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Impact and Implications of Comparative Effectiveness Research

by William DeMarco, November 2, 2010

MCOL asked me to respond to the following questions for their Thought Leaders publication: What will be the impact and implications of Comparative Effectiveness Research on U.S. health care delivery, in the short-term, and in the long-term? How dependent is CER, going forward, on federal policy and funding?

My abbreviated response is included in the current issue of Thought Leaders, but I wanted to provide a more complete response below.

Comparative effectiveness research is somewhat of a newcomer to healthcare.
Borne out of early practice variation studies at Dartmouth and other universities that reported surprising gaps in the delivery of care at the physician level, the CER takes this one step further to explain not just what the variance is but what the norm should be as a best practice.

These evidence based norms and practice guidelines are intended to give us a starting point to what we have been missing and that is ambulatory care comparators and a full disclosure of what are the best practices for a specific diagnosis for a specific population of patients with similar co morbidities and health status.

For decades we have seen hospital data on costs and length of stay being produced as DRGs and admissions data were available and understandable to many of us as a common unit of measurement and cost. Payers saw this as a large bottom line expense not realizing that the reason people were admitted was not because the hospital made that decision rather the doctors made the decision to admit based upon what they thought was a diagnosis that warranted such and action.

As we begin to look for root cause as to why the doctor thought this admission should occur we see again variation in practice style, training and capability come into play. The patient variation suddenly becomes key to understanding the physician logic and we start to see a move towards patient and population management which the CER process is trying to address.

Now we should have the ability with millions of records and billions of dollars invested in CER by HHS to discover just what is an appropriate admission for a specific diagnosis and begin to track this through impatient and outpatient treatment which is an imperative for a better understanding of how best to handle chronically ill populations as well as some of the less critically ill who need to be treated BEFORE they move to stage three or four cancer.

We have always asked about how lower back pain should be treated for the 70 year old versus the 50 year old, we have always wondered whether the mammogram should be done annually at 40 or 50 or is to tied to whether or not the patient has a predisposition and family history.

These are worth studying in terms of screening and are also worth building available database to see what works because much to the surprise of the public not all patients are treated the same because not all doctors are trained the same. Once can see a pattern of care in the medical notes and billing for a patient with hypertension yet 5 other doctors in the same group may treat this hypertension differently. Who is right and what is the best guideline to follow is.

In addition these guidelines change as we move from the discoveries and technologies of health care. CAT scans are useful but are they as useful for some illnesses as a MRI or would a simple x-ray do?

Most patients still ask for antibiotic for a cold yet truthful doctors will say it’s a virus and you have to ride it out... we can see how a national registry would enable our medical training and treatment expectations to come together over time to rid the system of wasteful tests and spending and assure both doctor and patient the results are predictable based upon good scientific population studies.

However we can also see the negative side of the argument.

In England and other countries we have seen the rise of the QUALY measurement that is used to determine wethere4 a patient really is a candidate for a specific procedure.

In several situations the QUALY dictates whether the man or women with stage 4 cancer gets treatment, whether the baby with an incurable disease is treated at all.

QUALY is the measurement of cost versus treatment for many countries and with CER we could see this occur here in the US as Harvard and other universities begin to but a VALUE on a human life.

The QUALY can be used to make some of the treatment decisions and also can place a number on ones forehead for underwriting just like a FICA score does for credit and loans.

Several states have banned using clinical effectiveness and similar means to be used to withhold issuing policies for GROUPS but as we see a move towards more individual policies with newly promised insurance exchanges and the like we see a potential for QUAYS being used to justify higher premiums or cancellation of insurance policies when the score does not justify expenditures of funds for saving or even extending a life represents a potential risk to an insurance and healthcare system that is already under funded.

One can see that in the hands of some insurers this methodology could be brutally unforgiving. In the hands of government one can see they like the idea of numbers and distancing themselves from patients just setting in motion a number and backing into a Medicare or Medicaid budget.

This Kevorkian factor represents all that most of us in health care and the health plan business are against but represents both am moral and ethical battles to fight to police one another and make sure we are not letting statistics dictate the value of a human life.
Rather we would like to see a more fruitful transition of using CER to build upon health and prevention. To determine what in a person’s lifestyle could be changed to avoid diabetes and heart problems, what could be done in an exercise routine to strengthen a back injury without needing formal rehab?

So what can health plans do? As the CER begins collecting data we see the opportunity for health plans to collaborate on a regional basis to also pool de-identified data to determine unique care patterns in their area that can be addressed or diagnosis that can be mentored to determine an outbreak of disease or unseal pattern in treatment protocols during different times of the year.

Lack of Iodine in the water in Detroit affecting thyroids, sinusitis conditions in Seattle affecting respiratory illnesses, allergies in droves in an urban population that uses antibacterial soap extensively could all tie to an unusual outcome unless treated,

Moreover these local models would have a national comparator baseline to look at but also contribute to local CER research that could help streamline care and diagnosis precision but most certainly would, be a way to obtain even further ROI on data collection process at the Health plan, ACO or similar integrated system.

This moves health plans data away from the typical claims warehouse into a life-science role that could also be shared with Pharma for testing and data sharing as well as scientific studies by local and regional medical schools to look at systemic variation in population health.

Health plans are already doing this in some cities such as ICSI in Minnesota and similar efforts are being headed by employers in Las Vegas and St Louis to try and come up with a value comparison of outcomes to be shared with all health plans in developing and monitoring their individual P4P and global payment reforms.

CER offers wonderful tools and more discussion of its application by the scientific community can help us really understand what works and what works best in short term and long term treatment.

If the research should go the other direction of assigning dollar amounts to QUALYS and reduction of services to those who need hope the most we will see a rapid de-funding of the program and a very loud outcry from the scientific and religious communities.

Health reform arguments have already surfaced this debate between the use of CER as a practice guideline builder versus a potential rationale to limit care. Health Plans have it in their power to build local and regional warehouses for clinical and scientific research always sharing such research with a national clearinghouse such as CER.

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