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improving-patient-safety

Healthcare’s most significant issue- Improving patient safety

Whenever medical records do not match with patients and are out of sync, all kinds of problems occur for everyone involved, both physically and financially. Keeping this in mind, patient matching errors seem never-ending. Is there a solution? Is there anything which will help in improving patient safety?

improving-patient-safety

A look at what patient matching errors are capable of

Let us see an example to understand the gravity of the situation presented by patient misidentifications. In the year 2016, a mistakenly identified patient’s kidney was already taken out, and by the time the doctor realized that the patient had no tumor, it was already too late. This disaster had occurred due to mix-ups of test results of patients sharing the same name. This incident was kept under wraps until government officials looked into the issue to know precisely what happened, and it became public knowledge. However, most people, as usual, thought that this blunder was one in a million cases. It was a blunder; however, it was not one in a million cases- it is a common scenario.

Such phenomenons occur almost every day within any given healthcare provider, big or small, all over the US. The hospital personnel very casually presume the EHRs they click on are the accurate ones which include patient data like history, diagnoses, test results, and so on. This type of behavior is reckless and can result in grave consequences for the patients.

This is sadly the most overlooked but one of the most dangerous problems the healthcare industry faces- patient misidentification. It is the worst kept secret of the industry and has been the talk of the industry by many groups for years. Now, the question on everyone’s minds is what is being done for improving patient safety?

Problems associated with patient safety issues

The most common type of patient matching errors faced by healthcare providers occurs when two patients have the same name. For instance, Samuel L. Jackson, S. E. Jackson, Samuel Luis Jackson, and Sam Jackson may indicate the same individual, but inadvertently, or to save time by not searching for the proper record, the hospital staff may have made four individual records for the patient. To make matters worse, this may not even be known by neither the doctor nor the patient while making treatment plans. Such duplicate records can lead to grave consequences as well- if they get merged, can lead to wrong treatments, medications, and sometimes even removal of completely healthy organs like the example above.

According to a recent study, one EHR out of five in a single healthcare provider is a duplicate record. That is not all; the problem only gets worse when different organizations try to share these EHRs. Even when two separate organizations share the same EHR software, match rates are only around 50%.

Healthcare's most significant issue- Improving patient safety
Healthcare's most significant issue- Improving patient safety

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What other problems arise from patient matching errors?

It is not just about patient safety, although it is the biggest concern of inaccurate patient matching. It is one of the costliest mistakes for any given healthcare system, as each correction of the records costs from $1000 to a whopping $5000, depending on the severity of the issue. Thus, this is a multibillion-dollar problem in the healthcare industry. Also, if there have been cases of patient matching errors, some healthcare providers recommend another round of medical tests to be sure.

There has also not been any national patient identifier other than EHRs, which is the cause of the patient matching errors in the first place. The problem lies with the fact that the healthcare providers decide what kind of information they want to keep and what to omit, as these create fragmentations regarding patient data. In other developed countries, this problem is tackled by a unique patient identifier, such as a number, so that even if the patients are sharing commonalities, it will be canceled out by the number which is unique for each patient. Unfortunately, the USA is the only first-world country without such an identifier due to privacy concerns back in 1996.

What is the solution for improving patient safety?

Many healthcare systems have waited it out for a proper patient identification solution which will work towards improving patient safety, and it looks like it paid off. Many healthcare providers are using solutions like RightPatient. It is a biometric patient identification system which utilizes iris scanning. Well-known health systems like Northwell Health are already using it and are reporting promising results. Patients love it, as they do not need to carry any IDs. All they need to do is look at the camera and get their irises authenticated, and it pulls their medical data from their EHRs, it is that easy. All of this saves time in the patient identification process. Also, it is safe and hygienic, as no physical touch is required; thus, no risk of diseases via contact. Hundreds of health systems are using RightPatient and are reiterating the same thing- enhanced patient safety, better patient experience, and reduced denied claims.

patient-safety-issues

Patient safety issues occur due to misidentifications

When electronic health records (EHRs) were introduced, people lauded it as the next big thing in the technological landscape of the healthcare industry. There were many reasons- it was entirely digital as the name suggests, could be accessed quickly and whenever required, reduced paperwork, among many other reasons. However, once it was widely implemented, the reality was drastically different. Instead of solving these problems, EHRs added additional ones along the way- patient safety issues.

patient-safety-issues

EHRs have created many problems for patients and healthcare providers alike. They have created risks which were unpredicted at the time of their implementation, which can potentially generate the chance to make grave errors in the treatment processes for patients, specifically if the treatment involves medicines. If this seems terrible, it gets even worse. These problems associated with EHRs are much more catastrophic for children and younger patients since their prescribed drugs are age-based. A study has found that EHRs do not take age into account; thus, it does not tackle the problems associated in a pediatric environment. Other than that, patient safety issues like matching errors are synonymous with EHRs. This is where biometric patient identification systems like RightPatient come into play.

