In this article by Tom Emerick and David Toomey, founders of Thera Advisors, we describe the net effect of ACA. The healthcare industry is changing – same old headline. You have read of all the buzz regarding ACOs, PCMH, ACA, and every other acronym.
In this article by Tom Emerick and David Toomey, founders of Thera Advisors, we describe various ways to define healthcare quality. In a previous article, we referenced CMS’s new provider reimbursement model, called Medicare Access and CHIP Reauthorization (MACRA), which replaces the current reimbursement formula.
In this article by Tom Emerick and David Toomey, founders of Thera Advisors, we describe the phenomenon of healthcare illusions. The New England Journal of Medicine carried an excellent article by David Casarette, MD, on the topic of health care illusions and medical appropriateness. Click here
Did you ever hear the old joke where the boss says floggings will continue until morale improves? Flogging the data until results improve…or the data confesses…is not uncommon. Too bad. In my career I’ve worked with companies with over 100k covered lives the claim costs of which could swing widely,
In this article by Tom Emerick and David Toomey, founders of Thera Advisors, we describe good uses of health plan data and discuss the limitations of health plan data. As you think about claims data, the information is capturing the services provided to a patient by
In this article by Tom Emerick and David Toomey, founders of Thera Advisors, we describe the net effect of ACA.
The healthcare industry is changing – same old headline. You have read of all the buzz regarding ACOs, PCMH, ACA, and every other acronym. Since we’ve been in the industry, the “unsustainable” cost increases have been the talk every year, yet somehow we have not reached a tipping point. So what’s different now? How has ACA impacted the healthcare industry, and more specifically the insurance companies?
The drafters of ACA set up a perfect adverse selection scenario – come one, come all, with no questions asked. First objective met – 20 million individuals now have coverage.
Next objective – provide accurate pricing for these newly insured. Insurance companies have teams of individuals who assess risk, so they can establish an appropriate price for the insurance protection. We experience this “underwriting’ process with every type of insurance – home, life, auto. In fact, we see this process with every financial institution, like banks, mortgage companies, credit card companies, etc. If a financial institution is to serve (and an insurance company is a financial entity), it has to manage risks, e.g., loan money to people who can repay the loan. Without the ability to assess the risk of the 20 million individuals, should we be surprised that one national insurance carrier lost $475M in 2015, while another lost $657M on ACA-compliant plans? Now if you’re running a business and a specific line has losses, your choices are pretty clear – either clean it up or get out.
Risk selection is complex. When you add this complexity to the dynamics of network contracting tied to membership scale, there is a reason numerous companies have made the decision to get out of health insurance. In 1975, there were over 2,000 companies selling true health insurance plans, and now there are far fewer selling true health insurance to the commercial population. Among the ones that got out were some big names – MetLife, Prudential, Travellers, NYLife, Equitable, Mutual of Omaha, etc. And now we’re about to be down to a few national carriers, which is trending consistently with other industries – airline, telecommunications, banking, etc.
Let’s play this one out for the 20M newly covered individuals. The insurance companies have significant losses on ACA-compliant plans. Their next step – assess the enrolled risk, and determine if they can cover the expected costs. For those carriers that decide to continue offering ACA-compliant plans, they will adjust the premiums accordingly. While the first year enrollees are lulled into the relief of coverage, they then get hit with either a large increase or a notice to find another carrier. In some markets, the newly insured may be down to only one carrier option. The reason most individuals do not opt for medical coverage is that they can’t afford it. If premiums increase 15% or more, how many of the 20M have to drop coverage because premiums are too expensive? Do we start the uninsured cycle all over again?
Net net, ACA has enabled more people to have health insurance, but at prices that are even less sustainable than before. ACA offers a web of subsidies to low income people, which simply means each of us, including businesses, will be paying for part or all of their premium through taxes. As companies compete globally, this additional tax burden will impact the cost of services being sold. As our individual taxes increases, we reduce our spending. While ACA has the right intention of expanded coverage, the unintended consequences of the additional cost burden on businesses and individuals will have an impact on job growth.
While it’s hard for anyone to dispute the benefits of insurance for everyone, we first need to address the drivers behind the high cost of health care, so we can get the health insurance prices more affordable. Unfortunately, ACA steered us further in the wrong direction. Self-insured employers are the key to lead the way in true reform of the cost and quality of healthcare.
