Category: Clinical Documentation Improvement

Hospital Outpatient Departments: Effective July 1, 2020 you must request prior authorization for certain hospital Outpatient Department (OPD) services

For dates of service beginning July 1, 2020, you must request prior authorization for the following hospital Outpatient Department (OPD) services:

  • Blepharoplasty
  • Botulinum toxin injections (when paired with specific procedure codes)
  • Panniculectomy
  • Rhinoplasty
  • Vein ablation

Medical necessity documentation requirements remain the same and hospital OPDs will receive a decision within 10 days.

While only the hospital OPD service requires prior authorization, CMS wants to remind other providers that perform services in the hospital OPD setting that claims related to/associated with these services will not be paid if the service requiring prior authorization is not eligible for payment. These related services include, but are not limited to, anesthesiology services, physician services, and facility services. Only associated services performed in the hospital OPD setting are affected. Depending on the timing of claim submission for any related services, claims may be automatically denied, reviewed, or denied on a postpayment basis.

For botulinum toxin injections, consult the list of codes that require prior authorization for more details. Generally, the use of botulinum toxin injection codes paired with procedure codes other than 64612 or 64615 will not require prior authorization under this program.

Saince announces the launch of tele-medicine feature within its clinical documentation solution

Doc-U-Scribe clinical documentation solution now comes integrated with tele-medicine workflow. Physicians and administrators can create tele-consultation sessions with patients seamlessly from within the application. This process eliminates the need for providers to use separate solutions – one for clinical documentation and another for video session.

The COVID-19 public health crisis has accelerated the use of tele-medicine solutions among healthcare provides across the nation. However, many small hospitals and physician offices do not have access to a single solution that takes care of all their needs. Physicians are forced to use multiple solutions to complete their tele-medicine workflow. They are often finding this process frustrating and cumbersome.

Doc-U-Scribe clinical documentation solution which is used by hundreds of hospitals and physician offices across the country provides an integrated and seamless workflow for clinical documentation as well as tele-medicine.   This new HIPAA compliant tele-medicine solution can cut costs, increase efficiency, and improve physician satisfaction significantly.

Saince announced that this new feature will be available to all their existing customers immediately. Saince also announced that with their plug and play model, any new hospital or physician office can be up and running with their tele-medicine program within 48 hours.

When Pursuing CDI, Using Risk Adjustment Is Vital

As healthcare has moved away from fee-for-service reimbursement models toward a more value-based system, the idea of using risk adjustment to account for individual patient risk and chronic conditions has become far more important for providers seeking to maximize quality of care.

In today’s healthcare environment, providers are often required to fight simultaneous battles on several fronts. For those pursuing clinical documentation improvement (CDI), they must balance sometimes-conflicting regulatory demands, workflow needs, etc. Further exacerbating the problem is the persistent shift of care provision to the ambulatory setting and the increasing demands it places on provider organizations.

As we have discussed in previous blog posts, outpatient CDI efforts face a number of unique challenges, such as decidedly larger case volumes than most inpatient settings and far shorter clinical visits. These shorter visits produce less usable patient data and offer a condensed window during which multiple team members must work in synchrony—accurately and efficiently—to gather that data. Outpatient providers must also go further, factoring in risk adjustment for each individual in their larger patient populations as well.

Often, problems with risk adjustment appear when inaccurate or incomplete diagnosis coding slips through the documentation workflow. For instance, failure to capture patients’ Hierarchical Condition Categories (HCCs)—and recapture year-over-year—can greatly skew risk scores for individual patients and potentially the overall population. Such mistakes can filter downstream to errors in patient care and increasing claim denials and, potentially, wreak havoc on pay-for-performance reimbursements.

This dynamic puts increased pressure on physicians to capture correct documentation at the point of care—getting it right the first time without a great deal of revision. Many have addressed the issue through Computer Assisted Physician Documentation (CAPD), which provides a number of CDI features. CAPD improves accuracy and lessens physicians’ burdensome workflow by precluding the need to rehash previously captured documentation.

The goal of these products is to allow physicians to complete patient care documentation faster and spend more time with their patients. Unfortunately, many traditional products, which were designed for inpatient settings, lack effective integration of risk adjustment. As a result, many providers are prevented from seeing the most accurate picture of the population they serve—and value-based care programs are not as successful as they could be.

