Blog Posts on Patient Identification in Healthcare

Is Petitioning Congress the Answer to Achieving Accurate Patient ID?

March 24, 2016/5593 views / 0 Comments/in BLOG, Comments On Recent Biometric News Stories, Health Care, Patient Identification, Patient Matching /by John Trader

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

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.

Latest Innovations in Technology and Data Tools in Life Sciences

March 22, 2016/3923 views / 0 Comments/in BLOG, Guest Blog Posts /by John Trader

The following guest post on data tools in life sciences was submitted by Daniel Lewis.

Elderly people have more and more trouble adjusting to the pace the world is changing. Even though it can be hard for our older demographic, it feels good when we can tell them that that same world that’s changing so fast, is changing for them as well. Today, there are many devices and apparatus that can contribute to something we call “aging-in-place.” What it means is that our oldest family members can spend their time at home for as long as they are medically capable. We’re here to take a look at some of the advancements made in the past couple of years when it comes to innovations in senior care technology and how we use them to make our eldest feel better and live more comfortable and care-free lifestyles.

BeClose

BeClose is an innovative online system that allows us to track our elderly’s daily house routine. Wireless sensors are put throughout the house to assure us that they are using the living spaces they are supposed to, be it because of their heart or feet, it’s important to take notice where they went, so that we can take better care of them. The sensors alert you via E-mail, phone or SMS if there are any disruptions.

Fitbit

Fitbit is a handy little gadget for our elderly (and even for us). It tracks how many steps we took at any moment, and it even detects stairs. Other than that it tracks calories, activity level, sleep quality and more. It’s a great way to keep tabs on our elect’s walks and grocery runs so that they don’t overdo it. As we’ve stated, this one is handy for everyone.

TV Ears

TV Ears is a tool that’s meant to help seniors hear the TV better. It looks like a pair of light-weight headphones, but in reality, it helps them during family sittings so that they can turn the volume to their desired effect while everyone else can set it to normal hearing volume. It’s easy to set up under the chin and it goes a long way in helping our elderly feel comfortable in family sitting but also hear everything like everyone else.

Telikin

Telikin is for the seniors who would like to go a step further and use a PC, but can’t quite get there. It’s a family computer designed with ease of use in mind, offering features such as picture albums, video chat, e-mail and other popular features that our elderly would like to have. It comes equipped with a touchscreen screen device so it’s easy for our seniors to get used to using it and passing some time.

TabSafe

TabSafe is a device that allows us to control the medicine administration to our elderly. The unit is capable of reminding of medicine, dispensing it when the time is right, alert about inventory information and other utility info and is accessible via an internet device. A patented design allows pharmacies to equip the unit with more medicine, and the access is impossible without a log-in. Placing it in a central part of the living area is a sure way for our senior to never lose sight of it and be sure to properly take medication when the unit dispenses it.
Technology is advancing at a really fast pace these days, and we’re not just referring to recreational gadgets and smart devices. Advances in the medical field, particularly in senior care, are currently helping caregivers provide better help for patients. From heart-monitoring devices to monitoring gizmos, there’s no doubt that families can look after their loved ones even from a distance.

As you can see, the 21st century has made it easier than ever for our seniors to spend time with their families instead of homes. With a few handy gadgets everyone can feel happy and satisfied knowing that their oldest relatives are close by and adapted to every need. Elder care is though, and given that most seniors want to live on their own for as long as possible, it is recommended for their kids to find a way and look after them anyhow. Technology is here to help, and out of a wide variety currently available, it’s very important to choose the ones that provide the best care for your aging parent.

By Daniel Lewis and Foresthc.com!

Patient Hand Hygiene Report Casts Shadow on Contact Dependent Biometric Patient Identification

March 16, 2016/7919 views / 0 Comments/in BLOG, Comments On Recent Biometric News Stories, Infection Control, Iris Recognition, Patient Identification, Patient Safety /by John Trader

Patient Hands May Pose Greatest Threat to Hospital Acquired Infections

Is the heightened awareness on ensuring that doctors, nurses, and other clinical staff wash their hands as part of strict hospital infection control protocols missing an important element? According to a new research report published by NBC News, hospitals would be well served to address another important demographic inside a facility that could perhaps pose an even greater threat to patient safety: patients themselves.

