicate medical record exists for a patient within an electronic health record (EHR) database or master patient index (MPI), chances are that clinicians may make a medical error based on a fragmented view of a patient’s medical history. There are myriad reasons why a duplicate medical record may exist ranging from patient names that have complex spellings and/ or variations of a name, data entry input errors by hospital staff, identity sharing among patients, and unenforced admissions quality standards across a provider network.

Eliminating duplicate medical records to improve revenue cycle management is achieved through accurate patient identification.

Duplicate medical records can be created from the simplest of errors — using nicknames to identify a patient or a missing digit on a social security number, date of birth, or address for example. Often times, the problem of duplicate medical records is most prevalent with patients who have similar or identical names.

Compounding the problem of duplicate medical records in healthcare is the shift change of healthcare providers from single entities to complex integrated delivery networks (IDNs) and Accountable Care Organizations (ACOs) which require that patient records contained in multiple MPIs be aggregated into a single Enterprise Master Patient Index (EMPI) to provide a holistic view of the patient’s record across the care continuum. Unfortunately, many healthcare organizations are unaware of the complex variations in how a person is demographically represented in multiple records in different systems. Consequently, when basic matching criteria is used on various combinations of a person’s name, date of birth, gender, and social security number, the end result is patient records with multiple typographical errors, or different representations of a person’s name as un-matched duplicates in the resulting EMPI.

It becomes quite clear that the evolution of healthcare to expand data sharing that benefits both individual and population health is exacerbating the risks that duplicate medical records have on the ability to provide safe and accurate care not to mention placing financial constraints that inhibit the flow of accounts receivable.

The Hidden Effect of Duplicates on Revenue Cycle Management

We talk a lot about how duplicate medical records negatively impact patient safety. We know that their presence can easily create unnecessary medical errors and weaken patient data integrity. We also understand that the bulk of duplicate medical records are created by patient misidentification.

What is often overlooked and not discussed enough is the effect that duplicate medical records have on efficient revenue cycle management. The Healthcare Financial Management Association (HFMA) recently wrote about the inverse relationship between duplicate medical records and revenue cycle management stating that, “Lowering the duplicate patient record rate increases revenue cycle efficiency by improving the accuracy of information used to submit claims, collect payments, and provide care.” (Source: http://www.hfma.org/Content.aspx?id=16788)

The fact is that the negative impact of duplicate medical records extends far beyond patient safety, affecting many other “downstream financial activities” — as HFMA states in their article. In other words, duplicates pose a direct threat to financial stability and efficiency because their existence leads to medical reporting inaccuracies and repeat testing that insurance companies will not reimburse. Plus, duplicates can negatively affect or even sabotage other hospital initiatives that rely on high levels of patient data integrity — the implementation of an EHR system for example. HFMA notes that that many other downstream activities can be affected by duplicates, specifically:

Inefficient use of medical records staff time on correcting duplicates rather than focusing on coding
Delayed claims payments or denials due to the use of an incorrect name or other identifiers, or for duplicated services
Higher A/R days due to late payments
Patient safety risks when the duplicate record does not include all important information, especially items such as medication allergies, diagnostic test results, or previous diagnoses
(Source: http://www.hfma.org/Content.aspx?id=16788)

What’s clear is that the most likely source of duplicate creation is patient registration leading many healthcare organizations to more closely evaluate best practices and existing workflow and identify areas of improvement. Many are also implementing modern patient identification technologies that eliminate duplicate medical records by removing the ability to create them in the first place.

Using Accurate Patient Identification to Increase Revenue Cycle Efficiency

Perhaps one of the hottest topics to surface in the wake of healthcare digitization is the absence of static patient identifiers, especially in the context of exchanging patient information quickly, affordably, and safely. Patient matching inconsistencies have bubbled to the surface in many broader discussions about establishing efficiencies in healthcare — most notably for healthcare information exchange and information governance. However, recognizing the need to establish tighter control over accurate patient identification should first be defined in the context of how it will improve internal initiatives (e.g. – revenue cycle management) before expanding applicability to projects that provide data sharing to a larger provider demographic.

