What if policymakers, science reporters and even scientists can’t distinguish between weak and trustworthy research studies that underlie our health care decisions?
Many studies of healthcare treatments and policies do not prove cause-and-effect relationships because they suffer from faulty research designs. The result is a pattern of mistakes and corrections: early studies of new treatments tend to show dramatic positive health effects, which diminish or disappear as more rigorous studies are conducted.
Indeed, when experts on research evidence do systematic reviews of research studies they commonly exclude 50%-75% because they do not meet basic research design standards required to yield trustworthy conclusions.
In many such studies researchers try to statistically manipulate data to ‘adjust for’ irreconcilable differences between intervention and control groups. Yet it is these very differences that often create the reported, but invalid, effects of the treatments or policies that were studied.
In this accessible and graph-filled article published recently by the US Centers for Disease Control and Prevention, we describe five case examples of how some of the most common biases and flawed study designs impact research on important health policies and interventions, such as comparative effectiveness of medical treatments, cost-containment policies, and health information technology.
Amid the rancorous debates over the Affordable Care Act, one provision deserves to be getting serious discussion.
It’s a provision that allows employers to increase the amount that they may fine their employees for “lifestyle” conditions, such as being overweight or having high blood pressure or high cholesterol.
Almost 37% of Americans are overweight or obese. The supposed goal is to use financial penalties to reduce obesity, the health costs of which exceed $200 billion per year. But this idea, while well intended, will not help Americans suffering from obesity, a medically defined disease and disability. In fact, it will likely make their situation worse.
For years, the country’s “wellness” industry has offered health-enhancement and obesity-reduction programs to corporations, from gym memberships to dietary counseling. For obesity, this approach has not worked. Research on these programs shows that they have not significantly reduced weight or cholesterol levels, or improved any other health outcomes.
Even the most successful programs, such as Weight Watchers, achieve an average two-year weight loss of only about 3% for their members— and even that tiny weight loss often returns later.
Among the sacrifices Congressional representatives placed on the altar of deficit negotiations is an “inflation adjustment” that will shave “only” a few hundred dollars from an average, newly retired Social Security beneficiary’s income each year. But the cruel hoax is that the reduction will amount to as much as $1600 when the beneficiary is older, poorer, and sicker. Many seniors already have a tough time paying for food, rent, and medical care.
Even worse, reductions in beneficiaries’ incomes may well cost government more for potentially preventable hospital and long-term care. Senator Elizabeth Warren and other New England lawmakers should be lauded for splitting from Democratic representatives and the Administration regarding this ill-conceived proposal.
Many senior citizens are already vulnerable to economic hardship. A recent US Census analysis that counts rising medical expenses found that over 1 in 6 elderly people live in poverty, unable to meet basic living expenses, and almost 20% more are living just above the poverty line. Social Security is the only or largest source of income for about 70% of seniors; the average monthly check is only about $1200.
The typical retirement savings of seniors is a paltry $50,000 — barely enough to get through several years’ living expenses, let alone 20-30 years of retirement. This is not the result of cavalier actions by the older generation; these are the Americans whose home values have plummeted, whose defined-benefit pension plans have been decimated or disappeared, and whose retirement accounts were eviscerated by the Wall Street meltdown of the last decade. Yet the current proposal punishes these Americans as if they were at fault for their poverty.
Fidelity Investments has estimated that the average retired couple will need more than $200,000 to pay their out-of-pocket medical expenses during retirement, and that figure is probably conservative.
The arithmetic of Social Security benefit reductions just doesn’t fit with this reality.
If one were writing about the improvement of gastronomy in America, one would probably not celebrate “over 300 billion hamburgers served.” But that’s very much the type of success Dr. Ashish Jha is celebrating in last week’s piece on recent US healthcare IT sales. Unfortunately, the proliferation of Big Macs does not reflect superior cuisine, and healthcare IT (HIT) sales do not equate with better healthcare or with better health. Quantity does not equal quality of care.
To be sure, Dr. Jha acknowledges the challenges of rolling out HIT throughout US hospitals. And he should be strongly commended for his admission that HIT doesn’t capture care by many specialists and doesn’t save money. In addition, Dr. Jha points to the general inability of hospitals, outpatient physicians and laboratories to transfer data among themselves as a reason for HIT’s meager results.
But this is a circular argument and not an excuse. It is the vendors’ insistence on isolated proprietary systems (and the government’s acquiescence to the vendors) that created this lack of communication (non-interoperability) which so limits one of HIT’s most valuable benefits.
In our opinion, the major concern is that the blog post fails to answer the question we ask our PhD students:
So what? What is the outcome?
This entire effort is fueled by $29 billion in government subsidies and incentives, and by trillions of dollars spent and to be spent by hospitals, doctors and others .
So where is the evidence to back up the government’s and industry’s promises of lower mortality, improved health and lower health care costs?
Single studies tell us little. Sadly, as many as 90% of health IT studies fail the minimal criteria of the respected international literature syntheses conducted by the Cochrane Collaboration.
In other words, studies with weak methodology or sweetheart evaluation arrangements just don’t count as evidence.