Our latest podcast features HIM Director Erin Head discussing the impact of duplicate medical records and overlays on health information management (HIM).
Erin brings a wealth of experience to health information management (HIM) work flow and managing patient data integrity so naturally we were excited to tap into her knowledge base to better understand the HIM “front line” – a deeper discussion about the day to day activities in the trenches and a firsthand account of the negative impact of duplicate medical record and overlay identification and reconciliation. Our conversation with Erin covered the following topics:
— How duplicate medical record reconciliation impacts HIM workflow and other job responsibilities sacrificed due to duplicate/overlay reconciliation
— The average FTEs health information management spends reconciling duplicates and overlays and the financial impact on the hospital if FTE’s that are currently cleaning up duplicates and overlays could be reallocated to more revenue generating activities such as coding
— How the shift to quality vs. quantity based care impacts the responsibilities and sense of urgency for HIM
— Whether the ONC cost estimate of $60 per duplicate record is low or high compared to her own experience
— The impact on HIPAA violations that duplicates/overlays cause and the cost if a hospital releases information to wrong patient
— How the introduction of the patient portal complicates management of duplicates
— How the implementation of a biometric patient identification system helps to lower the burden of reconciling duplicates and overlays and allows health information management to focus on their core competencies
For a full version of the podcast, please visit the landing page for more information.
Have an idea for a podcast or know a healthcare professional that would be a good candidate to interview? Email us at: info@rightpatient.com with your ideas!
https://www.rightpatient.com/wp-content/uploads/2016/02/Erin-Head.jpg209209John Traderhttps://www.rightpatient.com/wp-content/uploads/2021/04/RightPatient-Logoup.pngJohn Trader2016-02-09 20:01:132016-02-10 11:40:27New Podcast: The Impact of Duplicates and Overlays on Health Information Management (HIM)
Joe Lavelle from IntrepidNow Healthcare interviewed RightPatient® President Michael Trader to discuss the current state of patient identification in healthcare. (photo courtesy of Joe Lavelle and IntrepidNow Healthcare)
Our thanks to Joe Lavelle and his staff for inviting our President Michael Trader to the IntrepidNow podcast to discuss patient identification in healthcare. Joe invited Michael to not only talk about the current state of patient ID in healthcare and some of the problems that misidentification of patients creates, he also provided the opportunity for Michael to discuss the RightPatient® biometric patient identification platform and what distinct advantages it provides compared to other solutions on the market.
Listen in to Joe’s podcast and learn:
The impact of biometric patient ID solutions to eliminate duplicate medical records/overlays and sustain patient data integrity
How modern patient identification solutions help prevent medical identity theft and fraud at the point of service
How the digitization of healthcare now makes accurate patient identification essential at every touchpoint along the care continuum
The rising importance and ubiquity of photos for accurate patient ID in healthcare
The biometric patient identification solution competitive landscape
Looking ahead to what’s next for RightPatient® in 2016
Listen to the entire interview here:
Thanks again to Joe Lavelle from IntrepidNow for inviting us to be a guest on his podcast! For a complete list of all RightPatient® healthcare biometrics podcasts, please visit our podcast landing page.
Healthcare Scene’s John Lynn hosts a blab conversation on the topic of patient matching in healthcare with Michael Trader and Beth Just.
Our President Michael Trader was grateful for opportunity to discuss patient matching and patient identification in healthcare with Beth Just from Just Associates during John Lynn’s blab session earlier today. The discussion covered a wide range of topics including:
— How big is the patient identification problem in healthcare? — The continuing problem of duplicate medical records in healthcare and strategies to improve and sustain patient data integrity — Describing the availability and measuring the success of existing patient identification solutions in healthcare — Would a national patient identifier help or would the existing challenges still apply? — Why can’t the current solutions get to 100% patient matching? — How does the CHIME $1 million National Patient ID Challenge work?Is this challenge achievable?