To learn about PowerSpeak+RAPID—a CAPD platform combining powerful front-end medical speech recognition software (PowerSpeak) and Risk Adjusted Physician Documentation (RAPID)—contact Saincesaince inc logo

Hospital OPPS and ASC Payment System and Quality Reporting Programs Changes for 2018

On November 1, CMS issued the CY 2018 Hospital Outpatient Prospective Payment System (OPPS) and Ambulatory Surgical Center (ASC) Payment System final rule with comment period, which includes updates to the 2018 rates and quality provisions and other policy changes. CMS adopted a number of policies that will support care delivery; reduce burdens for health care providers, especially in rural areas; lower beneficiary out of pocket drug costs for certain drugs; enhance the patient-doctor relationship; and promote flexibility in healthcare.

CMS is increasing the OPPS payment rates by 1.35 percent for 2018. The change is based on the hospital market basket increase of 2.7 percent minus both a 0.6 percentage point adjustment for multi-factor productivity and a 0.75 percentage point adjustment required by law. After considering all other policy changes under the final rule, including estimated spending for pass-through payments, CMS estimates an overall impact of 1.4 percent payment increase for providers paid under the OPPS in CY 2018.

CMS updates ASC payments annually by the percentage increase in the Consumer Price Index for all urban consumers (CPI-U). The Medicare statute specifies a Multi-Factor Productivity (MFP) adjustment to the ASC annual update. For CY 2018, the CPI-U update is 1.7 percent. The MFP adjustment is 0.5 percent, resulting in a CY 2018 MFP-adjusted CPI-U update factor of 1.2 percent. Including enrollment, case-mix, and utilization changes, total ASC payments are projected to increase approximately 3 percent in 2018.

Physician Fee Schedule Final Policy for Calendar Year 2018

On November 2, CMS issued a final rule that includes updates to payment policies, payment rates, and quality provisions for services furnished under the Medicare Physician Fee Schedule (PFS) on or after January 1, 2018.

The overall update to payments under the PFS based on the finalized CY 2018 rates will be +0.41 percent. This update reflects the +0.50 percent update established under the Medicare Access and CHIP Reauthorization Act of 2015, reduced by 0.09 percent, due to the misvalued code target recapture amount, required under the Achieving a Better Life Experience Act of 2014. After applying these adjustments, and the budget neutrality adjustment to account for changes in Relative Value Units, all required by law, the final 2018 PFS conversion factor is $35.99, an increase to the 2017 PFS conversion factor of $35.89. 

Highlights of Quality Payment Program for Year 2 (Calendar Year 2018) Under MACRA

Here are the highlights of the Final Rule for QPP for Year 2 under MACRA as announced by CMS yesterday:

• Weighting the MIPS Cost performance category to 10% of your total MIPS final score, and the Quality performance category to 50%.
• Raising the MIPS performance threshold to 15 points in Year 2 (from 3 points in the transition year).
• Allowing the use of 2014 Edition and/or 2015 Certified Electronic Health Record Technology (CEHRT) in Year 2 for the Advancing Care Information performance category, and giving a bonus for using only 2015 CEHRT.
• Awarding up to 5 bonus points on your MIPS final score for treatment of complex patients.
• Automatically weighting the Quality, Advancing Care Information, and Improvement Activities performance categories at 0% of the MIPS final score for clinicians impacted by Hurricanes Irma, Harvey and Maria and other natural disasters.
• Adding 5 bonus points to the MIPS final scores of small practices.
• Adding Virtual Groups as a participation option for MIPS.
• Issuing an interim final rule with comment for extreme and uncontrollable circumstances where clinicians can be automatically exempt from these categories in the transition year without submitting a hardship exception application (note that Cost has a 0% weight in the transition year) if they were have been affected by Hurricanes Harvey, Irma, and Maria, which occurred during the 2017 MIPS performance period.
• Decreasing the number of doctors and clinicians required to participate as a way to provide further flexibility by excluding individual MIPS eligible clinicians or groups with ≤$90,000 in Part B allowed charges or ≤200 Medicare Part B beneficiaries.
• Providing more detail on how eligible clinicians participating in selected APMs (known as MIPS APMs) will be assessed under the APM scoring standard.
• Creating additional flexibilities and pathways to allow clinicians to be successful under the All Payer Combination Option. This option will be available beginning in performance year 2019.

EMRs Taking Away Close to One-Third of Physicians’ Work Time – AMA

The EMR Time Crunch

A common complaint among physicians across practices and specialties has been the amount of time that was previously spent attending to patients is now being occupied by clinical documentation.  These time disparities can have adverse effects on physician-patient relationships, and also limit the number of patients able to receive care from a physician or practice. Value-based purchasing models are frequently the basis for physician reimbursements, and because these models require extensive documentation to accurately report the quality and cost of care, the EMR software physicians are required to use is becoming increasingly complex and time consuming.

