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Is Petitioning Congress the Answer to Achieving Accurate Patient ID?

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Hat tip for the recent efforts by the American Health Information Management Association (AHIMA) to launch a petition drive that will move Congress to lift the federal legislative ban that has prohibited the U.S. Department of Health and Human Services (HHS) from participating in efforts to find a patient identification solution. It’s a noble effort and adds fuel to the hot fire burning in the industry to solve the persistent and dangerous problem of achieving accurate patient identification in healthcare. We understand that the effort to improve patient identification in healthcare has many downstream benefits to the entire industry including (but not limited to):

— Revenue cycle management
— Patient safety
— Health information exchange
— Population health

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AHIMA’s efforts to petition Congress to life the federal moratorium on funding research on developing a national patient identifier may not do much to adequately solve the problem.

The fact that organizations with the clout of AHIMA and CHIME have contributed their powerful voices to the battle of improving patient ID in healthcare is advantageous to the end goal of finding a universal solution that can be adopted collectively throughout the industry. AHIMA and CHIME’s efforts are working to garner more attention to the persistent patient matching problem in healthcare and sparking more discussions about how to solve the problem. Often relegated as a back seat initiative in favor of other healthcare technology initiatives (e.g. – ICD-10, EHR implementation, interoperability), we have always believed that improving patient identification in healthcare should be higher on the priority list.   

AHIMA’s initiative has merit, but is advocating the use of a credential predicated on the concept of presenting something you have or know the answer to solving the patient identification problem in healthcare? One of the reasons that the healthcare industry has struggled with accurate patient identification is that legacy methods of identifying patients have proven to be easy targets to exploit. Human identification generally falls into three distinct categories:

  • “What you know” – address, phone number, date of birth
  • “What you have” – insurance card, driver’s license, passport, government issued identity
  • “Who you are” – biometrics

Traditional identification methods generally rely on asking a patient what they know or what they have but we already know that these are frequently abused and easy sources to commit fraud. Just look at the continued rise in cases of medical identity theft at the point of service – an estimated 2.3 million Americans or close family members had their identities stolen during or before 2014, and a large number of these cases involve family members stealing or sharing medical insurance credentials.

In geographic locations throughout the country where a large percentage of the patient demographic may share similar names, providing a false name or multiple variations of a name at the point of service in order to defraud the system is common. An example widely used throughout the industry to illustrate this is the Harris County Hospital District in Houston where among 3.5 million patients, there are nearly 70,000 instances where two or more patients shared the same last name, first name and date of birth. Among these were 2,488 different patients named Maria Garcia and 231 of those shared the same birth date.

In geographic locations throughout the country where a large percentage of the patient demographic may share similar names, providing a false name or multiple variations of a name at the point of service in order to defraud the system is common. An example widely used throughout the industry to illustrate this is the Harris County Hospital District in Houston where among 3.5 million patients, are were nearly 70,000 instances where two or more patients shared the same last name, first name and date of birth. Among these were 2,488 different patients named Maria Garcia and 231 of those shared the same birth date.

Pushing Congress to lift the federal moratorium on funding research on developing a national patient identifier may lead to a solution that requires patients who opt-in to bring this credential with them when seeking medical treatment. In the absence of incorporating an additional identification credential that relies on “who you are,” simply creating another individual authentication credential that relies on “what you know” or “what you have” leads us down the same path of abuse and fraud. After all, in theory the national patient identifier would be similar to a social security number or other credential that is subject to being stolen, shared, or swapped just like current methods of identification. Do we really want to allow this to happen? Seems as if this solution would be the equivalent or rearranging the deck chairs on the Titanic. 

Moving forward, the smarter way to solve the identification crisis in healthcare is to adopt technology that identifies patients by who they are, or some sort of a combination of what you have or what you know with who you are. For example, the use of biometrics for patient identification – already a proven technology that patients accept and significantly reduces duplicate medical records, overlays, medical identity theft, and fraud – would be a more sensible way to identify patients to alleviate the problems caused by misidentification. 

Lobbying Congress to lift the moratorium on funding research to develop a national patient identifier won’t solve the patient ID problem in healthcare unless the industry realizes that it must move away from antiquated identification methods that rely on what you have and/or what you know and instead shift to identifying patients by who they are. Unless this is part of the equation, healthcare will continue to spin it’s wheels in the effort to solve the vexing problem of how to achieve 100% accurate patient identification.

review of biometric patient identification educational session at 2016 HIMSS conference

Takeaways on Biometric Patient ID from HIMSS 2016 Conference

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review of biometric patient identification educational session at 2016 HIMSS conference
review of biometric patient identification educational session at 2016 HIMSS conference

Several educational sessions at the 2016 HIMSS conference were dedicated to patient ID in healthcare.

