What the Wall Street Journal tells us about complications after surgery: Not much.

The Wall Street Journal published an article on Christmas day that told the story of an 83 year old woman who suffered a heart attack after a joint replacement at a rural hospital.  The story serves as an introduction to a piece about the higher cost and poorer care delivered at rural hospitals.  There are certainly some very interesting points I was not aware of with regards to financial incentives provided by the government to do procedures at rural 'critical access' hospitals, as well as higher 30 day mortality after joint replacement surgery at these rural hospitals.

The Wall Street Journal article does provide this nugget from a Harvard public health researcher: “Patients are getting bad outcomes, probably because they are getting procedures at hospitals without the experience to do it well.”  This certainly may be true, but no data exists in the article to back-up this assertion.  Are there more infectious complications of the surgery?  Are there more re-operations? Are the surgeons that operate at these centers less experienced?

The aim of the initial CMS initiative to expand access to care for rural patients seems to have worked. More patients are getting surgery closer to home as a result.  It is troubling that mortality rates are higher at these hospitals.  Perhaps the answer is to take away the incentives and move surgeries back to the larger hospitals.  I don't know, and the article isn't particularly helpful in answering those important questions. I would hope the folks in our profession who help shape public policy, like the Harvard physician quoted in the study, would be a little more careful in implying causation when all that has been discovered is a hypothesis generating correlation.  My hope is that he isn't advocating for changes to public health policy based on simple correlations.

I do take issue with the story used to make this point.  Unfortunately, a heart attack is a complication of any surgery.  It is not clear from the story what parts of care provided at this rural hospital were substandard.  Patients at teaching hospitals do have heart attacks post-operatively as well.  Differences in outcome may relate to delays in access to subspecialists you need in this situation.  Unfortunately, this article doesn't shed light on any of this.  It instead joins a laundry list of articles that leaves the distinct impression that something bad happened to a loved one at a hospital that was preventable. There are plenty of things I wish for.  I would love to have a light saber, I would love even more to travel at light speeds in the Millenium Falcon, and most of all I would love to live in a medical world free of any harm.  Elon Musk would lead me to believe we are a lot closer to flying in a Millenium Falcon than we are to working in a zero harm environment.  Surgery, especially, is not close to a zero risk endeavor.  While I have found estimates reported in the literature to be overstated at times, as many as 10 million patients (out of 200 million undergoing non-cardiac surgery) worldwide are estimated to suffer a major cardiac complication. There is a possibility that your 80 year old grandmother will have a complication of surgery even if it takes place at an ivory tower institution, and even if every single medical and surgical practice standard is met.

As we usher in 2016, I do have a solution that will definitely sate everyone's desire for zero risk.  In order to get to zero risk, I advocate we stop operating.  I feel safe in guaranteeing that there will be no complications of surgeries this coming year if there are no surgeries.

The quest for zero infections: A fool's mission?

Joyce is sick.  I am in the intensive care unit, peering at vital parameters that glow on the screen above her bed.  My eyes linger on those numbers because it is easier than looking at her.  A fever rages, her core temperature reads 103.4 degrees.  Her white hair is plastered on her forehead with sweat, and a tube to help her breathe emerges from her mouth and heads to a ventilator that angrily tweets a musical alarm every few minutes.  Her breathing is painfully obvious.  Her stomach moves paradoxically inward on every breath, and I can see the muscles in her neck tense with the effort of every breath.  Mercifully, her eyes are closed.  A nurse walks in and starts to change a bag of fluids that is hanging by her bed.  I follow the flexible plastic tubing that arises from the bag to an infusion pump, and then to a catheter that snakes under a see-through dressing underneath Joyce's left collarbone.  I ask the nurse about how long the catheter has been in place...'3 days'...I'm told.  I mutter about the possibility of a central line infection - the dreaded central line-associated blood stream infection (CLABSI).  The nurse shakes her head, and tells me - "we don't get those anymore".

CLABSIs are ground zero in the war on preventing patient harm.  The story entered the mainstream consciousness in the lyrical words of Atul Gawande in the New Yorker in 2007.  There he told a story of an unlikely Superman in the form of a critical care intensivist named Peter Pronovost. Dr. Pronovost was waging war against infections from these nefarious central lines that were saving and killing patients at the same time.  He published a landmark study in the New England Journal of Medicine that used an evidence-based intervention to dramatically reduce infection rates in the intensive care unit.  Some form of the implementation bundle that worked for Dr. Pronovost soon found itself in ICUs everywhere.  Dramatic reductions in CLABSI rates followed.

The remarkable part about this feel good story is that it seemed so easy.  The ICU I was in had seemingly reproduced this success as well.  I spoke to nurse after nurse who noted that CLABSI's were fairly rare events at this point.  Everyone had a different theory about how this happened.  Some attributed this to the full barrier sterile technique used for line insertion, others to the limitations put in place to draw blood from central line catheters, while others felt it was the maintenance of the catheters after they were placed.  Regardless, everyone had CLABSI on the brain.  The government had mandated that hospitals report their CLABSI rates, and with this, hospital resources to blot out this particular black spot were committed in earnest.  It should come as no surprise that infection rates would drop.  The size of the effect impressed me.  Hospitals, in my experience, are like large lumbering elephants.  It usually takes three forms, five signatures, and at the end of it all, I am told HIPAA won't allow it.  No matter what it is.

In 1958, Hawthorne Works, a Western Electric factory outside of Chicago commissioned a study to see if their workers would become more productive in higher or lower levels of light.  The workers' productivity improved when changes were made, but slumped when the study was over.  It was suggested the productivity gains were made because the workers were being observed. This has come to be known as the Hawthorne effect.  Not surprisingly the simple act of measuring, observing or testing has an effect on the performance of subjects.