What materialized was an excellent discussion on patient identification in healthcare with both Michael and Beth offering intelligent insight on the problems that exist, solutions built to address the problems, and what it truly means to achieve 100% patient ID accuracy. Take a moment to watch the blab session here:
The following post was submitted by Brad Marshall, Enterprise Development Consultant with RightPatient®
AHIMA Sheds Light on Patient Matching Problems in Healthcare
The American Health Information Management Society (AHIMA) released details of a survey yesterday that revealed over half of Health Information Management (HIM) professionals still spend a significant amount of time reconciling duplicate medical records at their respective healthcare facilities. The survey went on to reveal some very interesting statistics on patient matching and linking patient records, illustrating the burden that duplicate medical records have not only on HIM staff, but the dangers care providers face who increasingly rely on access to accurate, holistic patient data to provide safe, quality care. One particular stat that jumped out at us was:
“…less than half (47 percent) of respondents state they have a quality assurance step in their registration or post registration process, and face a lack of resources to adequately correct duplicates.”
A recent survey of HIM professionals by AHIMA illustrates the problems that duplicate medical records have on accurate patient matching in healthcare.
This is an area of particular concern due to the fact that our research has shown that many healthcare facilities spend tens, sometimes hundreds of thousands of dollars per year reconciling duplicate medical records but very few have technology in place to prevent duplicates in the future. It’s encouraging that accurate patient matching in healthcare seems to finally be getting the attention it deserves, due to the digitization of the industry, the shift change from fee-for-service to a value based payment system and a burgeoning healthcare ecosystem laser focused on improving both individual outcomes and population health. AHIMA’s survey supports this assertion by stating:
“Accurate patient matching “underpins and enables the success of all strategic initiatives in healthcare…”
Equally concerning is the fact that less than half of HIM professionals surveyed have any type of patient registration quality assurance policy in place and only slightly over half of survey respondents could accurately say what their duplicate medical rate actually is. Not to mention the fact that HIM professionals spend entirely too much of their time reconciling duplicate medical records, with 73% reporting that they work duplicates “at a minimum of weekly.”
As more healthcare organizations and facilities begin to understand that accurate patient matching has a major impact on other downstream activities, it is encouraging that the issue is finally getting the attention it deserves helped in part by the efforts of AHIMA, and CHIME’s national patient identification challenge which is scheduled to kick off this month. It’s clear that the healthcare industry is slowly coming to the realization that many new initiatives borne from the HiTech Act and Meaningful Use (e.g. – population health, ACOs, health information exchanges, interoperability) don’t really have any hope to succeed in the absence of accurate patient identification.
Duplicate Reconciliation Unnecessary Burden on HIM?
Early last year, we wrote a blog post on How Accurate Patient Identification Impacts Health Information Management (HIM) which highlights the exorbitant amount of time HIM spends reconciling duplicates and the opportunity cost this brings. For example, time spent on duplicate clean up and reconciliation could instead be allocated to coding for reimbursement and preparing, indexing, and imaging all paper medical records – a critical component in the effort to capture and transfer as much health data as possible to a patient’s EHR.
The fact of the matter is that as health data integrity stewards and medical record gatekeepers, HIM professionals are better served spending their time ensuring proper and accurate reimbursement and medical record accuracy then reconciling duplicates which should have never been created in the first place. HIM staff perform one of if not the most critical functions in healthcare by ensuring health data integrity, especially in light of the increasing reliance of often disparate healthcare providers need to access a complete medical record that includes as much information as possible.
As we noted in the post last January:
“…many hospitals have expanded responsibilities vis-à-vis Meaningful Use, EHR implementation, and meeting Affordable Care Act requirements, and it has become disadvantageous to continue devoting any time at all to duplicate medical record and overlay reconciliation. Biometric patient identification solutions open the door to re-allocation of HIM FTEs to more critical functions such as coding, reimbursement, and reporting. Simply put, implementing biometrics during patient registration is opening the door for HIM departments across the industry to provide a larger and more productive support role to meet the shifting sands of reimbursement and address the need to move towards quality vs. quantity of care.”