Tom Emerick and David Toomey are founders of Thera Advisors. Their focus is to help employers maximize their role as the purchaser of healthcare services in working with suppliers to impact their population’s health and to lower costs.where can i play roulette online for money Illinois mortgage lender casino online online casino with fast payouts
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In this article by Tom Emerick and David Toomey, founders of Thera Advisors, we describe various ways to define healthcare quality.
In a previous article, we referenced CMS’s new provider reimbursement model, called Medicare Access and CHIP Reauthorization (MACRA), which replaces the current reimbursement formula. MACRA will include an incentive component that will replace the incentive programs in plans today, and the details of the performance criteria are being determined for roll-out in 2019. From the providers’ lens, they are faced with the need to hire more administrative resources to keep up with the tracking of their performance, and the big question is – are consumers making different choices based on the performance results of a physician or hospital? When there are over 150 different measures in place today, how is an occasional consumer of healthcare services able to assess the most important criteria in finding the right physician?
During a recent employers’ conference on the east coast, the forum featured two panels consisting of the healthplans and the providers. The panels were set in a Q&A format to enlist the leaderships’ views on various topics facing the employers, and it was a fascinating dialogue that we have attempted to capture below.
In the first panel with the execs of five major carriers, the opening question asked for a one minute overview of their healthplan’s area of focus in addressing the employers’ challenges. The responses were consistent amongst the leaders – the focus is on the individual consumer and value-based contracting. When we evolved the discussion into quality criteria and outcomes to identify high performing physicians, the leaders acknowledged that defining quality and outcomes is a challenging endeavor, and each health plan has their own formula to assess the providers’ performance. One commented that a physician practicing in the morning could be viewed as a top performer by a carrier, while that afternoon, they could be ranked as a poor performer by another, even though the physician was delivering the same process of care for all their patients. They agreed that the employers really needed to weigh in on what was important to them, so there was greater consistency in the scoring logic with the physician community.
The next panel was with the Chief Medical Officers (CMO) from the major systems and a primary care practice. There were a number of relevant learnings from this panel. There was unanimity around the frustration with the variation in the quality metrics being used by commercial carriers and CMS. One physician commented that he had never been asked for input on the quality metrics, and he was ready to engage in that discussion. The physician leaders asked for the employers to outline what was important to them, so there could be a common set of standards for the commercial market – a consistent request from the leaders of both healthcare stakeholders.
Two of the CMOs were primary care physicians, and they both acknowledged that we have not given enough attention to the resource that has the greatest opportunity to lower employers’ costs – the family doctor. The primary care physicians can build trusting relationships with employees; they can help avoid the unnecessary services being provided; and they can help educate and channel the patients into the appropriate specialist, when they are equipped with quality and cost information.
The CMO from the largest health system acknowledged that there was 30% variation (aka waste) in the way care was being delivered within the community, and there was opportunity to improve the results. If we know there is variation in care even with performance-based contracts in place, what is the catalyst to get serious on consistency? Are there any other services that you purchase with a 30% variance? Would you continue spending money for that service knowing there is wasted spend?
After the event, there was a conversation with an employer, and we discussed the employers’ opportunity to help shape and to define the quality metrics. This employer stated that he did not have experience or knowledge on how to establish criteria, and he was surprised to hear that the healthplans were looking for his guidance since he thought it was their role. When the discussion moved to their overall business, he acknowledged that their internal business units established the quality criteria in assessing their vendors’ performance.
So how do we move beyond the billboards and the marketing campaigns to understand the healthcare suppliers’ performance? Who has the greatest opportunity to drive change in a free market system? We believe the one paying the bill has the ability to drive a more consistent outcome for high quality, cost effective healthcare. Let’s recognize and reward the physicians who are delivering a six sigma approach to healthcare, so the other suppliers will be motivated to change. It’s time for employer-driven healthcare.
Tom Emerick and David Toomey are founders of Thera Advisors. Their focus is to help employers maximize their role as the purchaser of healthcare services in working with suppliers to impact their population’s health and to lower costs.online roulette canada ramus,com,au/113-european-roulette-online-flash online keno ri
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In this article by Tom Emerick and David Toomey, founders of Thera Advisors, we describe the phenomenon of healthcare illusions.
The New England Journal of Medicine carried an excellent article by David Casarette, MD, on the topic of health care illusions and medical appropriateness. Click here to read the full article. Hats off to Bob Stauble for a heads up on this article.