There was no doubt that implementing a variety of maneuvers to reduce infections was having an impact, but this is not the whole story. In this particular ICU, for instance, I noticed that blood cultures were now rarely drawn from the central lines themselves.  They were now drawn peripherally.  This means hunting for a vein to thread a needle into to get a culture.  It was so much easier to take an empty syringe, hook it up to a catheter that was sitting in a vein and draw back 10 ml of blood.  The patient didn't have to be stuck with a needle and a nurse/physician didn't have to spend precious minutes hunting for a vein in a critically ill patient whose veins are either collapsed or buried in tissue laden with fluid.  Requiring peripheral cultures, though, does make plenty of clinical sense.

Cultures from catheters have a high false positive rate: organisms may grow that are colonizing the catheter but not causing an infection.  Deciding between the two - colonization or infection - can be challenging and is many times a clinical decision.  The CDC criteria for CLABSI in this regard is monolothic: any blood stream infection with a pathogenic organism counts against you.  Secondly, the act of collecting blood from a catheter is thought to raise the risk of introducing micro-organisms into the blood stream, and causing an infection.  These two points have been known for some time, but it was the specter of public reporting of these infections that really pushed hospitals to move in a systematic fashion to develop rigid protocols about cultures being drawn from central lines.  I applaud this new found fastidiousness with regard to cultures, but it does, however, make comparisons of infection rates somewhat challenging.  How much of the decline in infection rates is secondary to a more restrictive policy related to ordering blood cultures?  It is hard to know, and even Pronovost's landmark study cannot escape from the bias inherent in performing a non-randomized study that in essence tracked infection rates over time.  Regardless of the size of the true effect, Pronovost's accomplishment cannot be understated.  I can think of little that has been as clinically impactful in as short of a time.  To get hospital CEOs, CMO's, infection control committees, nurses, technicians and physicians on the same page with regards to evidence based practices for line infections is a true tour de force.

Of course, a hard lesson I learned after a peanut better and jelly sandwich orgy applies here too - there can be too much of a good thing.  Pronovost started on a mission to reduce infections, but yet that is not what we try to do now.  Our current mission statement is to get to zero.  CLABSI's have become the poster child for 'preventable harm',  a phrase that does not just imply,  but unabashedly states that any infection associated with a central line can be prevented.  Patients and stakeholders have carried this torch forward. Medicare has pushed forward with policies that would withhold reimbursement for any CLABSI's, because of course, they are all deemed preventable.

The evidence for a zero is non-existent.  Pronovost's study reduced infection rates a remarkable 66%.
A 2012 study provocatively titled: Zero risk for central line-associated blood stream infection: Are we there yet? found that we were not there yet.  The study based in 37 ICUs in South Wales sought to identify the longest time a central line could stay free of infection with another 'insertion intervention bundle'.  The authors reported a significant reduction in rates of infection with their prevention bundle, but importantly found no catheter dwell time that was associated with zero risk.  It should not take a study to say this.  In today's non-Star Trek world, the reality of critical care medicine frequently involves the insertion of central line catheters that are life saving.  These catheters are placed, not in the vacuum of space into sterile objects, but rather within the milieu of a hospital teeming with pathogenic organisms, and into patients that are far from sterile.  Our attempts to sterilize the human environment is an exercise in reducing the burden of micro-organisms, not eliminating them.

Tying reimbursement to an impossible goal places inordinate pressures on hospitals, which have consequences that are unintended, but quite predictable.  The response of hospitals and their staff takes many forms, and I have already written about the new found parsimony in blood cultures being drawn from central lines.  Other maneuvers are less sanguine.  A study done to compare infection control practitioners  to a standardized computer algorithm had disturbing results.  The medical center that had the lowest rate of central line infections as judged by infection control practitioners (2.4/1000 central-line days) had the highest rate by the standardized computer algorithm (12.6/1000 central-line days).  The study authors concluded that the variability of infection rates seen when compared to a reference standard suggests significant variation in the application of standard CLABSI definitions.  It would appear that the CLABSI definition was being applied in a subjective fashion to report rates much lower than an objective standard.  Welcome to a world that tells you what you want to hear.

The narrative that surrounds the noble sounding 'prevention of harm' strips meaning from the very phrase when applied in such a liberal, incoherent fashion. The reality is that patients arrive at hospitals and critical care units in extremis.  In that hospital room we struggle to make Joyce whole again.  It is a struggle we may not win because the very interventions we use to save a life can also take a life. The fervent hope of everyone in Joyce's room is that on balance the benefits of the interventions taken are greater than the risks.  Over time, mortality rates have fallen in intensive care units - a fact that is remarkable given that patients in ICUs today are sicker than ever.  This fall in mortality is driven by progress in treatment of underlying disease states, as well as improvement of processes in medicine that predates ProPublica-style transparency and 'performance'-based reimbursement.
Remarkably, yet predictably, the current iteration of 'transparency' combined with unrealistic expectations may be doing more harm than good.

The magical world of funding for the Affordable Care Act

Congressional leaders just agreed to a budget that would keep the government open through September 2016.  I was happy to hear the government was not going to shut down.  I was much less happy to hear about the fate of provisions supposed to fund the Affordable Care Act (ACA).  The ACA - costing $1.2 trillion over 10 years - was supposed to 'mostly' pay for itself.  Revenue was to be generated (in large part) by a series of taxes on a variety of different sources.  These taxes did not fare so well in the current budget.

