NATIONAL BUREAU OF ECONOMIC RESEARCH
NATIONAL BUREAU OF ECONOMIC RESEARCH

Organizational Innovation to Improve the Efficiency of Health Care Markets

The high and rapidly rising cost of health care in the U.S. remains a critical issue. High costs burden the fed-eral budget due to the government's large role in providing health care through the Medicare and Medicaid pro-grams, which jointly make up 40 percent of the total U.S. health care market. High costs also make it difficult for individuals to afford health insurance.

High costs are less of a cause of concern if health care is provided efficiently and generates benefits that exceed its costs. Unfortunately, numerous studies suggest that one-third or more of medical resources is not buying improved health. This translates into over $700 Billion of excess spending in the U.S. each year.

In Where are the Health Care Entrepreneurs? The Failure of Organizational Innovation in Health Care (NBER Working Paper No. 16030), researcher David Cutler explores the causes of this inefficiency and the reasons why it has not been eliminated by market forces.

Cutler begins by noting that productivity growth has been much slower in health care than in most other sectors of the economy. In other industries, productivity growth has been driven primarily not by the development of new goods but by new ways of organizing production, distribution, and sales, changes that jointly have resulted in more output per dollar of inputs. In health care, by contrast, there has been very little organizational innovation. This contrast shows up in sources of wealth creation. Many members of the Forbes 400 richest Americans earned their fortunes by re-organizing the way that consumers buy goods and services, but that is not true of medicine. Success in medicine has almost always been associated with more intensive care or interventions to treat more severe patients.

He details three dimensions of the inefficiency of medical care production. The first is "flat of the curve medicine," a term that refers to the provision of additional medical care that results in little to no health benefit. A key example here is the treatment of prostate cancer, where the majority of patients receive intensive treatments such as a radical prostatectomy or radiation therapy even though there is no evidence that these treatments lead to better outcomes. Another example comes from the treatment of heart attacks, where patients in the U.S. are ten times more likely to receive coronary bypass surgery or balloon angioplasty than patients in Canada, but have no better short-term survival rates.

A second source of inefficiency is poor coordination of care. Many medical conditions require patients to see generalist and specialist physicians, get regular lab tests, take medications, and modify their behaviors, a complex regimen that is almost always left to the patient to plan and coordinate. Diabetes is a natural example. There are consensus guidelines for how frequently diabetics should check in with their doctors, have lab work done, and take medications. Yet fewer than half of diabetics receive the recommended therapy. This failure results in expensive complications as well as premature mortality.

The third aspect of low productivity is the excessive cost of providing services. Numerous studies have documented the substantial cost savings that could result from changes in how health care is provided. These changes include greater use of technology (for example, computerized ordering systems that eliminate adverse drug interactions) or other changes in procedures (for example, the use of surgical checklists or dedicated surgical suites for particular operations).

Cutler estimates that reducing flat of the curve medicine by half could result in savings of $350 Billion per year, while similar reductions in excessive costs could save $100 Billion per year. The savings from poor coordination of care are harder to gauge.

The obvious question is why the health care market has not evolved to become more efficient. To answer this, Cutler explores the incentives for providers to make investments that will improve quality. He notes that providers cannot charge a higher price for providing higher quality care because prices are typically fixed (for example, by Medicare). Providing higher quality care might result in a greater volume of patients if consumers had ready access to information on quality, but generally this information is not available. In fact, providing higher quality care may lead to lower patient volumes and revenues, since higher quality care may mean patients need fewer services and providers are often reimbursed a fixed amount for each service.

Cutler also examines why insurers and other payers do not impose changes that would improve productivity, such as requiring providers to use electronic medical records. One issue is that any individual payer has both limited ability to change provider behavior on its own and limited incentive to do so because it will not reap the full benefits. A lack of public information on insurer quality (which greatly reduces the insurer's ability to benefit from quality improvements) and turnover in a plan's patient base may also create weak incentives for insurers to improve quality.

In short, "lack of information and poor incentives are the key barriers to new organizational models." However, recent legislation has made changes in both of these areas. The American Recovery and Reinvestment Act of 2009 committed $30 Billion to fund the creation of a national system of electronic medical records over the next five years. Similarly, the Patient Protection and Affordable Care Act of 2010 will make Medicare data available to insurers, employers, and others for the purposes of forming quality measures. This legislation also introduced alternative payment systems designed to stress value more than volume, systems that have met with some success in small-scale experiments. Cutler concludes "whether the legislation addresses these problems sufficiently is something that only time will tell."


The author is grateful to the National Institute on Aging for financial support.

 
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