Addressing the Need for Better Patient Matching

An often overlooked aspect of healthcare is the administrative side of it. Keeping patient records organized and maintained is a critical role that can negatively impact patient care if mismanaged. Healthcare providers are constantly searching for ways to optimize patient record keeping, ensuring that records are stored, protected, and retrieved accurately. 

One way providers have found to optimize record storage is through telehealth platforms, in which patient health records are stored electronically. While this is highly beneficial in managing patient records, the healthcare industry still faces a serious challenge - inaccurate patient matching. 

What is Patient Matching? 


As a patient, it can be easy to forget about the behind-the-scenes in a hospital. When you enter and give your name, they simply have your medical records - it’s that easy! In reality, every time you enter a hospital or doctor’s office, patient matching occurs. Patient matching identifies and links a patient’s data within and across healthcare systems to create a comprehensive view of your health records. 

When your provider goes to retrieve your medical records, they rely on the accuracy of the patient matching system to provide them with accurate data. Patient matching is supposed to verify that the information associated with you as a patient is actually yours. If patient matching is inaccurate, your provider may retrieve data that does not belong to you, but another patient. It’s not hard to imagine how that could cause significant issues for not only you but other patients and the practice as a whole. 

As such, patient matching is a critical component of the healthcare industry’s health information technology infrastructure. Still, practices worldwide have yet to accomplish flawless patient matching, which is a significant problem in the healthcare industry. 


The Problem


Clearly, it is a major issue for healthcare practices if they cannot guarantee accurate patient matching. Inconsistent patient matching creates several problems for both patients and providers. Should a provider care for a patient based on inaccurate data, it poses a significant threat to the delivery of acceptable patient care, patient safety, and consequences for the practice as a whole. 

While a significant cause for inaccurate patient matching is a lack of standard data collection, human error also contributes to the problem. A small typo can create a domino effect of inconsistencies, making it challenging to verify patient information. One mistake in a patient’s name can also create duplicate records or incomplete records scattered between several names instead of one. Regardless of how the data became inaccurate, it has severe consequences for both patients and practices. 


Patient Impact


The most prevalent concern for inaccurate patient matching is patient safety. If a patient is treated based upon inaccurate, mismatched data, or incomplete data, it can significantly compromise their health and safety, leading to potentially fatal consequences. A patient’s health records include vital information such as previous ailments and procedures, allergies, and every other piece of information relevant to one’s health. If any of this information is excluded from a patient’s treatment, it could significantly compromise their health. 

Anytime a provider lacks information about their patient, they cannot make the best possible decision for care, creating a significant opportunity for error. This means that if patient matching is not entirely accurate, there is always a chance that patient data will not be complete or accurate, creating an ever-present threat of inaccurate or unnecessary patient care. 

One example of an error due to inaccurate patient matching could be a delayed diagnosis resulting from incomplete patient records. A more dire example would be wrongly prescribing a drug to a patient based on incorrectly matched files. With a sensitive condition or unknown drug history, such a mistake could be fatal. While it may seem that patient matching is merely an administrative issue, in reality, it is a drastic matter of patient safety. 


Practice Impact


While patient care and safety are always the top priority of providers, inaccurate patient matching also poses a risk to healthcare practices worldwide. Incorrect patient matching has a significant cost burden on the healthcare system each time an error occurs. Practices must sort data and identify patients with each patient they meet with, as they cannot rely on a patient matching system for accuracy. 

Furthermore, practices must shoulder the hefty costs of mistakes made due to inaccurate patient matching, which can add up significantly. Whether records are incomplete, duplicated, or completely mismatched, healthcare practices lose money to correct the data - or make up for inaccurate care if the mistake is not caught in time. For larger hospitals and practices, these concerns - both financial and safety - are amplified. So, if patient matching is such a prominent concern, why has no one found a solution yet? 


The Solution


There is no one solution to the patient matching crisis, but there are a few alternatives that could improve the accuracy of patient matching and thus patient care. In efforts to address the issue, leaders in the healthcare industry are considering these solutions. 


1. Entrust a Single Organization to Oversee Nationwide Patient Patching


One proposed solution to overcome the patient matching problem is to entrust a single organization to oversee patient matching nationwide. This solution is believed to eliminate the risk of duplicated patient records, as one centralized organization can verify all data. While this would likely reduce the number of duplicates, it may not completely improve accuracy. 

As a major contributor to inaccurate patient matching is system or human errors, these may not be eliminated just by leaving patient matching to one organization. Furthermore, it will take a considerable amount of time to determine or create an organization for this sole purpose and collect and verify patient data nationwide.


2. National Patient Identifier


Another possible method of improving patient matching is assigning a unique identifier, or a national patient identifier, to each patient. Such an identifier would likely be a series of numbers, similar to a social security number. This would replace the current system that uses a patient's name, address, or date of birth to identify them. 

While it is believed that this system would be more accurate than our current one, it does pose some risks. If a patient’s national patient identifier is compromised, it would then compromise their entire medical history and collection of health records. Furthermore, there is a risk that patients will receive the same number, creating the same problem being addressed. 


3. Encourage Patients to Use Technology to Match Records


Finally, perhaps the most feasible of possible solutions is to encourage patients to use technology to help match records. Many healthcare practices and patients today are already embracing telehealth solutions for their accessibility and convenience, ignoring the fact that it is an excellent means of storing and protecting patient data. 

If patients upload their health records electronically into their telehealth platform, it can help link them to their records more accurately. As patients have access to their complete records at all times, it is easy to ensure that they are accurate, complete, and up-to-date. As such, providers can easily access patient data through the same portal, confident that they are treating patients based on accurate information. Not only is this faster and more convenient than traditional means of record storing and retrieving, but it may offer the level of accuracy that can overcome the patient matching dilemma.


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About the author - Mircea Popa

Mircea Popa is the CEO and co-founder of Medicai. Mircea previously founded SkinVision, a mobile app designed to detect melanoma (skin cancer) through ML algorithms applied on images taken with smartphones. He believes that a multidisciplinary approach to medicine is possible only when everyone has access to a better way to store, transmit and collaborate on medical data.