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Nurse Staffing In Hospitals: Is There A Business Case For Quality?

Abstract

 
We construct national estimates of the cost of increasing hospital nurse staffing and associated reductions in days, deaths, and adverse outcomes. Raising the proportion of nursing hours provided by registered nurses (RNs) without increasing total nursing hours is associated with a net reduction in costs. Increasing nursing hours, with or without increasing the proportion of hours provided by RNs, reduces days, adverse outcomes, and patient deaths, but with a net increase in hospital costs of 1.5 percent or less at the staffing levels modeled. Whether or not staffing should be increased depends on the value patients and payers assign to avoided deaths and complications.

The growing body of evidence linking hospital workforces to patient outcomes suggests that one way to improve quality is to increase nurse staffing.² Because nurses are a large portion of hospital labor costs, the cost of increasing staffing would not be insignificant. The additional costs of having more nurses, however, should be offset to some extent by the monetary and nonmonetary benefits of reducing adverse outcomes.

There are many ways to improve quality and patient safety in hospitals (for example, equipping hospitals with new technology, investing in training and education, imposing regulations, and increasing nurse staffing). Whether there is a business case for any particular option depends on many factors, and each hospital will have to make its own assessment. In instances where there is not a clear business case for increased nurse staffing, there might be a "social case"; thus, it would be socially beneficial to have policy intervention.

In this study we provide data to help hospitals and policymakers consider both the business and social cases for investing in nurse staffing by estimating the costs of increasing staffing and cost savings resulting from avoided deaths, reduced lengths-of-stay, and decreased adverse patient outcomes associated with higher nurse staffing levels.

Study Data And Methods

Top Study Data And Methods Study Results Discussion NOTES

 
In an earlier study we analyzed data from 799 nonfederal acute care general hospitals in eleven states. Discharge abstracts and nurse staffing data were obtained from the states; data on hospital size, location, teaching status, from the American Hospital Association (AHA) annual survey; and cost-to-charge ratios, from Medicare cost reports.

In regression analyses we found an association of nurse staffing and (1) lengths-of-stay, urinary tract infections, upper gastrointestinal bleeding, hospital-acquired pneumonia, shock, or cardiac arrest among medical patients and (2) "failure to rescue," defined as the death of a patient with one of five life-threatening complications—pneumonia, shock or cardiac arrest, upper gastrointestinal bleeding, sepsis, or deep vein thrombosis—among surgical patients. Details of that study are described elsewhere.³ Exhibit 1 presents rates of these outcomes and descriptive statistics for the 799-hospital sample.

Because many hospital costs are fixed in the short run, hospitals might not fully recover the average costs of avoided days or avoided complications. Based on a review of studies of hospital fixed and variable costs, we estimated variable costs of hospitals to be 40 percent of average costs, and we multiplied calculated costs by this amount to estimate the short-term cost impact of reduced hospital patient days and avoided adverse outcomes.⁴ Over time, hospitals should be able to adjust their fixed costs to reflect the change in volume. We present estimates of cost savings assuming short-term savings of 40 percent of average costs and with full recovery of fixed costs.

We projected the results from the sample to all nonfederal U.S. acute care hospitals and updated the estimates of needed staffing, avoided adverse outcomes and days, and costs to reflect hospital costs, admissions, and lengths-of-stay in 2002. Specifically, our sample had 26 percent of the discharges from U.S. nonfederal acute care hospitals in 1997. We constructed national estimates of adverse outcomes, nursing full-time equivalents (FTEs), and costs by multiplying estimates from the sample by 100 divided by 26. We used data on RN wages from the 1997 and 2002 Current Population Surveys (CPS) and the change in admissions, lengths-of-stay, spending per admission, and spending per day between 2002 and 1997 from the AHA annual survey to update the estimates of avoided adverse outcomes, avoided days, deaths, and costs. In aggregate, between 1997 and 2002, licensed hours per day and the proportion of licensed hours provided by RNs reported to the AHA, and average case-mix, measured by the Medicare case-mix index, did not change substantially; thus, no adjustments were made to the staffing variables.⁵

Because neither our prior work nor other studies capture all of the effects of nurse staffing on patient care, and because we do not have direct measures of patient-reported quality, we do not attempt a cost-effectiveness analysis of the impact of raising nurse staffing. We do present estimates of the cost per avoided death.