Like most who attended last week’s annual HIMSS conference in Las Vegas, I was a bit overwhelmed at the amount of information, activities, and traffic swirling around the Exhibit Halls and lecture rooms. It’s difficult to not get swallowed up among 40,000+ attendees and even more hard to block out the flashing lights and unbelievably cool technology on display in order to focus on what matters most, but I had a set agenda to follow and stuck to my plan. This was the third HIMSS conference I have attended and I continue to be amazed at the outstanding job that HIMSS staff does to pull off this event each year, which only seems to keep growing in size, scope, and complexity. Hat tip to HIMSS staff who work tirelessly on making this event successful!

Buried among the central themes of advancing interoperability, cybersecurity, population health, consumer and patient engagement, and connected health, there were a handful of educational sessions dedicated to patient identification in healthcare including a presentation by Dr. Raymond Aller, a Clinical Professor at the University of California entitled: “Patient Identification: Biometric or Botched?”

This was the only educational session at the conference that I could see which was 100% dedicated to the use of biometrics for patient ID in healthcare and it was well attended – I counted approximately 75 people who showed up for the session. 

Dr. Aller presented what I felt was a fair, unbiased analysis of the patient identification landscape in healthcare and a thorough analysis (including strengths, weaknesses, and deployment examples) of biometric patient identification modalities available to hospitals and health organizations. Here is a brief overview of Dr. Aller’s central themes, and what he presented:

  1.  Text based patient identification is simply no longer an efficient or safe way to ID patients: Dr. Aller began his presentation by listing the consequences of failing to properly identify a patient including the patient safety, legal, and liability issues and public relations nightmare misidentification can create. He then demonstrated the drawbacks and limitations of text based patient ID calling it “obsolete” and pointing out that in 2016, hospitals and healthcare organizations can no longer afford the risks associated with this form of identification. He even went so far as to question the viability of continuing to use a master patient index (MPI) as a patient data repository, calling it a “dangerous” and “obsolete” concept.
  2. Healthcare fraud and medical identity theft: Dr. Aller then explained the potentially catastrophic consequences of healthcare fraud, medical identity theft, and duplicate medical records from misidentifying a patient and the additional problems and risks that data merges pose stressing that too often, hospitals spend hundreds of thousands (sometimes millions) of dollars a year cleaning data and merging records without ever having the foresight to implement technology that will sustain patient data integrity in the future. Bottom line? Relying on names and dates of birth (“what you know”) and ID cards (“what you have’) to identify patients is simply no longer safe or sufficient. The patient identification industry is evolving to identify patients by “who they are.”
  3.  Biometric patient identification technology overview: The last third of Dr. Aller’s presentation centered on an overview of biometric patient identification technologies available including a detailed description of fingerprint, palm vein, and iris recognition (also referred to as “photo biometrics”). Although Dr. Aller left out some key points about these biometric patient identification modality options (for example, he did not mention the back end biometric matching technology behind each of these modalities and why this is important to understand), his review was fair and provided a relatively unbiased look at the strengths and limitations of using biometrics for patient identification. One interesting point that Dr. Aller made was the fact that in a clinical setting, the use of fingerprint and palm vein biometrics for patient identification creates questions about hygiene and supporting hospital infection control policies because a patient must physcially touch a device for identification – an attribute that is not a factor with iris recognition since it is contactless to the patient. 
  4. Conclusion: Dr. Aller concluded his presentation by further extolling on the strengths of biometrics for patient identification but cautioned the audience that biometrics are by no means a panacea due to select psychological, sociological, and physiological limitations. However, Dr. Aller did point out that his research indicated that when presented with the option of using biometrics to protect their medical identities and keep them safe throughout the care continuum, over 99% of patients opt-in to using the technology.
  5. Question and Answer session: Selected attendees asked some very interesting questions during the Q&A session including one woman from a neonatal hospital who lamented that it is very difficult to identify newborns with biometrics since neither palm vein or fingerprint biometrics can be used on children (photo biometrics can be used on any child 10 months or older). Another person asked what biometric technology could be used to verify patient identities over the phone when they call in requesting access to protected health information (PHI).

Several other educational sessions during HIMSS were centered on patient identification in healthcare with several common themes emerging:

  1. The healthcare industry is slowly shifting from credential based to identity centric patient ID.
  2. A central reason that more hospitals aren’t researching how to more effectively identify patients are competing priorities. Healthcare simply has to drop the “wait and see” attitude to more effective patient identification. 
  3. 198,000 deaths annually can be contributed to patient misidentification.
  4. Patient misidentification resulted in $77 billion Medicare and Medicaid fraud and improper payments.

