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Keeping on top of the claims review game has never been as important as it is today. The RCM environment is fast paced and ever changing, making a regular program assessment of available resources imperative to ensure the CDI and HIM professionals reach optimal quality and revenue standards.
http://faircode.com/news/optimize-drg-validation-take-full-advantage-of-rcm-tools
As COVID-19 figures begin to rise again throughout the Southeastern US, hospitals are seeking new avenues for generating revenue. FairCode hospitals will generate much needed cash in light of the revenue challenges hospitals now face. Over the past 19 years, we’ve found most (if not all) hospitals aren’t fully compensated for inpatient services they provide. Often, engaging the right clinical case review tool can make all the difference in generating new revenue.
Source: Hospitals Generate Unexpected Revenue During COVID-19 | LinkedIn
FairCode Associates, LLC, the leading company in hospital DRG revenue capture, announces the formation of a specialized cash flow response team. The team brings years of operational experience to advise hospitals on profitability during the COVID-19 crisis. FairCode shared its COVID-19 response and implemented plan with its 91 hospital clients and is now expanding its program to hospitals at large. FairCode’s CEO, Lisa Boyce stated, “With the current environment of cancelled elective procedures and empty beds in anticipation of acutely ill patients, hospitals are facing reduced inpatient revenue.” She went on to emphasize, “The demand for increased cash flow and revenue is greater than ever and FairCode is here to help.”
Source: FairCode Announces COVID-19 Emergency Revenue Response Program
SARS-COV-2,the pandemic coronavirus that surfaced for the first time in China last year, is an equal opportunity invader. If you’re a human, it wants in. Regardless of age, race, or sex, the virus appears to infect people at the same rate. Which makes sense, given that it’s a totally new pathogen against which approximately zero humans have preexisting immunity.
23 & Me launched a new study intended to illuminate any genetic differences that might help explain why people who’ve contracted Covid-19 have such varying responses to the infection.
Source: Why Does Covid-19 Make Some People So Sick? Ask Their DNA | WIRED
U.S. hospitals are battling Covid-19 on many fronts: Scrambling to create new intensive care unit beds, trying to secure scarce medical equipment to protect their patients and their workforces, training staff on novel treatment protocols, and hiring more nurses. In order to divert resources to the patients in the greatest need — and to protect the safety of the patients who can wait — hospitals are also postponing non-emergency care, cancelling elective procedures and, in general, halting the very activities that used to keep them in business.
The Centers for Medicare & Medicaid Services (CMS) has selected more than 200 emergency transport providers to participate in its Emergency Triage, Treat and Transport (ET3) model — a new payment model that leverages mHealth and telehealth to reimburse Medicare-enrolled ambulance providers that triage 911 calls, according to mHealthIntelligence.
Source: Centers for Medicare & Medicaid Services launch triage payment model – Business Insider
Protection of PHI is at risk with proposed HHS rules. Epic Systems CEO is urging its health system customers to take a stand against the U.S. Department of Health and Human Services’ proposed rules to make it easier to share patient data.
Source: Epic CEO sends letter urging hospitals to oppose HHS data-sharing rule
Epic Systems, one of the largest medical records companies, emailed the chief executives of some of the largest hospitals in the U.S. on Wednesday, urging them to oppose proposed regulation designed to make it easier to share medical information.
Source: Epic CEO sends letter urging hospitals to oppose HHS data-sharing rule
In June 2019, by the swipe of a pen on an executive order, healthcare price transparency was assigned to HHS directing hospitals and insurers to make publicly available the prices they charge for their healthcare services. Patients are on the hook for a greater percentage of their medical bills than ever before including non-urgent choices on where to receive their care. The logic flowed that patients will be provided a procedure’s costs before non-urgent surgery in order to make an informed financial decision. Price transparency allows patients to be able to take costs into account when making provider decisions.
The use of predictive analytics is becoming more and more prevalent in healthcare from patient care to billing to palliative care. Predictive analytics and machine learning are readily being used in patient care as systems now predict patient outcomes, assist in radiology diagnoses and identify cases needing extra attention or care. Hospitals accumulate massive amounts of data from patient care to billing and collection. By using past billing and claim data experiences in combination with the right business intelligence tool, hospital billers can improve collections and denials management by learning from experience and taking action to adjust claims and increase revenue.
Predictive analytics and machine learning are driven by data and algorithms using past data to predict future outcomes. The predictive ability of machine learning not only delivers results in patient care but also in administration and particularly in hospital billing. By applying years of DRG data, a hospital can isolate the cases needing special coding attention before billing. By using predictive analytics post-discharge hospitals are able to cull the cases most likely to be denied or most likely to be under-coded. Under-coding is the equivalent of not being paid for the services performed, and it leads to hospitals leaving significant revenue on the table.