Study Results

Top Study Data And Methods Study Results Discussion NOTES

 
Cost of increasing nurse staffing. In 2002, U.S. short-term acute general hospitals employed 942,000 FTE RNs and 120,000 FTE LPNs.⁶ Increasing the proportion of RNs to the seventy-fifth percentile (option 1) would require hospitals below this level to replace more than 37,000 FTE LPNs with RNs at an estimated cost of $811 million.

Increasing nurses in hospitals with licensed hours below the seventy-fifth percentile (option 2) requires an increase in FTE RNs of 114,456, and FTE LPNs of more than 13,000, costing $7.5 billion. If hospitals below either of these staffing levels increased staffing to the seventy-fifth percentile (option 3), FTE RNs would increase by nearly 158,000 and FTE LPNs would fall, changes that would cost $8.5 billion (Exhibit 3).

Hospital days would be lower by 1.5 million under option 1, almost 2.6 million under option 2, and 4.1 million under option 3. The larger reduction in length-of-stay (and corresponding reduction in cost) associated with option 2 compared with option 1 reflects our earlier finding that length-of-stay is associated more with hours of nursing care than with the RN/LPN mix.

Short-term cost savings associated with reducing adverse outcomes and hospital days are substantial (Exhibit 4). Because the costs of changing the RN/LPN mix without changing licensed hours are relatively low (option 1), short-term cost savings exceed the cost increases by $242 million. While options 2 and 3 are associated with substantial avoided costs, these are not enough to offset the costs of increased nurse staffing. The net short-term cost increase associated with options 2 and 3 would be $5.8 and $5.7 billion, respectively. Although large, these amounts are approximately 1.5 percent of annual hospital expenditures.

Over time, hospitals can adjust fixed costs to reflect reduced volume or replace these days and services with other, higher-value services or programs to which the fixed costs would be allocated. For some hospitals, this adjustment would be speedy; for others, slow. If fixed costs were fully recaptured, the net costs of increased nurse staffing would be much lower (Exhibit 4).

Decreases in length-of-stay associated with higher nurse staffing generate more than 90 percent of our projected cost savings. We examined four other studies finding an association of either hours of nurse staffing or the proportion of nursing staff that is RNs and lengths-of-stay in either medical-surgical units or hospitals in general, to determine whether using results from these studies would generate higher or lower estimates than ours.⁷ Although most are not directly comparable to our study, when we reanalyzed these results, we found that our estimates of the association of staffing and lengths-of-stay are approximately equal to those that would be constructed from two of the studies, and approximately half those that would be estimated from two others.⁸ Two additional studies assessing the association of nurse staffing and lengths-of-stay in intensive care units (ICUs) found that moving nurse staffing below a one-to-two ratio was associated with 30–50 percent longer stays.⁹ In light of these comparisons, our estimates of cost offsets appear conservative.

Avoided in-hospital deaths. Increased staffing under all options is associated with fewer in-hospital deaths (Exhibit 4). We examined results from two recent studies that reported an association of staffing and mortality, to determine whether applying results from these studies would generate higher or lower estimates of avoided deaths than ours. Applying the results of Barbara Mark and colleagues, we would increase our projected avoided deaths by 60–80 percent.¹⁰ Applying the finding of Linda Aiken and colleagues for surgical patients, our projected number of postsurgical deaths would be three times larger and, if we extrapolated this result to all patients, medical and surgical—which we do not believe is justified based on our and others’ research—the estimate of avoided deaths would be more than three times larger than we present.¹¹

Discussion

Top Study Data And Methods Study Results Discussion NOTES

 
There is an unequivocal business case for hospitals to improve nurse staffing under one option we examined: raising the proportion of RNs without changing licensed hours. This option also was the least costly—$811 million—and would achieve a net reduction in short-term costs of $242 million. We note that these are aggregate estimates, and some hospitals might not realize the expected savings, such as those where RNs’ wages are relatively high compared with LPNs’ wages. Although these hospitals might not experience a net cost savings, patients treated in them would likely still benefit from reduced lengths-of-stay and fewer adverse outcomes.