The problems healthcare providers face while using EHRs lead to misidentifications mostly. Some of the challenges EHR users face are:

  • Problems associated with displaying patient information, or incomplete/corrupt patient data
  • Issues related to patient data entries which cause delays
  • Problems with EHRs regarding feedback or notifications
  • Disruption in the workflow if data needs to be shared 

So what are the actual problems associated with patient safety issues caused by EHRs? 

Restricted information results in wrong medications

EHRs usually provide the hospitals with blank data fields which the latter can fill in, if required, regarding making notes making it easier for colleagues. However, they do not know whether their colleagues have access to those specific fields, which can create many problems. For example, if a doctor had made a note within the EHR regarding the medical condition of a patient, say glucose level, the nurse who will administer the medication may not be able to view this note because her access is restricted, not taking into account the medical condition. Such problems lead to a lot of medical complications. Likewise, if required fields are not available to be viewed by everyone in the hospital, the staff may get confused between patients with common characteristics like name, address, etc., causing patient matching errors.

A patient is provided with excess or wrong medication due to an entry error

This is the primary cause of confusing units- between imperial units and metric units. Thus, as it is common in the US to use pounds, and if the weight is entered in pounds, but the EHR accepts only kilograms, this will hamper with the medication. Medications are sometimes dependant on the weight, especially in the cases of children, and they may, unfortunately, receive larger doses of medicine than required, which can be fatal. Other than that, if a patient is misidentified, then this will cause the patient to receive the wrong medication as well.

Patient safety issues occur due to misidentifications
Patient safety issues occur due to misidentifications

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Missed doses of medications occur due to problematic information displays

EHRs can usually list all the medicines that have been scheduled for patients, along with time and dosage required. However, sometimes due to patient matching errors, they may end up with the medicines planned for some other patient, and this can be fatal for both the patients involved if someone is not cautious enough while administering the medications.

Duplicate patient IDs are created

By far, one of the most significant flaws of EHRs is consistent to this very day. News regarding patient matching errors are very common, and at least one person you know has faced it. How does it happen? Very simply- once a patient comes in and a hospital representative does not find the individual’s record in the EHR, the employee tries to save time by creating a new ID instead of searching more in-depth for the correct record. The staff thinks that this is the way to save time and effort but generates another source for losses by the employer. Sometimes even the patients are to be blamed- if they are not attentive enough while verification, the hospital staff may pick the wrong record for them. Its effects can range from being financial losses to even life-threatening. Due to this single issue, everyone involved with healthcare has suffered- patients, healthcare providers, insurance companies, and so on. Healthcare companies are now clamoring for a unique patient ID solution to eliminate these errors. 

Medical ID thefts take place

Another consequence of patient safety issues via EHRs- fraudulent activities. Addicts and professional thieves can very easily misuse others’ IDs and gain access to healthcare benefits or drugs which are entitled to the actual patients, resulting in financial losses incurred by the unfortunate patients. All this happens because there was no sure way to identify whether the medical record belonged to the perpetrator, until now.

What can be the solution to patient safety issues?

As seen from the problems, all of them point in one direction- patient matching errors. From all of this, patient identification error is seen as a disease in itself of the healthcare industry. Everyone involved is affected and suffers due to it in various ways and degrees. It is a multibillion-dollar problem in the US, where fixing a single entry costs from $1000-5000.

