In the dust-up about “rebooting” the EHR meaningful use incentive program, “the Emperor has no clothes” has been the most interesting response.

Cover of Reboot Meaningful Use ReportLast month, six Republican senators released a document entitled “Reboot: Reexamining the strategies needed to successfully adopt health IT.” The report asserts that the original goal of the $35 billion EHR meaningful use incentive program was to achieve “interoperability,” creating a “secure network in which hospitals and providers can share patient data nationwide.”  The report expresses concerns that the meaningful use incentives and federal HIT policy in general are not achieving this interoperability goal and are instead increasing costs, leading to waste and abuse, threatening patient privacy, and leading to unsustainable IT infrastructure.

Since then, a number of parties have offered written responses, including the American Hospital Association, the Texas Medical Association, a consortium of consumer groups,  a group of EMR vendors and the “Healthcare Innovation Council.”  Both the senators’ document and virtually all of the responses agree with the premise that the health care system needs to be improved, and that improvements to health information technology are a necessary component of any effort to improve the health care system.  Almost all parties also agree that the $18.5 billion spent so far on stimulating EMR roll-out has not yet led to any great improvement in the health care system.  But, different parties express very different views about whether the incentive program as currently designed will eventually lead to such improvements.  And, among those arguing for “rebooting,” there are diverse opinions about what a rebooted program should look like.

On one level, the senators’ report fits into the frustratingly conventional narrative of political polarization, with senators from one pole arguing that the administration from the other pole is doing a bad job.  On another level, it fits into the deeper philosophical differences of opinion regarding the role of government spending and regulation vs. private enterprise in the health care system.  On a third level, the report represents the special interest views of one set of constituents, health care providers, who like receiving government funded incentives, but would prefer the bar to be lowered to earn those rewards.

Likewise, the responses defending the meaningful use program can be viewed as defending the administration’s record, promoting public involvement in health care, and representing the views of another set of constituents, the health care IT vendors, who really like the tsunami of revenue they are receiving as a result of HITECH and who fear that “rebooting” might end up more like “unplugging.”

The most interesting response

Logo for Healthcare Innovation CouncilA group called the Healthcare Innovation Council released what I consider to be the most interesting of the responses to the senators’ “reboot” document.  This Council was assembled by Anthelio Health, a health care IT outsourcing  company and consultancy that is not among the EMR vendor insiders that are reaping the greatest rewards from HITECH.  The Council includes a few leaders of health care provider organizations and leaders from other health IT and analytics companies not including any major EMR vendors.  Their report is entitled “Let’s Admit the Emperor has No Clothes: It’s Time to Redesign EHRs to Improve Patient Care.” They assert that EHRs have not led to the envisioned improvement in the health care system, and offer their diagnoses:

EHR design issues

    • “EHRs, to date, have been fundamentally designed to create electronic versions of paper medical records.”
    • “EHRs focus on data collection mostly for regulatory compliance and financial reporting, not to assist physicians, nurses and other clinicians in providing higher quality more efficient patient care. “

EHR implementation issues

    •  “EHR implementations are often led as IT projects by teams that do not obtain robust, meaningful, future-focused input/involvement from nurses, physicians, pharmacy and other clinicians who provide patient care. The end result typically is that EHR implementations don’t make life better for EITHER the clinician or the patient.”
    • “CMS’ and healthcare providers’ focus has been to ‘just get EHRs up and running‘ in a way that meets CMS’ meaningful use requirements so that they can get meaningful use dollars, without regard to how that affects patient care.”

I see the problem the same way.  But, the tricky part is the remedy.

The Healthcare Innovation Council’s paper first advocates for increased involvement by clinicians (with an emphasis on nurses) in the redesign of EHR technology.  On the surface, this is not really a controversial point.  The Council’s paper reverently referenced Steve Jobs twice in the paper as an innovator and simplifier.  But, it is interesting to note that Jobs was famously against too much end user involvement in the design process, arguing that users don’t have an easy time re-conceptualizing things.  People wouldn’t have asked for an iPod, an iPhone, or an iPad because they had never experienced them before and had established mental models of how to buy music, navigate, take movies, read books, etc.  The problem is on display within the Council’s document.  They write:

  • “EHRs are not designed to reflect or facilitate the way in which providers deliver patient care, and thus disrupt, rather than enhance, patient care”
  • “Improved focus on EHR design and implementation that starts by mirroring the way care is actually delivered by nurses, doctors and other clinicians.”