Casarette observes that humans have a tendency to see success in what they do, even if in truth there is none. Casarette writes, “Psychologists call this phenomenon, which is based on our tendency to infer causality where none exists, the ‘illusion of control’.” This illusion applies in all walks of life, especially in politics and parenting, and it includes medical care as well.
In medical care, the phenomenon has been referred to as “therapeutic illusion“, and it impacts both doctors and patients. Undoubtedly, therapeutic illusion is why placebos can so effective.
In one clinical study, faux surgery worked as well or better than an actual surgery for the treatment of specific conditions. If patients perceive they need surgery or a procedure, e.g. for knee pain, even though it may not be medically appropriate, some will search for a surgeon who can validate the need and perform the surgery.
Casarette further writes, “…physicians also overestimate the benefits of everything from interventions for back pain to cancer chemotherapy.” Of course, that’s simply a form of confirmation bias.
Casarette’s article is most interesting to us. Why? We’ve often felt that doctors who perform unnecessary surgeries have ethical problems. The reality is that it may be a little more complicated than that. When you throw in confirmation bias, the surgery decisions may have a subconscious influence.
The attention today is on value-based contracting and data analysis. A group of 20 national employers have come together to share data, so they can assess the healthcare supply chain. As noted in our last blog post, analyzing big data is complex, especially since claims data are just a collection of medical bills. How are employers assessing medical appropriateness? What reports can be generated to assess a need for care?
As we know, price X volume = costs. Medicare generally has more aggressive discounted prices than commercial plans, but there is still significant cost variation – in 2014, one states’ Medicare costs was $6,631 per capita while another was $10,610. A big driver – variation in volumes.
Toomey had an interesting conversation with the Chief Medical Officer (CMO) of a major health system. He relayed that his wife was having pain in her hand, so they scheduled an appointment with one of their system’s highly recommended specialists. The specialist looked at the wife’s hand, and after a few minutes, he stated that she needed surgery. Since the specialist did not know he was a physician, the CMO questioned how the specialist could arrive at a diagnosis from just looking at a hand, and the response was, “based on his years of experience.” They got a second opinion and opted for the recommended therapy instead, which solved her issue.
Healthcare involves people – patients, physicians, and other providers, and the human element makes it even more complex. So how do those involved in healthcare address the variation in medical care that is driving up costs? We are biased – we believe the employers are the catalyst to drive change for increased consistency by working collaboratively with suppliers (think six sigma). It’s time for change.
Tom Emerick and David Toomey are founders of Thera Advisors. Their focus is to help employers maximize their role as the purchaser of healthcare services in working with suppliers to impact their population’s health and to lower costs.
Did you ever hear the old joke where the boss says floggings will continue until morale improves? Flogging the data until results improve…or the data confesses…is not uncommon. Too bad.
In my career I’ve worked with companies with over 100k covered lives the claim costs of which could swing widely, from year to year, all because of a few extra transplants, big neonatal ICU cases, ventricular assist cases, etc.
Here are just a few of the huge single case claims I’ve observed in recent years:
- $3.5M cancer case
- $6M neonatal intensive care
- $8M hemophilia case
- $1.4M organ transplant
- $1M ventricular assist device
This is not a complaint. After all this is what health insurance should be about, huge unbudgetable health events.
All plans have one organ transplant every 10k life years or so, most of which will cost about $1M over 6 years. A plan with 1k covered lives will have such an expense on the average of every 10 years. Of course the company may have none for 15 years and two in the 16th year. The same goes for $500k+ ventricular assist device surgeries.
Looking at claims data for small groups is perilous, sometimes for large groups as well. Because of the high cost and relative infrequency of so-called “shock” claims, those over $250k, you need about 100k life years for the claims data to be even approximately 75% credible. When a group with 5k lives said they did something that cut the claims costs, they can’t really know if the change made a significant difference for a couple of decades.
Here is an example. A smallish group, about 3k covered lives asked me to help calculate how much their wellness plan was saving. They had all employees listed in three tiers: active wellness participants, moderate participants, and non-participants. I warned them they didn’t have enough data to be credible but they proceeded anyway. They expected active users would have the lowest claim costs and so on. When the data were reviewed, there was perfect reverse correlation. Active wellness users had the highest claim costs, moderate users had the next highest costs, and non-participants the lowest. In their final report, which I had nothing to do with preparing, and from which I had recused myself, they subtracted out big claims by the active and moderate users to get the results they wanted. In short they flogged the data until it confessed. Alas.
