Nurse-Staffing Levels and the Quality of Care in Hospitals

Jack Needleman, Ph.D., Peter Buerhaus, Ph.D., R.N., Soeren Mattke, M.D., M.P.H., Maureen Stewart, B.A., and Katya Zelevinsky
N Engl J Med 2002; 346:1715-1722May 30, 2002DOI: 10.1056/NEJMsa012247

Hospitals, wrote Lewis Thomas in The Youngest Science, are “held together, glued together, enabled to function . . . by the nurses.”1 More than 1.3 million registered nurses work in hospitals in the United States. As hospitals have responded to financial pressure from Medicare, managed care, and other private payers, registered nurses have become increasingly dissatisfied with the working conditions in hospitals. They report that they are spending less time taking care of increasingly ill patients and believe that the safety and quality of inpatient care are deteriorating.2-7 Although the number of hours of care per patient-day provided by registered nurses rose through the mid-1990s,8-12 some question whether the staffing of nurses has increased rapidly enough to keep pace with the increasing severity of illness among hospitalized patients and thus to ensure safe and high-quality care.13

Research on the relation between the level of staffing by nurses in hospitals and patients' outcomes has been inconclusive. Whereas some studies have reported an association between higher levels of staffing by nurses and lower mortality,14-20 as well as lower rates of other adverse outcomes,21-30 others have found no such relations.30-39 Previous studies have assessed only a limited number of outcomes that are sensitive to the extent or quality of nursing care, such as falls by patients and errors in medication. Many studies have used small samples of hospitals, controlled only to a limited extent for the patient's initial risk for the outcomes under study, failed to include nurses' aides as part of the nursing staff, and used inconsistent measures of staffing levels. We examined the relation between the levels of staffing by nurses in hospitals and the rates of adverse outcomes among patients, using administrative data from a large multi-state sample of hospitals.

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