They seem to be asking for EMRs that “repave the cow paths,” a problem I’ve discussed in a prior post.  But, the Council at least seems aware of the difference between status quo and real disruptive improvement:

  • “This basic design then would move to new, information enhanced processes that not only help clinicians do their jobs easier, but measurably improve patient care safety and quality.”
  • “Rethinking, redesigning and re-engineering nurse, physician and clinician workflows to take full advantage of the capabilities of the new (and evolving) EHR tools to result in improved healthcare processes and care experiences.”

In addition to advocating for clinician-led EHR redesign, the Council’s remedy also includes having the federal government require providers to demonstrate “actual patient care improvement and better patient care process” to earn the incentives.  That’s a lovely thought, but imagine how many pages of regulation it would take for the federal government to define specific care processes that it considered to be “better” and methods to document that such care process changes were connected to the EHR technology.  Beware of what you ask for.

The last line of the Council’s paper is, perhaps, the most interesting.  The authors agree with the senators that it is time to “reboot” the meaningful use incentive program before all the money is spent.  Then, almost as a throw-away line, they add:

  • “Unless that is done, then we urge Congress to halt CMS’ “meaningful use” EHR program and spend the remainder of the “meaningful use” funds on providing financial incentives for hospitals and other providers that demonstrate “meaningful improvements in patient care” through whatever means they choose, and leave it to the healthcare providers, not our federal government, to choose the most effective means to improve patient care.”

Financial incentives for improvements in patients care is what value-based reimbursement is all about.  The Healthcare Innovation Council is basically saying that if you want effective, real improvement, rather than just superficial “compliance,” you need to pay for value.  Of course, the nation is transitioning to value-based reimbursement.  But that process is going slowly and the percentages of reimbursement that is value-driven has tended to be small.  As I’ve argued before, incentives tied to compliance is the opposite of real improvement, no matter how hard you try to make compliance meaningful.  If so, maybe we really need to consider re-allocating the remaining meaningful use funds to speed up the transition to value-based reimbursement, rather than just rebooting meaningful use.

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Physician-led ACOs now outnumber Hospital-based ACOs: Why this makes sense, and where our terminology breaks down.

At a recent meeting of the American College of Physicians covered in MedPage Today, Neil Kirschner, PhD reported on the growth of ACOs. Dr. Kirschner is the ACP’s senior associate of regulatory and insurer affairs. He reported that in March, 2012, there were only 136 ACOs  that had ACO-style gain-sharing contracts with Medicare, a commercial payer or both. Those ACOs included 91 “hospital-based ACOs” and 45 that were described as “physician-led ACOs.” In the last year, the number of ACOs has almost tripled from 136 to 391.  And, significantly, the 202 physician-led ACOs now outnumbers the 189 hospital-based ACOs.

ACOs by doctor vs hospital sponsorship 2012-2013

Why are physician-led ACOs growing faster?

The rapid growth of physician-led ACOs makes sense because ACO-style gain-sharing reimbursement arrangements are more favorable to physician organizations than hospitals. When a hospital-based health system enters into an ACO contract, it basically says “if you succeed in reducing the total cost of care (primarily by reducing your own hospital revenue), we’ll give you back a portion of your lost revenue.” That’s reminiscent of the old business joke “we lose money on each unit sold, but we’ll make up for it in volume.” But, from the point of view of a physician organization, particularly a physician organization that emphasizes primary care, the ACO contract basically says “if you do more primary care work to avoid the need for hospitalizations and emergency department visits, we’ll pay you for that extra work and we’ll give you a portion of the money we no longer have to pay to the hospitals.”

So, why would hospital-based organizations ever enter into an ACO-style gain-sharing agreement?  Two main reasons.

  • First, as a defensive measure. By forming an ACO in which they are involved, they can avoid or delay the formation of a physician-led ACO. It is better to be “doing” than to have it done to you.
  • Second, as a way to prepare for a potential future state where providers are bearing far more risk, such as in capitated reimbursement arrangements. It takes a very long time to develop effective population management capabilities, including establishing effective governance, building trust, deploying the right health information technologies and analytic systems, and, most importantly, recruiting and developing human resources that can effectively use data and improve care processes.