One large company claimed huge reductions in plan costs by adding a wellness program. It turns out during that period in question they also implemented an “early out” incentive. Upon examination, the early out program resulted in a big reduction in the number of older employees which more than accounted for the reduction in claims costs.
Here is yet another example. I was in a conference a few years ago in which a presenter from a small company, about 1k covered lives, claimed to have kept their health costs flat for five years through wellness initiatives. While he got a big ovation, his numbers just didn’t add up. I asked him a few questions after his speech about what other changes he made during that period. He said they lowered their “stop loss” limit from $100k to $50K a few of years earlier. Then he admitted to excluding his stop loss premium costs, which were skyrocketing, from his presentation. With a little bit of mental arithmetic I added that back in, which revealed his company’s total health costs were going up at the same rate as everyone else’s, perhaps even a little higher. Hmmm. I don’t think he deliberately mislead the audience. He just didn’t know better. When you hear boasts of big short-term impacts of wellness programs, beware of confirmation bias.
When a company claims they implemented something that caused their health plan costs to drop 15% or so, ask a few questions:
- The big question is did the company adjust for plan design changes, such as raising deductibles and copays, that merely shifted costs to employees?
- Did the changes really save claim dollars?
- Did they factor in stop loss premiums?
- How many life years of data did they observe?
- Did the company exclude large or “shock” claims? (This is not uncommon, especially among wellness vendors.)
- Did it experience any big changes in demographics, such as through implementation of an early retirement program or layoffs that impacted older workers the worst?
When I’ve asked those kinds of questions, I’ve almost never seen a big claim of cost reductions by a small company hold up under scrutiny, and same for some big companies too.
Today flogging the data to get the desired results is all too common. That’s no surprise. They keep catching academics and big pharma doing the same thing. Skepticism is in a good thing.
Tom’s latest book, “An Illustrated Guide to Personal Health”, is now available on Amazon.mega fortune jackpot at an online casino kapish,com,au/8979-play-online-blackjack-no-download online casino allowing u s players
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In this article by Tom Emerick and David Toomey, founders of Thera Advisors, we describe good uses of health plan data and discuss the limitations of health plan data.
As you think about claims data, the information is capturing the services provided to a patient by a healthcare provider for preventive care or for the diagnosis or the treatment of a condition. This information can be grouped by different cohorts—those getting preventive exams, those examining categories of care, or those that seeing specific physicians and/or hospitals for conditions. These data, for example, can be grouped by diagnoses, called a diagnosis related group, involving a hospital stay. However, all claims data is just a collection of medical bills. Medical bills do not contain a complete look at the patient, such as important information as a patient’s prognosis. That’s a gap. Thus, it is important to set appropriate expectations on the use of the data.
Number 1 (one of the most important): Avoid the averages
Most claims data sets are not normally distributed, so the averages do not provide relevant information. In most discussions today, employers evaluate the average cost of employees with specific conditions, e.g., diabetes or high blood pressure. This is a flawed approach because spending by employees with various chronic conditions is skewed, thus not really “averageable”. For example, assume 90% of an employee population with diabetes is spending $10,000/year and 10% is spending $250,000/year, the average will be a meaningless $34,000/year. All too often, a wild goose chase ensues, when in fact the focus should be on the $250,000 cohort to understand why they were so much more expensive.
Number 2: Follow the money
A superior use of claims data is to look at distributions of spending. In most plans today, roughly 8% of enrollees are consuming 80% of plan dollars, and these 8% typically change every twelve to eighteen months. (We still run into benefit managers who were unaware of that.) The future belongs to micro-managing these “outliers”, rather than the 92% who spend only 20% of the dollars. If you study those outliers carefully, you will find that only about 7% of their spending possibly would have been preventable, and then only if they faithfully did what their doctors told them to do decades earlier. A cardiologist recently told me that of the patients he has seen with a significant acute blockage, about 25% had no known health risks of any kind…no high blood pressure, cholesterol, diabetes, obesity, no smoking, no genetic predisposition, etc. As such, there is a component of randomness in terms of many who gets blocked arteries. The same holds true for cancer. For the other 75%, their physicians have usually counseled them on the importance of exercise and nutrition and the dangers of tobacco use, but to no avail.
