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Special Communication
February 3, 1999

Avoiding the Unintended Consequences of Growth in Medical Care: How Might More Be Worse?

Author Affiliations

Author Affiliations: VA Outcomes Group, Department of Veterans Affairs Medical Center, White River Junction, Vt, and the Center for the Evaluative Clinical Sciences, Dartmouth Medical School, Hanover, NH.

JAMA. 1999;281(5):446-453. doi:10.1001/jama.281.5.446

The United States has experienced dramatic growth in both the technical capabilities and share of resources devoted to medical care. While the benefits of more medical care are widely recognized, the possibility that harm may result from growth has received little attention. Because harm from more medical care is unexpected, findings of harm are discounted or ignored. We suggest that such findings may indicate a more general problem and deserve serious consideration. First, we delineate 2 levels of decision making where more medical care may be introduced: (1) decisions about whether or not to use a discrete diagnostic or therapeutic intervention and (2) decisions about whether to add system capacity, eg, the decision to purchase another scanner or employ another physician. Second, we explore how more medical care at either level may lead to harm. More diagnosis creates the potential for labeling and detection of pseudodisease—disease that would never become apparent to patients during their lifetime without testing. More treatment may lead to tampering, interventions to correct random rather than systematic variation, and lower treatment thresholds, where the risks outweigh the potential benefits. Because there are more diagnoses to treat and more treatments to provide, physicians may be more likely to make mistakes and to be distracted from the issues of greatest concern to their patients. Finally, we turn to the fundamental challenge—reducing the risk of harm from more medical care. We identify 4 ways in which inadequate information and improper reasoning may allow harmful practices to be adopted—a constrained model of disease, excessive extrapolation, a missing level of analysis, and the assumption that more is better.