Although the increase in nurse staffing under option 2 yields a smaller reduction in both adverse outcomes and their associated costs compared with option 1, it results in a much larger reduction in hospital days because of unmeasured complications and delays in care, with sizable cost savings. Nevertheless, the costs of this approach are not offset by cost savings associated with the reduction in adverse outcomes and the increase in avoided hospital days.

Changing nurse staffing to meet both thresholds (option 3) results in an increase in RN employment but a decrease in LPNs. Although this option would achieve the greatest reduction in adverse outcomes and hospital days, estimated staffing costs would be highest and not totally offset by estimated savings.

Our cost estimates of short-term savings are based on an assumption that hospitals’ variable costs are 40 percent of average costs. Over time, hospitals should be able to reduce fixed costs in response to changes in use, and long-term savings are likely to be much higher than in the short term, although options 2 and 3 still do not pay for themselves (Exhibit 4). The speed of this adjustment depends on whether the hospital can scale back operations or replace the lost volume with other services to which the fixed costs can be allocated.

Reduction in patient deaths. We estimated that more than 6,700 in-hospital patient deaths could be avoided by raising nurse staffing and that approximately three-quarters (4,997) of these could be achieved by increasing the proportion of RNs (option 1). To provide context for this finding, we estimated the cost per avoided death by dividing the net cost of increased nurse staffing by the number of avoided deaths associated with each staffing option. Under option 3, in which both staffing thresholds are met, estimated short-term costs per avoided death are $846,000. Under option 2, in which only licensed nursing hours are increased, short-term costs per avoided death are $3.23 million, which approximates the marginal cost per avoided death of moving from option 1 to option 3. Estimated costs of avoided deaths, assuming full recovery of fixed costs, would be $231,000 for option 3 and $1.8 million for option 2.

In estimating the benefits of increased nurse staffing, we did not consider the value to patients and their families of reduced morbidity (such as decreased pain and suffering, and days lost from work), the economic value to hospitals of lower liability and improved reputation and image from reducing adverse nursing-related morbidity and mortality, or the positive effects of increased nurse staffing in reducing adverse outcomes not considered in this analysis but observed in other studies, including patient falls, bloodborne infections, decubitus ulcers, and medication errors.¹² Similarly, increased patient satisfaction, good discharge planning, and patients’ increased ability to perform self-care were not included in this study, yet they, too, have both economic and noneconomic value.¹³ Nor did we estimate potential cost savings from reducing nurse turnover through increased nurse staffing.¹⁴ Given this undercounting of the cost offsets from increased nurse staffing, our estimates of the cost per avoided death should be viewed as upper-bound estimates. The costs per avoided death that we estimated are below the values of a statistical life used by federal agencies in their rule making on health and safety, which range from $3 million to $6 million.¹⁵ By these standards, investing in additional licensed nursing hours is worth doing.

Implications for hospitals and policy-makers. Pressures are mounting for hospitals to control costs at the same time patient volume is increasing and the demand to improve patient safety and quality is gaining momentum. Our analysis examines the costs of responding to this demand by raising hospital nurse staffing, and it estimates the cost offsets and economic value associated with avoided hospital days, morbidity, and mortality. These estimates can inform discussions and influence judgments about nurses’ contribution to improving the quality of care.

From a hospital’s perspective, increasing nurse staffing is costly. Nevertheless, greater use of RNs in preference to LPNs appears to pay for itself. Improved patient outcomes and reduced days associated with more hours of nurse staffing would only partially offset the costs to achieve them, and, depending on the reimbursement systems in use, cost savings could be shared with payers instead of accruing solely to the hospital. This creates a strong disincentive to increase nurse staffing. From a patient’s perspective, however, using standard measures of value, the additional costs to increase nurse staffing appear justified.