Conclusion
We could not have summed up the issue of duplicate medical record creation and reconciliation and inaccurate patient matching in healthcare more succinctly than this quote from AHIMA in the survey summary:
“Reliable and accurate calculation of the duplicate rate is foundational to developing trusted data, reducing potential patient safety risks and measuring return on investments for strategic healthcare initiatives.”
Trusted data. Isn’t this the backbone of the new healthcare paradigm? Certainly we can’t expect to achieve many of the purported advances in healthcare in the absence of clean, accurate health data. It’s time to eliminate duplicate medical records forever, and establish cohesive, quality assured patient matching in healthcare.
What are your biggest takeaways from the AHIMA report on accurate patient matching in healthcare?
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.
https://www.rightpatient.com/wp-content/uploads/2016/01/HCCH-medical_records.jpg600800John Traderhttps://www.rightpatient.com/wp-content/uploads/2021/04/RightPatient-Logoup.pngJohn Trader2016-01-07 16:31:582021-06-30 14:19:26AHIMA Survey on Patient Matching Illustrates HIM Burdens, Frustrations
Hugh Chatham Memorial Hospital recently used photo biometrics to prevent healthcare fraud.
One form of healthcare fraud seen in emergency departments at hospitals around the country is individuals attempting to commit identity theft in order to obtain prescription medication. With approximately 8.76 million people in the U.S. abusing prescription medicationand the lion’s share of those medications coming from a doctor’s prescription, medical facilities are proactively stepping up their efforts to implement stronger patient identification safeguards to ensure that the problem is addressed. After all, many patients may not understand the health dangers and risks of someone stealing your identity and inaccurate health data being attributed to your medical record – it is extremely dangerous and could result in serious injury, even death should a clinician act on incorrect protected health data (PHI) in your medical record.
Just how bad is the problem of prescription drug abuse in the U.S.? Consider the fact that every day in the United States, 44 people die as a result of prescription opioid overdose. Fortunately, there are tools available to catch identity fraud at the point-of-service in hospitals before harm is done.
Using Photo Biometrics to Deter Healthcare Fraud
Hugh Chatham Memorial Hospital implemented the RightPatient® patient identity management solutionusing photo biometrics to help support patient safety, eliminate duplicate medical records, and prevent and deter medical identity theft. Recently, a patient arrived at the Hugh Chatham Memorial Hospital emergency room seeking treatment for an injury that according to the patient had just occurred in the prior hour. The patient signed in under a fraudulent name, date of birth, address, invalid marital status, a disconnected phone number, invalid employment status, fraudulent emergency contact, and an invalid social security number. The patient proceeded with registration, and signed all admission paperwork under the fraudulent information.
Hugh Chatham Memorial Hospital recently used photo biometrics to prevent healthcare fraud.
During the registration process, the registration clerk used the RightPatient® photo biometrics solution to enroll the patient since this was (according the patient) the first time they had ever been to the hospital. The RightPatient® system worked just as it was designed, sending the registration clerk an alert that indicated the patent had been previously enrolled and that their biometric credentials had already been linked to another unique electronic medical record, providing the medical record number the patient had been registered under.
The clerk was then able to access the medical record the patient had been previously registered under and after review, Hugh Chatham was able to see other visits for that same day in other clinic/practice locations. A decision was made to contact local authorities.
Thanks to the RightPatient® software and the efforts of this staff member, Hugh Chatham Memorial Hospital was able to securely identify the patient, avoid duplicate medical records, prevent identity theft and associated healthcare costs, and help maintain a safe environment for patients.
Conclusion
Encouraging healthcare facilities to implement safeguards that ensure accurate patient authentication through technologies such as photo biometrics has been our mission since we founded RightPatient®. We will continue to share our success stories with others to help educate and inform in the overall effort to remove fraud and increase patient safety in healthcare.