However, its days are numbered, it seems, as biometric patient identification systems like RightPatient are successfully eliminating it from the healthcare providers who use it. It uses iris scanning, which is easy and convenient for patients- all they need to do is look into the camera, and they are identified accurately. Another benefit of this biometric modality is that it also correctly identifies the irises of the younger patients as irises are formed within ten months of birth and remain unchanged. Patients also love it because there is no chance of getting any contagious diseases as it does not require physical touch. Over a hundred healthcare providers are using it, and they are reiterating the same thing- patient experience has improved along with patient safety due to the reduction of errors and the speed of the process.

patient-misidentification-cases

Patient misidentification cases are persistent as no industry-wide solution exists

Synchronizing medical information with the appropriate patients accordingly- how hard can it be, right? Well, it is precisely the opposite. It is easier said than done- patient misidentification cases are abundant. Since the introduction of electronic health records (EHRs), people thought that it would make the lives of everyone involved easier, but the reverse has happened. EHRs are filled with issues like misspellings, incomplete data, common names, outdated addresses, and so on, which overall leads to duplication of records. One of the consequences of all of this, according to a reputed organization, is the match rates being an average of 80%, sometimes even lower. It doesn’t sound all that bad, but it is the result obtained from the same healthcare provider the records have been created in! 

patient-misidentification-cases

One out of every five patients is likely to suffer from patient identification errors and become one of the many patient misidentification cases in the US. This is not the only problem, however. Patient matching errors are like a web created by spiders- trapping all the parties who are connected to patient identification- patients, healthcare providers, physicians, insurance companies, and so on. 

Patient misidentification cases are also synonymous with rising costs as patient misidentification is famous for being a persistent multibillion-dollar problem in the healthcare industry. A patient matching error costs a hospital around $2000, and if we look at the bigger picture, there are $1.5 million of denied claims for a single hospital in a given year. That is an outrageous amount of money which is completely wasted due to these errors.

As per the definition, patient matching refers to obtaining the accurate medical record for a given patient whenever necessary, to make informed decisions regarding the health of the patient. Healthcare professionals are frustrated that this is not what they experience whenever they are matching the patients with their records and are clamoring for something which will change the industry and generate accurate patient identification- something RightPatient is very good at doing. 

Let’s explore more in-depth into why patient matching errors occur. Patient matching is also reliant on the hospital employees who come into contact with it- they need to fill in the gaps for the new data, or else they might need to update changes in data like a surname, address, etc. to ensure accuracy. However, errors, in this case, maybe made by either the patient, the staff, or both. A patient might not be attentive and may not check whether accurate data has been entered; likewise, an employee may not check with the patient to ensure he has put in the correct data or not. They might think that it is not a big deal, but there lies the problem. Such inconsistencies which they believe are inconsequential lead to increased waiting times, worse patient outcomes, financial losses, wrong treatments, and sometimes even result in deaths. 

Patient misidentification cases are persistent as no industry-wide solution exists
Patient misidentification cases are persistent as no industry-wide solution exists

#1 Biometric Patient ID Platform

Superior flexibility, power & ROI

A reputed individual in the industry stated that to combat these errors, a lot of countries have switched to unique IDs for patients. Sadly, the US is not doing that yet, as it has no nationwide standardized patient identifier nor any effective strategy to do so. Thus, the responsibility is pushed onto the shoulders of the healthcare providers, each coming up with their own approach for identifying patients. 

A lot of suggestions have been made by experts to solve these errors, like software for patient identification, improvements in data standards, and ID cards, among many other options. However, the only one which is being pursued by many and used by early adopters are biometric patient identification systems. RightPatient is the most appropriate choice to eliminate patient matching errors. It uses iris scanning to ensure that the correct patient is identified, and it does so with ease, as reported by over a hundred healthcare providers who are using it. As it is using iris scanning, it is also hygienic and safe, as it requires no physical contact, and is convenient for the patients, as all they need to do is look into the scanner to match with their records. Since it is also less time consuming than traditional patient matching, it is lauded by many for improving the patient experience as well as patient safety. Patient matching has never been easier and more accurate, according to the users of RightPatient

patient engagement

Patient Engagement and Patient Experience help reducing hospital readmissions

Patient engagement refers to the concept of the patient’s behavior where he/she proactively participates with the healthcare provider, whereas patient experience is a concept which encompasses the range of interactions that patients have with the different tiers of the healthcare system such as interactions with doctors, nurses, and staff in hospitals, or basically the whole healthcare system. Some people use it interchangeably because both are linked together and are used towards achieving a common goal- reducing hospital readmissions.

doctor actively participating in patient engagement for reducing hospital readmission

Patient Engagement

Patient engagement is a concept which deals with patient activation, which is mostly empowering the patient so that the patient feels like they can take an informed decision about their healthcare to improve treatment outcome, lower costs, and also help provide more efficient patient care. This also rests in the hands of the healthcare system, as they are the ones who encourage patient engagement in the first place. There is also a framework for patient engagement, which is as follows:

  1. Shared Decision-Making Stage: In this stage, the patient is informed about his/her condition, and the patient participates in the decision-making process along with the healthcare provider. This approach is used mostly for patients whose situation is more preference sensitive.
  2. Patient Activation: In this stage, the patients are more aware and understand their situation as they know their condition. Research among 30,000 patients at Fairview health services in Minnesota suggests that patients with a lower level of understanding about their condition incurred 8% – 21% more costs in healthcare. Thus, this step of active involvement of the patient to treat their situation is the stage called patient activation. However, it does require the assistance of the healthcare systems, as they have accurate information regarding the patients.
  3. Broader Patient Engagement: This step is more about mass awareness creation and social interpretations of patient engagement. The concerned parties are to influence patient participation in such a way that it helps the masses; they try to educate the masses about their conditions so that they can make informed consensual decisions about their healthcare with respect to their healthcare providers.

Patient Experience

Patient experience refers to the number of interactions patients have with the healthcare system. It includes their care from health plans, and doctors, nurses, and staff in hospitals, physician practices, and other healthcare facilities. It is a core aspect of healthcare quality and is used to help measure a healthcare system’s ranking- the better the patient experience, the better the healthcare system, and vice versa. It also consists of components which patients value highly, like appointments, the hospital itself, the care they receive – basically everything associated with the healthcare provider. This is the basic concept of the patient experience. Healthcare providers use a combination of tools to enhance the patient experience. For example, to have an edge over other healthcare systems, many uses biometric patient identification like RightPatient, which matches the patient with their EHRs using iris scanning.

The link between Patient Engagement and Patient Experience

There are several factors which can interlink patient engagement and patient experience amongst them. A few are mentioned below:

  • Better patient engagement and experience lead to better patient satisfaction.
  • Better patient engagement and experience offer better value for patients’ money.
  • Better patient engagement leads directly to better patient experience.
  • Better follow up results in positive patient experience.
  • Patient engagement makes having a better patient experience more comfortable for the patient.
  • The liability of informed consent is divided between the patient and the caregiver, which affects the patient experience positively.
  • Better patient experience and better engagement go hand in hand in the financial aspects of the healthcare system as they help reducing hospital readmissions.
  • Patient Engagement and Patient Experience help reducing hospital readmissions

    Patient Retention App

    Retain patients, improve wellness, and keep your brand connected

Effects on the hospital readmission rate

  • Better engagement and experience relate to better reputation buildup of the hospital, which affects readmission rates by reducing hospital readmissions.
  • Better engagement leads to more effective treatment, which reduces risk-standardized readmissions.
  • Better overall patient experience will result in the patient choosing the hospital over other hospitals in case of another condition of him/her or a family member.
  • Better engagement and experience lead to patient satisfaction, which results in a reduction of risk-based readmissions and increases reputation-based readmissions.
  • With better patient engagement, patients are acquainted with the treatment plans and procedures correctly, which results in lowering risk-based readmission as well.
  • Involvement of the hospital staff leads to better mental satisfaction in the patient as well, which results in better word of mouth reputation, and also leads to more effective treatment, which helps in reducing hospital readmissions.

Many healthcare providers are very successfully providing both positive patient experience and increased patient engagement. For enhanced patient experience, RightPatient is the choice of many for biometric patient identification, which speeds up the overall process, helping the hospital staff to save significant time identifying the incoming patients so that they can put resources to better use in critical tasks. Patient engagement has a lot of tools, as well. However, the recent trend is to use apps like CircleCare, a patient retention app with a lot of benefits for both the patients as well as the healthcare systems. It can track steps, provide reminders regarding medicine, record glucose levels, blood pressure, as well as help the patients communicate with their healthcare providers. After the hospital subscribes to the app, the patient only needs to download it and use it, not only to communicate with their physicians but also for better health, which will help with patient engagement as well as provide better patient outcomes by reducing hospital readmissions, creating a win-win situation for all.

patient matching improvements

Hospitals are Prioritizing Patient Matching Accuracy

Patient identification has been haunting the healthcare industry since its inception. Using the existing practices in the industry, accuracy rates are significantly low and cannot be used to exchange health data effectively, as reported by officials from different healthcare systems such as hospitals and physicians. The industry is in dire need of patient matching improvement. 

patient matching accuracy

However, the above report is not the only one- other statements point towards the same conclusion of requiring patient matching improvement, as per the research brief from Pew Charitable Trusts. A study was conducted by Pew researchers along with Massachusetts eHealth Collaborative (MAeHC) that sought to identify the current situation of patient identification in the healthcare industry. They did so by collecting information from different healthcare executives with the use of interviews. Another aspect of the study was to identify how to achieve patient matching improvement. The sample of this study was healthcare experts and influential figures from various practices and sizes who served numerous patients in diverse regions all over the country.