Policymakers and public and private payers should focus on finding ways to reconcile patient and hospital perspectives. For example, when Medicare was established in 1965 and hospitals faced a large shortage of nurses, Congress included extra payments to help hospitals raise wages and increase staffing. Might providing payment supplements to hospitals to increase nurse staffing bridge the gap between public and private valuation of increased staffing?

The central questions that emerge from this study for public and private payers, patient advocates, hospitals, accreditation agencies, and others involved in setting policy are as follows: How important is the goal of improving patient quality? Should increasing nurse staffing be encouraged as a means for pursuing this goal? Should funds be made available to hospitals to help realize this goal? And finally, What assurances are needed that any funds provided to hospitals are actually used to increase nurse staffing?

Editor's Notes

 
Jack Needleman (needlema{at}ucla.edu) is an associate professor in the Department of Health Services, School of Public Health, University of California, Los Angeles (UCLA). Peter Buerhaus is the Valere Potter Professor and senior associate dean for research, Vanderbilt University School of Nursing, in Nashville, Tennessee. Maureen Stewart is a National Institute on Alcohol Abuse and Alcoholism (NIAAA) fellow at the Heller School, Brandeis University, in Waltham, Massachusetts. Katya Zelevinsky is a programmer/analyst in the Department of Health Care Policy, Harvard Medical School, in Boston, Massachusetts. Soeren Mattke is a scientist at RAND Health in Arlington, Virginia.

This study was supported by the Commonwealth Fund, a New York City–based private, independent foundation. The views presented here are those of the authors and not necessarily those of the Commonwealth Fund, its directors, officers, or staff. The authors thank the reviewers for their helpful suggestions on an earlier version of this paper.

NOTES

Top Study Data And Methods Study Results Discussion NOTES

 

