As the Centers for Medicaid and Medicare Services (CMS) and the Office of the National Coordinator for Health IT (ONC) finalized a regulation granting providers additional flexibility in meeting meaningful use (MU) requirements in 2014, the final rule lacked a key provision that would ensure continued EHR adoption and MU participation, according to CHIME.
CHIME issued as statement stating that the organization is “deeply disappointed in the decision made by CMS and ONC to require 365 days of EHR reporting in 2015. This single provision has severely muted the positive impacts of this final rule. Further, it has all but ensured that industry struggles will continue well beyond 2014.”
According to the statement by CHIME, roughly 50 percent of EHs and CAHs were scheduled to meet Stage 2 requirements this year and nearly 85 percent of EHs and CAHs will be required to meet Stage 2 requirements in 2015. Most hospitals who take advantage of new pathways made possible through this final rule will not be in a position to meet Stage 2 requirements beginning October 1, 2014. This means that penalties avoided in 2014 will come in 2015, and millions of dollars will be lost due to misguided government timelines.
Nearly every stakeholder group echoed recommendations made by CHIME to give providers the option of reporting any three-month quarter EHR reporting period in 2015. “This sensible recommendation, if taken, would have assuaged industry concerns over the pace and trajectory of rulemaking; it would have pushed providers to meet a higher bar, without pushing them off the cliff; and it would have ensured the long-term vitality of the program itself. Now, the very future of Meaningful Use is in question,” said CHIME.
Reports state that only 39 percent of physicians share data using a health information exchange (HIE). There is even a lower number of only 14 percent who electronically share data with ambulatory care providers or hospitals outside their organization. While these numbers may seem astounding to some with Stage 2 fast approaching — the reason is clear. Because even though providers want to share health information electronically they are hindered by EHRs that can’t communicate with one another, lack information-exchange infrastructure, and the high expense of setting up electronic interfaces and health information exchanges.
Below are the top reasons why EHR sharing remains low for adoption:
Lack of Interoperability. The majority of providers and physicians have acknowledged lack of EHR interoperability and exchange infrastructure as major barriers to health information exchange. They have also identified the cost of creating and maintaining interfaces and exchanges as a major barrier.
Lack of Advanced Technology. Over the last few years, various HIE systems have been developed, but many have failed for technological and organizational reasons. High-level issues must be addressed to implement an HIE successfully, including disparate EHR and HIS systems. Most previous HIE research focused on high-level issues and evaluating impact on healthcare delivery, ROI, Syndromic Surveillance, etc.
Lack of Security and Streamlining. Quantitative measures are crucial to the long-term sustainability of HIEs. Interoperability of patient data doesn’t effectively address concerns on privacy, productivity, workflow and costs. Streamlining HIE access through integration with electronic health records to minimize workflow interruption, and keeping costs reasonably low for providers, may increase participation.
Lack of Affordability and Productivity. The cost and loss of productivity are major barriers to HIE adoption. While there are many compliant products on the market, not all of them provide cost savings and lead to efficiency or increased productivity.
The purpose of EHR and HIE is to make patient specific information available at the point of care to improve the delivery and quality of care. Interoperability of patient data no doubt has many advantages, including improved care coordination, elimination of paperwork, reduction in duplicate tests and reduction of medical errors. It is imperative to develop a long-term plan for standards and interoperability that will support competing public and private-sector Interoperability efforts. We should also encourage clear regulation on compliance with federal privacy and security laws. There should also be national benchmarking to share best practices and lessons learned. There should be significant cooperation among primary-care providers, medical specialists, long term care providers and hospitals to outline common information sharing needs promoting a value-based care.
Guest post by Adnan Ahmed, president of the health IT solutions provider CNSI.
Each year, health IT experts and state health officials from across the country convene at the Medicaid Enterprise Systems Conference (MESC) to discuss the latest technology solutions for serving a diverse and growing Medicaid population.
This year’s event was held the week of August 18 in Denver, CO, bringing together state, federal and private sector individuals who provided the latest insights for the exchange of ideas related to Medicaid systems technology.
With seven million new Medicaid recipients this past year alone, state Medicaid systems face the challenge of onboarding a high volume of newly enrolled recipients, but also benefit from the opportunity to collect a wealth of data that IT systems can utilize to help government health and human services departments optimize managed health care and patient service.
While Medicaid has long been known simply as a system of payments, IT solutions increasingly present the transformative ability to develop and experiment with new value add-ons that will introduce cost-cutting efficiencies while also improving patient care.
The following is a fascinating infographic from UC Berkeley School of Information highlighting, very nicely, the information contained in an EHR; the difference between an EMR and an EHR; top specialties to adopt electronic health records, as well as top (and not top) states to adopt the technology.
The information here clearly speaks for itself. According to Berkeley’s School of Information, “data science holds great promise for patient health, but patient data is only actionable in so far as it is digital. This is where EHRs come in. By 2019, the majority of physicians will have adopted a basic EHR system, and with good reason, too. EHRs may reduce outpatient care costs by 3 percent.
This “Electronic Health Records & the Data of Health Care” infographic from datascience@berkeley explores the health data revolution; if nothing else, I thought it was worth a share.
George Robinson, RPh, senior product manager, First Databank.
