Category: Healthcare

Is MIPS really doing what it is supposed to do? Research suggests that it is not.

How well does the Merit-based Incentive Payment Program (MIPS) of Medicare measure the caliber of medical treatment that is given? According to the findings of a recent study, not very.

The 2017 introduction of MIPS, which replaced three prior quality measurement programs, aimed to enhance patient care by financially rewarding or penalizing physicians based on their performance on particular “process” and “outcome” metrics in four key areas: cost, quality, improvement activities, and fostering interoperability.

The six metrics that participating physicians choose to report on must include one outcome indicator, such as a hospital admission for a particular disease or condition. Currently, MIPS is the biggest value-based payment program in the country.

Data from Medicare statistics and claims records for 3.4 million individuals who saw about 80,000 primary care providers in 2019 were evaluated for the study by researchers. They compared doctors’ overall MIPS scores with their scores on five process measures, including breast cancer screening, tobacco screening, and diabetic eye exams, and six outcome measures, including ED visits and hospitalizations.

The findings showed there was no consistent relationship between the measures’ performance and the final MIPS ratings. For instance, doctors with low MIPS scores scored somewhat better on the other two process measures, while having much lower average MIPS scores than physicians with high MIPS scores on three of the five process measures examined.

Low-scoring doctors performed much worse on the all-cause hospitalizations per 1,000 patients metric than they did on the other four outcome measures, although they performed significantly better on the metric of ED visits per 1,000 patients. Similar to this, 21% of physicians with high MIPS scores had outcomes that were in the poorest percentile, compared to 19% of those with low MIPS scores who performed in the top quintile for composite outcomes performance.

The findings suggest that the MIPS program’s accuracy in identifying high- versus low-performing providers is really no better than chance.

For these findings, the authors provide a number of interpretations. Among them are the challenges in making meaningful comparisons when doctors are free to select the metrics they report on, the fact that many program metrics, as other research has shown, are either invalid or of dubious validity and thus may not be linked to better outcomes, and the possibility that high scores may simply be an indicator of a program’s capacity for data collection, analysis, and reporting rather than of higher quality medical care.

They claim that the latter conclusion is supported by the discovery that participants with low MIPS scores were more likely to work in independent, small practices even though their clinical outcomes were frequently comparable to those of medical professionals in large, system-affiliated practices with high MIPS scores.

This research was released in JAMA on December 6. https://jamanetwork.com/journals/jama/article-abstract/2799153

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.

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. 

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 Prevalence and Consequences of Medical Errors in American Medicine

Part I

There are numerous records that we maintain, or are maintained on us, over the course of our lives.  Our school records track our grades and accolades. Our public records track our civic life and criminality. Our resumes document our accomplishments and abilities.  And our medical records compile the history of our overall health and wellness throughout the course of our lives. Inevitably, we are all dependent on the precision of these records to portray ourselves truthfully. Any inaccuracy could have a monumental impact on some aspect of our lives. Missing credits could keep us from graduating. A mistake in our criminal background could result in the loss of liberties. And an error in our medical records could cost us our health, perhaps even our lives.

 

Patient Perception on Healthcare Safety

We trust doctors, as we should. They’re dedicated, intelligent, and went to school a lot longer than most of us did, so we put our health and well-being in their hands and trust that they will know how to fix us and keep us healthy.  A recent study out of the University of Chicago and the Institute for Healthcare Improvement found that 90% of Americans interacted with some kind of healthcare provider in the last year, and that most people’s experiences were positive. The care was comprehensive, the physicians were attentive, and they understood how to care for themselves after their visits. (1) Over all, Americans do not feel that they run the risk of experiencing a medical error. However, this could largely be contributed to a general misunderstanding of what, exactly, constitutes one.

