NEWS
Evidence-Based Staffing: Potential Roles for Informatics
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June 1, 2008
Sookyung Hyun, Suzanne Bakken, Kathy Douglas, Patricia W. Stone, Nursing Economics
DELIVERY OF NURSING CARE in hospitals may be heading to the “perfect storm.” The phrase “perfect storm” refers to the simultaneous occurrence of events, which individually would be far less significant; but, these forces in combination are much more powerful. In the delivery of quality care, the events converging for the storm include a nursing shortage that is predicted to worsen, an increase in volume and acuity of patients, and rising health care costs. Therefore, understanding how to provide high quality nursing care efficiently and making staffing decisions based in evidence is of increasing importance. An element that may help us navigate through the perfect storm is the increased use of health care information technology in hospitals. The purposes of this article are to briefly review evidence related to nurse staffing and patient outcomes; provide an overview of current methods used to inform nurse staffing; and, discuss potential informatics solutions that could support evidence based nurse staffing decisions.
Patient Outcomes and Nurse Staffing
Over the last 15 years, evidence has been accumulating relating higher levels of nurse staffing (both in quantity and experience) to lower rates of adverse patient outcomes. To synthesize this evidence, we developed two tables. In both tables, we limited the evidence to those investigations conducted in U.S. hospitals and published since 1990. Table 1 summarizes 11 relevant studies assessing nurse staffing and patient outcomes at the hospital level. The sample sizes in these studies ranged from 162 hospitals in one state to 799 hospitals in 11 states. Researchers mainly used public use files to estimate staffing and patient outcomes were measured using patient discharge abstracts. There are a number of limitations in this literature. This body of research focused on hospital level staffing rather than unit-specific staffing. Variations in the demand for nursing care due to different types of patients was only minimally considered as follows: (a) Unruh and Fottler (2006) examined the effect of adjusting patient-to-nurse ratios by patient’s length of stay as a proxy for nursing demands, and (b) Needleman et al. (2002) measured nursing case mix using nursing intensity weights to adjust for nursing demands. Another group of researchers has examined data at the unit level (see Table 2). While these researchers used more precise measures of nurse staffing, usually the data were collected directly, which generally resulted in smaller sample sizes. The exceptions were Donaldson et al. (2005) and Dunton, Gajewski, Taunton, and Moore (2004) who used large databases. The outcome measures chosen were uniquely defined for each study. Only Blegen and Vaughn (1998) controlled for patients’ needs for nursing care using a patient acuity classification scale.
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Patient Outcomes and Nurse Staffing
Over the last 15 years, evidence has been accumulating relating higher levels of nurse staffing (both in quantity and experience) to lower rates of adverse patient outcomes. To synthesize this evidence, we developed two tables. In both tables, we limited the evidence to those investigations conducted in U.S. hospitals and published since 1990. Table 1 summarizes 11 relevant studies assessing nurse staffing and patient outcomes at the hospital level. The sample sizes in these studies ranged from 162 hospitals in one state to 799 hospitals in 11 states. Researchers mainly used public use files to estimate staffing and patient outcomes were measured using patient discharge abstracts. There are a number of limitations in this literature. This body of research focused on hospital level staffing rather than unit-specific staffing. Variations in the demand for nursing care due to different types of patients was only minimally considered as follows: (a) Unruh and Fottler (2006) examined the effect of adjusting patient-to-nurse ratios by patient’s length of stay as a proxy for nursing demands, and (b) Needleman et al. (2002) measured nursing case mix using nursing intensity weights to adjust for nursing demands. Another group of researchers has examined data at the unit level (see Table 2). While these researchers used more precise measures of nurse staffing, usually the data were collected directly, which generally resulted in smaller sample sizes. The exceptions were Donaldson et al. (2005) and Dunton, Gajewski, Taunton, and Moore (2004) who used large databases. The outcome measures chosen were uniquely defined for each study. Only Blegen and Vaughn (1998) controlled for patients’ needs for nursing care using a patient acuity classification scale.
Continued… Click Here to view full article (PDF)
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