'Cadillac' Tax
The ACA took aim squarely at high cost employer-sponsored plans.  Economists believe that since employer health insurance is tax deductible, high cost plans proliferate as a mechanism to provide a tax free benefit to employees.  These expensive plans are expensive because they cover most of the cost of medical care, insulating the patient from the actual cost of medical care.  The ACA imposed an annual 40% tax on plans with annual premiums exceeding $10,200 for individuals and $27,500 for families to be paid by the insurers.  The results were to be two fold: One, create a disincentive for employers to offer 'cadillac' plans, and two, generate revenue to pay for the ACA.  A broad coalition composed of democrats and republicans lobbied to defeat this tax.

Medical Device tax.
A tax was imposed on medical device companies, in part because expanded insurance coverage was believed to increase their revenue.  This tax has also been 'delayed'.  It is estimated that this will cost the federal government $2 billion dollars per year.  A quick review of stock prices of three dominant cardiac device companies show major increases since signing of the ACA into law in 2010.  For reference, the S&P 500 gained 50% in the same period of time.

Health Insurance Provider tax
The insurance companies that were supposed to see more revenue as a result of taxpayer subsidized coverage had an annual fee they had to pay.  This annual fee was related to the dollar amount of the net premiums written during the prior year.  In 2016 that fee would have amounted to $11 billion dollars. The insurance companies argued that the fee would 'have' to be passed on to the consumer in the form of higher premiums.  This is the same insurance industry that has seen significant stock gains and returns for their shareholders as well since the ACA was signed.

The White House obfuscates

No statement from the whitehouse has been forthcoming on how this revenue will be made up. I suspect the whitehouse team would point to healthcare savings because of the ACA. They would, of course, be wrong.

From the obamacare facts website:

"In 2015, due in part to the ACA, health care spending grew at the slowest rate on record (since 1960). Meanwhile, health care price inflation is at its lowest rate in 50 years." (accessed 12.16.2015)

This hyperlink references CMS data from 2013 that healthcare costs were growing at the slowest rate since 1960. The whitehouse took credit for bending down the cost curve despite the fact that the slowdown predated the signing of the ACA. Despite the claims on the obama website, the actual 2014 health care cost data reflects quite a different story. 

 In 2014, Health care care expenditure is projected to have increased 5.5% (year over year), the first time growth would be higher than 5% since 2007. As a consequence, in 2014 health care expenditures are now projected to be 17.7% of GDP, the first increase in the health care share of the economy since 2008. Why did health care costs go up so much? As per the economists at CMS (Health Affairs) the rise in healthcare costs are mostly related to the expansion of healthcare coverage under the Affordable Care Act (ACA). Not surprisingly, expanding coverage to millions of people costs money. To reiterate, the ACA is largely responsible for changing the trajectory of the health care cost curve in the wrong direction

Of course, this was before the most recent iteration of the budget that deep-sixed revenue supposed to 'self-fund' the ACA.  Don't even get me started on the revenue that was supposed to come from reductions in overpayments to private Medicare Advantage plans.

The ACA, of course, continues to be funded.  The White House quotes 2013 numbers when talking about 2015.  It's magical.  Maybe Santa Claus is for real.  

Risk scoring/value based payment models haven't worked: The MedicareAdvantage story

Mrs. Cassidy slowly walks into my office one busy afternoon.  I see her out of the corner of my eye because she is so hard to miss.  Mrs. Cassidy has some serious style.  She is wearing a deep orange dress with a bright blue blazer.  There aren't too many folks that can pull that outfit off, but she can.  She has a wide slow smile, and she speaks with a slow southern drawl that belies her southern roots.  This was supposed to be a routine follow up visit for a 67 year old woman with a history of a mechanical mitral valve replacement and coronary disease.  Unfortunately, she tells me a story that is concerning for angina.  I think she needs a stress test. I slide over to the insurance tab on the EMR and I let out a somewhat audible groan.  She has a Medicare Advantage (MA) plan.  I explain to Mrs. Cassidy that we will need to go through an extra step to pre-certify her stress test.  She expresses surprise and asks me what she should do.  I will tell you what I told her, but first, let me tell you why.

Medicare Advantage Plans: A brief history

The concept of receiving medicare benefits through private health plans has existed since the 1970's, providing an alternative to traditional fee for service (FFS) Medicare.  The federal government pays private insurance companies a capitated amount per enrollee, with the idea that the private market would be more cost effective than traditional Medicare.  Prior to the Balance Budget Act (BBA) of 1997, Medicare paid 95% of average traditional Medicare costs to private plans. The idea behind lower payments seemed sound.  Managed care had more flexibility with paying providers (i.e. using gatekeepers, demanding prior authorizations for tests, etc.), and managed care patients were, in general, healthier.  Under these rules, however, the private market was a relatively small slice of the total Medicare pie, covering only 13% of all Medicare enrollees.

The year everything changed was 2003.  The Medicare Prescription Drug, Improvement, and Modernization Act (MMA) is best known for introducing prescription drug coverage to Medicare patients (Medicare Part D).  Less well known is the provisions within the bill to provide a major increase in government contributions to private (Medicare Advantage) plans.  As a result, Medicare now pays more for private plans per enrollee (~$1,000) than the cost of care for beneficiaries in traditional Medicare. In 2014, payments to MA plans totaled ~$159 billion.

Not surprisingly, enrollment in MA plans has exploded since 2003.  MA plans went from enrolling 13% of Medicare beneficiaries in 2003 to 30% of beneficiaries in 2014.   To be fair, much of this extra payment is mandated to be used as benefits for MA enrollees.  This can take the form of extra benefits to plan members or premium relief.  This still sets up a payment scheme that favors those enrolling in MA.  Sign up for an Advantage Plan! Get free stuff that the 70% of folks enrolled in traditional Medicare will pay for!

