Implementation of electronic health records is considered a national priority in this era of healthcare reform. However if EHRs are not implemented correctly they can be painful.
EHRs that are not implemented effectively can affect productivity and revenue. The extra documentation requirements and intricate workflows create distance between physicians and their patients. Physicians have reported that they spend too much time on EHRs and that they don’t get enough time to interact with their patients. But physicians often communicate that spending time on EHRs is crucial to creating a trusted set of structured data that can guide their business. Every click that providers make creates important data points that can be used to inform the efficient delivery of their practice.
Every EHR saves a large amount of data inside it regarding patient health, effectiveness of treatments, system efficiency and provider tendencies. Despite the extra time and effort that is dedicated to electronic documentation, many practices and physicians do not make full use of this precious data set that they have produced.
If a practice can get its EHR adoption right they can make a number of positive results, some of which are mentioned below:
By overcoming the difficulties providers can see more patients and will be able to generate more billed revenue using its existing staff. Furthermore, if a provider is using its EHR efficiently then the improved documentation produces billing at higher rates, combined with increased patient flow. This represents significant potential revenue.
Quick Cash Flow
Many of the practices work on revenue cycle management, but few make it flawless. With increased charge accuracy and reduced time for denials, there will be an increase in the yield with timely reimbursements by the payers.
Guest post Kathleen Myers, MD, FACEP, is an emergency physician and founder/chief medical officer of Essia Health.
A few years ago, JAMA published a drawing by a 7-year-old girl after a recent visit to the doctor. It showed the girl on the examination table. Her older sister was seated nearby in a chair, as was her mother, who was cradling her baby sister. The doctor sat staring at the computer, his back to everyone – including the patient. The picture was carefully drawn with beautiful colors and details, and you couldn’t miss the message: Technology is making us physicians less human.
This powerful picture paints the role of the medical scribe in re-humanizing healthcare: If a medical scribe had been there, the doctor would have been able to focus 100 percent on the little girl while the scribe entered the necessary documentation into the computer.
Medical scribes specialize in charting physician-patient encounters in real-time in the electronic health record (EHR) during medical exams, freeing physicians from the data entry burden. They are typically bright, tech-savvy college students or recent graduates interested in pursuing a career in medicine and other healthcare disciplines. Many of them go onto medical school and become physicians themselves, having gained invaluable experience and insights into real-world medicine through scribing.
When I first started using an EHR, I realized that I didn’t want to be the doctor depicted in that drawing. And I was sure other doctors felt likewise. So I started a medical scribe program in my emergency department physician group as a way to integrate EHRs while re-humanizing healthcare – helping physicians maintain a more personal relationship with their patients, helping hospital customers ensure high-quality care for their patients and helping create a meaningful place for people to work. It wasn’t long before I realized that the model I started to solve our needs internally had significant potential in the marketplace, so I turned our program into a company that could serve the medical scribe needs of other healthcare providers.
In the nearly 10 years I’ve personally been using a scribe, I have observed how they are improving the practice, as well as the business, of healthcare. And our customers have confirmed these benefits time and time again.
First, patient satisfaction increases when they receive a physician’s full and focused attention. In fact, studies show improvement of 40 percent to 45 percent in Press Ganey patient satisfaction scores to overall levels 90 percent and higher when scribes are used.
As clearly identified in the PCAST Report on Health Information Technology (2011), and as echoed in the recent GAO report Electronic Health Record Programs — Participation Has Increased, but Action Needed to Achieve Goals Including Improved Quality of Care (2014), healthcare continues to have a data problem. The country has invested significantly to advance EHR adoption.
In simpler terms, healthcare data is messy and makes for building of accurate, actionable metadata a problem. It’s clear that the next generation of standards that are being developed by the numerous committees and acronyms and professional societies tackling measure development, harmonization and testing will now need to address the relevance of each measure.
More than a decade ago, a coalition of purchasers, payers and providers came together across Wisconsin to form the Wisconsin Collaborative for Healthcare Quality (www.wchq.org). Groundbreaking initiatives like Get with the Guidelines, Leapfrog and JCAHO revealed that “quality” and “healthcare” could be used in the same sentence (or displayed on a website). These efforts were largely inpatient-focused. Measurement in the outpatient setting, long considered the keystone of payment reform, was an unsolved riddle. WCHQ, at the urging of the IOM, IHI and others accepted the challenge of tackling performance in the ambulatory arena.
At the direction of some very engaged employers, and with input from most of the state’s payers, WCHQ was charged with one very simple goal — apples to apples quality measurement, regardless of health IT infrastructure. The focus had to include both processes of care and outcomes. Oh, and if health systems didn’t have any health IT in place, data still needed to be included for these groups in the measurement effort. What transpired over an 18-month period was remarkable. With unwavering support from administrative and clinical leadership, health systems rolled up their sleeves and dug into their very messy data. Each Monday, we would devise a fiendish list of new tasks to be completed in the next four business days.
