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Hospital Readmission Prevention is a Must as CMS Fines Half of Hospitals

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The US healthcare system is in an unfortunate state – it just can’t seem to catch a break. While it was already coping with a number of issues – such as medical identity theft, the lack of price transparency, interoperability issues, and healthcare data breaches, among others – COVID-19 hit it hard. As a result, healthcare providers across the US are facing huge losses. With increasing COVID-19 cases across the States and with experts predicting even more during the fall, healthcare providers received yet another blow. CMS (Centers for Medicare & Medicaid Services) will fine about half of hospitals due to readmissions of Medicare patients, although this is for the pre-pandemic period and therefore COVID-19 cannot be held accountable for the lower payments. Let’s take a look at the numbers, how this will affect the hospitals further, and how hospital readmission prevention can be achieved with a proper patient identity verification platform.

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CMS will lower payments

While it’s already been quite a harsh year for healthcare providers, it’s about to get worse. Many caregivers are resorting to cost-cutting strategies by laying off employees, furloughing them, or even shutting down; however, the lowered payments will only add to the unprecedented costs.

Some numbers surrounding the penalties

During the fiscal year 2021, CMS will fine 2,545 hospitals due to increased Medicare patient readmissions that occurred within 30 days. The penalties were based on patient data ranging from July 2016 through June 2019. A staggering 83% of the hospitals received penalties, and they will be facing payment cuts as high as 3% per Medicare case during 2021. 39 caregivers will face the maximum penalty next year, which is an improvement over this year, when the number of hospitals hit with the maximum penalty was 56. However, with the pandemic disrupting everything, hospitals will lose more than ever. As a result, hospital readmission prevention becomes a topmost priority.

Why is the program important?

This is the ninth year of the Hospital Readmissions Reductions Program, and it has been created to improve patient care quality while lowering overall costs. As previously mentioned, it takes into account the readmissions of Medicare patients that occur within 30 days. While CMS is considering a suspension of the penalty program due to COVID-19, the penalties are still in effect this year.

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Some exceptions

Congress has exempted 2,176 hospitals out of the 5,267 from penalties due to a number of reasons. The hospitals exempted are either:

  • Critical access hospitals,
  • The only inpatient facility in the area,
  • Hospitals specializing in long-term care, children, veterans, or psychiatric patients.

What the industry thinks about hospital readmission prevention

While many participants within the US healthcare system have voiced disapproval regarding the penalty program, others have said that, while not perfect, the Hospital Readmissions Reductions Program is useful – it pushes caregivers to find innovative solutions to provide better quality care. 

The penalties will further increase hospital losses

Moreover, as healthcare providers are already facing huge losses due to the pandemic, they need to ensure hospital readmission prevention if they want to survive in the long run. Several hospitals are heavily relying on CMS reimbursements, and if they can reduce readmissions, it might help them survive the pandemic’s financial strain. By improving patient safety and quality of care, hospitals can significantly lower readmissions. Fortunately, RightPatient can help with that.

RightPatient enhances hospital readmission prevention

RightPatient has been helping leading healthcare providers with its touchless patient identification platform for years. It ensures improved healthcare outcomes by eliminating one of the most overlooked problems within hospitals: patient misidentification.

Patient misidentification leads to duplicate medical records and overlays, jeopardizing patient safety. Moreover, it provides the wrong medical records to caregivers, resulting in negative healthcare outcomes. Naturally, these are the patients who are readmitted within hospitals frequently. So, how does RightPatient help?

It locks the medical records of the patients using their photos during registration. Patients receive an SMS/email after they schedule appointments, and they are required to provide a personal photo and a photo of their driver’s license. RightPatient compares the photos for a proper match, eliminating any chance of misidentifications. All of this is done without requiring the patients to touch any foreign objects, eliminating infection control issues – something that is crucial during and after the pandemic.

Reduce patient readmissions, improve healthcare outcomes, and ensure patient safety with RightPatient – contact us now to learn how we can help you.

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Patient Data Accuracy is More Crucial Than Ever for Value-Based Care

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While the US healthcare system, as well as the entire world, is still facing the effects of the COVID-19 pandemic, the former has several issues not directly associated with the novel virus. For instance, the lack of price transparency, increasing healthcare costs, healthcare data breaches, medical identity theft, the lack of interoperability, and the lack of effective patient identification in hospitals are just some of the many problems that plague healthcare providers. While we’ve already covered many of the aforementioned topics, today’s focus will be on value-based care, some upcoming adjustments, and why accurate patient data is crucial for it.

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Value-based care in a nutshell

Value-based care is a frequently discussed topic within the healthcare space – it’s supposed to transform healthcare for everyone. While healthcare costs have been ever-increasing and accompanied by all-too-often poor healthcare outcomes, value-based care is thought to be the game-changer. Instead of focusing on the fee-for-service model, value-based care focuses on paying hospitals and physicians based on the patients’ health outcomes.

Due to value-based care, patients will experience lower costs and better healthcare outcomes, healthcare providers will experience better patient satisfaction scores and improved efficiencies, and everyone involved in the model will experience reduced costs and better overall results.

Value-based care has been heavily focusing on:

  • reducing price and providing transparency regarding it,
  • enhancing care quality by providing a competitive environment for caregivers,
  • pushing for enhanced interoperability to improve coordinated care.

However, value-based care will be focusing on more areas as it seeks to improve healthcare as a whole. Let’s take a look at some of the recent updates.

Some current updates regarding value-based care

Medicaid will finally be integrated into value-based care, according to Seema Verma, Administrator of the Centers for Medicare & Medicaid Services (CMS). Medicaid directors across the States have been sent letters including ideas that will help incorporate value-based incentives within programs. Moreover, CMS wants all public and private entities to participate alongside Medicare and Medicaid.