Scoring risk: You are higher risk if they say you are

The current mantra about cost in health care places a large portion of blame on a fee for service culture.  You will find little argument from me that paying per unit of healthcare delivered will result in a lot of health care being delivered.  However, the prevailing ideology that states bundled payment models will be cost effective is more faith-based than evidence-based.  The history of payment to MA plans is quite instructive in this regard.  The idea of capitated payments to private insurers started as an attempt to cut costs.  Capitated payments, however, encourage insurers to enroll a lower cost, healthier enrollee, and not surprisingly, that is exactly what insurance companies have done, and continue to do.  Offering free gym memberships (Silver Sneakers) is very nice, but it also does tend to attract beneficiaries that can go to a gym and workout.  The end result is that the federal government pays more for MA enrollees relative to their costs in traditional Medicare.

The solution seemed clear.  In 2004, the Medicare program began to tie payments to private plans to beneficiary risk score.  Medicare calculates payments to plans separately for each beneficiary, multiplying the the plan's payment rate by the beneficiary's risk score.  Risk scores are based on diagnoses coded during the year prior to the payment year.  Insurance companies responded by investing resources in ensuring 'appropriate' coding.  The appropriately titled "Upcoding: Evidence from Medicare on Squishy Risk Adjustment" by the National Bureau Of Economic Research (NBER) found that a 10% increase in MA market penetration lead to a 0.64 percentage point increase in the average risk score in a county.  MA plans generate risk scores for their enrollees that is on average 6.4% higher than what those same enrollees would have generated under traditional Medicare. Moreover, consumers choosing traditional Medicare have similar risk scores and diagnoses in their employer plans at age 64 and in traditional Medicare at age 65, but consumers choosing MA show a boost in risk scores and diagnoses the year after their transition.  Who would have imagined it?  Simply enrolling in a MA plan makes you higher risk.

The other nostrum to cure all ills of the current health care system proselytized by fast talking policy makers and politicians are value based payments.  Once again, the MA experience provides lessons aplenty.

Measuring value: Harder than it sounds.

Quality in the MA program is graded on a 5 star scale that is determined from a weighted scale comprised of variables that include adherence to best practice processes (adults should get flu shots) and outcomes (diabetics should have blood pressures < 130/80).   These specific parameters come from the 2010 MEDPAC report on comparing quality in medicare plans.  The problems are readily obvious.  2010 was also the same year that the ACCORD trial examining aggressive blood pressure targets in diabetics was released: Targeting a systolic blood pressure target of < 120mmHg compared to < 140mmHg did not reduce the composite endpoint of fatal/non fatal cardiovascular events.  The world of hypertension was so spooked by this trial that the panel convened to create a national guideline used this trial as evidence that lower was not always better when it came to blood pressure lowering.  That was until Nov 2015, when the SPRINT trial (that excluded diabetics but included patients at high risk of cardiac events) did show a mortality benefit of targeting systolic blood pressures less than 120.   So it is entirely possible that in 2010, plans were incentivized to do harm to diabetic patients by having lower blood pressure targets.  

Mired in this quicksand of higher cost and who-knows-what-value care, there was no damsel in greater need of being rescued than the health care system.  Riding to the rescue was the Affordable Care Act (ACA).  Unfortunately, the ACA has proved so far to be more Don Quixote than Sir Lancelot.

The Affordable Care Act (ACA)  and Medicare Advantage plans

The ACA sought to balance the scales by reducing the extra payments to MA plans.  The idea was to stop overpaying certain parties, and use the money saved to help pay for provisions of the ACA.  This seemingly reasonable course of action has been fairly bumpy.  In 2014 and 2015, CMS announced that Medicare Advantage payments were set to rise for the following years.  This reversed a decline proposed earlier in the year, and came after a major lobbying effort from the health insurance industry, as well as members of both political parties.  So much for Sir Lancelot.

In brief, the federal government's experiment in risk-adjusted, value-based payments to private insurance companies has been a failure.  It has only served to shift health care dollars to insurance companies at increased cost to the taxpayer.  Our senior citizens do, happily, have more 'free' gym memberships as a result. 

Adding insult to injury, the same insurance companies being paid more for each enrollee increase the degree of difficulty for physicians trying to take care of their patients.  Today, my staff has to spend time pre-certifying a test; tomorrow promises to be an even greater time-sink as payers demand even greater reporting of practice demographic and outcome data.  One would think the people in charge would have learned lessons from the MA misadventures.  After wading through meaningful use stages, PQRS initiatives, and queries from clinical documentation specialists about what type of respiratory failure my patient had, I can most definitely say: They have not.

Between January 1st and February 14th each year, if you are enrolled in a Medicare Advantage plan, you can leave your plan and return to original Medicare.  John F Kennedy famously said, "Ask not what your country can do for you, ask what you can do for your country".  Mrs. Cassidy, do what's right for your country.  Choose traditional Medicare.

The cost-effective cardiologist..

Safe, appropriate, effective care at a reasonable cost.  Such a simple goal.  The message is clear. Leaders in hospitals, congress, and even my chihuahua echo the dawning of a new age in health care. Down with the private practice, fee-for-service mentality, they all say.  I pay attention to a lot of this chatter since I happen to be in private practice.  I split my time on the internet between the latest exploits of the Kardashians and gravestones for my practice.  I can picture the epitaph:

In loving memory of 

Koka Cardiology

3/1/2013 - 3/1/2016.  