Guest post by Anil Jain, MD, FACP, chief medical officer, Explorys, and staff, Department of Internal Medicine, Cleveland Clinic.
Nearly every aspect of our lives has been touched by advances in information technology, from searching to shopping and from calling to computing. Given the significant economic implications of spending 18 percent of our GDP, and the lack of a proportional impact on quality, there has been a concerted effort to promote the use of health information technology to drive better care at a lower cost. As part of the 2009 American Reinvestment and Recovery Act (ARRA), the Health Information Technology for Economic and Clinical Health (HITECH) Act incentivized the acquisition and adoption of the “meaningful use” of health IT.
Even prior to the HITECH Act, patient care had been profoundly impacted by the use of health informationtechnology. Over the last decade we had seen significant adoption of electronic health records (EHRs), use of patient portals, creation of clinical data repositories and deployment of population health management (PHM) platforms — this has been accelerated even more over the last several years. These health IT tools have given rise to an environment in which providers, researchers, patients and policy experts are empowered for the first time to make clinically enabled data-driven decisions that not only at the population level but also at the individual person level. Not only did the 2010 Affordable Care Act (ACA) reform insurance, but it also has created incentive structures for payment reform models for participating health systems. The ability to assume risk on reimbursement requires leveraging clinical and claims data to understand the characteristics and needs of the contracted population. With this gradual shift of risk moving from health plans and payers to the provider, the need to empower providers with health IT tools is even more critical.
Many companies such as Explorys, a big data health analytics company spun-out from the Cleveland Clinic in 2009, experienced significant growth because of the need to be able to integrate, aggregate and analyze large amounts of information to make the right decision for the right patient at the right time. While EHRs are the workflow tool of choice at the point-of-care, an organization assuming both the clinical and financial risk for their patients/members needs a platform that can aggregate data from disparate sources. The growth of value-based care arrangements is increasing at a staggering rate – many organizations estimate that by 2017, approximately 15 percent to 20 percent of their patients will be in some form of risk-sharing arrangement, such as an Accountable Care Organization (ACO). Already today, there are currently several hundred commercial and Medicare-based ACOs across the U.S.
There is no doubt that there are operational efficiencies gained in a data-driven health system, such as better documentation, streamlined coding, less manual charting, scheduling and billing, etc. But the advantages of having data exhaust from health IT systems when done with the patient in mind extend to clinical improvements with care as well. We know that data-focused health IT is a necessary component of the “triple-aim.” Coined by Dr. Donald Berwick, former administrator of the Centers for Medicare and Medicaid Services (CMS), the “triple-aim” consists of the following goals: 1) improving health and wellness of the individual; 2) improving the health and wellness of the population and 3) reducing the per-capita health care cost. To achieve these noble objectives providers need to use evidence-based guidelines to do the right thing for the right patient and the right time; provide transparency to reduce unnecessary or wasteful care across patients; provide predictive analytics to prospectively identify patients from the population that need additional resources and finally, use the big data to inform and enhance net new knowledge discovery.
Hospitals and eligible professionals that have yet to meet their meaningful use requirements are facing a good news/bad news scenario. First the bad news: The clock is ticking, as major deadlines loom. The good news: It’s not too late to hop aboard the MU train, although some running might be required. If you’re among those seeking MU attestation this year, here are key points you need to know.
Before you take one more step, make sure your technology vendor is 2014 certified. Regardless of whether you are attesting to meaningful use Stage 1 or Stage 2, all eligible professionals (EPs) and eligible hospitals (EHs)/Critical Access Hospitals (CAHs) are now required to use an ONC 2014 Edition Certified technology to successfully attest to both MU1 and MU2.
You might have been under the impression that Stage 1 corresponds with the 2011 Edition and Stage 2 corresponds to the 2014 Edition. This is not the case, but your confusion is understandable.
What happened? When meaningful use was first introduced, the Centers for Medicare and Medicaid Services (CMS) published MU Stage 1 and the Office of the National Coordinator for Health Information Technology (ONC) published the 2011 Edition Certification; then MU Stage 2 and the 2014 Edition Certification Criteria were released within days of one another.
Guest post by Darin VanderWell, Director of Product, DocuTAP.
Rumors about the next phase of the Centers for Medicare and Medicaid Services (CMS) EHR Incentive Program has prompted concern among healthcare providers. To truly understand meaningful use Stage 3 and its impact, it is important to differentiate between the rumors and the truth.
The final rule for meaningful use Stage 3 has yet to be published, so discussion on its effects are based on available drafts. Even those drafts are in question since the December 2013 announcement that Stage 3 would be delayed until 2017. One reason cited was to allow more time to research the impacts of Stage 2 before finalizing Stage 3. The delay will be particularly important for that research, since compared to Stage 1, 2011 Edition, there are so few Stage 2 vendors certified currently.