Number 3: Realize the limitations for quality designations
Yet another big error is trying to use claims data to determine the best quality doctors. You better be really, really talented to try that one. Why? We are in an era in which many doctors are making their “quality” and “outcomes” look better by referring their most complex and risky patients to someone else. (Much has been written about this.) On the other hand, there are highly effective doctors, who take responsibility for their riskiest patients, but as a consequence score poorly on so-called “quality measures”. The real travesty is that the low scoring doctors ironically may be the most cost-effective and provide the best care.
Number 4: Misdiagnoses are a real cost driver
Another huge shortcoming of claims data is one that Readers of Cracking Health Costs know about. Namely, a large number of patients with complex health problems are simply misdiagnosed – today, that’s about 20% of the outliers in benefit plans accounting for 18% of claim dollars. Thus, you cannot rely on diagnoses in claims data, and you cannot tell who is getting diagnoses right or wrong – this takes detective work beyond claims data. Click here for a good article by the Mayo Clinic on rates of misdiagnoses. We have sent hundreds of people to the Mayo Clinic for second opinions and can verify by personal experience the truth in that article…same for other clinics we have used for employers. Our first rule in selecting a Center of Excellence is its success in correctly diagnosing patients with complex health problems. Huge amounts of claim dollars are spent on treatments or surgeries that are either completely erroneous or clearly suboptimal. An executive at a Fortune 100 company once said to me that the biggest quality failure in healthcare is to misdiagnose a patient…everything that follows harms the patient.
Number 5: Coding can impact the data analysis
During a data analysis for a very larger employer, over 250k covered lives, they told me they had not paid for a solid organ transplant in a number of years. Based on their size, they should have been paying for about 25 a year. After further detective work, we discovered their consultant was using a DRG grouper that coded all transplants as ventilator cases…who knows why…but a huge error. The benefit team had no idea they were really paying for about 25 a year at an average cost over five years of about $1,500,000 each.
Number 6: Reversion to the mean One thing we’ve learned from years of claims analysis of big companies’ benefit programs is that if you have enough life years of data, it all looks about the same, i.e., it reverts to the mean. If the workforce is comparatively older, they will have somewhat more high cost claims.
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By David Toomey and Tom Emerick
In most healthcare discussions today, “the exchange” is usually referenced as a solution to address the employers’ health and cost challenges. The exchange model is now being offered by carriers, by consulting firms, and by independent companies. Per Accenture, the enrollment in private exchanges have exceeded 6M in 2015, and it’s projected to be at 40M by 2018.
Since the age of consumerism began back in the early ‘90’s, the theory has been that if we can transform employees into consumers of healthcare services, the free market will drive out the price variation amongst the providers as patients question the cost of services. As more employers have increased deductibles, many are still waiting for their employees to become a healthcare consumer. The reality is that healthcare is complex, so individuals are challenged with deciphering the medical terminology and obtaining the actual price for a specific service, especially when majority of people access the healthcare system infrequently. So is the exchange the answer for consumerism to take hold?
At a recent exchange conference, there were national experts discussing the impact of the exchanges. After hearing the various messaging and the statistics from the presenters, it became clearer that the value of the private exchange is basically an administrative platform designed to give individuals plan and program choices, so they can make the right decisions based on their needs. Now the concept of giving employees’ choices and allowing them to make a personalized decision is not new–cafeteria plans have been around for 25+ years.
Cafeteria plans in the 90’s had some big problems. The main problem was serious adverse selection between the plans. When you have big bills planned, you switch to the “richest” plan, and then switch to a low cost option later. When this happens, the “sponsor” gets shorted on payroll deductions as well the spread of the costs amongst those not using services. It will be interesting to see if the exchanges have a better design these days.
When questions were posed to the exchange experts on whether the data was showing an impact to the healthcare decisions and to the health of the population, the consistent response—we’re not sure. Now cafeteria plans/exchanges can serve a purpose when an employer is interested in giving a diverse employee population choices. It’s important not to get caught up in the marketing that an administrative platform is going to solve the healthcare challenges confronting employers today. As we discussed in Part 5 of this series, the marketing around value-based contracts/ACOs has also positioned that concept as a solution, when in reality, performance contracts with provider have also been around for 25+ years.
Employers continue to be faced with about 8% of their population consuming 80% of the total spend, and there is a new 8% every 12-18 months. Is it time to get back to the basics? Should the focus be on finding the right physicians committed to delivering evidence-based healthcare, and then ensuring that patients are accessing care from these providers? When providers see that employers are truly committed to supply chain management, we can expect the process of care to change significantly, and there will be a commitment to removing the non-value added waste from the system. As with many other industries, the ultimate purchaser has the ultimate power by working with the interested suppliers to improve the process and to impact quality and costs.