More and more hospitals are using outside vendors for to optimize their DRG billing. Vendors using predictive analytics, machine learning and artificial intelligence are leading the way towards optimizing hospital DRG revenue. The right business intelligence partner can target high value actions to deliver the greatest and fastest ROI.
FairCode combines the domain expertise of experienced physicians with modern data science and analytics technologies to increase hospital revenue. We bridge the gap between your attending physicians and hospital coders. The result? Patient acuity and Case Mix Index are more accurately captured with the correct DRG; hospital reimbursement adjusts accordingly. DRG Validation and physician conducted medical chart reviews happen in real time, significantly impacting hospital quality rankings, case mix index (CMI) and bottom-line results. From clinical validation and chart reviews to payor denial defense, our physicians and data scientists are part of your team! Add us to your existing CDI initiatives, and see the difference. Outcomes are measurable and significant. FairCode averages greater than 4:1 Gross Return on Investment in client hospitals and has been delivering hospital revenue solutions for over 18 years.
Source: Predictive Analytics & Machine Learning in Hospital Billing | Fair Code Associates | DRG Assessment
In June 2019, by the swipe of a pen on an executive order, healthcare price transparency was assigned to HHS directing hospitals and insurers to make publicly available the prices they charge for their healthcare services. Patients are on the hook for a greater percentage of their medical bills than ever before including nonurgent choices on where to receive their care. The logic flowed that patients will be provided a procedure’s costs before nonurgent surgery in order to make an informed financial decision. Price transparency allows patients to be able to take costs into account when making provider decisions.
Now that we are in the midst of HHS price transparency, we see great disparity in the hundreds of prices for the same procedure at various hospitals. Costs vary greatly on a local basis, and in many cases billed revenue is reflective of the costs incurred. In any event, whether it is a published rate or negotiated rate, hospitals need to get paid for every bit of services they perform for their patients. With the amount of under coding present in the market, a hospital can maximize billed revenue by using a well-tested DRG validation process.
FairCode combines the domain expertise of experienced physicians with modern data science and analytics technologies to increase hospital revenue. FairCode bridges the gap between a hospital’s attending physicians and hospital coders. The result? Patient acuity and Case Mix Index are more accurately captured with the correct DRG, and hospital reimbursements adjust accordingly. DRG Validation and physician conducted medical chart reviews happen in real time, significantly impacting hospital quality rankings, case mix index (CMI) and bottom-line results. From clinical validation and chart reviews to payor denial defense, FairCode’s physicians and data scientists are part of a hospital’s coding team. Add FairCode to your existing CDI initiatives and see the difference. Outcomes are measurable and significant. FairCode averages greater than 4:1 Gross Return on Investment.
Provider organizations are finding that full revenue cycle outsourcing is not meeting expectations, according to a new market report from KLAS.
For the report “Outsourced Revenue Cycle Services 2019,” KLAS spoke to 140 provider organizations using either revenue cycle outsourcing or extended business office services to identify the vendors delivering the most value.
Of the respondents using revenue cycle outsourcing, one-third said they would not purchase their vendor’s services again, and an even larger number reported dissatisfaction with their vendor’s full revenue cycle outsourcing product.
Source: Third of Providers Regret Revenue Cycle Outsourcing Purchase
Artificial intelligence is only as strong as its ability to properly process aberrations. The Greeks said it best, a chan is only as strong as its weakest link! In healthcare, using AI for diagnosis is a useful tool but FAR from being a replacement for hands-on diagnoses.
Well planned aberrations could also be used to trick medical A.I. vision systems that are designed to identify diseases designed to identify diseases. In that study, the researchers tested deep learning systems with adversarial examples on three popular medical imaging tasks – classifying diabetic retinopathy from retinal images, pneumothorax from chest X-rays, and melanoma from skin photos. In such attacks, pixels within images are modified in a way that might seem like a minimal amount of noise to humans but could trick these systems into classifying these images incorrectly. The scientists noted that their attacks could make deep learning systems misclassify images up to 100 percent of the time and that modified images were imperceptible from real ones to the human eye. They add that such attacks could work on any image and could even be incorporated directly into the image-capture process.
Source: (14) How To Play Tricks On Artificial Intelligence? | LinkedIn
The overall economic burden associated with diabetes, heart disease, dementia and other chronic medical conditions in the United States now adds up to more than $4.5 trillion, a new report has found.
While already staggering, that economic burden is projected to double within the next three decades as well, propelled by the wave of aging baby boomers soon to making landfall.
Source: Chronic Conditions Cost US Economy More Than $4.5 Trillion – Home Health Care News