The chest CT report was a bit worrisome. Henry had “pleural based masses” that had grown since his previous scan, which had been ordered by another doctor for unrelated reasons. But as Henry’s PCP, it had become my job to follow up on an emergency room doctor’s incidental finding. The radiologist recommended a PET scan to see if there was increased metabolic activity, which would mean the spots were likely cancerous.
So the head of radiology says this is needed. But I am the treating physician, so I have to put the order in. In my clunky EMR I search for an appropriate diagnostic code in situations like this. This software (Greenway) is not like Google; if you don’t search for exactly what the bureaucratic term is, but use clinical terms instead, it doesn’t suggest alternatives (unrelated everyday example – what a doctor calls a laceration is “open wound” in insurance speak but the computer doesn’t know they’re the same thing).
So here I am, trying to find the appropriate ICD-10 code to buy Henry a PET scan. Why can’t I find the diagnosis code I used to get the recent CT order in when I placed it, months ago? I cruise down the list of diagnoses in his EMR “chart”. There, I find every diagnosis that was ever entered. They are not listed alphabetically or chronologically. The list appears totally random, although perhaps the list is organized alphanumerically by ICD-10, although they are not not displayed in my search box, but that wouldn’t do me any good anyway since I don’t have more than five ICD-10 codes memorized.
Over the last few years, we have seen large EHR vendors purchase the moderate size EHR vendors, while moderate-size EHR vendors acquire smaller EHR vendors. We can expect to see a further decline in the number and diversity of EHRs as the IT mandates of Meaningful Use 2 and 3 are technically unachievable for all but the most well-endowed EHR vendors.
Along with the decreasing diversity of EHR options, an increasing number of physicians have lost the ability to choose the most important tool in their black-bag, their EHR, as many are now employed by large organizations which tell the physicians which EHR/HIT tools they are allowed to use.
If there was data that “Certified” EHRs, “Meaningful Use,” ICD10 and PQRS mandates had an impact on the cost or quality of healthcare which was commensurate with the IT costs and logistical disruptions, I would be the first to encourage physicians to use the new and proven technology. Unfortunately, we still do not know if “more” HIT is good for the healthcare system and society in general, or if it is only good for the IT industry.
In my work with hundreds of over stressed and burned out physicians, one thing is constant. Documentation is always one of their biggest sources of stress.
In fact, if you ask the average working doctor to make a list of their top five stresses, documentation chores will take up three of the five slots.
1. EMR – especially if you use multiple EMR software programs that don’t talk to each other
2. Dealing with lab reports and refill requests
3. Returning patient and consultant calls and documenting them adequately and all the other places information streams have to be forced together by the sweat of your brow.
The average doc is walking the cliff edge of overload on a significant number of office days in any given month. Now comes ICD-10 and my biggest fear is the extra work of the new coding system will push many physicians over the edge into burnout.
CMS releases a final rule updating the Medicare Shared Savings Program, which includes a new higher-risk, higher-reward Track 3 option; streamlines data sharing between CMS and ACOs; and adds a requirement that ACOs applying for the program describe how they will promote the use of health IT to boost care coordination.
Organizations Urge Stage 3 Delay
The AMA and MGMA join the AHA and CHIME in calling for a delay in finalizing Stage 3 Meaningful Use requirements. The current version is largely viewed as too burdensome for providers with the potential to impede the use of health IT to improve quality and efficiency.
Quite simply, Stage 3 will not be successful without provider buy-in. There have been delays before; look for another oneContinue reading…
The AMA and about 100 other physician groups urge CMS to develop an ICD-10 contingency plan in the event of a “catastrophic” backlog following the October 1 transition. The organizations want CMS to make public its plans to make advanced payments or reimbursements for services already rendered, work with ONC to ensure EHR systems are ICD-10 ready, and confirm contractors won’t audit for the correct code.
The silver lining here is that these organizations are (finally) not asking for a delay in implementing ICD-10. CMS apparently has drafted a contingency plan in the event of claims process disruptions but does not plan to make it public. In this age of more transparency, CMS needs to make the plan public – even though provider groups will surely find fault with the plan. But, isn’t it better to continue moving the conversation forward, just in case of there is a catastrophe?
CMS reports that the majority of physicians who will be penalized this year for not having met MU requirements will lose less than $1,000 of their Medicare reimbursement; 34% of the penalties will be $250 or less, while 31% will exceed $2,000.
The adjustments will impact approximately 257,000 eligible providers. While no one likes losing money, the CMS penalty “stick” is pretty small compared to the overall cost of implementing an EHR.
Mayo Provides Dr. Google with 2nd Opinion
Google consults with the Mayo Clinic to expand its healthcare information for 400 medical conditions.
Given that 20% of all Google searches are related to health conditions, the change will no doubt shake up what Americans find when searching for medical information. The update includes the addition of illustrations for each condition, plus a full list of search results from sites such as WebMD and Wikipedia.
CMS recently announced another change to health IT policy in order to offer healthcare providers greater flexibility. But what will the unintended consequences of this latest change be?
Over the Labor Day weekend, CMS announced that the Meaningful Use Stage 2 deadline will be extended through 2016 in order to offer more options and greater flexibility to providers for the certified use of EHRs. In the interest of full disclosure, I found the timing to be strange— a rule published over a holiday weekend seems an odd choice, particularly when it is being touted as a benefit to the industry and the impact on healthcare provider organizations and clinicians, alike, is monumental.