As for what is expected, the attention turns from data capture and access (Stage 1) and information exchange (Stage 2) to improved outcomes in Stage 3. One expected goal is to simplify and reduce the reporting requirements on those attesting. Some of that change can be achieved by consolidating the program’s current objectives, which I expect hospitals and providers will welcome, provided it truly reduces the reporting burden and does not coincide with other, new objectives and reporting requirements.
Stage 3’s goal of improving outcomes will be incredibly interesting – through November 2013, CMS had disbursed nearly $18 billion in incentive payments. Until now, the program’s success has been judged by the number of participants adopting certified EHRs. At some point during Stage 3 (or thereafter), we will know whether those payments have truly improved outcomes.
Given the recent focus on the value of health IT (HIMSS recently asked those of us covering the space to respond to its importance; you can see my response here: HIMSS Asks: What is the Value of Health IT?), the topic remains an intriguing one. With ever-present changes to the landscape, we’re in the midst of major and continual upheaval about how technology can serve, yet improve care quality and outcomes.
The use of electronic health records, for example, continues to permeate the space. But even as pervasive as the technology is — during 2006 through 2013, the percentage of physicians using any EHR system increased 168 percent, from 29.2 percent in 2006 to 78.4 percent in 2013, according to the CDC. Nearly half of physicians (48.1 percent) were said the be using the more comprehensive “basic system” by 2013, up from 10.5 percent from 2006, but that doesn’t mean the solutions are completely meeting the needs of physicians.
That said, I asked Sean Morris, director of sales for Digitech Systems, for some perspective. He’s worked in health IT for more than 20 years. He agrees with me, that penetration of EHRs remains less than 50 percent. Even so, as physicians have moved aggressively toward the technology, in large part because of meaningful use, not all of the systems that have been deployed are working as expected.
“EHRs were the new shiny thing and everybody wanted to chase after them,” Morris said. “But issues came up as people began to evaluate and use the technology. They discovered that there’s really no bridge from the information stored in EHRs charts and other records outside the EHR. They need to bring it together without killing their practice.”
As the age of EHRs begins to fade past its prime and as practices begin to evaluate second generation solutions, Morris said history is likely going to repeat itself unless practices begin to deploy solutions that help them use all of the data stored in the records.
Morris said that in many cases, current EHRs don’t actually need to be replaced, rather built upon.
Guest post by Andy Nieto, health IT strategist, DataMotion.
The HITECH Act’s goal of improving clinical outcomes for patients using technology through meaningful use is admirable and quite overdue. However, where the Office of the National Coordinator for Health Information Technology (ONC), and to a much greater extent, electronic health records (EHR), have missed the mark is in the deployment and execution.
The stated goal of meaningful use Stage 1 (MU1) was to deploy, integrate and use EHRs to gather and document “structured and coded” healthcare data. Rather than take ONC’s directives as a framework to improve provider care tools, they viewed it as a “minimum requirement” and missed the spirit of the initiative. EHRs remain cumbersome, challenging and inefficient.
Providers now spend more time clicking boxes and typing than they do speaking to their patients. To make matters worse, the data gathered is maintained in the EHR’s “unique” way, making exchange and interaction challenging and interfaces costly.
Guest post by Daniel Piekarz, vice president of life sciences business development at DataArt.
The life sciences industry will be defined in 2014 by the growing market demand to apply newly developed technology, including big data analysis, to healthcare and medical device practices. While many of the amazing technological advances in the space are driven by a desire to aid humanity, the industry is also caught between increased economic and regulatory pressure that is forcing many to electronically collect heaps of data while looking for custom technology solutions that will allow them to leverage this valuable data and adhere to new industry standards.
Over the next year, trends that reflect newly available technology will start to develop. The adoption of healthcare big data technology will become a major theme in the sector this year, just as it has in several other industries. Many new technology offerings have been created to tie together data from multiple sources that can be accessed by researchers and physicians to allow them to easily exchange information. This also aids in research and development practices by offering another valuable tool to gather and analyze data.
Tied to the big data trend is the emergence of personal healthcare data aided by physicians’ adoption of EHR technology. By allowing patients to own and access their healthcare data on a healthcare information dashboard, patients can more easily understand risks and preventable care options. Pooling anonymized patient data together can also lead to better analysis, and physicians are already starting to work with vendors to develop big data diagnostic tools. These new technology advancements have started to create a generation of patients more committed to their own healthy future than ever before. Through an intelligent system database, patients and physicians can better understand patterns and symptoms that affect their healthy lifestyles. While this type of big data solution is gaining a foothold, there is still resistance from some doctors due to their concern over critical review of their procedures.
Today’s healthcare IT departments have a relatively tall order when it comes to effective EHR data management. In an environment that often requires them to be simultaneously budget-conscious, growth-minded and patient-driven, healthcare IT must also address the often-competing data management needs for:
Data at rest
Data mining and analytics
Popular EHR system vendors have made significant strides to address several of these data management issues. Unfortunately, they can only go so far given the current state of many healthcare IT environments. Some departments may still require custom software applications, complete with specially configured servers, storage and network hardware to support them.