Ambiguous ACO Terminology

Finally, a note about the use of the term “ACO” and ACO growth statistics.

Many people get confused about the definition of ACO.   Some argue that an ACO is, by definition a specific type of Medicare reimbursement arrangement, the Medicare Shared Savings Program (MSSP), created by the Affordable Care Act (ACA).  But, I don’t agree that the term “ACO” defines a type of contract, and that the term ACO only refers to Medicare.  The “O” is for organization. On its face, the term refers to a type of organization, not to a type of contract.  When people generate statistics about ACOs, they should be counting organizations, not gain-sharing contracts.

I consider a provider organization to be an ACO if:

  1. It includes primary care physicians, and
  2. It has or plans to enter into at least one contractual arrangement where the provider organization takes responsibility for an attributed population of patients, and bears at least some risk for quality and economic performance

In common use, people are most likely to refer to a provider organization as an ACO if at least one such contractual arrangement includes a fee for service component with some risk sharing that includes at least some up-side opportunity to share in savings. The Medicare MSSP and Pioneer ACO contractual arrangements are just prominent examples of such contracts, not limiting to the definition of ACO. Because of that fee-for-service connotation, people don’t tend to describe a staff-model HMO as an ACO, even though they meet the definition I proposed above.

Furthermore, when categorizing ACOs, it is important that the categories are mutually exclusive.  The term “physician-led” seems to refer to an attribute of the governance of the ACO, such as whether the person serving as the CEO is a physician or whether the majority of the shares or votes on the board of directors are controlled by physicians or by people that are employed by physician organizations.  The term “hospital-based” seems to refer to whether the provider organizations that own the ACO include at least one hospital or hospital-based health system.  An ACO can include a hospital as a co-owner and still be “physician-led.”  Therefore, there is inherent ambiguity in the statistics comparing the number of physician-led to hospital-based ACOs.

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Beautiful video from Cleveland Clinic advocating empathy

We focus on optimizing care processes, analyzing data, implementing technology, and the other technical and scientific aspects of our work to improve health care.  But, this video created by the Cleveland Clinic is a touching reminder of the human element, advocating for empathy in our work.

http://www.youtube.com/watch?v=cDDWvj_q-o8&feature=youtu.be

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Compliance and Process Improvement are Opposites, no matter how hard you try to make compliance “meaningful”

HIMSS13 iconI’m attending the HIMSS’13 conference in New Orleans this week, a huge assemblage of health care IT people and the bewilderingly diverse collection of technology vendors that sell to them.  The first meeting I attended was billed as a “town hall” meeting by the Federal Government’s “Office of the National Coordinator” (ONC).  The session was heavy on self-congratulatory enthusiasm, even including a demonstration of an ONC team cheer — and I mean that literally.  The session was very light on the type of challenging discussion connoted by the “town hall” concept.  No time for any questions from the microphone.  Just some time towards the end for some selected questions written on small cards, all of them softballs.

I don’t want to be too harsh on the ONC crew.   They are clearly talented, well educated and working hard for government salaries.  They clearly are inspired by the cause of improving health care.  And they are sincere in their belief that requiring or incentivizing compliance with a minimum standard set of technology capabilities is what we need.

In my experience, that is a very natural belief system for people in government agencies, accreditation organizations, philanthropic organizations, health plans, and many healthcare information technology vendors.  I admit to being guilty of going down that road myself.

But, I see it as an honest mistake.  In my experience, people within health care provider organizations are easily convinced that pursuing compliance, no matter how small the penalties and rewards involved, always seems like the most urgent priority.  It’s a mandate, so it gets to win in any internal prioritization debates.  And, that compliance mandate travels up the food chain to all the product management executives of health information technology vendors.   I used to be one of those too, and admit to making such arguments.  As a result, the compliance features occupy all the available near-term slots in the product roadmap, and the innovations have to wait until a future phase that never arrives because there is fresh batch of mandates coming up quickly on the heels of the last batch.