A recent NBC news article reported that patients carry superbugs on their hands raising concerns about whether contact dependent biometric patient identificaiton solutions support hospital infection control.

Researchers at the University of Michigan released details of a report that found “nearly a quarter of patients they tested had some sort of drug-resistant germ on their hands when they were discharged from the hospital…” The results support the theory that many healthcare experts have long asserted – patients are a major threat to spreading the germs of superbug infections. Researchers tested for a number of bugs, and reported:

“We swabbed the palm, fingers, around nails of patients’ hands. The tests were done when patients were admitted, two weeks later, and then once a month for the next six months.” (Source: http://nbcnews.to/1Xv5Rck)

The report goes on to say that patients frequently bring multi-drug-resistant organisms on their hands to a hospital environment and drew the conclusion that this increases the probability that these organisms are likely to be transmitted to other patients and healthcare workers. A concluding thought of the report was:

“Despite concerns raised by some recent studies, patient hand-washing is not a routine practice in hospitals to date.” (Source: http://nbcnews.to/1Xv5Rck)

Patient Hand Hygiene Raises Concerns About Contact Dependent Biometric Patient Identification Solutions

As more hospitals investigate the use of biometrics for patient identification, they quickly discover that hardware options available include contact-dependent devices (fingerprint, palm vein) and non-contact devices (iris and facial recognition). Is it a healthcare organization’s responsibility to evaluate the hygiene risks of asking patients to physically touch a biometric device for identification? Do hospitals have an obligation to weigh the risks of hospital-acquired infections that could materialize from using contact-dependent biometrics for patient identification?

The NBC News report certainly calls into question the hygiene risks of deploying any type of technology solution that requires physical contact with a patient and could lead to the spread of germs and disease. Our hope is that hospitals assessing the use of biometrics for patient identification will take this into account and understand the risks involved when using contact-dependent devices and the responsibility to sterilize the device after each use if the decision is made to deploy this type of hardware.

There are many factors to consider when evaluating the use of biometrics for patient identification in healthcare. As we learned from the NBC News report, supporting hospital infection control to prevent the spread of germs and disease by using contactless biometric patient identification is important to consider.

Curious to know more about how to assess the differences in patient identification technology? Download our eBook for more details.

IntrepidNow Radio Discusses Current State of Patient Identification in Healthcare

March 14, 2016/5843 views / 0 Comments/in BLOG, Comments On Recent Biometric News Stories, Health Care, Patient Identification, Patient Safety /by John Trader

Delighted at the opportunity to discuss the current state of patient identification in healthcare with Joe Lavelle (@Resultant) from IntrepidNow Radio and Jared Johnson (@jaredpiano) today via blab. Joe and I had a lengthy discussion about patient ID in healthcare at this year’s HIMSS16 trade show and Joe was gracious enough to follow up our conversation with a formal blab session addressing the topic. Here is a brief summary of what we discussed today:

Joe Lavelle from IntrepidNow Healthcare Radio interviewed us during a blab session today to talk about the current state of patient identification in healthcare.

How does RightPatient® serve its customers?
Clearing up some of the common misunderstandings about the use of biometrics for patient identification in healthcare.
What is the current state of the patient identification market? What are the leading technologies? What are the key issues? How are customers deploying patient ID solutions?
Are their privacy issues related to implementation of patient identification solutions?
A recent guest on my show, a telemedicine company CEO, told Joe that his largest competition is the status quo. Is that also true for RightPatient®?
Information on CHIME’s National Patient ID Challenge launched in January.
What can we expect from RightPatient® in 2016?

Grateful for the chance to talk about this critical issue in healthcare and offer insight on solutions and initiatives underway. It was an excellent discussion and we were able to touch on a number of issues affected by inaccurate patient identification including: medical identity theft/healthcare fraud, duplicate medical records/overlays, identifying patients at new touchpoints along the care continuum, the advantages of using photo biometrics for patient ID, the culture of patient ID, patient privacy, and more!

Here is the blab session in its entirety:

Thank you to Joe Lavelle and Jared Johnson for their time today! Stay tuned to the “Resources” section of our Web site for future podcasts, blab sessions, and video interviews.