If I had a crystal ball, I’d venture to say that patient identification will continue to be a hot-button topic in healthcare during 2016 and beyond, largely because so many other elements of care along the continuum are contingent upon it and so many back-end processes and functions (e.g. – revenue cycle management) depend on getting it right. 

What lessons did you take away from any of the HIMSS 2016 educational sessions dedicated to patient ID in healthcare?

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Achieving Higher Patient Data Integrity Requires a Multi-Layered Approach

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

Patient Data Integrity and Duplicate Medical Records

It is a well known fact that inaccurate or incomplete data within a patient’s medical record can be a catastrophic risk to patient safety, not to mention a serious hospital liability. As a result, many hospitals and healthcare organizations across the industry are closely examining the integrity of their health data and taking steps to clean it, most by using third party probabalistic and deterministic de-duplication matching algorithms (often directly from their EHR providers) that search and identify possible duplicates for an automatic or manual merge.

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Improving patient data integrity in healthcare requires a multi-layered approach that addresses both data matching and more accurate patient identification.

Several key players in the healthcare industry including CHIME, AHIMA, HIMSS, and major EHR providers are beating the drum to improve patient identification and patient data matching, all important catalysts for the push to improve patient data integrity.

If you are a hospital or healthcare organization that is knee deep in the middle of a health IT initiative to help increase patient data integrity (especially in the context of prepping for participation in a local or regional health information exchange), you may want to stop and reassess your strategy.  The rush to cleanse “dirty data” from EHR and EMPI databases is often addressed by relying on an EHR vendor’s de-duplication algorithm which is supposed to search and identify these duplicate medical records and either automatically merge them if similarity thresholds are high, or pass them along to the HIM department for further follow up if they are low. 

This could be a very effective strategy to cleanse an EMPI to ensure patient data accuracy moving forward, but is it enough? Is relying on an EHR vendor’s de-duplication algorithm sufficient to achieve high levels of patient data integrity to confidently administer care?  It actually isn’t. A more effective strategy combines elements of a strong de-duplication algorithm with strong patient identification technology to ensure that patient data maintains its integrity.

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Duplicate Medical Record Rates are Often Understated

The industry push for system-wide interoperability to advance the quality and effectiveness of healthcare for both individuals and the general population has been one of the main catalysts motivating healthcare organizations to clean and resolve duplicates but it also has revealed some kinks in the data integrity armor of many different medical record databases. Most hospitals we speak with either underestimate their actual duplicate medical rate, or do not understand how to properly calculate it based on the actual data they can access.  An AHIMA report entitled “Ensuring Data Integrity in Health Information Exchange” stated that:

“…on average an 8% duplicate rate existed in the master patient index (MPI) databases studied. The average duplicate record rate increased to 9.4% in the MPI databases with more than 1 million records. Additionally, the report identified that the duplicate record rates of the EMPI databases studied were as high as 39.1%.”

“High duplicate record rates within EMPI databases are commonly the result of loading unresolved duplicate records from contributing MPI files. EMPI systems that leverage advanced matching algorithms are designed to automatically link records from multiple systems if there is only one existing viable matching record. If the EMPI system identifies two or more viable matching records when loading a patient record, as is the case when an EMPI contains unresolved duplicate record sets, it must create a new patient record and flag it as an unresolved duplicate record set to be manually reviewed and resolved. Therefore, if care is not taken to resolve the existing EMPI duplicate records, the duplicate rate in an EMPI can grow significantly as additional MPI files are added.”

(AHIMA report, “Ensuring Data Integrity in Health Information Exchange”  http://library.ahima.org/xpedio/groups/public/documents/ahima/bok1_049675.pdf)

Clearly, the importance of cleansing duplicate medical records from a database cannot be understated in the broader scope of improving patient data integrity but relying on an EHR vendor’s probabilistic matching algorithm as the only tool to clean and subsequently maintain accurate records may not always be the most effective strategy. Instead, healthcare organizations should consider a multi-layered approach to improving patient data integrity beyond relying exclusively on an EHR vendor’s de-duplication algorithm. Here’s why.

Why Patient Data Integrity is a Multi-Layered Approach

Often not clearly explained to healthcare organizations, EHR de-duplication algorithms allow end users to set matching thresholds to be more or less strict, which comes with trade-offs. The more strict the threshold is set, the less chance of a false match but the higher chance of a false reject. The less strict the algorithm is set, the lower the chance of a false reject but the higher the chance of false acceptance.

Translation: Often times hospitals who say they have a low duplicate medical record rate might have a strict false acceptance rate (FAR) threshold setting in their de-duplication algorithm. That may mean that there could be a significant amount of unknown duplicate medical records that are being falsely rejected. Obviously, this is a concern because these databases must be able to identify virtually every single duplicate medical record that may exist in order to achieve the highest level of patient data integrity.