Unfortunately, I think the additional flexibility allotted by this rule is the latest example of the unintended consequences of health IT regulations. In an effort to make things easier and give healthcare providers more leeway, they have, in fact, made the situation unnecessarily more complex.
Agility is not healthcare’s strong suit
It seems at this point, too many options, or waffling between them (for instance the new ICD-10 transition deadline), can be more crippling than stringent regulations, particularly when there is so much on the line. Healthcare organizations don’t have the wherewithal to vacillate with implementations; they are wrestling with string-tight budgets and constantly shifting rules require large cultural and behavioral changes. As a result, as Dr. John Halamka noted, health IT agendas are being constantly hijacked by regulatory changes, such as Meaningful Use and ICD-10.
It now seems that hospital administrative teams and physicians again must endure constantly shifting rules that they’ve been coping with for years under Meaningful Use. As Dr. Ben Kanter, former CMIO of Palomar Health, so astutely noted “A computer system is a tool, just as a scalpel is a tool. What if a surgeon’s scalpel changed every few weeks? How is it possible to deliver good care if the primary tool you are using keeps changing on an irregular basis?”Continue reading…
The health care field is in the grip of a standard that drains resources while infusing little back in return. Stuck in a paradigm that was defined in 1893 and never revised with regard for the promise offered by modern information processing, ICD symbolizes many of the fetters that keep the health industries from acting more intelligently and efficiently.
We are not going to escape the morass of ICD any time soon. As the “I” indicates in the title, the standard is an international one and the pace of change moves too slowly to be clocked.
In a period when hospitals are gasping to keep their heads above the surface of the water and need to invest in such improvements as analytics and standardized data exchange, the government has weighed them down with costs reaching hundreds of thousands of dollars, even millions just to upgrade from version 9 to 10 of ICD. An absurd appeal to Congress pushed the deadline back another year, penalizing the many institutions that had faithfully made the investment. But the problems of ICD will not be fixed by version 10, nor by version 11–they are fundamental to the committee’s disregard for the information needs of health institutions.
Disease is a multi-faceted and somewhat subjective topic. Among the aspects the health care providers must consider are these:
Disease may take years to pin down. At each visit, a person may be entering the doctor’s office with multiple competing diagnoses. Furthermore, each encounter may shift the balance of probability toward some diagnoses and away from others.
Disease evolves, sometimes in predictable ways. For instance, Parkinson’s and multiple sclerosis lead to various motor and speech problems that change over the decades.
Diseases are interrelated. For instance, obesity may be a factor in such different complaints as Type 2 diabetes and knee pain.
All these things have subtle impacts on treatment and–in the pay-for-value systems we are trying to institute in health care–should affect reimbursements. For instance, if we could run a program that tracked the shifting and coalescing interpretations that eventually lead to a patient’s definitive diagnosis, we might make the process take place much faster for future patients. But all a doctor can do currently is list conditions in a form such as:
E66.0 – Obesity due to excess calories
E11 – Type 2 diabetes mellitus
M25.562 – Pain in left knee
The tragedy is that today’s data analytics allow so much more sophistication in representing the ins and outs of disease.Take the issues of interrelations, for instance.
European health care systems are already awash in “big data.” The United States is rushing to catch up, although clumsily thanks to the need to corral a century’s worth of heterogeneity. To avoid confounding the chaos further, the United States is postponing the adoption of the ICD-10 classification system. Hence, it will be some time before American “big data” can be put to the task of defining accuracy, costs and effectiveness of individual tests and treatments with the exquisite analytics that are already being employed in Europe. From my perspective as a clinician and clinical educator, of all the many failings of the American “health care” system, the ability to massage “big data” in this fashion is least pressing. I am no Luddite – but I am cautious if not skeptical when “big data” intrudes into the patient-doctor relationship.
The driver for all this is the notion that “health care” can be brought to heel with a “systems approach.”
This was first advocated by Lucien Leape in the context of patient safety and reiterated in “To Err is Human,” the influential document published by the National Academies Press in 2000. This is an approach that borrows heavily from the work of W. Edwards Deming and later Bill Smith. Deming (1900-1993) was an engineer who earned a PhD in physics at Yale. The aftermath of World War II found him on General Douglas MacArthur’s staff offering lessons in statistical process control to Japanese business leaders. He continued to do so as a consultant for much of his later life and is considered the genius behind the Japanese industrial resurgence. The principal underlying Deming’s approach is that focusing on quality increases productivity and thereby reduces cost; focusing on cost does the opposite. Bill Smith was also an engineer who honed this approach for Motorola Corporation with a methodology he introduced in 1987. The principal of Smith’s “six sigma” approach is that all aspects of production, even output, could be reduced to quantifiable data allowing the manufacturer to have complete control of the process. Such control allows for collective effort and teamwork to achieve the quality goals. These landmark achievements in industrial engineering have been widely adopted in industry having been championed by giants such as Jack Welch of GE. No doubt they can result in improvement in the quality and profitability of myriad products from jet engines to cell phones. Every product is the same, every product well designed and built, and every product profitable.