CER and MCC: a marriage made in DC

Share with your friends


The NEJM has just published another promotional piece on “Comparative Effectiveness Research” in its on-going series on health policy and reform. But this time, behind the usual grandiose claims of CER, authors Tinetti and Studenski betray a certain tone of apprehension…

The aim of comparative effectiveness research (CER) is to improve the quality, effectiveness, and efficiency of health care and to help patients, health care professionals, and purchasers make informed decisions. CER is moving forward, with recently defined priorities and a newly funded Patient-Centered Outcomes Research Institute, which we hope will survive congressional cost cutting.

Congressional cost cutting!  How dare they!  Those tea-party rubes!  Anti-quality, that’s what they are!

To achieve its goals, CER must address the population that consumes the most health care: patients with multiple chronic conditions, especially those with combinations of behavioral and physical conditions such as dementia, mental illness, end-stage renal disease, and heart failure. Such patients account for more than 80% of Medicare costs and are overrepresented in Medicaid and private insurance plans.

Truly the most favored diagnosis of the age is “multiple chronic conditions (MCC)” or it’s clinical variant, “multiple medical problems (MMP).”  We seem to be literally plagued by this condition.  Just hear a resident say the words “a 67-year-old female with multiple medical problems,” and you know she shall not be healed.  It is quite puzzling that no ICD-9 code has yet sanctioned the syndrome…

But at least, CER will now turn its attention to confront this dreaded affliction.  Indeed, “such patients” are “overrepresented,” whether MCC reflects the muddled thinking of indifferent doctors, the epiphenomenon of a compensation system that rewards “risk-adjustment,” or the unwieldy reality of an aging population.

The almost infinite combinations of diseases, treatments, and other factors affecting health outcomes or treatment responses will make identifying representative study populations a daunting task.

Yes, an honest appraisal of the challenges ahead doesn’t hurt…

The requisite sample sizes and long-term follow-up all but preclude conducting randomized, controlled trials for multiple chronic conditions. Observational research can better accommodate the large, heterogeneous populations needed to examine treatment effects and outcomes under real-world conditions over long periods. However, confounding and bias limit observational studies’ capacity to distinguish treatment effects from the effects of patient-related, disease-related, and provider-related factors.

To isolate treatment effects, researchers must consider myriad personal and provider characteristics that are associated with the likelihood of either receiving the study treatments or achieving the target health outcomes.

Indeed they must…

The heterogeneity of treatment effects will further complicate CER. Although studies typically report average effects, most participants experience more or less benefit and harm than average. Such heterogeneity results from variability in patients’ initial level of risk for a given outcome, in their responsiveness to treatment, and in their vulnerability to adverse effects — issues with particular relevance to patients receiving treatment for multiple coexisting conditions.  Treatments must be compared within homogeneous risk strata, defined according to characteristics that affect both benefit and harm from those treatments.

But who defines what’s a benefit and what’s a harm?

The benefits and harms of any treatment may also change over time, as people age and accrue additional conditions and treatments. Current treatment studies rarely last more than 5 years. Changing responses to treatment must be incorporated into CER, necessitating longitudinal studies.

You bet…but wait, we have the solution…

Fortunately, large, representative, and heterogeneous cohorts with well-documented characteristics are or will soon be available for longitudinal observational studies. The Medicare Current Beneficiary Survey (MCBS) and the HMO Collaboratory from the National Institutes of Health (NIH) are examples of relevant sources.

That’s right, the hope of CER is a Medicare survey and HMO GIGO!..

In theory, electronic health records (EHRs) would be the ideal source of participants and data, allowing for real-time comparisons of treatment in real patients. To isolate treatment effects, however, EHRs will need to contain more comprehensive, reliable data on health, function, and other variables than they currently do.

And on who else but the doctor can we rely to enter the “reliable data?” Continuing…

Perhaps the most fundamental question is how to define benefit or harm when multiple conditions coexist and multiple treatments are being compared…Aggressive antihypertensive treatment, for example, may benefit relatively healthy hypertensive people at any age, but what about a 75-year-old who is depressed, cognitively impaired, and taking 10 other medications?

That means no Tekturna for aunt Hilda! and the benefits don’t end here…

CER will probably accelerate the movement toward outcome-driven decision making, reimbursement, and quality assessment.

Yes, in one fell swoop, the big computer will optimize cost, quality, and safety.  But here’s the big one:

As this shift occurs, we must move toward a focus on cross-disease, “universal” outcomes in research and clinical care. Universal health outcomes — outcomes on which all diseases exert an effect — are the consequences that matter to patients…

I don’t know about you, but when I hear “universal outcomes” common to “all diseases” I have this nagging vision of a tall figure with a large scythe and a black cloak.  But no death panel to see here, move along…Oh wait!…

Because older adults may value independence over longevity, it makes sense to assess active life expectancy, measured over time to capture periods of disability and recovery…

Yes, they may value independence over longevity, and they’d better not change their mind!

Head-to-head comparison is the third key feature of CER. To reduce the complexity of treatments, interventions such as exercise that affect multiple conditions simultaneously should be a high priority.

Indeed,  who could think of a better-suited candidate for an exercise program than the patient with “dementia, mental illness, end-stage renal disease, and heart failure?”

Researchers have largely shied away from the complexity of multiple chronic conditions — avoidance that results in expensive, potentially harmful care of unclear benefit. We cannot improve health care’s quality, effectiveness, and efficiency without addressing its greatest consumers. Development and testing of innovative approaches to care for patients with multiple chronic conditions could prove the most lasting legacy of CER.

Ponder that, Paul Ryan!

Whether CER survives congressional cost cutting remains to be seen.  But it seems that we keep raising the ceiling to accommodate all the hot air coming out of DC-based medical think tanks.