Shed not for her the bitter tear

Nor give the heart to vain regret

'Tis but mere ashes that lie here

The gem that filled it sparkles yet

As I shuffled towards this abyss, my reverie was broken by a letter.  It was from Independence Blue Cross (IBC) in Pennsylvania.  It was titled: The Cardiology/Invasive Cardiology Comparative Cost report.  It looked like a report card, so I opened it with some trepidation.

My first impression?  I was in the green! That was good. Maybe the headstone could wait.  They like me.  They really, really like me.  Of course, then I kept reading, and the headstone popped back into my head.  

I wasn't that good.  I scored an 80 out of a total score of a 100.  In the cost-effective outpatient category in the city of Philadelphia, there was a green category and a danger zone orange category.  I was comfortably in the green category, but within the green category I was 21st out of 26 sites. 

Great.

I started a solo practice in March of 2013.  I had been out of fellowship for two and a half years and parted ways with a local cardiology group with the firm belief that I wanted to be different. I had learned a lot in my two and a half years, and lived through the mass migration of private cardiology practices to hospitals.  Everyone I told about my plans to start private practice in this climate said I was crazy (and they were being polite).  The private practices that were rushing to join hospitals were doing so out of desperation, primarily because of large cuts that had been made to imaging reimbursements in 2008.  Alarmed at the rapid growth of imaging studies in the outpatient setting, CMS had instituted a 36% cut to myocardial perfusion imaging reimbursement, and a 25% cut to echocardiogram reimbursement in 2008.  This was clearly incredibly painful to many practices that had a cost structure based on high margin imaging revenue.  Practices were faced with tough choices. Luckily CMS had a reserve parachute handy - hospital outpatient prospective payment (HOPP). Physician practices leased themselves to hospitals - and voila - no more reimbursement cuts.

This was the climate I started my practice in.  I did have some advantages relative to the established practices around me.  Unfortunately, I was no more affable, intelligent, or more attractive than my colleagues. But most importantly, I had no fixed cost structure (technicians, underproductive physicians, or costly equipment), which gave me the freedom to set up a practice that was not dependent on imaging.  Since I was trained in the world of CARP (limited/no role for preoperative coronary revascularization) and COURAGE (medical management of stable angina is equivalent to revascularization), I decided to forgo an in-office stress lab.  If a patient needed a stress test, I would have it done at one of the nearby hospitals.  I focused on being accessible to subspecialists, surgeons, and patients.  As a result, after two years of being in practice, only 7% of the revenue for the practice comes from echocardiograms or the supervision/interpretation of a stress test. I saw ~3500 outpatients in 2015.  I did 537 echocardiograms, and personally supervised the ECG portion of 48 stress tests.  13% (537/3500) of my patients had an echocardiogram, which contrasts with a national average from Medicare data of 20%.  I was paid ~ $144 per echocardiogram, and $23 per stress test I supervised.  In contrast, the hospital was paid ~ $400 per echocardiogram performed, and $1140 per stress test.  

In the cat and mouse game providers and payers love to play, the payers, of course, noticed that practices like mine are a fairly good deal.  The medicare payment advisory commission (MEDPAC) specifically cited the differential reimbursement of echocardiograms in recommending that this playing field be leveled.  The reason for the difference in hospital reimbursement has always been explained by the significantly higher cost of doing business hospitals have relative to outpatient practices.  I don't have to comply with JCAHO and I don't have to staff a 24/7 ER that must take all comers regardless of ability to pay.  However, there is something fundamentally rotten if the patient mix, the providers, the equipment, and the physical space are the same, but the addition of the hospital logo doubles or triples the price of the service being delivered.  MEDPAC has recommended in 2014, and again in 2015, that "Congress should direct the Secretary of Health and Human Services to reduce or eliminate differences in payment rates between outpatient departments and physician offices for selected ambulatory payment classifications".  IBC took a different approach.  IBC set up programs that would allow for bonus payments to doctors who practiced high value/cost effective care.  In order to guide test/consult ordering physicians to cost effective facilities/providers, a comparative cost report for each facility in a certain geographic area was generated and distributed. This report was meant to highlight those providers that were practicing as hospital outpatient facilities.  This was the report I had received. 

Sure enough, all the 'penalties' (those facilities marked in orange/red) in the report were for facilities that were hospital outpatient practices.  Certainly, a very interesting first step by a private insurer to use data to give physicians information about the cost of procedures.  This does, though, provide yet another opportunity to look at why one has to be so careful about what quality metrics actually tell us. 

I called one of the medical directors at IBC to inquire about how exactly the score was arrived at, but I only got the general information that the cost/procedure performed was the primary determinant of final score.   This did serve to explain why I ranked 21/26 in the 'green' category.  Even though I did not have a stress lab and did fairly few echo's or stress tests, those stress tests I did do were at a local hospital at the 'hospital rate'.  I was actually encouraged by the medical director at IBC to get my own stress lab! Interestingly, a physician practice that did echocardiograms on 50% of its patients would come out smelling like a rose to the IBC folks.  Meanwhile, a hospital based practice that only tested 5% of their patients would be penalized.

So much for this particular score.  I understand this report as a first step that does deliver some good data, but I surmise that a lot of resources and capital went into generating a list that essentially tells you which practice is hospital-based, and which isn't.  I'm not sure how much that cost IBC.  I would have done it for half (I hope someone at IBC reads this :-) ). Saurabh Jha, Lisa Rosenbaum, and Rocky Bilhartz are a few fellow physician who have spoken eloquently about the pitfalls of quality metrics.  As I look down the list of facilities I am being compared to, I know who the most efficient, highest value providers are.  The challenge of quantifying this effectively in a reliable manner remains a vexing one.  