In the ONC town hall session yesterday afternoon, the ONC leaders seemed to acknowledge that the results of earlier phases of “meaningful use” incentives had been somewhat superficial, not anything that led to transformative change yet.  They emphasized that this is a long term journey, and that we need to have reasonable expectations and be patient.  But, they failed to recognize that the superficial nature of the response by vendors and providers may be due to the very fact that it was a compliance response, rather than an internally-initiated agenda driven by the process innovations the technology is intended to support.  Rather, they just looked forward with eagerness and cheerful enthusiasm to the next round of meaningful use standards that will continue the journey.

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New HIT ROI lit review is a methodologic tour de force, but misses the point

JAMIA logoRecently, Jesdeep Bassi and Francis Lau of the University of Victoria (British Columbia) published in the Journal of the American Medical Informatics Association (JAMIA) another in a series of review articles that have been written in recent years to summarize the literature regarding the economic outcomes of investments in health information technology (HIT).  Such articles answer the questions

  • “How much do various HIT technologies cost?”
  • “How much do they save?”
  • “Are they worth the investment?”

They reviewed 5,348 citations found through a mix of automated and manual search methods, and selected a set of 42 “high quality” studies to be summarized.  The studies were quite diverse, including a mix of types of systems evaluated, methods of evaluation, and measures included.  The studies included retrospective data analyses and some analyses based on simulation models.  The studies included 7 papers on primary care electronic health record (EHR) systems, 6 on computer-based physician order entry (CPOE) systems, 5 on medication management systems, 5 on immunization information systems, 4 on institutional information systems, 3 on disease management systems, 2 on clinical documentation systems, and 1 on health information exchange (HIE) networks.

Lau HIT ROI results

Key results:

  • Overall, 70% of the studies showed positive economic results, 24% were inconclusive, and 6% were negative.
  • Of 15 papers on primary care EHR, medication management, and disease management systems, 87% showed net savings.
  • CPOE, immunization, and documentation systems showed mixed results.
  • The single paper on HIE suggested net savings, but the authors expressed doubts about the optimistic assumptions made in that analysis about a national roll-out in only ten years.

My take:

Bassi and Lau have made an important contribution to the field by establishing and documenting a very good literature review methodology – including a useful list of economic measures, a nice taxonomy of types of HIT, and many other tools which they graciously shared online for free in a series of appendices that accompany the article.  They also made a contribution by doing some tedious work to sort through lots of papers and sorting and classifying the HIT economics literature.

But, I think they missed the point.

Like many others, Bassi and Lau have implicitly accepted the mental model that health information technology is, itself, a thing that produces outcomes.  They evaluate it the way one would evaluate a drug or a cancer treatment protocol or a disease management protocol.  Such a conceptualization of HIT as an “intervention” is, unfortunately, aligned with the way many healthcare leaders conceptualize their investment decision as “should I buy this software?”  I admit to contributing to this conceptualization over the years, having published the results of retrospective studies and prospective analytic models of the outcomes resulting from investments in various types of health information technologies.

Process PuckBut, I think it would be far better for health care leaders to first focus on improvement to care processes — little things like how they can consistently track orders to completion to assure none fall through the cracks, bigger things like care transitions protocols to coordinate inpatient and ambulatory care team members to reduce the likelihood that the patient will end up being re-hospitalized shortly after a hospital discharge, and really big things like an overall “care model” that covers processes, organizational structures, incentives and other design features of a clinically integrated network.  Once health care leaders have a particular care process innovation clearly in sight, then they can turn their attention to the health information technology capabilities required to enable and support the target state care process.  If the technology is conceptualized as an enabler of a care process, then the evaluation studies are more naturally conceptualized as evaluations of the outcomes of that process.  The technology investment is just a one of a number of types of investments needed to support the new care process.  The evaluation “camera” zooms out to include the bigger picture, not just the computers.

I know this is stating the obvious.  But, if it is so obvious, why does it seem so rare?