Approximately $20 billion is lost annually in the United States because of medication errors, with the average hospitalized patient subject to at least one medication mistake per day.Alert fatigue is often cited as a reason for these errors—even though alerts generated by clinical decision support (CDS) systems call attention to important information (such as potential drug interactions), excessive alerts wear clinicians down, resulting in boy-who-cries-wolf scenarios. The result: clinicians instinctively override the alerts instead of implementing an override monitoring plan.
Consider the following:
In 2009, researchers at the Boston-based Beth Israel Deaconess Medical Center and the Dana-Farber Cancer Institute looked at the safety alerts generated by 2,872 clinicians through 3.5 million electronic prescriptions over a nine-month period. Of the 233,537 alerts, 98 percent were drug-drug interaction issues, and more than 90 percent were overridden.
A more recent 2013 study, published in the Journal of the American Medical Informatics Association, showed improved override rates with only about half of alerts overridden by providers, with half of those overrides classified as appropriate. Authors concluded that further refinement of these alerts could improve relevance and reduce alert fatigue.
A Driver in Need of a Clearer View
The afore-mentioned studies conclude that clinicians are indeed overriding medication alerts at alarming rates. Although the industry has made significant progress in addressing alert fatigue during the time the data from these studies was being analyzed, these studies clearly support what most healthcare professionals already suspect: The practice of ignoring and overriding medication alerts is widespread and can potentially lead to undesirable consequences.
The term “patient engagement” has emerged as this year’s buzz phrase much the same way “patient portals” were a couple years ago and even similar to “electronic health records” and “meaningful use” before that. Volumes of articles, case studies, white papers and educational sessions have been dedicated to the topic of patient engagement and even at this years’ annual HIMSS conference patient engagement as a topic discussed was the rule and not the exception. With every step through the maze of booths in Orlando it seemed as if the words – “patient engagement” — were whispered and shouted from every direction.
Patient engagement is now synonymous with health IT, yet the topic is proving to be one of healthcare’s stickiest wickets because no matter whom or how many people you ask there seems to be a different response or definition to the term and how it is achieved.
With all of this uncertainty and confusion about patient engagement, I set out to see if I could define the term by asking a number of health IT insiders what they thought “patient engagement” meant, or what it meant to them. Their insightful and educational responses are what follow.
CrowdMed is a website that uses the “wisdom of crowds” to solve medical cases quickly and accurately online. We provide a place for patients to post their symptoms and broadcast their cases to our medical detective community, which includes doctors, med students and patients themselves. Our medical detectives collaborate to solve each case and suggest possible diagnoses. Our system assigns a probability to each diagnosis based on our research and the behavior of the medical detectives who worked on the case. Once enough medical detectives have participated in a case, we deliver an extensive report to the patient. Just like that, we’ve gotten a patent a second, third, 50th opinion without any invasive tests and unnecessary doctor visits.
We tested our system on cases with known diagnoses that cost patients hundreds of thousands of dollars, lasted many years, and taken dozens doctors to solve—my case included. We were able to solve these cases in a matter of weeks, at a fraction of the cost.
Now we’ve helped diagnose 200 of the world’s most difficult medical cases, and that’s only the beginning. By designing a site that simplifies complex medical data, connects patients with the people who understand this data, and uses statistics and technology to uncover answers, we’re making medical diagnoses more accessible to everyone.
Elevator pitch
We’re crowdsourcing medical diagnoses.
Founders’ story
During my junior year of college I got sick. My appetite disappeared. I had difficulty remembering things. I always felt cold, and I started losing my hair.
I visited the university health center. They sent me to a doctor, who sent me to a specialist, who sent me to more specialists for testing. I was biopsied, scanned and blood tested—often multiple times a month. The uncertainty, stress and financial burden this placed on me was crippling—especially as a college student.
After months of poking and prodding, I finally got my diagnosis: a thyroid disorder with a very simple treatment. I take one pill in the morning, every day. Compared to all the terrible possible diagnoses and treatments my doctors were considering, this was a huge relief. The process of finding the name for my condition, so that I could get the proper treatment, turned out to be far more painful than the treatment itself.
No matter what the discussion is or who you are talking with, this often seems to be the big question. It’s not enough to say “what;” what matters is, “What’s Next?”
Healthcare: This area is the largest, fastest growing and perhaps the fastest changing element of our economy and lives. As a result, just about every conversation we have about healthcare involves a “What’s next?” discussion.
At Fathom, we have the privilege of spending a lot of time exploring what’s next in healthcare marketing and communications. Based on our conversations, observations and research, here is a list of the top 10 tech trends every hospital and healthcare professional should know about.
Predictive analytics. Real time isn’t fast enough. Predictive analytics—or the systematic use of data to predict patient behavior—will usher a big shift in the quality of care. By analyzing hospital data, social media conversations and search patterns, hospitals can predict patient behavior and needs. Hospitals can predict and be ready for flu outbreaks. By analyzing historical admissions data, weather patterns and census data, hospitals can predict emergency room volume and staff for it. Healthcare systems can even look ahead 10 or 20 years and predict the need for cancer care or assisted-living facilities with population data.
Wearables. Wearable devices can monitor blood pressure, heart rate, insulin levels and more. Forget the simple devices we use today: The next generation of wearables will elevate health monitoring to the next level. All this information can also be shared in real time with a healthcare provider, making it part of a larger trend: Partnership between patients and providers.
Elevator pitch