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This is the title of an article by Jack Craver in benefitspro.com. Hats off to Al Lewis for contributing to and socializing this article.
The article describes how work stresses are a huge root cause illness and increased mortality rates.
I urge you to read the full article. It’s a gem.
Tom’s latest book, “An Illustrated Guide to Personal Health“, is now available on Amazon.
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By David Toomey and Tom Emerick
Readers of Cracking Health Costs know that healthcare is a big business. It’s both complex and consuming, and an ever greater share fo GDP in the US, while our health outcomes are falling behind our peer countries.
According to the 2015 Health Care Services Acquisition Report, the deal volume for the health care services sector rose 18%, 752 transactions in 2014, for a total of $62 billion; physician acquisitions accounted for $3.2 billion of the total. As healthcare suppliers continue to consolidate, what does this mean for the employers who pay for these services?
With the attention around value-based contracts and ACOs, we should expect the number of “ACO” contracts will continue to expand beyond the 750 in existence today. While the value-based concept sounds good, Dr. Eric Bricker’s blog pointed out that 41% of all physicians did not know if they participated in an ACO, as referenced in the February 10, 2016, issue of Medical Economics magazine. Is there real motivation to change?
As noted in the February 24, 2016, Health Affairs’ blog, hospital mergers have average price increases over 20%, while physician prices increase nearly 14% post-acquisition. The result: the value-based contracts will be based on higher fee levels for the combined entities.
In the last Seattle example (Part 3 in Series), the provider we mentioned built a strong market reputation, which resulted in their ability to command higher per unit fee levels.
When that provider enters into value-based contracts, their future renewal increases will be based on their ability to hit mutually agreed upon cost targets based off a higher fee level with the insurance companies. While the per unit price is important, the Seattle provider’s biggest opportunity is to establish a more consistent process of care among their physicians for the treatment of patients by condition, so employers stop paying for the wide variation in the treatment and for the unnecessary care being provided.
Here’s what we know: 1) there has been value based contracting, 2) there has been data to assess performance, and 3) yet there remains extremely wide variation in care among providers, especially for patients with complex health problems. Where such variation exists in healthcare, and such variation is ubiquitous, many people are getting substandard care.
So why is there still variation? If you sold a consumer product, like a flat screen TV, that had wide variation in results yet commanded a premium price, how motivated are you to change your process if sales remain at strong levels? In the TV example, there is ample competition to purchase another TV brand if the TV is over-priced or has poor results.
In self-insured benefit plans most employers have not had an appetite to take tough but necessary steps to engage in “disintermediation” ( Wiki definition of disintermediation) with those prices and quality differences. Benefit managers generally want the best care for their employees, but about half the providers in their networks are below average.
It’s high time for employers to replicate how purchasers in other industries have collaborated with their suppliers in addressing the process and quality variations, and cost inefficiencies too.
In fact this kind of approach is way overdue.
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By David Toomey and Tom Emerick
Over the last few years, the latest buzz in the healthcare industry has been Accountable Care Organizations (ACOs), and the next wave will be the promotion of “value-based contracting”. These are similar approaches, different words.
Generally, an ACO is formed around a physician group or a hospital linked to physicians. The basic concept is for the provider system to be accountable for patients, and the providers are financially motivated to impact their patient population’s overall costs. Makes sense, right?
For the past 25 or so years, physicians have been linked to Independent Practice Associations, Medical Groups, and Management Services Organizations. Many of these provider organizations have had financial incentives tied to performance. Data have been available to assess physician performance. So what’s different now?
Today the Feds are re-emphasizing performance in their physician contracting under the new Medicare Access and CHIP Reauthorization (MACRA), which replaces the current reimbursement formula.
Beginning in 2019, the existing incentive programs now used for Medicare physicians will be replaced by a new performance-based model with four components. Those components are 1) quality, 2) resource use, 3) meaningful use of technology, and 4) clinical practice improvement.
Based on the Medicare physicians’ results, the reimbursements can be decreased by as much as 4% (adjusting to 9% by 2022). The program will have upside incentive for achieving exceptional performance up to 12% in 2019.