A vast majority of the sample expressed the same view- patient identification and matching were quite inaccurate and desperately needs an overhaul, thanks to the increasing demand for interoperability.

Healthcare providers are now motivated to exchange more health data due to the recent CMS Promoting Interoperability program. That’s not all! CMS is also going to be granting incentives to accountable care organizations (ACOs) who will show savings through activities which support care coordination.

According to the Pew researchers, healthcare systems like hospitals and clinicians eligible for these programs need to exchange information with others so that all of the parties have the latest patient data from other various institutions.

Hospitals are Prioritizing Patient Matching Accuracy
Hospitals are Prioritizing Patient Matching Accuracy

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The hospital officials stated that it is quite challenging to measure the match rates, resulting in their efforts being ineffective to examine and improve the patient identification rates. They also had difficulty providing a number when asked for the identification rates within their organizations. This was because many hospitals only keep a record of the duplicates identified through EHRs, whereas others do not know which files are relevant and which are unlinked.  Thus, without knowing the actual number of correct matches, these healthcare systems cannot determine their match rates. Therefore, only the amount of misidentifications was provided by them, thus summarizing the research.

It was also identified that healthcare systems could easily match patient identities when asked by organizations they are in constant contact with. Both automated and manual processes are utilized to link records to the correct individual.

However, whenever it is an organization with whom the healthcare system is not in contact with regularly, match rates are inclined to be lower. This is because these unsolicited requests introduce more blockades because the healthcare system may not have a record of that individual, and the healthcare system uses automated processes for such applications. On top of that, the research also showed that urban areas require better identification rates compared to rural areas as not much-sharing activities take place in the latter.

Some healthcare executives also think that improved patient identification matching requires significant costs. However, many believe that biometric patient identification is the solution to improve matching rates and is worth the cost. Some hospitals are even utilizing iris scanning solutions like RightPatient to identify all their patients and pull their relevant data from their EHRs and show a significant change. They report that it is fast, accurate and improves the overall patient experience as well as speeding up the whole process and saving valuable time of the physicians so that they can concentrate on more critical tasks such as the patients themselves.

Scanning a patient for identification

Hospitals Need a Better Patient Matching System to Identify “John Does”

Patient identification or lack thereof is a topic which we hear about every day. We always read news about mistaken patient identities due to mix-ups, frauds, insufficient patient matching system, etc. What about those who arrive at the hospitals and are never identified? Let’s look at these John Does but from a different angle- from the perspective of the emergency hospital staff who receive and treat them rather than from the outside viewer.

Scanning a patient for identification

Imagine this: A man in his 50’s arrived in the emergency room, wheeled in by paramedics, shaven head, brown eyes, unconscious. To make matters worse, he had no materials on him that could have helped the staff with his identity for crosschecking with their patient matching system– no wallet, cellphone, papers, or anything at all. To top it all off, he did not have any distinguishing features such as a tattoo or scar. This incident was back in 2017- a car hit him in January, and he was rushed in with a fatal brain injury to Los Angeles County+USC Medical Center. He did not have any visitors, nor was he ever reported missing. Sadly, he passed away being a John Doe, no one ever knowing who he was.

This is just one example of how serious and pressurizing it is for the hospital staff to deal with such emergencies regarding patient matching systems, primarily when they consist of a John Doe. In these cases, they are required to become a form of detective in order to determine the identities of these unknown patients when they arrive at the hospitals. This is done for several reasons: firstly, finding the identity helps with the treatment- the staff can then determine the patient’s medical history and whether he/she has any complications or not. Also, it allows them to find and contact a next of kin or close one to make any critical decisions if it becomes necessary. The identity also helps the hospital to contact the insurance company or government health programs, whichever the patient is associated with, regarding payment of their services.

