Nurse-Staffing Levels and the Quality of Care in Hospitals
List of authors.Abstract
Background
It is uncertain whether lower levels of staffing by nurses at hospitals are associated with an increased risk that patients will have complications or die.
Methods
We used administrative data from 1997 for 799 hospitals in 11 states (covering 5,075,969 discharges of medical patients and 1,104,659 discharges of surgical patients) to examine the relation between the amount of care provided by nurses at the hospital and patients' outcomes. We conducted regression analyses in which we controlled for patients' risk of adverse outcomes, differences in the nursing care needed for each hospital's patients, and other variables.
Results
The mean number of hours of nursing care per patient-day was 11.4, of which 7.8 hours were provided by registered nurses, 1.2 hours by licensed practical nurses, and 2.4 hours by nurses' aides. Among medical patients, a higher proportion of hours of care per day provided by registered nurses and a greater absolute number of hours of care per day provided by registered nurses were associated with a shorter length of stay (P=0.01 and P<0.001, respectively) and lower rates of both urinary tract infections (P<0.001 and P=0.003, respectively) and upper gastrointestinal bleeding (P=0.03 and P=0.007, respectively). A higher proportion of hours of care provided by registered nurses was also associated with lower rates of pneumonia (P=0.001), shock or cardiac arrest (P=0.007), and “failure to rescue,” which was defined as death from pneumonia, shock or cardiac arrest, upper gastrointestinal bleeding, sepsis, or deep venous thrombosis (P=0.05). Among surgical patients, a higher proportion of care provided by registered nurses was associated with lower rates of urinary tract infections (P=0.04), and a greater number of hours of care per day provided by registered nurses was associated with lower rates of “failure to rescue” (P=0.008). We found no associations between increased levels of staffing by registered nurses and the rate of in-hospital death or between increased staffing by licensed practical nurses or nurses' aides and the rate of adverse outcomes.
Conclusions
A higher proportion of hours of nursing care provided by registered nurses and a greater number of hours of care by registered nurses per day are associated with better care for hospitalized patients.
Methods
Measures of Adverse Outcomes
Appendix. Coding Rules for Adverse Outcomes. The study was approved by the Harvard School of Public Health Human Subjects Committee. On the basis of published21,27,28,30,39-47 and unpublished materials, we identified 14 adverse outcomes during hospitalization (11 for both medical and surgical patients and 3 for surgical patients only) that could be coded on the basis of hospital-discharge abstracts and that are potentially sensitive to staffing by nurses. Building on previous studies,30,48-50 we developed coding rules to construct risk groups of patients and to identify patients with each outcome (listed in the Appendix).
Study Population
We obtained data on hospital discharges and the staffing by nurses from 11 states that collect both types of data: Arizona, California, Maryland, Massachusetts, Missouri, Nevada, New York, South Carolina, Virginia, West Virginia, and Wisconsin. We estimated 1997 staffing as the weighted average of staffing in the hospital's fiscal years 1997 and 1998, except in Virginia, for which only fiscal 1997 data were available. We obtained data on discharges for the 1997 calendar year (for Virginia, we obtained data for the four calendar quarters matching each hospital's fiscal year). The initial sample was 1041 hospitals. We then excluded hospitals with an average daily census of less than 20, an occupancy rate below 20 percent, or missing data on staffing, as well as those reporting extremely low or high levels of staffing per patient-day (below the 7.5th percentile or above the 92.5th percentile). The final sample included 799 hospitals, which together accounted for 26 percent of the discharges from nonfederal hospitals in the United States in 1997.
Measures of Staffing
The levels of staffing by registered nurses, licensed practical nurses, and nurses' aides were estimated in hours. For states reporting staffing as full-time equivalents, we used a standard year of 2080 hours (52 weeks at 40 hours per week). In California, the levels of staffing of nurses for inpatient and outpatient care are calculated directly from financial data reported by the California Office of Statewide Health Planning and Development. Using these data, we found that the standard measure, “adjusted patient-days,” that was used to adjust total hours of nursing care to reflect the number of both inpatients and outpatients treated at the hospital (hospital volume)51 underestimated staffing for inpatient care and overestimated staffing for outpatient care. To adjust for this bias, we constructed a regression model, using data from California, that predicted staffing for inpatient care per inpatient-day on the basis of the level of staffing per adjusted patient-day and the number of outpatients treated; we used this model to estimate staffing for inpatient care from the staffing levels per adjusted patient-day reported in the other 10 states.
For easier comparison of the levels of staffing by nurses in different hospitals, we adjusted the hours of nursing care per day for differences in the nursing care needed by the patients of each hospital. We used estimates of the relative level of nursing care needed by patients in each diagnosis-related group28,52 to construct a nursing case-mix index for each hospital. We divided hours of nursing care per inpatient-day by this index to calculate the adjusted number of hours of nursing care per day.