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The Center for Medicare and Medicaid Innovation (CMMI) was established to test alternative payment models. It created fifty-four models; however, only five of them demonstrated savings, and only three of them are applicable for national expansion. CMS is hard at work observing the data in order to mitigate these issues.

Being flexible regarding regulations might do the trick, as the CMS believes that the exemptions introduced during the pandemic might be offered within the models for more participants.

There are many other proposed changes as well as those already underway, along with what might be the future of value-based care. A more detailed explanation can be found here.

However, even when value-based care was introduced, one thing was certain – accurate patient data is crucial for it to work. Let’s take a look at why patient data will make or break CMS reimbursements that focus on such models.

Accurate patient data is required for value-based care

Since the focus of value-based care is better healthcare outcomes, providers need to ensure that the right patient is receiving the right treatment at the right time. However, if patient data is inaccurate, it will significantly degenerate healthcare outcomes. For instance, if a patient is misidentified during registration, that patient will be treated using someone else’s medical record – someone with different diagnoses, test reports, ailments, allergies, and so on. If one takes previous patient misidentifications into account, both the misidentified patient, as well as the record holder, have faced adverse health outcomes. Thus, patient data integrity must be maintained to ensure that the information is consistent, accurate, and useful. That’s where RightPatient can help.

RightPatient enhances patient data integrity

Right from the beginning, RightPatient ensures accurate patient data by eliminating patient misidentification, avoiding duplicate medical records, and preventing medical identity theft.

It is a touchless patient identification platform used by several caregivers such as Community Medical Centers, Grady Health, MediSys Health, and Catholic Health of Long Island. By using patients’ faces, RightPatient locks the medical records upon registration with their photos. While scheduling appointments, patients only need to provide a personal photo along with a photo of their driver’s license – the platform automatically verifies the photos to ensure a proper match.

Within healthcare facilities, patients only need to look at the camera – the platform verifies the identities to see if the patients are who they say they are, preventing patient misidentification, avoiding duplicates, and maintaining patient data integrity as well. All these lead to better healthcare outcomes, something which is crucial for value-based care.

Choose RightPatient now and enhance healthcare outcomes by ensuring patient safety across the care continuum.

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Reducing opioid abuse by knowing the right patient

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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.

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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 of 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.

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

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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.

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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.

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How RightPatient Prevents Chart Corrections in Epic and Other EHRs

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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.

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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.

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Value-Based Care: A Patient-Centered Approach Requires Knowing Your Patient

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Aspirin, penicillin, monoclonal antibodies, interventional cardiology, and genome editing have undoubtedly revolutionized medicine. However, while all of these have been breakthroughs in the field of medicine, not much has changed in the way that doctors do their jobs. Patients visit their doctors, the doctors diagnose, they recommend tests, they prescribe drugs, and they are compensated according to the volume of work done or the number of procedures performed.

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If medicine is to progress in the 21st century, things have to change at every level, including the way that doctors work and receive compensation, the way they identify the right patient, and the way that patients are treated.

The long-awaited system that is going to change the way doctors work and are compensated will soon become a reality. This new system is called value-based care.

Value-based care is about compensating doctors according to outcomes. This encourages more personal attention to patients and transitions the healthcare system from cure-based to preventive medicine. It is a system in which doctors receive a higher level of compensation for either better outcomes from procedures or enabling patients to avoid health-related problems altogether.

There are several benefits of a healthcare system where the right patient gets the right kind of care.

Value-based care can save patients a lot of money. Putting aside the historical projections of healthcare inflation, the U.S. is also facing major epidemics of chronic, non-communicative diseases like diabetes, high-blood pressure, and cancer. It is no secret that many of these ailments are preventable with timely intervention and/or the correct behavior. Value-based care creates an environment where doctors can help patients to avoid these diseases by intervening at the right time. A doctor would identify the right patient to design a prevention plan before a disease can manifest where things become more complicated and expensive.

Once the right patient, a patient with a high risk of developing a chronic illness, has been identified, the doctor would be encouraged to spend more time with her, teaching her to take better care of herself so that complications can be avoided. There would be a reward system for identifying the right patient and taking timely preventative measures. It would also result in higher patient satisfaction.

A value-based care system would also lower drug costs. Historically, manufacturers decide the price of their medications without taking into consideration the value that a particular drug has in terms of its effectiveness and overall patient wellbeing. A value-based system would also encourage the development of personalized medicine where treatment plans and even pharmaceuticals can be tailored to specific patient needs.

The backbone of the value-based care system would be patient identification and data mining. Many are already demonstrating why medicine should incorporate more data-based modeling to augment physician decision-making.  Data mining helps doctors and the healthcare industry as a whole to better understand the outcomes of various therapeutic approaches. Ultimately, it can help to create the right kind of individualized solution for the right patient.

Unfortunately, realizing optimal results from data mining and value-based care has its challenges, especially as healthcare organizations start mining data that has been accumulated over long periods of time. On average, at least 8% of hospital patient records consist of duplicate data. Thus, an intelligent way to sort out these duplications and identify the right patient is desperately needed.

It is stated that value-based care is about the right patient getting the “right care, in the right place and at the right time.” Instead, the maxim should be, “RightPatient® enables the right care, in the right place, at the right time.”

RightPatient® guarantees that a patient medical record is never mixed up with another record and the hospital ecosystem will always recognize the patient with the help of cognitive vision. Mistakes from common patient names, fraud, human error and other issues are always prevented.

As we all know, chains are only as strong as their weakest link. In many hospitals or medical institutions, there is an urgent need to strengthen this weakest link throughout the entire system – overcoming the errors of false identity and data duplication with RightPatient. Only then can the benefits of value-based care and data mining be fully realized.