Have a story on how the use of biometrics prevented a potential case of healthcare fraud? Please share it with us in the comments!
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:
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.
https://www.rightpatient.com/wp-content/uploads/2015/10/Wireless-biometric-patient-identification-devices-improve-patient-safety.png422615John Traderhttps://www.rightpatient.com/wp-content/uploads/2021/04/RightPatient-Logoup.pngJohn Trader2015-10-21 15:29:582020-08-10 09:43:22Improving Mobile Patient Identification with Wireless Technology
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.
https://www.rightpatient.com/wp-content/uploads/2015/10/RightPatient-can-save-hospitals-millions-with-accurate-patient-identification.jpg445800John Traderhttps://www.rightpatient.com/wp-content/uploads/2021/04/RightPatient-Logoup.pngJohn Trader2015-10-01 21:03:382021-06-25 11:35:31Improving Revenue Cycle Management with Accurate Patient ID
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.
https://www.rightpatient.com/wp-content/uploads/2015/09/One-to-many-biometric-patient-ID-systems-are-the-only-way-to-prevent-duplicate-medical-records.png250650John Traderhttps://www.rightpatient.com/wp-content/uploads/2021/04/RightPatient-Logoup.pngJohn Trader2015-09-23 17:19:362020-08-10 09:55:51The Difference Between 1:N, 1:1, and 1:Few and Why it Matters in Patient ID
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!
https://www.rightpatient.com/wp-content/uploads/2015/08/free-webinar-2.jpg445800John Traderhttps://www.rightpatient.com/wp-content/uploads/2021/04/RightPatient-Logoup.pngJohn Trader2015-08-25 16:52:312021-06-25 10:29:03Free Webinar: The State of Patient Identification in Healthcare
The explosion of mHealth apps and patient portals for PHI access demands more modern patient and clinician identification technologies than user names and passwords.
The following guest post was submitted by Michael Trader, President and Co-Founder of RightPatient®
The rise of digital health tools for PHI access
Encouraging patients to take a more active and engaged role in their healthcare has been a key focus of healthcare providers in the wake of Meaningful Use requirements. What began as an industry mission with specific benchmarks and goals has since manifested into the actual use of myriad digital tools and platforms that are educating, engaging, and working to empower patients to increase accountability and responsibility for their own health and, when applicable, the health of their families. In fact, a recent HIMSS survey on how mobile apps and portals improve patient engagement indicated that on the provider side:
73% of organizations used app-enabled patient portals to increase consumer participation in their overall health and wellness goals as well as meet relevant Stage 2 and Stage 3 Meaningful Use requirements under the Medicare and Medicaid EHR Incentive Programs.
Nearly half of those polled stated that “implementation of mobile services for access to information is a high priority at their organization.” Additionally, more than half – 57 percent – indicated that their facility implements a mobile technology policy, which often has a focus on mobile health security capabilities.
About one-third of polled healthcare organizations stated that they provide “organizational-specific apps” to the patient community.
One important facet in the goal to improve patient engagement is providing easier and faster access to personal health information (PHI). Manifested through Meaningful Use Stage 2, the benchmark is stated as:
The idea is for healthcare providers to reach beyond traditional means of accessing PHI (think in person visits) and adopt digital health tools for easier, faster, and more convenient ways of accessing this data (think patient portals and provider mHealth apps). In concept, increasing the availability of tools and platforms to access PHI is a good thing — it caters to increasing patient demand to offer greater PHI accessibility through resources that offer more convenience and are in lockstep with the rise of the digital health movement. However, the explosion of digital tools for PHI access carries an inherent risk that patient identities will be compromised, stolen, or shared leading to a sharp increase in fraud and medical ID theft that poses a direct threat to not only patient safety and provider medical error liability, but also to the rising cost of healthcare. Not to mention the fact that the rising use of digital tools to access PHI compromises patient data integrity which is critical to maintain because of the ripple effect it has on the ability to provide accurate care along the continuum and the confidence it represents to successfully participate in health information exchanges (HIEs).