Takeaways on Biometric Patient ID from HIMSS 2016 Conference

March 9, 2016/7844 views / 0 Comments/in BLOG, Comments On Recent Biometric News Stories, Events/Conferences, Health Care, Infection Control, Iris Recognition, Patient Identification, Patient Matching, Patient Safety, Revenue Cycle Management /by John Trader

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:

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.
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.”
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.
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.
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:

The healthcare industry is slowly shifting from credential based to identity centric patient ID.
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.
198,000 deaths annually can be contributed to patient misidentification.
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?

Achieving Higher Patient Data Integrity Requires a Multi-Layered Approach

February 15, 2016/7414 views / 1 Comment/in BLOG, Data Integrity, Patient Identification, Patient Matching /by John Trader

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.

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.

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?

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

5 Big Indicators You Should Replace Your Revenue Cycle Management Solution

February 11, 2016/4981 views / 0 Comments/in BLOG, Guest Blog Posts, Revenue Cycle Management /by John Trader

The following guest post was submitted by Eugenia Lin.

If you saw a friend using a computer still running on Windows XP, your immediate reaction would be to ask why they haven’t updated to a newer operating system. XP is now 15 years old and Microsoft no longer provides technical support or security updates for it. Unless they really enjoy playing Solitaire and putting their data at risk, then there’s no excuse for having outdated software. The same reasoning applies to your revenue cycle management (RCM) system. Having an updated RCM solution will not only empower your staff, but also benefit your financial bottom line. Here are a few indicators that your RCM software needs updating:

What are some obvious signs that you need to upgrade your revenue cycle management (RCM) system?

1. Lack of business intelligence (BI) reporting and analytics
BI reporting is an incredibly powerful tool that allows one to obtain insights and identify trends on both a macro and micro level. For example, through macro level reporting a practice’s overall profitability can be reviewed. Then through the same interface, the data can be segmented further down to the profitability of all offered procedures. Easily accessing such information in a self-service manner not only shortens the decision making process but also excludes the need for outside consulting parties.

2. Unable to manage a growing or a multi-clinic practice
If your RCM system isn’t scalable or doesn’t offer customization for medical specialties, then it is time to look for another solution. There are systems available that are able to manage a solo provider, a multi-clinic practice, and anything in between. The benefit of this, is that a business manager can oversee and administer at any level easily.

3. Fails to manage and facilitate the entire claims process
It is essential that your RCM system be capable of managing the claims process from start to finish. Starting with claims from scrubbing to prevent coding errors and typos, as human error is one of the most common causes for payment denial. Your RCM system should also provide snapshot reporting, allowing you to monitor outstanding claims and categorizing them by where in the process they are. It should also provide alerts on claims that need following up on, so that none fall through the cracks.

4. Doesn’t fit into current workflow
Another clue that your RCM solution needs replacing is when it’s impeding your practice’s efficiency. Current RCM systems contain tools and features that improve workflow and staff productivity. RCMs can instantly verify insurance eligibility directly through the user interface, allowing your staff to focus on other tasks and avoid wasting time navigating through an insurance provider’s automated phone system. They can also easily manage payment reminders and follow-ups through automated texts or emails.

5. Doesn’t provide important features or cannot integrate with other systems
Having an RCM system able to seamlessly cooperate with your practice’s other system can be greatly beneficial. For instance, when integrated with an EHR system, the claims process becomes even more automated and less prone to errors. As forms can be auto filled with data from a patient’s file, versus a staff member having to manually fill the forms while referring to a paper chart or a separate note taking system.

Eugenia Lin avidly enjoys writing about a variety of topics and currently writes on behalf of the revenue cycle management experts at OmniMD. When not writing, she can be found spoiling her pet, Yeti, with treats or trying to be active outside on those typical Seattle rainy days. You can find her at LinkedIn.

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

February 9, 2016/5911 views / 0 Comments/in BLOG, HIM, Patient Identification, Patient Matching, Podcasts /by John Trader

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!

IntrepidNow Healthcare Podcast Highlights Patient Identification in Healthcare

February 1, 2016/6262 views / 0 Comments/in BLOG, Data Integrity, Future of Biometrics, Iris Recognition, Patient Identification, Patient Matching, Podcasts /by John Trader

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.

Healthcare Scene Blab Tackles Patient Matching and Patient Identification

January 25, 2016/5813 views / 0 Comments/in BLOG, Health Care, Patient Identification, Patient Matching /by John Trader

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.