Public program evaluators more often than not find that things did not go as the program designers planned. The most cynical prediction of such results is Murphy’s Law: Everything That Can Go Wrong Will Go Wrong. In my experience as an evaluator of major health policy programs, this is way too cynical. Typically only a few things go wrong, but unfortunately, predictably, often it is the same ones. I call them Murphy’s Regulations: The idea is that when laws are turned into regulations and are implemented, things go wrong. Two common ways they go wrong are the woodwork effect and slippery slope.
The Woodwork Effect
When public policy tries to substitute a new good thing for an old bad one, we often get more of the new thing without much reduction in the bad thing. When a new more attractive service is offered as a substitute for an older less attractive service, a whole population of new users is attracted to the new service. Rather than reducing use of the old service, people seem to “come out of the woodwork” to use the new service, thus increasing the scope—and cost—of the program. Economists call this phenomenon getting “complementarity” when what you wanted was “substitution.” It is ubiquitous in health policy.
A recent example is e-cigarettes. FDA hoped the new product would help smokers quit cigarettes. While a bit of that may have occurred, what e-cigarettes also did was usher in a whole new generation of teen smokers who were strongly turned off to actual cigarettes but were delighted to try the new cool indulgence of vaping. So now we have millions of teenagers hooked on nicotine who wouldn’t have even considered smoking a cigarette.
Another example involves nursing homes–no one’s favorite place to live. As a way to keep patients out of nursing homes, advocates pushed for Home and Community Based Care—where services are delivered in the patient’s home. But study after study shows that those who use home care services are not the same kind of patients as those who use nursing homes. They differ in age, level of disability, likelihood of having a living spouse, and presence of mental illness. The result is that expansion of home and community based care has not substantially reduced nursing home use, but has increased the use of home care services, the total people served, and spending when the goal was to reduce Medicaid outlays. Nor have promised improvements in longevity, mobility, activities of daily living, life satisfaction and caregiver satisfaction been borne out in a plethora of studies.
The Slippery Slope
One way the Woodwork Effect occurs is through eligibility screening. Imagine yourself spending your day deciding which frail elderly patient is likely to go to a nursing home, and which is not. To avoid the Woodwork Effect, you must limit home care to only those who would otherwise be in a nursing home. (The law actually calls for enforcing that very criterion – a nearly impossible notion requiring screeners to be soothsayers.). So you decide that a patient fits the criterion. An hour later, someone very similar, not precisely as frail and ill as the one you decided upon, but very close appears and you decide she is so close to the one you let in earlier that it would be unfair to deny her home care. As the days wear on, you decide each new case in relation to the most recent cases you’ve admitted. The criteria you are applying have broadened, and you’ve moved down a Slippery Slope.
So too for new bonus payments in hospitals and those to physicians to improve care, called Pay for Performance. It is a seemingly great idea that Congress seems to love. But when it was studied years earlier in nursing homes, the Slippery Slope problem arose. The payment scheme paid the highest bonuses for caring for comatose patients who required skilled nursing attention, frequent turning and positioning in their beds, and frequent taking of vital signs.
But nurses working in the nursing homes pointed out that patients who lapsed in and out of coma required the same amount of care. Then other nurses pointed to their patients who were not suffering coma but required turning and positioning, vital signs, etc. And these cases were followed by patients not in coma, but unable to move without turning and positioning by nurses, even though the patient could lift an arm and put it on the bed rail, but could bear no weight and was unable to assist in her care. Finally, came a nurse with a patient who could lift two arms, but required turning, etc.
Government programs inevitably require deciding who will and who will not be deemed eligible and therefore get or be denied benefits. It’s a hard, nearly impossible task in many cases not to mention the human toll on the decision maker who must deny help to obviously needy people. The threat of law suits, including class action suits, may contribute to weakening of selection criteria as well: The Slippery Slope.
Solutions to Challenging Problems
There are ways to counter some of these problems, but they are challenging. For example, one can give up on screening and focus instead on how much to spend on each patient, ignoring whether they are “sick enough to quality, or not.” That is, titrate the amount of care and the budget allowance for a particular patient to their level of illness and need for help. Care prescribers seemed to welcome and accept the approach when tried in a randomized trial. It not only mitigates the Woodwork Effect because the new patients are served very cheaply if they don’t need much care, but it also vitiates the need for the loathsome eligible/ineligible Slippery Slope screening decision.
Yet these solutions have not caught on because screening against a single criterion is so entrenched in public policy. Perhaps if Murphy’s Regulations were to become as much a part of the public policy lexicon as Murphy’s Law, attention would turn to what actually does go wrong as opposed to throwing up hands in the assumption that everything is going wrong.
Dr. William Weissert is a Professor of Political Science and an expert in health politics and policy.
The feature image is from Amazon.com.