 

Defining “Medical Error” and Patient Experience

For most of us, the thought of “medical error” conjures images of a scalpel left inside of us after a surgery or something else gruesome, newsworthy, and incredibly unlikely to ever occur. In reality, a medical error can mean a simple miswording in diagnoses, perhaps stating an injury to a right foot instead of left, or a few switched numbers in a medical code show you diagnosed and treated with something else entirely. The same study found that, after having the term “medical error” defined to them, 21% of participants expressed that they had personally experienced a medical error, while 31% said that they had cared for someone who had experienced one.  All total, 41% of adults in the United States have either personally experienced a medical error in their own care, or were directly involved in caring for someone who had. (1)

The Consequences of Medical Errors

When it comes to medical errors, 41% is a disparaging, and frankly, frightening number, especially considering that 73% of people who reported experiencing a medical error or caring for someone who had said that the mistake had some kind of long term or permanent health detriment or financial impact. There is also a clear correlation between medial errors and harm with 36% of patients who reported personally experiencing a medical error also reporting that they had been harmed while receiving medical care. (1)

Another alarming statistic coming out of this study is that only about 1/3 of the participants who reported experiencing a medical error were made aware of the error by someone at the facility where they were treated. Around half of the participants brought their medical error to the attention of medical personnel on their own. (1) The important assumption to then take from this data, is that not only are medical errors occurring frequently, most of them are not being caught by medical personnel or facility staff. This leads then to the even larger issue of medical disparity, as medical record errors tend to impact vulnerable populations more so than populations with greater health literacy, a factor closely tied to education and income.(1)

Of the participants who reported dealing with medical errors, 59% reported that the error was centered around diagnosis, where the patient was either diagnosed incorrectly, had a delayed diagnosis, or was not diagnosed at all when they were, in fact, ill or injured. (1) The reasons for misdiagnosis are broad and varying, and misdiagnosis is the leading cause of medical malpractice suits in the United States. Diagnostic errors can have dire, long lasting, and even fatal consequences for patients, and yet they are so common that nearly everyone will experience at least one incorrect or delayed diagnosis in their lifetime. (2)

The question then becomes, what is causing such a high prevalence of medical errors and what can be done to rectify that?

Changes in Medical Documentation and Resulting Challenges

In 2004, thanks to new government incentives, medical records began to change with a push from paper charts to electronic archives. While the benefits of EMRs are undeniable—they can lower costs, enhance efficiency, and make patient records immediately available across care settings– the transition, unfortunately, has been less than smooth. Many medical facilities are still scrambling to fully and comprehensively changeover. (3)

One of the biggest hinderances to care and sources of medical errors is the extra documentation burden that now falls on doctors. Prior to EMR, physicians would fill out charts or record their observations, and those documents would then go to a trained medical transcriptionist, a coding expert, and then a billing specialist. In this new system of clinical documentation, doctors are responsible for filling out patient charts and coding, often using clunky systems that they are ill-trained to use. (3) Not only does this result in a substantial amount of physicians’ time shifting from patient interaction to documentation as they navigate unfamiliar and complicated computer programs, but it also drastically reduces the potential for any mistakes that physicians might have made to be caught and queried by professionals trained in transcription and coding. 

In addition to the obvious consequences placed on patients when medical errors arise from EMR complications, medical documentation is also a significant factor in the increasing rise of physician burnout. Physicians report higher levels of job dissatisfaction when the amount of time they spend on documentation encroaches on, and even surpasses in many cases, the amount of time they spend on patient care. (4) Essentially, new clinical documentation standards are forcing doctors to perform tasks and use technology with which they’ve had practically no training, resulting in transitional delays with the learning curve, professional frustrations, and a high prevalence of mistakes.

 

New Solutions in Traditional Practices

Medical errors are costly and dangerous and combatting them is a top priority in patient safety and hospital efficiency. With EMR hiccups contributing to a substantial amount of errors in medical documentation, the most obvious solution to begin combating medical error is to elevate the quality, capabilities, and usability of clinical documentation workflows. New software solutions and technology, specifically backend speech recognition and natural language processing, are capable of significantly improving the quality and accuracy of medical transcriptions.

The traditional transcription model where physicians dictate patient encounters and trained transcriptionists and coders review the reports to ensure quality and integrity is by far the most comprehensive way to prevent medical errors. Thanks to advancements in transcription technologies, the cost of transcription has come down significantly, and can more than offset the costs accumulated as a result of the medical errors it can eliminate. With new solutions and technologies, the outlook for not only reducing medical error, but enhancing the entire system of medical transcription and diagnosis, is exciting and promising.           

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.