So, what can healthcare organizations do to ensure they are not only holistically addressing duplicate medical record rates, but also adopting technology that will maintain high patient data integrity levels moving forward? One answer is to implement a stronger de-duplication algorithm that has the ability to “key” and link medical records across multiple healthcare providers on the back end, and deploying a technology such as biometrics for patient identification on the front end to ensure that not only is care attribution documented to the accurate medical record, but a provider has the ability to view all patient medical data prior to treatment. 

For example, many credit bureaus offer big data analytics solutions that can dig deep into a medical record database to better determine what identities are associated with medical records. These agencies are experts in identity management with access to sophisticated and comprehensive databases containing the identification profiles for millions and millions of patients — databases that are reliable, highly accurate, and secure with current and historical demographic data.

Once data is analyzed by these agencies, they are able to assign a “key” to match multiple medical records for the same patient within a single healthcare organization and across unaffiliated healthcare organizations to create a comprehensive EHR for any patient. Offering a unique ability to augment master patient index (MPI) matching capabilities with 3rd party data facilitates more accurate matching of medical records across disparate health systems and circumvents the problem of MPIs assigning their own unique identifiers to individual patients that are different than unaffiliated healthcare organizations that have their own MPI identifiers.

Benefits of using a third party big data analytics solution that has the ability to “key” medical records for more accurate patient data matching at a micro level include:

  • More accurate identification of unique patient records resulting in a more complete medical record and improved outcomes
  • Prevention of duplicate medical records and overlays at registration reduces the cost of ongoing MPI cleanups
  • Medical malpractice risk mitigation 
  • Reduced patient registration times
  • The ability to more accurately link the most current insurance coverage patient information for more accurate billing

On the marco level, benefits include: 

  • Positive patient identification for eligibility verification, billing, coordination of benefits, and reimbursement
  • Improved care coordination
  • Information and record keeping organization 
  • Linkage of lifelong health records across disparate healthcare facilities
  • Aggregation of health data for analysis and research
  • Accurately aggregating patient federated data via a HIE

Conclusion

We have long championed the idea that improving patient data integrity can never be achieved in the absence of establishing patient identification accuracy or relying on EHR vendor de-duplication algorithms as the single resource to clean an MPI database. Hospitals and healthcare organizations that are truly committed to cleansing duplicate medical records from their databases and preventing them from reoccurring through more accurate patient identification must consider deploying stronger front and back end solutions that have the ability to more comprehensively identify and resolve these dangers to patient safety. Why not leverage the clout and reach of these big data analytics solutions to more effectively improve patient data integrity instead of putting all of your eggs in an EHR vendor’s de-duplication algorithm?

What other strategies have you seen as effective methods to increase patient data integrity in healthcare?

biometric patient identification prevents duplicate medical recordsDavid 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.

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New Podcast: The Impact of Duplicates and Overlays on Health Information Management (HIM)

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biometric patient identification solutions prevent duplicate medical records and overlays
biometric patient identification solutions prevent duplicate medical records and overlays

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!

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IntrepidNow Healthcare Podcast Highlights Patient Identification in Healthcare

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patient ID in healthcare podcast
patient identification in healthcare podcast

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
  • Updates on The College of Healthcare Information Management Executives (CHIME) national patient ID challenge
  • 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.

patient matching and patient identification in healthcare

Healthcare Scene Blab Tackles Patient Matching and Patient Identification

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patient matching and patient identification in healthcare
patient matching and patient identification in healthcare

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:

Special thanks to John Lynn and Healthcare Scene for hosting the discussion! 

What are your top concerns surrounding the issue of achieving 100% patient matching in healthcare? Please share them with us in the comments below.

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AHIMA Survey on Patient Matching Illustrates HIM Burdens, Frustrations

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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.”

Accurate-patient-matching-in-healthcare-through-reconciling-duplicate-medical-records

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 works for RightPatient - the industry's best biometric patient identification solution.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.

 

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RightPatient® Helps Hugh Chatham Memorial Hospital Fight Healthcare Fraud

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RightPatient-for-patient-identification-prevents-healthcare-fraud

Prescription Drug Abuse

Eliminating fraud is a pressing issue in healthcare that continues to threaten patient safety. The FBI states on their Web site: “With no signs of slowing down, healthcare fraud is a rising threat, with national health care expenditures estimated to exceed $3 trillion in 2014 and spending continuing to outpace inflation.” On average, healthcare fraud accounts for 10% of our nation’s annual healthcare expenditure.

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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 medication and 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.

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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!

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Improving Mobile Patient Identification with Wireless Technology

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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. 

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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:

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 works for RightPatient - the industry's best biometric patient identification solution.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.

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Improving Revenue Cycle Management with Accurate Patient ID

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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. 

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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.

RightPatient is a smart health platform thatJeremy 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.