Among the numerous options available to help identify and reduce duplicate medical records and improve patient identification in healthcare is the use of deterministic or probabilistic data matching. Although these methods are relatively sufficient to clean MPIs of duplicates, the disconnect seems to be implementing a more secure and accurate patient identification technology on the front end to sustain a clean MPI moving forward. Remember that there is a distinct difference between identifying and cleansing an MPI of duplicates, and deploying another strategy to ensure that a database remains clean. This is where many healthcare providers fall short.

The most effective approach to eradicating duplicate medical records and improve revenue cycle management is evaluating modern patient identification solutions that are powerful enough to sustain a clean MPI and prevent some of the aforementioned downstream repercussions that can damage financial health. After all, a fluid and efficient revenue cycle management system uninhibited by the impact of duplicate medical records helps to keep costs down and improve the quality of care.

Jeremy has worked in the biometrics industry for nearly a decade and has real world experience with fingerprint, palm vein, finger vein, iris and face recognition technologies. He currently oversees the RightPatient™ Healthcare division of M2SYS Technology, including sales, business development and project management. Before taking over the Healthcare unit, Jeremy spearheaded the growth of the core biometrics division, working closely with Fortune 500 clients like ADP, JP Morgan & BAE Systems to implement biometrics in large identity management projects.

The Difference Between 1:N, 1:1, and 1:Few and Why it Matters in Patient ID

September 23, 2015/9405 views / 1 Comment/in Biometric Terminology, BLOG, Patient Matching /by John Trader

The following guest post was submitted by Joe Kubilius, Director of Product and Process Management at RightPatient®

Understanding the Digital World

In a world rife with digital devices and electronic gadgets, few of us probably know or understand how they actually work. Think about a smartphone for example – myriad buttons, switches, cameras, lights, and sounds instruct us to swipe this, or press that and we oblige. After all, the complexity of the backend processor and sensor network that makes these devices do what they do is probably of little interest to most of us, myself included.

Did you know that not all biometric patient ID systems have backend matching types that can prevent duplicates, eliminate medical ID theft, and improve patient data integrity? Only 1:N biometric matching has this capability.

Instead what we focus on is the end result – what you see, hear, and experience when you use a digital device. Few would argue that it’s necessary or even mandatory to have a thorough understanding of backend functionality on any digital device in order to appreciate the value it brings to our lives. For biometric patient identification solutions, this is definitely not the case.

Why Biometric Patient ID Technology is Different

Understanding biometric matching types is critical when selecting a patient identification solution. Most of us probably see biometric matching as rather black and white — for example, you place your finger on a fingerprint reader, a backend software program recognizes and verifies your identity, and you are on your merry way. The problem is that backend biometric matching technology is not cookie cutter and there are different matching types that carry different capabilities.

Why is this important to know and understand? We know that most healthcare organizations invest in the use of biometric patient ID solutions to increase patient safety by:

Eliminating medical identity theft and fraud at the point of service
Preventing duplicate medical records and overlays
Achieving and sustaining patient data integrity
Safeguarding personal health information (PHI)
Identifying unconscious or unknown patients

What most people don’t realize is that depending on which biometric matching type you select, achieving these goals is not 100% attainable with select patient ID solutions. The ONLY way to achieve the bulleted objectives is to implement a system that, during patient enrollment, compares a patient’s stored biometric template against ALL stored templates in the biometric database. If the ultimate goal is to improve patient safety and patient data integrity, only a one-to-many (1:N) biometric matching type can accomplish this.

Let’s take a closer look at the available biometric matching types and what they have the ability to do.