AMA Findings

A recent study conducted by the American Medical Association focusing specifically on the use of electronic health records in academic centers concluded that an average of 27% of the participating Ophthalmologists’ time spent on patient examinations was occupied by EMR use. On average a total of 5.8 minutes per patient and 3.7 hours was spent working in EMR on any given full day of clinic.  The study also found a negative association between the amount of time spent on EMR per patient encounter and overall clinic patient volume.

The AMA study concluded what many physicians have been expressing for years: doctors have limited time to spend with patients while they are spending more time within EMRs. Aside from the strain EMR places on physicians’ time and patient relationships, it is also creating cumbersome clerical burdens when completed incorrectly or hastily. Large swaths of copied and pasted text create bloated and messy records, and a lack of training and technical knowledge can result in incorrect coding, medical errors, and frequent interruptions in the documentation process.

Physician Dissatisfaction

The amount of physician dissatisfaction has also grown with the increased implementation of EMRs. Nearly half of all physicians report feeling unsatisfied with their work-life balance, and 57% of physicians display signs of burnout. The additional time requirements of clinical documentation are a significant factor in both of these statistics. Physicians are spending an increasing amount of time outside of regular work hours completing EMRs, and an increasingly less amount of time on actual patient care and interaction. This has led to heightened levels of stress and job dissatisfaction.

Looking Forward

While the path hasn’t always been an easy one, electronic medical records are here to stay, and they do present a plethora of benefits to clinical documentation, patient care, and bottom lines. The challenge that needs to be addressed is how to make EMRs efficient and thorough, while minimizing the amount of time physicians are required to spend on them.  Perhaps the solution for better EMR efficiency lies within a hybrid workflow — a workflow that combines the traditional model of medical transcription, where physicians dictate patient encounters and trained transcriptionists and coders review the reports for accuracy and sufficiency, combined with the advantages of using a modern day EMR is the most efficient way to ensure document quality and lessen the time burden EMRs place on physicians. When the responsibility of clinical documentation is not placed solely on the physician, doctors will be able to attend to more patients, improve patient relationships, and increase their job satisfaction.

The Cost of Care: How AI is Revolutionizing Healthcare and Driving Down Prices

The cost of healthcare is once again at the center of a national debate.  With premiums rising, the baby boomers aging, and diabetes, the most expensive disease in the world, affecting 10% of the US population, the rising cost of healthcare in America is an issue that affects all of us.  In the past, the implementation of new and emerging technologies in healthcare has contributed to the climbing costs. In contrast, the application of AI into healthcare is promising to drive those costs down.

Healthcare is an enormously expensive industry and the costs are steadily climbing.  According to World Book, in 2014 healthcare made up 17.1% of the GDP of the United States– up 4% from 1995, and continuing to grow.  The application of artificial intelligence into healthcare is promising to greatly reduce these expanding expenses while improving healthcare quality and access.  By 2026, it’s estimated $150 billion could be saved annually in the US healthcare economy by AI applications. It’s no wonder that healthcare is currently the number one investor in AI.

One of the areas in healthcare that will be most significantly impacted by the application of artificial intelligence is clinical documentation. AI applications in medical workflow management are estimated to accumulate $18 billion in annual savings for the healthcare industry by 2026, the third largest estimated savings from AI technology in healthcare after robotic surgery and virtual assistants.  Modern healthcare AI is capable of learning and comprehending and can perform clinical healthcare functions in much the same way as a human, minus human error.

Physician error in clinical documentation is an understandable yet costly complication in healthcare, and AI is able to streamline the tedious clinical documentation process and automatically generate accurate and complete reports.  Many AI healthcare programs are capable of fully augmenting human behavior and can perform tasks from risk analysis to patient diagnosis. Physician engagement in clinical documentation is a critical component to the quality and costs of healthcare, and AI applications are proving to increase physician engagement and improve clinical documentation quality.

With so much potential to improve not only healthcare costs, but also access and quality, the AI health market is currently experiencing a boom, and is expected to grow into a $6.6 billion dollar industry by 2021. This growth makes sense when you consider that the nation and the world are currently facing a shortage of doctors and healthcare personnel, and AI offers hospitals and physician practices a way to combat their rising operational and labor costs, while enabling them to better perform critical administrative functions quickly, accurately, and cost effectively.