My response to Dr. James

What follows is an email correspondence that nicely represents the different positions Dr. James and I take on the issue.


Dear Dr. Koka,

I really appreciate the respectful way you disagreed with me, and I agree with you that it is probably time to let the issues rest in the realm of respectful disagreement. I never expected to make anyone comfortable with my analysis, least of all physicians and hospitals. Harm during hospital care is an uncomfortable topic. One comment I received on the paper from a physician was something like "How good do you expect us to be? Maybe 1% is the best we can do." I don't know the answer to that.  I think physicians and patients working together can substantially reduce the preventable harm.

What I would say to your physician colleagues that do not like my assumptions - then please go ahead and survey the data and draw your own conclusions, and then publish them in a peer-reviewed journal. Better yet, do a comprehensive study of preventable harm in hospitals that has the scope and depth to at last get irrefutable data on preventable harm in U.S. hospitals. Then we can track improvements as those unfold.

I wish you well in your efforts to heal those with heart troubles. I think there can be nothing better in life than healing another human being.

Best Regards,

john james

-----Original Message-----
From: Anish Koka 

Sent: Nov 30, 2015 7:07 PM
To: John James , dwbates@bics.bwh.harvard.edu
Subject: Re: Journal of Patient Safety article

Dear Dr. James,

Thank you again for your response. I do appreciate your time.  I don't think I'm trying to impose my beliefs on the data.  I guess you can say I am trying to strictly interpret the data, but that is what evidence based medicine is. I am fairly certain you are comfortable with your assumptions, which is why you made them in the first place.  I have yet to find a physician who takes care of patients who is comfortable with the assumptions you have made.  

My comments below, but  I think we will have to agree to disagree.  

Again, I do appreciate your time, and I do applaud your efforts to shed light on this very important issue

Respectfully,

Anish Koka

On Mon, Nov 30, 2015 at 6:13 PM, John James <john.t.james@earthlink.net> wrote:

Dear Dr. Koka,

My comments below on your thoughts. I think you are trying too hard to demand precision and impose your beliefs upon the data available. No one has performed a single study that would represent the nation as a whole. You seem to be stuck on the Landrigan study as somehow representative and it is not. There is certainly more than one way to handle the available data, but in my paper I made it clear which choices I made and why. I might point out that the number 178,000 you suggest below would make preventable adverse events the third leading cause of death.

Best Regards,

john james

-----Original Message-----
From: Anish Koka 
Sent: Nov 30, 2015 1:18 PM
To: John James , dwbates@bics.bwh.harvard.edu
Subject: Re: Journal of Patient Safety article

Dear Dr. James,

Thank you for the response. I sent a letter to the editor as I was hoping to have a peer review your approach as well.

Your response does clarify one matter I was confused with, but does reaffirm my challenge to your estimate.  The clarification that I didn't grasp in my initial email was that you assumed the total preventable harm rate to be equivalent to the lethal event harm rate. I do not feel this is a reasonable assumption.  While I understand that science and evidence based medicine must necessarily have some assumptions contained within them, I do feel your assumptions are a leap too far, especially for a paper that is intended to provide an 'evidence based' estimate of patient deaths due to medical error. 

My response to you with regards to the major issues are as follows:

1. The preventable harm rate is 69%

Only one paper has a preventable death rate noted (Landrigan).  The OIG study does not list preventable deaths, just a total preventable harm rate.

You have to assume that the Classen paper would have shown a similar rate of preventable harms.  You then have to assume that the preventable death rate is equivalent to the total preventable harm rate.  The classen authors write that all harms may in some way be preventable?  Since they have no way of telling they chose not to say so in their paper.  I don't think its fair for you to take that statement as a blessing to use all their harms as preventable.  Your attempt was to create an evidence based approach for harm data (this I applaud), but you are creating evidence in this case.  You excluded a number of papers because they didn't you the GTT, you could have excluded the Classen paper in coming up with a preventable harm rate. The actual evidence for preventable harms is below.  There are no assumptions in the numbers below.  That is what the evidence says.  If your interpretation of classen et al.,  were to hold, why not say all the harms were in fact preventable?  The OIG and landrigan paper specifically don't believe all adverse events that happen in hospitals are preventable.  Regardless of your belief or my belief, that is what the evidence says.  Again, the Classen folks could have said in their conclusion that they felt all harms were preventable.  They did not, and you shouldn't make that assumption for them.

Landrigan paper:

588 total harms,  364 preventable (63%)

OIG Medicare analysis

128 total harms, ~56 preventable (44%)

(364+56)/(128+588) = 58%

Assuming that.. (34.4 million x .58. x .0089) = 178,310.  Of course this assumes the preventable harm rate is equivalent to the preventable death rate.

PREVENTABILITY IS SUBJECTIVE AND AS I SAID, I COULD NOT IGNORE THE  OPINION OF THE WRITERS OF THE CLASSEN PAPER. CLEARLY, THEY BELIEVED THAT THE VAST MAJORITY OF ADVERSE EVENTS WERE PREVENTABLE. AS I SAID IN MY ORIGINAL RESPONSE, EVEN IF ONE TOOK THE MIDDLE VALUE OF 44, 63, AND >>63, THE RESULT IS HARDLY DIFFERENT THAN MY ORIGINAL ESTIMATE. LET ME EMPHASIZE THAT THIS IS AN ESTIMATE. YOU ARE ALSO TRYING TO TREAT EACH PAPER AS AN INDIVIDUAL SOURCE AND THIS IS NOT JUSTIFIED. ONE MUST LOOK AT THE AGGREGATE OF THE DATA.