Understanding the Differences Between Biometric Matching Types

Biometric matching types can be categorized as: One-to-many or “Identification” (1:N), one-to-one or “Verification” (1:1), and 1:Few Segmented “Identification” (1:Few). Here is a breakdown of each matching type and how to interpret their capabilities:

(1:1) Verification: 1:1 biometric “verification” matching authenticates a patient’s identity by comparing a captured biometric template with a biometric template pre-stored in a database. 1:1 biometric matching rejects or accepts a patient’s identity but before the comparison takes place, hospital staff must first input a personally identifiable credential (e.g. – a date of birth, gender, etc.) prior to comparing a stored biometric template against a live scan. This personally identifiable credential points to a specific enrollment template in the database so using a 1:1 matching type answers the question, “Is a patient who they claim to be.”

Example: A patient walks into the ED. Hospital staff asks the patient for their date of birth then scans the patient’s biometric credential to compare it against the stored template for that patient to verify that the patient is who they claim to be. With 1:1 biometric matching, the registrar has to retrieve a patient’s medical record first. Assuming the patient has been previously enrolled, they then scan their biometric and the system compares the captured data only against the data on file for that medical record.

Takeaway: 1:1 biometric verification is beneficial for verifying a patient’s claimed identity but since it does not search the stored biometric template database in its entirety, it does not have the ability to prevent medical identity theft or fraud at the point of service nor does it have the capability to identify an unconscious or unknown patient since a personally identifiable credential is needed prior to conducting the biometric scan.

(1:Few) Segmented Identification: 1:Few biometric matching compares a patient’s captured biometric template against a segmented portion of the entire biometric database, therefore a personally identifiable credential must be provided prior to the biometric scan to determine the subset of biometric templates to compare against. For example, a patient would provide a date of birth prior to the biometric scan and a 1:Few segmented identification system would then compare that patient’s biometric template only against the templates that share the same date of birth.

Example: A patient arrives at a medical facility for treatment. At registration, hospital staff asks the patient for their date of birth which segments the biometric database to only those records that share the same date of birth and then captures the patient’s biometric credential for comparison against the segmented database.

Takeaway: 1:Few segmented identification does not have the ability to search an entire biometric database in real time to prevent the creation of duplicate medical records or eliminate medical identity theft or fraud at the point of service. What if a patient attempting to commit fraud had previously enrolled their biometric credentials and it was linked to another electronic medical record, then returns to the medical facility claiming another identity and providing a falsified, different date of birth? Hospital staff would then link that patient’s biometric credentials to another electronic medical record and a 1:Few segmented identification matching type would not be able to catch the fraud or prevent a duplicate medical record for this patient. In addition, if a patient arrived unconscious without any identification credentials in the ED, 1:Few segmented identification does not have the ability to identify them because a personally identifiable credential is required. How would an unconscious, unknown patient be able to provide this? Biometric patient ID matching systems based on 1:Few segmented identification do not have the ability to identify unconscious/unknown patients.

(1:N) Patient Identification: A one-to-many (1:N) biometric identification matching system instantly compares a patient’s captured biometric template against ALL stored biometric templates in the system. No other information is required from the patient other than their biometric credentials and this matching type represents the only true de-duplication mechanism and the only way to prevent duplicate medical records to achieve and sustain patient data integrity. 1:N biometric mathcing types ensure that once a patient enrolls, it is impossible to create a duplicate medical record for that patient.

Example: A patient arrives at a hospital for outpatient surgery. At the registration desk, hospital staff takes a patient’s photo with an iris recognition camera. The backend software instantly compares that patient’s biometric credentials to every single stored biometric template in the database.

Takeaway: 1:N biometric matching is the only true way to prevent duplicate medical records and overlays and eliminate medical identity theft and healthcare fraud at the point of service. By searching the ENTIRE biometric enrollment template database, hospital staff ensures that a patient has not tried to claim another patient’s identity, and is able to access the only electronic medical record linked to that patient with confidence. If a healthcare organization seeks to improve and sustain patient data integrity and patient safety, 1:N biometric searches are the only way to accomplish this. In our 1:Few example above, if an unconscious, unknown patient arrived in the ED and a hospital had implemented a biometric patient ID system with 1:N matching, hospital staff would only need to capture the patient’s biometric credential for accurate identification.