This inappropriate conceptualization of HIT as an intervention is not limited to our field’s approach to economic evaluation studies.  It is also baked into our approach to HIT funding and incentives, such as the “Meaningful Use” incentives for investments in EHR technology, and the incentives created by HIT-related “points” in accreditation evaluations and designations for patient-centered medical home (PCMH), accountable care organizations (ACOs), organized systems of care (OSC), etc.  The designers of such point systems seem conscious of this issue.  The term “meaningful use” was intended to emphasize the process being supported, rather than the technology itself.  But, that intention runs only about one millimeter deep.  As soon as the point system designers put any level of detail on the specifications, as demanded by folks being evaluated, the emphasis on technology becomes instantly clear to all involved.  As a result, the intended focus on enabling care process improvement with technology slides back down to a  requirement to buy and install software.  The people being evaluated and incentivized lament that they are being micromanaged and subject to big burdens.  But they nevertheless expend their energies to score the points by installing the software.

So, my plea to Bassi and Lau, and to future publishers of HIT evaluation studies, is to stop evaluating HIT.  Rather, evaluate care processes, and require that care process evaluations include details on the HIT capabilities (and associated one time and ongoing costs) that were required to support the care processes.

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Big Data: A break-through, or just new terminology?

I don’t normally read the Harvard Business Review.  I find it a bit too cool.  Trying too hard to coin new words.  Over-simplifying complex issues.  Over-confidently setting expectations.

Recently, Harvard Business Review sponsored a web-seminar entitled “Big Data: Can You Seize the Opportunity.”  Classic HBR.  Don’t challenge the premise.  Just challenge the audience to sign up.

Big Data GraphicBut, as covered by Health Data Management, two of the presenters challenged the “big data” framework — criticizing those who defined big data as “magic bullet” technology projects that can be expected to yield big short term returns, and essentially redefining the terminology to conform to their insights about how to gain long term value from analytics.  The heretics were Donald Marchand and Joe Peppard, two professors and analytics entrepreneurs from Switzerland and the U.K., respectively.  They argued that IT people have to stop thinking about building analytic applications (“design to build”) and, instead, think about developing data for use by non-IT people (“design to use”).   They emphasized the unfortunate reality that using data will drudge up problems with the data itself – problems that can’t be miraculously resolved by the big data technology (no matter what the vendor of the big data technology says…).

Marchand and Peppard acknowledged that long-standing conflict between the “c-suite” and IT leaders can present obstacles to enterprise information management.  They pointed out that getting value from analytics requires engaging lots of non-IT people in a long-term process that involves cultural change.  People have to get used to the idea of using data to support decisions, rather than just to make the case for already-made decisions.  IT people can provide some tools, but the non-IT people need to develop new skills and competencies in order to harvest the value of big data projects.

I can’t argue with any of that.  All of that was true before the words “big data” were uttered.  Much of that is quite different than what the proponents of big data are talking about — break-though technology with magical properties that can overcome data problems and shower untrained decision-makers with insights and instant return-on-investment.  But, I really like the idea of capturing the undeniable market momentum of the term “big data” and redirecting that momentum back toward the less glamorous, but ultimately far more valuable journey toward developing useful data and learning how to use it to support evidence-based decision-making.

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Al Lewis calls workplace wellness programs “get well quick schemes”

Al Lewis is an actuarial consultant that has long focused on challenging wellness and care management vendors to prove their value.  He founded the “Disease Management Purchasing Consortium” and established a training and certification program for “critical outcomes report analysis.”

Al has been calling out the methodological carelessness and dirty tricks of wellness and care management vendors and health plans for years.   These shoddy and unethical methods produce deceptively optimistic results, often to the delight of the customers of the programs who crave evidence that they made a wise choice. Many of the methods have been discredited long ago, but like cockroaches and ants, they just keep coming back. Faced with this unsavory state of affairs over many years, poor Al has resorted to sarcasm — probably partly to avoid getting bitter, and partly to keep his audience awake long enough to absorb the otherwise dry, tedious concepts.

He recently collaborated with Vick Khanna in a blog post in Health Affairs that focused on a particular type of wellness and care management program — workplace wellness — now a $6B industry.  Such programs typically are funded and sponsored by employers, and involve incentivizing employees to complete a health risk assessment and then, hopefully, pursue healthier lifestyle behaviors. Employers purchasing these programs typically believe they will lead to substantial, short term increases in worker productivity and decreases in health care costs. The blog post is definitely worth reading.