It remains a fact that the Classen paper does not comment on preventable harms.  I also can't seem to find your quote in the article.  I searched the text for the same, with no results.  I assume this was personal communication?  I know you disagree but I certainly would not assume 100%.  I agree that this does not have a sig. effect on the number.  But of course, I don't think much of that number since I take issue with assuming total preventable harm rate is the same as preventable death.

AT THE RISK OF MORE CONTENTION, I SHOULD POINT OUT THAT I COULD HAVE WEIGHTED THE THREE LARGE PAPERS EQUALLY INSTEAD OF HEAVILY WEIGHTING THE LANDRIGAN PAPER. THAT WOULD BE OIG (2010), CLASSEN AND LANDRIGAN. IF I HAD DONE THAT, THE AVERAGE PERCENTAGE OF ADVERSE EVENTS WOULD HAVE BEEN 1.4 + 1.1 + 0.6 = 1.03%, WHICH IS A GOOD BIT HIGHER THAN THE WEIGHTED AVERAGE I USED OF 0.89%.

If you weighted the 3 papers equally that would be completely wrong, since the landrigan paper is 2-3 x larger than the other papers.

 

2. The lethal preventable harm rate is equivalent to the total preventable harm rate

In your article you assume the lethal preventable harm rate is equivalent to the total preventable harm rate.  You say in your response that you think the lethal preventable event rate is higher than the total preventable harm rate.  What basis do you have to make that assumption? The landrigan paper is the only paper that allows a comparison of this, and only in this one case does this happen to be about the same.  As a busy clinician in the hospital, I feel that of all the people dying in hospitals, much less than 63% are preventable.  Again, that doesn't give me the right to write a paper about it.  I'm just one guy, and I could be completely wrong.  But you assume this based on your feeling, and have written a evidence based paper on this.

THE LANDRIGAN PAPER DOES STATE THAT THE OVERALL PREVENTABILITY IS 63%, WHICH IS WHAT I USED. FROM THEIR TABLE ONE CAN CALCULATE THAT THE PREVENTABILITY RATE IS 9/14 = 64% FOR LETHAL EVENTS.

You, elsewhere, have taken issue using one paper as being globally representative.  However, in this case, you have no issues with using the one papers lethal preventable event rate and extrapolating to the other 3, and of course to the 34 million folks.

PLEASE, WE ARE NOT TALKING ABOUT ALL THE PEOPLE DYING IN A HOSPITAL. WE ARE TALKING ABOUT DEATHS IDENTIFIED USING THE GLOBAL TRIGGER TOOL AS APPLIED TO WHATEVER INFORMATION MAY OR MAY NOT BE CONTAINED IN THE MEDICAL RECORD. OBVIOUSLY MANY PEOPLE PEOPLE DIE IN HOSPITALS IN WAYS THAT WOULD NEVER BE FLAGGED BY THE GTT. I ALSO MADE IT CLEAR THAT MANY DO NOT ACTUALLY DIE IN HOSPITALS. THEIR DEATHS ARE HASTENED BY FAILURE TO USE EVIDENCE BASED MEDICINE. THE MURTHA EXAMPLE ATTEMPTED TO MAKE THAT CLEAR TO YOU. 

I agree completely with this comment.  But then how do we know what the number is?  This smells of something I was taught in computer science class all the time -- Garbage inputs lead to garbage outputs. 

I ASSUME YOU ARE WELL AWARE THAT CARDIOLOGISTS OFTEN DO NOT FOLLOW EVIDENCE-BASED MEDICINE IN THEIR PRACTICES. I HAVE MESSAGES FROM CARDIOLOGISTS FRUSTRATED BECAUSE THEIR COLLEAGUES IGNORE THE NEED FOR CAREFUL ELECTROLYTE MANAGEMENT IN THE FACE OF HEART ARRHYTHMIA. I READ IN THE LITERATURE THAT FAR TOO MANY CARDIAC CATHS ARE PERFORMED - AGAINST THE EVIDENCE. ONE STUDY I RECALL SHOWED THAT IF TROPONIN IS USED AS AN INDICATOR OF TISSUE DAMAGE, THEN A LARGE PERCENTAGE OF CARDIAC CATHS CAUSE SOME SUBCLINICAL TISSUE DAMAGE. THERE IS ONE NOTORIOUS EXAMPLE OF HUNDREDS OF CARDIAC BYPASS SURGERIES DONE ON PATIENTS THAT NEVER NEEDED THEM. MANY DIED.

Again, while all of this does happen, one needs to know how often this happens. What are the numbers?  How often are lethal arrhythmias happening because of inadequate electrolyte repletion , how often are inappropriate bypass surgeries being done? How often do people die?  You assume this happens commonly..again I don't know for sure, it doesn't feel like any of this is happening on a daily basis...but I would not deign to write an article based on that feeling.  With no intention to agitate/upset you I would suggest your underlying belief of the frequency of these events is shading the assumptions you make.

I THINK YOU NEED TO VIEW THIS AT A TOP LEVEL. WHAT I ASSERT IS THAT SOMEWHAT MORE THAN 1% OF THE TIME WHEN A PERSON IS HOSPITALIZED, THEIR LIFE IS SIGNIFICANTLY SHORTENED BY INAPPROPRIATE (NON-EVIDENCE BASED) CARE IN HOSPITALS. THAT DOES NOT MEAN THAT THEY DIE IN THAT HOSPITAL. PLEASE ALSO NOTE THAT MY ESTIMATE INCLUDES HOSPITAL ACQUIRED INFECTIONS, WHICH THE CDC ESTIMATED KILL 100,000 PERSONS EACH YEAR IN 2007.