Keep in mind that each time a perpetrator commits healthcare fraud or medical ID theft, the fallout of legal fees, settlement costs, and expenses to restore an identity are passed down to ALL patients in the form of higher fees for medical services. Therefore, collectively there is a pressing need to ensure that adoption of stricter and more secure methods of patient identification must run parallel to the rise in digital tools and platforms for safe access to PHI. Otherwise, patients may not be as willing to use these tools for fear of medical ID theft or unlawful access to their PHI data which directly compromises their safety, security, and privacy.
Monetary damages are only the tip of the iceberg for healthcare organizations when discussing the impact of fraud and medical ID theft. It was been well documented that reputation can be negatively effected when patients perceive or a data breach confirms that healthcare providers are not taking the necessary action to increase PHI access security.
How can we correlate an increase in quality patient engagement with secure PHI access? Patient engagement is, without a doubt, a key linchpin to the success of healthcare’s triple aim. Simply stated, it is not possible for the healthcare industry to achieve the goals of lower costs, an enhanced patient experience, and improving population health in the absence of strong and sustainable patient engagement.
Securing PHI access for higher levels of patient engagement
Scour the internet for articles that cover patient willingness to use digital health IT tools to access PHI and you will discover that despite the industry wide effort to adopt tools that provide more convenient and faster access to medical data, few patients are actually doing so. In fact, a recent survey revealed that just 21% of respondents said they use the Web to access their health data. Meanwhile, 10% said they use e-mail and 40% view the data in person.
The reason behind patient unwillingness to use mHealth tools and portals for PHI access runs the gamut from dissatisfaction with mobile health applicationsto challenges in finding and using instructions, data inaccuracy, and device malfunctions or data syncing issues. Furthermore, issues related to poor mHealth app and portal securityhave hampered more widespread adoption of these tools and stoked patient fears that their privacy could be compromised by using them.
Setting aside those with opinions that privacy can never exist in the healthcare industry, the link between patient confidence and trust that their identities and PHI are protected when using mHealth apps or patient portals is palatable and has a direct effect on their willingness to use these tools as part of their overall care.
First, it’s important to distinguish the difference between “privacy” and “security” as it applies to healthcare data. HIMSS does an excellent job of breaking down the differences:
“Privacy” is the right of an individual to make choices with respect to the collection, use and disclosure of their data; “security” is the safeguards – physical, administrative and technological – used to protect the confidentiality, integrity and availability of the data. Because the challenges are many, there is a tendency to focus on “security” in mHealth. Patient privacy cannot be achieved without adequate data safeguards; however secure devices do not necessarily preserve patient privacy.
One of the largest impediments to widespread adoption of mHealth tools, portals, and other digital health platforms is inadequate mobile security policies that fail to take into account the necessity of adopting more modern patient identification tools that are commensurate to the data they protect. For example, most healthcare providers continue to use user name and passwords to protect patient identities when using mHealth tools and portals. While these may have once been permissible security protocols in the past, these identity verification methods are now considered antiquated and should be replaced. Even though user names and passwords have proven to no longer be secure enough to protect patient identities, almost all healthcare providers still rely on their use for mHealth apps and patient portals.
Secure PHI access requires modern patient and clinician ID technology
If healthcare providers expect patients to adopt mHealth tools and patient portals as a more convenient way to access PHI, the implementation of stronger and more secure identification technology is critical. Most healthcare security experts agree that due to the large amount of PHI data moving across provider locations via mHealth apps and patient portals, stronger security is needed to prevent data breaches if a patient’s identity is compromised. Plus, the increasing complexity of mHealth apps and their distinct ability to sync PHI data across multiple devices raises important questions about how to properly protect patient privacy to ensure HIPAA compliance for these new tools.