However, there is a catch- federal laws concerning privacy make it difficult for the hospital staff to determine the unknown patients’ identities. In the previously mentioned example as well as in many similar cases, the team along with the social workers frantically rummage through whatever a John Doe brings with him- bag, clothing, phones without passwords, receipts, or whatever piece of document or device which can help them identify the individual and proceed to their patient matching system. Their efforts don’t stop there- they also question the paramedics and dispatchers. Tattoos, piercings, and scars are duly noted, and when all else fails, dental records are checked against the individual. However, because the police can only access fingerprints, it is often left unchecked, mainly because the police only involve themselves only when a criminal element is present in the situation.

Hospitals Need a Better Patient Matching System to Identify “John Does”
Hospitals Need a Better Patient Matching System to Identify “John Does”

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These John Does are usually the ones hit by vehicles and had unfortunately left their IDs back at home, and can also be poor people with cognitive diseases such as Alzheimer’s. Other times, they are overdosed individuals. Unsurprisingly, socially isolated individuals like homeless people are the ones who are the most difficult to identify, and sadly, they are the ones who are the most common John Does in recent years.

The Health Insurance Portability and Accountability Act (HIPAA) was made to ensure the privacy of an individual’s medical data. However, in cases of these John Does, it can make patient matching increasingly difficult as the hospitals cannot release any information to those searching for missing family members regarding these patients. For instance, a patient with Alzheimer’s was admitted to a NY hospital with the name “Trauma XXX.” The police and his family members went in search for him several times at the very same hospital, but they were told nothing. Weeks later, a doctor while watching television saw that man in the news and identified him as the patient “Trauma XXX.” Afterward, when charged with why the hospital hid the patient, the staff said that they did not ask about “Trauma XXX” specifically.

Due to this incident, a lot of rules were set up and changed regarding information requests about missing persons. It consisted of following over twenty steps for hospitals, starting from notifying the reception, to taking DNA samples.

All of this could have been avoided if a fast, accurate, and reliable patient matching system was used. RightPatient is one such patient identification system that utilizes biometrics and AI. Through this, it uses iris scanning to quickly match the patients with their EHRs so that the whole patient experience can be enhanced. It also helps the physicians focus on more critical tasks such as the patients themselves instead of going through matching patients. Thus, not only is it beneficial for the patients, but it is also beneficial for the hospitals as well, creating a win-win situation for all and ensuring patient safety through the enhancement of the whole patient experience.

Statistics regarding how low HAC score reduces CMS and incurs loss

CMS cuts payments to 800 hospitals for patient safety incidents – is yours next?

Patient safety incidents should be taken seriously by all hospitals. Unfortunately, CMS is penalizing 800 of them for having the highest rates of patient injuries and infections. The agency will trim these hospitals’ Medicare payments in the fiscal year 2019.

The HAC Reduction Program is a Medicare pay-for-performance program that supports CMS’s long-standing effort to link Medicare payments to healthcare quality in the inpatient hospital setting. Put more simply, hospitals are offered a financial incentive for preventing harm to patients! Under the program, a hospital’s total score is based on its performance across six quality measures. Each year, Medicare cuts payments by 1 percent for hospitals that fall in the worst-performing quartile due to patient safety incidents.

It’s alarming that, according to Kaiser Health News, 110 hospitals are being penalized in the fiscal year 2019 for the fifth straight time. Considering the daily news announcements about hospitals that are suffering financially or have gone out of business, we wonder why they aren’t taking more steps to address this issue.

Statistics regarding how low HAC score reduces CMS and incurs loss due to patient safety incidentsIf you think that only small rural hospitals are facing this problem, you will be surprised. CMS recently threatened to terminate Vanderbilt’s Medicare contract after a fatal medication errorVanderbilt!

Since patients share common names and show up to the hospital many times without proper identification, 8-10% percent of the time their existing medical record is not found or they are potentially treated as a different person. This is a serious incident that can happen in every hospital at any time.

While the industry is going through serious financial pressure, I don’t think any hospital can afford to wait on this issue and get carried away with focusing solely on switching or upgrading EHR systems. Your hospital is just an event away from losing medicare payments due to patient mismatches. Someone can lose their life and the reputation of your organization will forever be tainted. That’s why many prominent healthcare providers have implemented our RightPatient biometric patient ID method to protect their patients and to protect themselves by preventing patient safety incidents caused by identification issues.

reducing-opioid-abuse-by-knowing-the-right-patient-rightpatient

Reducing opioid abuse by knowing the right patient

The US is enduring a massive opioid abuse epidemic. Not only are they widely prescribed, but prescription opioids are now more widely abused than street drugs. If we look at the anatomy of the opioid crisis, it is genuinely frightening. In 2016, 116 people died each day due to opioid overdose, resulting in more than 42,000 fatalities in a single year.