Understanding the capabilities and limitations of biometric matching types is key to select a biometric patient ID system that will accomplish the goals of improving patient safety and patient data integrity in healthcare. Take the time to ask the right questions when evaluating a biometric patient ID solutions so you won’t be left in the dark about what a solution can and can’t achieve.

Have you implemented a biometric patient ID system based on 1:1 or 1:Few segmented matching type and did not understand the limitations? Please share your comments and feedback below!

Joe Kubilius is Director of Product and Process Management with RightPatient®. With over 10 years of experience in the design, development, and implementation of biometric identity management solutions, Joe has been integral to the success of hundreds of large and small scale deployments across the globe.

Novant Health Uses Iris Biometrics to Identify Unknown Patient

September 3, 2015/5788 views / 0 Comments/in BLOG, Comments On Recent Biometric News Stories, Health Care, Iris Recognition, Patient Identification /by John Trader

It’s a familiar case. An unconscious or unknown patient arrives in the ER without any identification leaving clinicians to administer care in the absence of any medical history to review. This presents a serious patient safety risk since treating an unknown patient without the benefit of securing their identity is dangerous and can be a huge liability. What if they are allergic to a certain medication? What if they have a pre-existing condition that must be considered prior to receiving any treatment?

Novant Health recently used the RightPatient iris biometrics patient identification system to identify an unknown, disoriented patient.

Since these cases are more often trauma related requiring immediate attention, clinicians must take a risk and administer care in the absence of any historical medical data. An obvious threat to patient safety and a situation that clearly raises liability, healthcare organizations have long sought to adopt technology that can instantly identify patients in these cases without the need for any demographic information.

The staff at Novant Health decided to proactively implement an iris biometric identification system throughout their network as a means to secure accurate patient ID and ensure that patients, no matter what the circumstances, are kept safe throughout the care continuum. Although adopting a biometric patient identification system to identify unconscious or unknown patients wasn’t the sole reason that Novant implemented this technology, they knew that by choosing to use iris recognition as their primary biometric modality they would be able to quickly and accurately identify any patient in these circumstances without having to ask for an additional identification credentials (e.g. – D.O.B.).

Novant’s iris biometric patient identification system was recently put to the test when a disoriented, unknown patient arrived in the ER without any identification credentials. Novant staff quickly realized that they could take the patient’s photo with a RightPatient iris camera and if they had been previously registered in their Epic EHR database, the biometric patient identification system would recognize them and immediately pull up their medical record. Fortunately, the patient had previously been enrolled with the RightPatient system and their identity was instantly recognized after their photo was taken with the iris camera. A big relief to Novant staff since they were now able to not only access her medical history prior to treatment, but they were also able to quickly contact the patient’s relatives to inform them of the situation.

Thank you to our partners at Novant Health for sharing this story and demonstrating the value of using biometrics for patient identification in the context of keeping patients as safe as possible throughout the care continuum!

How often do you experience situations where patients arrive at your facility without identification credentials? Did you know that not all biometric patient identification solutions have the ability to identify unknown or unconscious patients?

Join the Biometrics in Healthcare LinkedIn Group

August 31, 2015/4141 views / 0 Comments/in BLOG, Patient Identification, SSO /by John Trader

LinkedIn has emerged as one of the most important social platforms to collaborate, educate, network, and publish content. Professionals from around the globe use LinkedIn as a way to establish and cultivate relationships, leveraging its communication capabilities to establish relevance and demonstrate expertise on just about any topic you can imagine.

The relevance of biometric technology to improve patient identification and SSO in healthcare is a main focus of the new “Biometrics in Healthcare” LinkedIn Group.