To summarize:

  1. Both workplace wellness program vendors and the benefit consultants who advocate for them have conflicts of interest which lead them to use deceptive methods and publish papers and marketing material which claim implausible levels of savings and return-on-investment.
  2. Although health plans often sell workplace wellness programs to self-insured employers (for a profit), virtually none of them believes they really produce savings, so they don’t spend the money on such programs for the fully-insured business for which the health plan itself bears the risk.  Health plans don’t eat their own dog food.
  3. The most common trick is to compare the outcomes for highly motivated employees who choose to complete the health risk assessments and participate in wellness interventions to the outcomes for poorly motivated employees who do not.  Epidemiologists call this “volunteer bias.”  It is a problem in evaluation studies of all types of member/patient-facing programs, but is obviously an even bigger problem with workplace wellness, when motivation to change behavior is the whole point of the program.
  4. Other common tricks include taking credit for improvements that occur due to random variation (“regression to the mean”), or taking credit for improvements that occurred before the program actually started — as was the case with the widely-touted results from Safeway’s famous workplace wellness program.
  5. They recommend that employers should avoid these “get well quick” schemes and, instead, do the harder work of creating a deep culture change promoting wellness.  If employers want to try workplace wellness programs, they should at least commit to identifying and then counting the events that the wellness program is intended to reduce to see whether they really decrease across the entire work force after the program is implemented.
  6. Lastly, they point out that the workplace wellness industry convinced the federal government to include taxpayer-financed wellness incentives in the Affordable Care Act.   The Federal Employee Plan is in the process of picking a wellness vendor.  They recommended dropping federally-funded wellness programs until valid evaluations show they work.
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Conceptualizing “over-treatment” waste: Don’t deny health economics

A Health Policy Brief published in Health Affairs on December 13, 2012 referenced an analysis published last April in JAMA regarding waste in health care.  In this analysis, Don Berwick (one of my health care heroes) and Andrew Hackbarth (from RAND) estimated that waste in health care consumed between $476 billion and $992 billion of the $2.6 trillion annual health care expenditures in the US.  That’s 18-37% waste.  They divided this estimate into 5 categories of waste.  Their mid-point estimates are as follows:

Berwick and Hackbarth estimates of waste in health care - JAMA 2011

They consider “failures in care delivery” to include failures to execute preventive services or safety best practices, resulting in avoidable adverse events that require expensive remediation.  By “failures of care coordination,” they mean care that is fragmented, such as poorly planned transitions of care, resulting in avoidable hospital readmissions.  They categorize as “overtreatment” care ordered by providers that ignored scientific evidence, were motivated to increase income or to avoid medical malpractice liability, or out of convenience or habit.  They considered “administrative complexity” to be spending resulting from “inefficient or flawed rules” of insurance companies, government agencies or accreditation organizations.  They estimated the magnitude of administrative complexity by comparing administrative expense in the US to that in Canada’s single payer system.  They considered “pricing failures” to be prices that are greater than those which are justified by cost of production plus a “reasonable profit,” presumably due to the absence of price transparency or market competition.  Finally, they considered “fraud and abuse” to be the cost of fake medical bills and the additional inspections and regulations to catch such wrongdoing.

Underestimating Over-treatment

These estimates are generally in alignment with other attempts to categorize and assess the magnitude of waste in health care.  But, I think Berwick and Hackbarth’s estimates of “overtreatment” are probably far too low.  That’s because they, like so many other health care leaders, are so reluctant to address the issue of cost-effectiveness.  Obviously, the definition of over-treatment depends on one’s philosophy for determining what treatments are necessary in the first place.  Everyone would agree that a service that does more harm than good for the patient is not necessary.  Most would agree that a service that a competent, informed patient does not want is not necessary.  Some argue that, if there is no evidence that a treatment is effective, it should not be considered necessary, while others argue that even unproven treatments should be considered necessary if the patients wants it.   Berwick and Hackbarth are ambiguous about their application of this last category.

But, the big disagreement occurs when evaluating treatments for which there is evidence that the treatment offers some benefit, but the magnitude of the benefit is small in relation to the cost of the treatment.  This is a question about cost-effectiveness.  It is at the heart of medical economics.  In my experience, most health care leaders and an even higher proportion of political leaders choose to deny the principles of medical economics and the concept of cost-effectiveness.  They describe attempts to apply those principles as “rationing” — a term which has taken on a sinister, greedy meaning, rather than connoting the sincere application of rational thought to the allocation of limited resources.   Berwick and Hackbarth implicitly take that view.  They are unwilling to define over-treatment based on cost-ineffectiveness.

