Inpatient quality deficits have important implications for the health and well-being of patients. They also have important financial implications for payers and hospitals by leading to longer lengths of stay and higher intensity of treatment. Many of these costly quality deficits are particularly sensitive to nursing care.
To assess the effect of nurse staffing on quality of care and inpatient care costs.
Longitudinal analysis using hospital nurse staffing data and the Healthcare Cost and Utilization Project State Inpatient Databases from 2008 through 2011.
Hospital discharges from California, Nevada, and Maryland (n=18,474,860).
A longitudinal, hospital-fixed effect model was estimated to assess the effect of nurse staffing levels and skill mix on patient care costs, length of stay, and adverse events, adjusting for patient clinical and demographic characteristics.
Increases in nurse staffing levels were associated with reductions in nursing-sensitive adverse events and length of stay, but did not lead to increases in patient care costs. Changing skill mix by increasing the number of registered nurses, as a proportion of licensed nursing staff, led to reductions in costs.
The study findings provide support for the value of inpatient nurse staffing as it contributes to improvements in inpatient care; increases in staff number and skill mix can lead to improved quality and reduced length of stay at no additional cost.
*RAND Corporation, Pittsburgh, PA
†Formerly of RAND Corporation, Boston, MA
‡Truven Health Analytics, Santa Barbara, CA
§Agency for Healthcare Research and Quality (AHRQ) Center for Delivery, Organization, and Markets (CDOM), Rockville, MD
∥RAND Corporation, Santa Monica, CA
¶Truven Health Analytics, Ann Arbor, MI
Supported by the Agency for Healthcare Research and Quality (AHRQ) (Contract HHSA-290-2006-00009-C) through intramural research. The findings and conclusions in this document are those of the authors, who are responsible for its content, and do not necessarily represent the views of AHRQ, or the US Department of Health and Human Services.
No official endorsement by any agency of the federal or state governments, RAND Corporation, or Truven Health Analytics is intended or should be inferred.
The authors declare no conflict of interest.
Reprints: Teresa B. Gibson, PhD, Truven Health Analytics, 777 E Eisenhower Pkwy, Ann Arbor, MI 48108. E-mail: email@example.com.