The question is, why is this happening? How are 11.5 million individuals misusing prescription opioids? How is it that each year, 2.1 million people misuse opioids for the first time? It seems that, at present, there is no clear path to stunting this epidemic. Opioid abuse is already costing the US economy more than half a billion dollars annually.

How did we get to this point?

Since the 1990s, the pharmaceutical industry started pushing opioids and assured doctors that these drugs were safe. Consequently, doctors began widespread prescription of these drugs. However, blaming the pharmaceuticals industry and doctors alone ignores many other pertinent factors.

There have been many changes regarding the prevalence of various diseases over the last three decades. Slowly and steadily, medicine has become dominated by chronic and painful health conditions. It is estimated that one-third or the U.S. population or 100 million Americans are living with a chronic and acute pain condition. Among them, one-fifth are living with moderate to severe pain. Considering these statistics, it follows that opioids would be widely prescribed. However, 8-12 percent of those prescribed opioids result in patients developing an addiction.

Opioid misuse is not just limited to those living with painful conditions. Many of the prescribed opioids end up in the wrong hands. Many addicted to opiates hide their identity or medical conditions and visit various clinics under different aliases. For doctors, it is challenging to identify the right patient.

How can we reverse the epidemic?

To bend the trend downwards, efforts must be implemented at every level. At the community level, we must educate the public and raise awareness about the health risks of opioid abuse. Policymakers should advance legislation to address the problem. Above all, there is a need to change the way medicine is practiced; healthcare providers must take higher precautions at the clinical level.

Clinicians cannot and should not deprive people in pain from drugs that can bring them needed comfort. However, big data and technology can assist them in differentiating between the right patient and the wrong one. This is where RightPatient can play a vital role. Powered by artificial intelligence, the platform can help clinicians to thwart medical identity fraud and ensure that a patient’s complete and accurate medical history can be retrieved.

By recognizing the correct patient, clinicians can better understand the validity of patient complaints along with a patient’s disease history. When and where was the patient last prescribed an opioid? Did the patient rightly identify himself/herself?

RightPatient can be one way to prevent opioid abuse.

RightPatient augments population health investments

How Can You Protect Your Investment in a Population Health Solution?

Healthcare in the U.S. is going to see a paradigm shift in the next five years that will move it from a fee-for-service (FFS) payment model towards a value-based model. Simply said, those who produce better results and improve patient quality of care at lower costs will reap higher dividends. This shift will require better use of technology and significant changes to many platforms and their capabilities, including more investment in big data, analytics, and patient matching systems. These investments in population health management technologies will provide the real-time information needed to make more informed decisions.

Population health solutions play a critical role in moving healthcare from a treatment-based to a prevention-based model. These platforms enable providers to better prepare for patient-reported outcomes, provide data regarding social determinants of health and activity-based costing, and match extracted data outcomes with the right patient.

Current state of U.S. healthcare

The U.S. spends more on healthcare per capita than any other nation in the world but fails to produce better results for life expectancy and other health outcomes. Moreover, U.S. taxpayers fund more per capita on healthcare (64%) than those in other countries, including those with universal health programs.

These facts suggest that encounter-based medicine might be contributing to sub-optimal results in the U.S. and there is a need for change. That change is prompting the rise of population health management and data analytics technologies.

The population-based model is based on aggregating patient data across various health information resources, forming a comprehensive, longitudinal health record for each patient, and leveraging analytics to produce insights that clinical teams can use to improve care and lower costs. In addition to health and financial data derived from electronic health records (EHRs) and medical claims, information such as a patient’s socio-economic status, personal support network, and habitat conditions can be useful in building preventative care strategies.

For example, a patient diagnosed as prediabetes would be classified as high-risk in an encounter-based model. However, this does not take into consideration the patient’s lifestyle and behavioral patterns. Many prediabetics can avoid developing diabetes by modifying habits such as diet and exercise. Patients who smoke, abuse drugs, or have a sedentary lifestyle are much more at risk of developing the disease. Identifying these genuinely high-risk patients requires access to accurate data that is linked to the correct record. 