The analysis I want to see

For years, I’ve been looking for an analysis that attempted to estimate the magnitude of waste from over-treatment based on the principles of health economics.  The diagram below illustrates the hypothetical results of the type of analysis I’d like to see.

Diagram re Conceptualizing Overtreatment

 In this diagram, the horizontal axis represents the total cost of health care to a population.  I don’t want to see the entire US health care system.  What is more relevant is the population served by an Accountable Care Organization or an HMO.  To create such a diagram, we would first need to break down health care cost into a large number of specific treatment scenarios.  Each of these scenarios would specify a particular treatment (or diagnostic test) with enough clinical context to permit an assessment of the likely health and economic outcomes.  For each scenario, each of the possible health outcomes would be assigned a probability, a duration, and a quality of life factor.  My multiplying the duration by the quality of life factor, we could calculate the “quality-adjusted life years” (or “QALY”) for the outcome.  Then, by taking the probability-weighted average of all the possible health states for the scenario, and then dividing the result by the cost, we could calculate the “cost-effectiveness ratio” for the scenario, measured in “$/QALY.”   Then, we would sort all the treatment scenarios by the cost-effectiveness ratios, with the treatment scenarios with the most favorable health economic characteristics on the left.

Some of the scenarios will generate net savings, such as for certain preventive services where the cost of the avoided disease is greater than the initial cost of the preventive service.  These are clearly cost-effective.  On the other end of the spectrum are scenarios that offer net harm to the patient, such as when adverse side-effects are worse than the benefits of the treatment.  These are clearly cost-ineffective.  In the middle of these extremes are scenarios where there is a positive net benefit to the patient and a positive net cost borne by the population.

If a person rejects the principles of health economics, they would consider all of these middle scenarios to be “necessary” or “appropriate” regardless of how small the benefits or how large the costs.  But, among those who accept the principles of health economics, some of these scenarios could be judged to be cost-effective and others to be cost-ineffective.  Such judgments would presumably reveal some threshold cost-effectiveness ratio that generally separated the scenarios into cost-effective and cost-ineffective.  Since different people have different values, their judgments could reveal different cost-effectiveness thresholds.  If we had many people making these judgments, we could find a range of cost-effectiveness ratios that were considered to be reasonable by 90% of the people.    Applying this range to all the treatment scenarios, one could find a group of scenarios that were considered wasteful by most, and another group of scenarios that were considered wasteful only by some.

Variations on this theme have been used throughout the world for decades by various practice guidelines developers, healthcare policy analysts, health services researchers and health economists.  It is complex and time-consuming.  As I’ve discussed before, it is also controversial in the United States.

Right now, in the US, we all recognize that health care costs are too high.  We’re all focusing on merging providers into larger organizations, installing computer software, and exploring new reimbursement arrangements to address the problem.  But, I’m convinced that over-treatment with cost-ineffective services is a major source of waste.  We will inevitably get back to the core issue of having to figure out which treatment scenarios are wasteful.  We will inevitably have to overcome our denial of health economics and our irrational fear of rational allocation.

 

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The race in on between triple-aimers and hospital defenders

This week, Julie Creswell and Reed Abelson published an interesting piece in the New York Times about how the war between hospital chains puts doctors in a bind.  I think the article includes many relevant facts about the consolidation of the health care market.  But, I conceptualize the conflict a little differently.

Here’s my take…

For a number of years, there has been an internal battle within the federal government.  The CMS has been promoting the idea of formation of ACOs to achieve clinical integration of physician and hospital services.  But, as I described in an earlier post, the FTC and the Justice Department have been concerned that hospitals would use ACO safe harbor provisions as cover for consolidation to increase market power and drive up prices.

CMS was confident that, if ACOs faced enough risk, the savings from clinical integration and care process transformation would outweigh cost increases from higher prices.  But, when CMS proposed ACO regulations that had the audacity to include a modest amount of downside risk for providers, they faced a huge provider backlash.  CMS buckled under the pressure, and approved final ACOs regs that allowed providers to choose only upside rewards, with no downside risk.  As I’ve noted before, the vast majority of providers that ended up forming ACOs have very little skin in the game.