Securing PHI access is not limited to patient interactions with mHealth tools or patient portals however. A sound strategy to secure mobile and remote access to this sensitive data is required not only for patients, but also for any clinician that has access to mobile technologies. A 2014 HIMSS Analytics Mobile device study reported that:
…approximately one-quarter of US hospitals (28 percent) reported that smartphones are in use at their organization. On average, 169 devices are deployed per hospital. In comparison, 24 percent of US hospitals reported that tablet computers are in use at their organization, with an average of 37 devices deployed per hospital. (source – https://capsite.himssanalytics.org/assets/Uploads/2014-Mobile-Essentials-Brief-TOC12914.pdf)
Healthcare organizations must plan to implement a technology that has the flexibility to be used for secure patient and clinician identification, usually through a strategic combination of a strong single sign-on (SSO) platform to establish strict identification checks and provide a concrete audit trail of data access history with an enterprise-wide patient ID solution to secure remote access to PHI from mHealth apps and patient portals. The modern identification technology of choice for many healthcare providers to meet the rising demand for tighter security to access PHI is biometrics.
Lack of a strong PHI access policy can also have a negative impact on provider reputation. In a recent report on medical identity theft by The Ponemon Institute, 79% of patients surveyed said it is “very important” for healthcare providers to ensure the privacy of health records and allow them to have direct control of their health records.
Why biometrics?
The HIPAA Privacy Rule requires healthcare organizations to secure remote access to PHI data as a safeguard for patient privacy and to eliminate data breaches that can lead to fraud and medical identity theft. Once considered secure identification criteria, user names and passwords are now considered antiquated and unable to offer strong protection to secure PHI access largely due to the fact that:
Most patients don’t want to worry about memorizing a complex password and thus default to using a simplistic password that’s easily guessable.
Most patients use the same password for many accounts, resulting in one key that unlocks dozens (or hundreds) of doors.
Most patients don’t even keep their passwords in secret. Everything from Netflix accounts to bank accounts to web accounts to video game accounts are often shared between friends, family members, and even strangers.
The use of biometrics for individual identification poses a much more secure and flexible technology to address the pressing need for healthcare to adopt stricter PHI access security protocols. Why?
We have written extensively about the applicability of biometric patient identification to improve patient safety in healthcare. Biometrics relies on identifying patients and clinicians by who they are, rather than what they have (ID badges) or what they know (user names, passwords) which can be more easily stolen or shared. Biometric identification technology is a more secure method to identify patients in self-driven interactions by allowing them to use the camera or microphone on their smartphone or tablet and use facial or voice recognition biometrics for accurate authentication. Biometrics offers more flexibility and convenience because it has the ability to be implemented at patient touchpoints where user name and password entry would be cumbersome and inappropriate — home health settings for example.
The use of biometrics for identification also offers a concrete PHI access audit trail, a more accurate tracking mechanism than user names or passwords which can easily be shared and often skew analytics because it’s impossible to determine the actual individual using the credentials. This is important because litigation often relies on these audit trails used in the defense of medical identity theft or healthcare fraud claims.
Conclusion
Participation in portals and the use of mHealth and other mobile apps to access PHI is a key catayst to increase patient engagement in healthcare. Patients must have the confidence in their healthcare provider that their PHI is easily accessible and protected with the strongest authentication security on the market that ensures their privacy and safety. User names and passwords are no longer sufficient authentication credentials to meet the expanding need to offer a more flexible, scalable, and more secure identification technology for mHealth apps and patient portals.
Equally important is protecting clinician access to sensitive PHI data. Protocols must be implemented that abandon user names and passwords in favor of technologies such as biometrics that are more secure, less susecptible to being stolen or shared, and leave a concrete PHI data access audit trail.
Have questions about the use of biometrics for patient identification in healthcare? Feel free to leave a comment or question below.
