Reducing Cancer Care Costs by Comparative and Cost-Effectiveness Research (CER)
Well, it’s the day after Labor Day, time to resume our discussion of Bending the Cost Curve in Cancer Care.
We’ve reached the end of the list, on ideas to reduce oncology costs put forth by Drs. Smith and Hillner in the May 25 issue of the NEJM. Really this 10th and final point intended for oncologists is two-in-one: “The need for cost-effectiveness analysis and for some limits of care must be accepted,” they chart. So doctors should embrace studies of comparative effectiveness and cost effectiveness.
Hard to argue with reason – they’re correct, of course. They write:
… The national imperative is to empower a transparent, acceptable, equitable, politically independent agency for guidance in making tough choices in the public interest so that doctors do not have to make them at the bedside.60 Ultimately, we will have to make decisions based on some criteria, and comparative-effectiveness61 and cost-effectiveness62 analyses are good ways to align resource use with the greatest health benefit.
This sounds great, and is probably right, but I don’t think it’s realistic.
A more detailed consideration on the issue of cost-effectiveness, IMO, came out a few weeks later, also in NEJM: Comparative Effectiveness Research and Patients with Multiple Chronic Conditions. This piece, by Drs. Mary Tinetti and Stephanie Studenski, considers the problematic application of CER in the real world.
The problem with CER, these authors emphasize, is that most medical patients have more than one condition and many are elderly; clinical trials tend to include, exclusively, patients who don’t have more than one major illness are relatively young. This limits the physicians’ abilities to apply data to their patients.
What’s more, reported results tend to focus on central results, but most patients fall elsewhere on measured curves:
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.
The authors, who recognize the need for better research to support treatment decisions, write that “CER will probably accelerate the movement toward outcome-driven decision making, reimbursement, and quality assessment. As this shift occurs, we must move toward a focus on cross-disease, “universal” outcomes in research and clinical care.” Their thesis gets more abstract (which I admire), but meets a wall or two: the lack of consensus on a set of universal health outcomes, different parameters measured by the likes of the VA administration, CMS, the FDA, NIH and other huge agencies.
They make a practical suggestion, about the need for head-to-head comparisons in CER:
… interventions such as exercise that affect multiple conditions simultaneously should be a high priority…Studies should include assessment of the burden of treatments for patients and families. Another CER priority should be the examination of treatments for common pairs of diseases in which treatment of one may exacerbate the other. For example, when hypertension and osteoporosis coexist, what treatment best minimizes the risk of adverse cardiovascular outcomes without increasing the risk of falls and fractures?
All of this sounds reasonable to this patient-doctor, but it’ll take a lot of time and money to accomplish effective CER that encompasses the needs and conditions of sufficient numbers of patients in disease and age combinations to power any meaningful studies. You have to wonder at some point, as I have been lately, is all this clinical research worth the effort?
That said, I respect this paper‘s conclusions on CER:
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…
My bottom line: CER, and consideration of treatment costs, should underlie reduction of cancer care costs in the near and long-term future. As to how we accomplish sufficiently careful research, and avoid inappropriate cutting of helpful treatments – especially those that prove beneficial for some younger and otherwise healthy cancer patients – is one of the two main challenges ahead.
(The other big challenge, mainly a moral one, is the subject of rationing, to which Smith and Hillner allude but don’t detail, and which subject I won’t address in this post.)
Meanwhile: thorough, apolitical, nuanced and transparent reporting of trial results would help doctors, patients and the general public understand what information is available.
Finally, in the next month or so I will look back over the full, provocative and generally excellent list by Drs. Smith and Hillner, and see what holds hope for the future of cancer medicine. What’s clear is that the path ahead mandates clear thinking through some very tough clinical decisions.
Excellent post. While I agree with most of what you wrote here – keep in mind that we can’t even begin to discuss what treatment works best for which patient (the ideal we are trying to get to….) without DATA. Right now – there are TONS of data on millions and millions of people with cancer – sitting in data warehouses – but they are underused because they are incomplete in their capture of the clinical cancer picture. In some regards – it is almost a crime that we have so much data and yet know so little from it. As you point out – trials can’t answer many questions because they are expensive, include too few people and exclude many due to other conditions. We need to harness the observational data that exists with insurers, hospitals and clinics – and find a way to work with it while protecting patient privacy. This should be our first order of business. The data are there…..
Kathy, I agree; there’s lots of untapped data on cancer treatment and other conditions. The problem is organizing and mining it in a way that doctors find credible and (more importantly) that reveals genuine (non-artifactual) information.