Challenges in moving to a population health solution

At present, a tremendous amount of patient data is available but it is not unified – it exists within different institutions and across various platforms. Thus, the available information is very difficult to match with the right patient (if not impossible in some cases) and such data has little practical value. Population health solutions need a system that can match patients with their available data and provide information on the best recommendations for preventative care, helping to improve outcomes and save resources.

Therefore, the most important variable in extracting value from a population health solution is ensuring that a patient’s captured data is matched to the correct record. Better data warehousing and mining capabilities will serve no purpose if healthcare providers lack the ability to match the output with the right patient. At present, not only do patient identification issues exist within a single healthcare institution, but these issues become even worse when patient data is exchanged across multiple systems, with error rates rising to 60%.

Failure to properly identify a patient means loss of historical medical history, social indicators, financial information, medications, allergies, pre-existing conditions, etc. – vital information that puts the patient and healthcare provider at greater risk. These data integrity failures can significantly dilute the efficacy of population health initiatives.

In fact, the transition from fee-for-service to value-based healthcare is only going to work if healthcare entities invest in patient matching technology alongside their investments in big data and analytics platforms. These investments should go hand-in-hand since patient matching errors can have such a substantial impact on data quality.

Population health management is among the top six categories in healthcare that are attracting investments from venture capital firms. Other segments include genomics and sequencing, analytics and big data, wearables and biosensing, telemedicine, and digital medical devices.

Thus, the industry is investing in technologies that will play a significant role in value-based care and population health management. However, the success of any population health initiative depends on the right patient being identified every time so that medical records and the corresponding patient data are not mixed-up. Considering the data fragmentation that exists in healthcare and lack of standards around patient identifiers, AI-based systems like RightPatient® are the only way to ensure reliable identification of patients across various data platforms and maximized investment in population health management.

chart corrections impact healthcare data integrity

How RightPatient Prevents Chart Corrections in Epic and Other EHRs

I’ve visited enough of our customers to know that hospital emergency rooms and free-standing EDs can sometimes be chaotic environments. Unlike most outpatient registration areas, patients who arrive to the ED do not have scheduled appointments and often go through a triage process with a nurse where they are “arrived” within the electronic health record (EHR) system. This is essentially a quick registration that begins the documentation of a patient’s visit information on his/her medical record. Unfortunately, this process often results in what are known as chart corrections.

As one might imagine, a clinician’s primary focus is on the health and safety of the patient. Nurses that triage patients are trying to enter patients into the EHR system so they can receive the appropriate care as quickly as possible. Unfortunately, data entry errors during this process are commonplace. For example, EHR system users may create a “John Doe” or “Jane Doe” medical record if they cannot properly identify the patient. Or, users may mistakenly select the wrong record because it shares a similar name with the patient in need of care.

When EHR users select the wrong patient medical record, all subsequent information pertaining to that visit is entered into that record (sometimes referred to as a medical record “overlay”). This is a data integrity failure and results in data entry errors that need to be resolved with a chart correction. So, a chart correction in the Epic EHR or other EHR systems is the process of fixing a “wrong chart entry” or overlay record that was caused by a patient identification error.

Wrong patient, wrong record data integrity failures within the EHR system can have disastrous consequences. At best, the healthcare provider must spend internal Health Information Management (HIM) resources to perform chart corrections and resolve medical record overlays, costing $60-$100 per hour for an average of 200 hours per overlay record. At worst, wrong patient errors can affect clinical decision making, patient safety, quality of care, and patient lives. This is why organizations like AHIMA have strongly advocated safeguards that healthcare providers can use to prevent medical record mix-ups, improve data integrity, and reduce the risk of adverse events.

RightPatient® is the ideal safeguard to prevent wrong patient medical record errors and chart corrections within Epic and other EHR systems. The AI platform uses cognitive vision to instantly recognize patients when their photo is captured and automatically retrieve the correct medical record. This becomes a seamless module within EHR system workflows so there is no disruption to users.

Customers like University Health Care System in Augusta, GA are effectively using RightPatient® to reduce chart corrections in Epic. In fact, UH saw a 30% reduction in Epic chart corrections within months after implementing RightPatient®. 

Healthcare providers using RightPatient® to capture patient photos significantly reduce their risk of data integrity failures. This enhances patient safety and health outcomes while reducing costs – important goals in the age of population health and value-based care.