Within hospital organizations that formed ACOs, there are a mix of leaders.  Some leaders are enthusiastic promoters of the CMS vision of clinical integration, a resurgence of primary care, and achieving the “triple aim” of improving quality, increasing satisfaction and reducing per capita cost.  Other ACO leaders are more focused on the financial health of the hospital portion of the delivery system.  Such leaders are concerned that the per capita cost take out will come out of the hides of hospitals, some of which will be forced to close when their revenue cannot cover their substantial fixed costs.  These two types of leaders have been unable to agree on the need to make substantial investments in clinical process transformation and the associated clinical information systems designed to achieve the cost take-out.  So, the federal government came to the rescue with HITECH funding for EMR technology.  The Feds were able to justify this funding based on the need to stimulate the economy, rather than the need to reduce health care cost.  As a result, the HITECH “meaningful use” regulations are focused more on quality than cost take-out.  Though well meaning, the HITECH funding and the associated meaningful use regs actually created a huge distraction for IT professionals within provider organizations.  Many ACO leaders have directed their IT professionals to focus on meeting externally-defined meaningful use requirements — studying for the test — rather than doing the far more challenging work of actually figuring out how to support the triple aim through clinical process transformation.

The one thing that the two types of ACO leaders could agree upon was physician practice acquisition.  The triple-aim-oriented leaders were in favor of acquiring practices as a means to get sufficient control to achieve clinical integration.  The hospital-oriented leaders were in favor of acquiring practices as a means of controlling the hospital’s inbound referral pipeline to keep the beds filled and to increase market share to gain bargaining power against health plans.  So, practice acquisition has proceeded vigorously.  Now, the race is on to see which group of ACO leaders is going to dominate.  To this point, the triple-aim-oriented leaders remain hampered by longstanding weakness in physician leadership and governance structures (the problem of “herding cats”), the traditional dominance of specialty leaders over primary care leaders, the lack of available analytic talent, and lame clinical information systems.

Right now, the hospital-market-power-oriented leaders are out in front. There is a great risk that they will be too successful, making it too obvious that the FTC and the Justice Department were right about market consolidation. That outcome would lead the health care policy community and the public to conclude that “accountable care” is a failure, as happened with “managed care” in the 1990s, sending the idealistic triple-aimers back into exile for another decade.  But, that outcome is not yet certain. There remains a chance for some provider organizations to figure out ways to achieve the triple aim, including per capita cost take-out, and still accomplish profitability and growth, thereby disrupting the long-standing hospital-centric order. I would estimate the probability of that outcome to be less than 50%, but still likely enough to be worth fighting for.

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We’re up to 154 Medicare ACOs

Today, the CMS announced that it added another 89 ACOs to the Medicare Shared Savings Program (MSSP).  Including the original 6 Physician Group Practice Transition Demonstration participants, the 32 Pioneer ACO, and the 27 MSSP participants announced in April, that brings the total number to 154, serving more than 2.4 million Medicare beneficiaries.  Beginning this year, new applicants will be accepted only annually.

The new ACOs includes some that serve Michigan:

  • Oakwood Accountable Care Organization, LLC, located in Dearborn, Michigan (with 1,546 physicians and partner hospitals), and
  • Southeast Michigan Accountable Care, Inc., also located in Dearborn, Michigan (comprised of 333 physicians, including group practices and a network of individual practices), and
  • ProMedica  Physician Group (250 physicians in Michigan and Ohio)

Other new Medicare ACOs that are particularly large include:

  • Advocate Health Partners (2,237 physicians in Illinois)
  • Wellstar Health Network, LLC (1,203 physicians in Georgia)
  • Indiana University Health ACO (1,837 physicians)
  • Iowa Health Accountable Care (1,551 physicians),
  • University of Iowa Affiliated Health Providers (1,791 physicians)
  • Maine ACO (1,595 physicians)
  • Essential Health (1,404 physicians in Minnesota, North Dakota and Wisconsin)
  • Balance Accountable Care Network (1,069 physicians in New York City)
  • Mount Sinai Care (2,249 physicians in New York City)
  • University Hospitals Coordinated Care (1,770 physicians in Ohio)

The full list of new ACOs is available here.

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