As the largest purchaser, Medicare is striving to establish per unit cost consistency in every market. Yet Medicare’s 2014 costs vary from $6,631 to $10,610 across markets. Why? Even if the cost per unit of service is standardized, extremely wide variation exists in how patients are treated for given conditions. When wide variation in care plans exists, some are right and some are wrong, as regular readers of Cracking Health Costs know. Some are better and some are worse. Period.
It’ll be interesting to see if the four new performance measures under MACRA will have a better impact than what’s in place today.
Self-insured employers don’t need to wait four or five years to see the results. They can leverage their purchasing scale with the providers to drive out both inappropriate care and unit price variations. The time to start is now.
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One of the myriad reasons workplace wellness is not performing well is that all humans have about 100 risk factors, of which obesity, high blood sugar, high blood pressure, and high cholesterol are only four. If those four are in pretty good shape but the other 96 are out of whack, don’t expect good health results.
Further, putting bandages on symptoms of metabolic disease has limitations. Such bandages do not address the root causes of metabolic syndrome. According to Wiki, “Root cause analysis (RCA) is a method of problem solving used for identifying the root causes of faults or problems. A factor is considered a root cause if removal thereof from the problem-fault-sequence prevents the final undesirable event from recurring; whereas a causal factor is one that affects an event’s outcome, but is not a root cause. Though removing a causal factor can benefit an outcome, it does not prevent its recurrence within certainty.” (Emphasis mine.)
One thing sorely missing from most modern wellness methods is RCA. Unless one deals with RCA in metabolic syndrome it will continue to recur.
Some other huge health risks factors are job misery, terrible marriages, very poor money handling skills, envy, general lack of contentment in life, and loneliness. Another health risk is how far you live from a “dial-911-first-responder”. Yet another is how safe your neighborhood is. I could go on and on. Worksite wellness does nothing to address the vast majority of personal health risks. My book, An Illustrated Guide to Personal Health*, elaborates on such health risks.
This article will cover just one of those risks, loneliness which among other things is a root cause of metabolic syndrome. (Let’s hope this information does not inspire true believers in wellness penalties to look for ways to charge lonely employees higher payroll deductions.)
Loneliness harms your immune system, makes you depressed, impacts cognitive skills, and can lead to heart disease, vascular disease, cancer, and more. Loneliness is roughly the health risk equivalent of being a diabetic who smokes and drinks too much. Read on.
An article in the National Science Foundation explores the health hazards of loneliness. Click here to see the full article. According to this article, “Research at Rush University has shown that older adults are more likely to develop dementia if they feel chronic loneliness.”
Moreover, John Cacioppo, neuroscience researcher of the University of Chicago, says of loneliness, “One of the things that surprised me was how important loneliness proved to be. It predicted morbidity. It predicted mortality. And that shocked me.”
Dr. Sanjay Gupta recently wrote, “The combination of toxic effects [of loneliness] can impair cognitive performance, compromise the immune system, and increase the risk for vascular, inflammatory, and heart disease.”
According to studies in Europe, loneliness has about the same health risk as obesity.
Per an article in Caring.com, “A 2010 Brigham Young University review of studies involving more than 300,000 people concluded that loneliness is as unhealthy as smoking 15 cigarettes a day or being an alcoholic.
This is a headline in the UK’s Express: “Loneliness is as big a KILLER as diabetes”. The article describes how loneliness is like a deadly disease that decreases life expectancy and makes you more susceptible cancer, heart disease, and stroke. The study behind that was published in the Proceedings of the National Academy of Science.
Here are some personal observations:
Why do many people have so few friends as they age?
- Maintaining long-term friendships takes a lot of work and investment of time.
- Don’t let your career stand in the way. Don’t wait for someone to befriend you; reach out.
- Some people have invested their time and energy solely in a spouse, who may predecease them by 25 years, or in children who fly the nest in time.
- Many people have invested much in work-related friendships, which, while genuine at the time, can wilt almost immediately when they retire or move on.
- In friendships, one has to give more than he or she takes. Make yourself likable. Who wants to spend time with someone who complains all the time? People like that are often avoided by people around them.
- Be a good listener.
- If you’re lonely, try joining something…a place of worship, a book club, a hiking club, anything. In every community are places everyone is welcome.
In the end, a true measure of your wealth is the number of lifelong friends you have. Having lifelong friends is a joy and a perfect cure for loneliness.
*Coauthor is Robert Woods, PhD.
Tom’s latest book, “An Illustrated Guide to Personal Health“, is now available on Amazon.online gambling sites online poker Online casinos usa bonus online blackjack mastercard
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