Why do you think that?  A better way to think about this is that out of a 1000 patients that are presenting to hospitals in need of help, 4 are dying due to a preventable error (Landrigan).  Using your numbers (0.58 x .0089), 5 out of a 1000 patients presenting in need of help are dying due to a preventable error.  And while much can be done to prevent, for example, infections in the hospital, there are some infections that will not be preventable.  Some patients who get central lines, despite appropriate, evidence based care, will have infections.  Some patients who get put on antibiotics to save their lives from sepsis, will get Clostridium difficile, and some may die from this.  

3. The evidence for lethal preventable deaths.

You note that you can't just use one paper to make an estimate.  Why not? IT IS NOT REPRESENTATIVE OF THE NATION AS A WHOLE.  If only one paper has the answers you seek, and the other papers are not appropriate, you use whatever you can.  Regardless of whether you use one paper or four papers, you are talking about extrapolating data from ~3000 patients to 34 million patients.  It would be better to use only papers that allow you to make reasonable assumptions.  Again I would have used the Landrigan paper to be pure.  If you wanted to assume that the lethal harm rate was equivalent in the OIG analysis, I guess that may be done, but you're starting to walk on planks not supported by evidence.

Simply put, If you want to know what the lethal event rate in a population is, multiply that by the population.  

In this case, the most evidence based number is to take the landrigan papers lethal event rate (9/2341) .384% x 34,400,000 (medicare admissions 2010). That equals ~ 130,000.  

AS I HAVE SAID, ONE MUST LOOK AT ALL THE STUDIES AVAILABLE, AND THE LANDRIGAN PAPER, AS I POINTED OUT IN MY JPS PAPER, IS LIKELY TO BE A LOW ESTIMATE OF THE NATION AS A WHOLE.

I understand that one paper is a poor representation.  Obviously my argument is that pooling together, and aggregating/extrapolating inappropriately isn't a good representation either.  By the way, while you state that the north carolina folks may be better than the nation part of the conclusion of the landrigan paper is that no significant improvement has been seen in harm rates over the years (2002-2007)

4. The factor of 2.

There is little question that this approach does not capture errors not captured in the medical record, errors happening after leaving the hospital, or errors of misdiagnosis, nondiagnosis.  But again, the question, and your charge was to come up with an evidence based estimate.  Where is the evidence for your factor of 2, 3, or 4? WEISMANN IS THE BEST THERE IS. Perhaps I feel its 1, or 1.2, or 1.3 or 10?  who knows?? Again, I surmise from your response that you think the factor should be even higher.  I will submit readily to not knowing what that number is.  It doesn't 'feel' like medical errors are the 3rd leading cause of death, but again I wouldn't write a paper based on that feeling.  MEDICAL ERRORS ARE OFTEN A CONTRIBUTING FACTOR IN PATIENT DEATH; OF COURSE, A MEDICAL ERROR ALONE IS UNLIKELY TO KILL A HOSPITALIZED PATIENT - THEY ARE IN THE HOSPITAL BECAUSE THEY DO HAVE AN ILLNESS IN MOST CASES. 

In essence, you have used a feeling to come up with that number.  THAT IS NOT TRUE. THE EVIDENCE IS LIMITED, BUT THERE IS SOME EVIDENCE THAT MEDICAL RECORDS ARE MISSING INFORMATION THAT WOULD ALLOW A REVIEWING PHYSICIAN TO SEE THAT AN ADVERSE EVENT HAD OCCURRED. YOU PRESUME THERE IS NO EVIDENCE AND THAT IS NOT TRUE. This has a place in an op-ed, but not in a paper that should require some type of evidence to back up this claim.

IN MY PAPER I POINT OUT THE BASIS FOR THE ESTIMATE THAT THE GTT MISSES AT LEAST HALF OF THE ACTUAL LETHAL, PREVENTABLE, ADVERSE EVENTS. ONE CANNOT IGNORE THE LIMITATIONS OF THE SEARCH TOOL AND THE LACK OF VERACITY OF THE MEDICAL RECORDS. THE WEISMANN PAPER SUPPORTS MY CHOICE. YOU MAY HAVE CHOSEN TO IGNORE THIS FACTOR, BUT I COULD NOT. I KNOW THAT ERRORS OF OMISSION, CONTEXT AND DIAGNOSIS ARE LARGE AND NOT TYPICALLY DETECTED BY THE GTT, AND I KNOW THAT MEDICAL RECORDS ARE OFTEN NOT A TRUE REPRESENTATION OF WHAT HAPPENED WHEN THERE IS AN ADVERSE EVENT. PLEASE READ THE WEISMANN AND DUNLAY PAPERS. 

I don't see an evidence based estimate for the factor of 2.  I read the Weisman paper.  This was a paper that used post discharge interviews of patients to find events not in the medical record.  So necessarily, these were all patients that survived.  I still don't see how you come up with your factor based on this.  Again, I could say its 10, and you wouldn't (by your logic) say I was wrong.

As, an aside... I reviewed the serious adverse events deemed preventable in this paper.  Let me just give you the first one.. DVT develops after open heart surgery.  If the patient was receiving appropriate DVT prophylaxis after their open heart surgery, was it really preventable? I guess if the open heart surgery was unindicated? But who knows??  After I read this paper, I emailed Dr. landrigan to ask him if the clinical summaries on the 9 deaths in his study were available somewhere.  He has not responded :/

Respectfully,

Anish Koka