LinkedIn “Groups” are an integral tool to categorize discussions that center on a particular topic or subject matter and a chance to learn and converse from some of the most trusted global experts in their respective fields. In that spirit, we have created a brand new LinkedIn Group centered on the use of biometrics in healthcare. Biometrics in Healthcare was created to help advance discussions on the use of this technology for patient identification and single sign-on (SSO) in the industry but more importantly, it was established to help others understand and appreciate the benefits of using biometrics including:

Testimonials
Case studies
Examples of return on investment (ROI)
Technology updates
Clearing up misunderstandings on what biometrics can and can’t accomplish

We invite you to join the Biometrics in Healthcare LinkedIn Group and participate in the discussion. It’s your chance to ask questions, read more about how the use of biometrics is helping increase patient safety and improve data integrity across the industry and interact with professionals who understand the benefits and limitations of this technology.

Expect the significance and impact of biometrics in healthcare to grow in the coming years as more hospitals and healthcare organizations understand its value and flexibility. The new Biometrics in Healthcare LinkedIn Group will prove to be an important tool for healthcare professionals to use in their quest to research the technology and determine if their facility can benefit from its use.

We hope that you will consider joining the Biometrics in Healthcare LinkedIn Group and participate in the discussions!

Free Webinar: The State of Patient Identification in Healthcare

August 25, 2015/5868 views / 0 Comments/in BLOG, Data Integrity, Events/Conferences, Health Care, Patient Identification, Patient Matching, Webinar /by John Trader

Accurate patient identification and data matching in healthcare to ensure patient safety along the care continuum is a complex challenge for most healthcare organizations. Common names, lack of proper ID, identity swapping, and the explosion of new patient touchpoints (mHealth apps, patient portals for example) to access personal health information (PHI) has created problems for organizations that still rely on antiquated methods of identifying patients and places them at a high risk of committing medical errors that could jeopardize patient safety.

The increased complexities of achieving accurate patient identification in healthcare raise questions about the most suitable strategies to implement. Join us on September the 10th from 1 – 2pm EDT for a free webinar on patient identification in healthcare.

Achieving accurate patient identification in healthcare is a key strategic goal of healthcare organizations across the industry as they continue to explore new technologies that have the ability to meet modern demands of the new digital health paradigm in the wake of the shift to a patient-centered wellness approach and a push to better understand the individual patient. Unified views of patient data across any care setting is a growing necessity despite the variability in data capture methods, systems, and a lack of patient identification industry standards.

In the absence of a unified view of patient data, healthcare organizations will continue to make medical errors with incomplete or inaccurate information. Access to accurate, complete PHI is one of, if not the most vital component to deliver quality, cost-effective care and the only way to accomplish this is to establish accurate patient ID at the point of registration/access so the patient’s entire medical history supports immediate care or a wellness event. Complete and accurate medical histories must be linked to any point along the care continuum to truly achieve patient-centered care.

Join us on September the 10th for a free webinar on the state of patient identification in healthcare and a comprehensive overview of strategies and technologies healthcare organizations can use to improve and sustain accurate patient ID. Plus, we will address the growing use of biometrics for patient ID, explain how it’s being used, and what return on investment (ROI) hospitals have realized since implementing it at their facilities.

Topics covered during the free one-hour webinar include:

• The current state of patient identification in healthcare
• Patient identification challenges
• Using biometrics for patient ID across the care continuum

Join us on September the 10th from 1pm – 2pm EDT as we explore the topic of patient identification in healthcare and offer an overview of how biometrics is a viable solution to increase patient ID accuracy and patient safety along the care continuum.

Tell a friend or colleague! This is your chance to learn from experts in patient identification, ask questions, and engage in the discussion. Have a question you would like to ask during the webinar? Please visit the webinar landing page to sign up and leave your question or write it in the comments below.

Looking forward to seeing you on September the 10th!