1. S. Leatherman et al., "The Business Case for Quality: Case Studies and an Analysis," Health Affairs 22, no. 2 (2003): 17–30.[Abstract/Free Full Text]
2. See, for example, Institute of Medicine, Keeping Patients Safe: Transforming the Work Environment of Nurses (Washington: National Academies Press, 2003); M.W. Stanton and M.K. Rutherford, "Hospital Nurse Staffing and Quality of Care" (Rockville, Md.: Agency for Healthcare Research and Quality, 2004); and J. Needleman and P. Buerhaus, "Nurse Staffing and Patient Safety: Current Knowledge and Implications for Action," International Journal for Quality in Health Care 15, no. 4 (2003): 275–277.[Free Full Text]See also R.J. Blendon et al., "Views of Practicing Physicians and the Public on Medical Errors," New England Journal of Medicine 347, no. 24 (2002): 1933–1940[Abstract/Free Full Text]; and D.E. Altman, C. Clancy, and R.J. Blendon, "Improving Patient Safety—Five Years after the IOM Report," New England Journal of Medicine 351, no. 20 (2004): 2041–2043.[Free Full Text]
3. J. Needleman et al., "Nurse-Staffing Levels and the Quality of Care in Hospitals," New England Journal of Medicine 346, no. 22 (2002): 1715–1722[Abstract/Free Full Text]; and J. Needleman et al., "Nurse Staffing and Patient Outcomes in Hospitals" (Boston: Harvard School of Public Health, 2001).
4. The studies reviewed include B. Friedman and M.V. Pauly, "A New Approach to Hospital Cost Functions and Some Issues in Revenue Regulation," Health Care Financing Review 4, no. 3 (1983): 105–114[Medline]; J.R. Lave and L.B. Lave, "Hospital Cost Functions," Annual Review of Public Health 5 (1984): 193–213[CrossRef][Web of Science][Medline]; M.V. Pauly and P. Wilson, "Hospital Output Forecasts and the Cost of Empty Hospital Beds," Health Services Research 21, no. 3 (1986): 403–428[Web of Science][Medline]; and T.W. Grannemann, R.S. Brown, and M.V. Pauly, "Estimating Hospital Costs: A Multiple-Output Analysis," Journal of Health Economics 5, no. 2 (1986): 107–127.[CrossRef][Web of Science][Medline]
5. Methods are described in greater detail in an online Technical Appendix, http://content.healthaffairs.org/cgi/content/full/25/1/204/DC1.
6. American Hospital Association, Annual Survey of Hospitals, 2002.
7. K.G. Behner et al., "Nursing Resource Management: Analyzing the Relationship between Costs and Quality in Staffing Decisions," Health Care Management Review 15, no. 4 (1990): 63–71[Medline]; S.D. Flood and D. Diers, "Nurse Staffing, Patient Outcome, and Cost," Nursing Management 19, no. 5 (1988): 34–43[Medline]; L.K. Lichtig, R.A. Knauf, and D.K. Milholland, "Some Impacts of Nursing on Acute Care Hospital Outcomes," Journal of Nursing Administration 29, no. 2 (1999): 25–33[Web of Science][Medline]; and M.A. Schultz et al., "The Relationship of Hospital Structural and Financial Characteristics to Mortality and Length of Stay in Acute Myocardial Infarction Patients," Outcomes Management for Nursing Practice 2, no. 3 (1998): 130–136.[Medline]
8. Our findings were approximately equal to those found by Lichtig and Schultz. They were half those estimated by Flood and Diers and by Behner.
9. R.K. Amaravadi et al., "ICU Nurse-to-Patient Ratio Is Associated with Complications and Resource Use after Esophagectomy," Intensive Care Medicine 26, no. 12 (2000): 1857–1862[CrossRef][Web of Science][Medline]; and P.J. Pronovost et al., "Organizational Characteristics of Intensive Care Units Related to Outcomes of Abdominal Aortic Surgery," Journal of the American Medical Association 281, no. 14 (1999): 1310–1317.[Abstract/Free Full Text]
10. B.A. Mark et al., "A Longitudinal Examination of Hospital Registered Nurse Staffing and Quality of Care," Health Services Research 39, no. 2 (2004): 279–300.[CrossRef][Web of Science][Medline]
11. L.H. Aiken et al., "Hospital Nurse Staffing and Patient Mortality, Nurse Burnout, and Job Dissatisfaction," Journal of the American Medical Association 288, no. 16 (2002): 1987–1993.[Abstract/Free Full Text]
12. The other studies are cited in Note 2.
13. P.H. Mitchell, S. Ferketich, and B.M. Jennings, "Quality Health Outcomes Model: American Academy of Nursing Expert Panel on Quality Health Care," Image—The Journal of Nursing Scholarship 30, no. 1 (1998): 43–46.
14. See, for example, T.W. Tai, S.I. Bame, and C.D. Robinson, "Review of Nursing Turnover Research, 1977–1996," Social Science and Medicine 47, no. 12 (1998): 1905–1924[CrossRef][Medline]; S.J. Cavanagh, "Nursing Turnover: Literature Review and Methodological Critique," Journal of Advanced Nursing 14, no. 7 (1989): 587–596[Web of Science][Medline]; C.B. Jones, "Staff Nurse Turnover Costs, Part I: A Conceptual Model," Journalof Nursing Administration 20, no. 4 (1990): 18–23; and C.B. Jones, "Staff Nurse Turnover Costs, Part II: Measurements and Results," Journal of Nursing Administration 20, no. 5 (1990): 27–32.
15. W.K. Viscusi, "The Value of Risks to Life and Health," Journal of Economic Literature 31, no. 4 (1993): 1912–1946[Web of Science]; U.S. Environmental Protection Agency, Office of the Administrator, "Guidelines for Preparing Economic Analyses" (Washington: EPA, 2000); U.S. Department of Transportation, Office of the Secretary of Transportation, "Revised Departmental Guidelines: Treatment of Value of Life and Injuries in Preparing Economic Evaluations" (Washington: DOT, 2002); and DOT, "Revision of Departmental Guidance on Treatment of the Value of Life and Injuries," 2002, http://ostpxweb.dot.gov/VSL_background.htm (accessed 18 October 2005).

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