Artificial Intelligence seems like the wave of the future, but the reality is, the future is here. In today’s medical environment of value-based care, appropriate reimbursements are incumbent upon accurate, high quality clinical documentation. As AI continues to grow and evolve, AI enabled clinical documentation improvement technology will continue to transform the healthcare industry, improving patient outcomes and optimizing revenue.

Rise of the Machines: Artificial Intelligence in Healthcare

Artificial intelligence in Clinical Documentation

When we think of artificial intelligence, the images that come to mind for many of us are probably somewhere along the lines of Rosie from The Jetsons or Arnold in Terminator.  While we’re still most likely several years from sentient household or murder robots, AI is playing an increasingly large role in our everyday lives.

One area that is beginning to see a significant increase in the applications of artificial intelligence systems is healthcare.  Massive amounts of clinical health data are becoming increasingly available through clinical documentation, electronic health records, and online medical interactions, as well as new and evolving academic health data which is constantly being generated and updated. This increase in available data coupled with the emergence of new, sophisticated algorithms and software has begun a revolutionizing trend in the healthcare industry that is changing the way we’re diagnosed and treated, how we interact with physicians, and how physicians operate within a clinical setting.

Artificial intelligence is a computing system engineered to allow digital devices to perform tasks without being directly instructed by a human. By utilizing multiple algorithms to sort and analyze data, these systems are able to recognize patterns, make decisions, and even change the way they “learn” when presented with new information. Ultimately, AI is designed to emulate the human cognitive process at an exponentially accelerated rate. In healthcare, essentially this means teaching a computer system to learn and think like a doctor.

Diagnosis and Treatment

One of the most practical yet profound applications of AI in healthcare is in patient diagnosis. Using algorithms that are capable of scouring enormous databases of both structured data from clinical trials and unstructured data from medical journals, AI systems can search for a patient’s symptoms while also considering the patient’s own medical history to come up with the most likely diagnoses. It can then generate a list of probable diagnoses and assist in structuring highly personalized treatment plans based on the patient’s medical history, and considering the latest advancement in medical treatments and their success rates across broad population spectrums.

In a clinical trial of 1000 cancer patients, Watson, a technology being developed by IBM which uses an AI system to diagnose and treat cancer, concluded the same diagnoses and treatment recommendations as oncologists 99% of the time.  The far reaching implications of this are particularly important for rural and remote communities where finding a doctor who specializes in a particular kind of disease may be impossible. For example, if there are only two doctors in the country who specialize in a rare, genetic kidney disorder and they are both located in Manhattan while the patient with the kidney disorder lives in Honolulu, using AI diagnoses and treatment plans, a local doctor who is not an expert in the kidney disorder can treat that patient with all of the expertise of the specialist available to them.        

Personal Assistants and Remote Access

Personal health assistant apps operate by asking the patient a series of pointed questions about their symptoms and medical history to reach a diagnosis. The apps can then recommend treatments or suggest that the patient see a doctor in person. As this technology becomes more widely available, it could help to see a significant decrease in doctor’s office traffic since patients with minor illnesses or injuries who only require rest, over the counter medication, or home remedies won’t need to make the trip, freeing up doctor’s time to focus on more critical patients.

These “pocket doctors” can also essentially function as a live-in doctor and health coach for chronically sick patients who require round the clock care. By periodically entering their health data like blood pressure, heart rate, blood glucose, weight, activity, temperature etc, and answering questions regarding physical and mental functions like appetite, energy levels, and sleep patterns, medical personal assistants can track a patient’s health and treatment plan, recommend changes to things like diet and exercise to improve outcomes, and monitor for warning signs that something more serious that requires a visit to an IRL physician is occurring.  

Clinical Documentation Improvement

Clinical documentation in and of itself is an important aspect in the development and accuracy of medical AI technology because it is the data from clinical documentation that is fed into EMR and EHR systems that produce the robust structured databases AI uses to “learn”. In our next post, we’ll be taking a closer look at the pragmatic applications of artificial intelligence in clinical documentation and how they are maximizing appropriate reimbursements and alleviating physician burnout.

Only for about the last two years has the technology and the data that are driving the AI revolution in healthcare been available, and already the results are awe inspiring and the potential seemingly limitless.  While AI still has some obstacles to overcome in the healthcare field the artificial intelligence movement is likely to continue to grow in healthcare, and help improve upon the human endeavor of providing the most comprehensive and effective healthcare possible.