Risk Adjustment and Characteristics of the Hospitals
To control for differences among hospitals in the relative risk of the outcomes as a result of variations in the mix of patients, we used patient-level logistic-regression analyses to predict each patient's probability of having each adverse outcome. Patient-level variables in these analyses included the rate of the outcome in the patient's diagnosis-related group, the state of residence, age, sex, primary health insurer, whether or not the patient was admitted on an emergency basis, and the presence or absence of 13 chronic diseases.48 The regression analyses also included interactions between the specific rate of each outcome in each diagnosis-related group and all the other variables, as well as interactions between age and the variables related to chronic disease. We added the predicted probabilities for patients in each hospital to obtain the expected number of patients in that hospital who would have each outcome. We used the same variables in an ordinary least-squares regression analysis to estimate the expected length of stay. We obtained information on the other characteristics of the hospitals (number of beds, teaching status, state, and metropolitan or nonmetropolitan location) from the American Hospital Association's Annual Survey of Hospitals for 199751 and 1998.53
Statistical Analysis
The unit of analysis was the hospital. We calculated the length of stay, the rates of adverse outcomes, the hours of nursing care per inpatient-day, and the proportion of hours of nursing care provided by each category of nursing personnel.
For each outcome, we performed regression analyses with the use of nurse-staffing and control variables. In all analyses, the control variables included the state, number of beds, teaching status, and location of the hospital. We used ordinary least-squares regression to analyze the difference between the actual and expected length of stay. We report regression coefficients for these analyses. For other outcomes, we included the number of patients with the adverse outcome as the dependent variable in a negative binomial regression model (the appropriate model for this type of data53) and the expected numbers for each adverse outcome as the measure of exposure required by the model. We report incidence-rate ratios from these analyses.
We tested each coefficient for statistical significance using t-tests in the ordinary least-squares regression analyses and z statistics in the negative binomial regression analyses.54 After controlling for other variables, we estimated the differences in the outcomes between hospitals with staffing levels of registered nurses at the 75th percentile and hospitals with staffing levels of registered nurses at the 25th percentile (the “decrease” in outcomes with higher levels of staffing). The 95 percent confidence intervals for the decreases were calculated with the use of Huber–White standard errors.55 All P values are based on two-tailed tests. Statistical analysis was performed with the use of Stata software.55
To examine whether the mix of skills or the number of hours of nursing care was more important in influencing patient outcomes, we analyzed 10 models involving nurse-staffing variables and compared the results. We present results from the two models that most closely match those used in previous published studies. Model 1 examines the mix of skills and includes the proportion of hours of care by licensed nurses (registered-nurse–hours plus licensed-practical-nurse–hours) that were provided by registered nurses, plus aide-hours and the total hours per day provided by licensed nurses. Model 2 measures all staffing of nurses — by registered nurses, aides, and licensed practical nurses — in hours per day. Results obtained with the other models we analyzed have been reported elsewhere.56
Results
Rates of Adverse Patient Outcomes and Length of Stay
Table 1.
Table 1. Patient Outcomes and Characteristics of the 799 Hospitals. The patient outcomes and characteristics of the hospitals are summarized in Table 1. Complications that are common in hospitalized patients, such as urinary tract infection, pneumonia, and metabolic derangement, were the most frequent. The highest rates were for “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 venous thrombosis — for which early identification by nurses and medical and nursing interventions can influence the risk of death. The mean death rates were 18.6 percent among medical patients with one of these complications and 19.7 percent among surgical patients with one of these complications. Rates for outcomes were similar in all 11 states. The low rates of deep venous thrombosis — 0.4 percent among surgical patients and 0.5 percent among medical patients — may reflect underreporting of this common complication.
Variations in Staffing Levels and Mix of Skills
Table 2.
Table 2. Hours of Nursing Care. The mean (±SD) numbers of hours of nursing care are shown in Table 2. Hours per inpatient-day averaged 7.8 for registered nurses, 1.2 for licensed practical nurses, and 2.4 for aides. Hours of care by licensed nurses per day averaged 9.0. The mean proportion of total hours of nursing care provided by registered nurses was 68 percent; aides provided 21 percent of total nurse-hours.
Association between Adverse Outcomes and Staffing by Nurses
Table 3.
Table 3. Relation between Adverse Outcomes among Medical Patients and the Levels of Staffing by Registered Nurses (RNs). Table 4. 
Table 4. Relation between Adverse Outcomes among Surgical Patients and the Levels of Staffing by Registered Nurses (RNs). The relations between adverse outcomes and the levels of staffing by registered nurses are shown in Table 3 for medical patients and in Table 4 for surgical patients. The ordinary least-squares–regression coefficients (for length of stay) or the incidence-rate ratios (for other outcomes) are given for both registered-nurse–hours as a proportion of total hours of care by licensed nurses and the number of registered-nurse–hours per patient-day. A negative regression coefficient or an incidence-rate ratio of less than 1.00 indicates that the frequency of the outcome declines as the staffing level increases. The estimated percent decreases in the rates of the outcomes associated with increasing nurse-hours from the 25th to the 75th percentile are also listed. We report results for death and outcomes for which a greater number of registered-nurse–hours or a higher proportion of licensed-nurse care provided by registered nurses was associated with lower rates of the outcome. Additional results are reported elsewhere.56
Registered Nurses and Adverse Outcomes
Among medical patients, we found an association between registered-nurse staffing and six outcomes. Both a higher proportion of licensed-nurse care provided by registered nurses (model 1) and more registered-nurse–hours per day (model 2) were associated with a shorter length of stay and lower rates of urinary tract infections and upper gastrointestinal bleeding. A higher proportion of registered-nurse–hours (model 1), but not a greater number of registered-nurse–hours per day (model 2), was associated with lower rates of three other adverse outcomes: pneumonia, shock or cardiac arrest, and failure to rescue. The association for failure to rescue was not as strong as the associations for the other five outcomes, and it was more sensitive to the specifications of the models.56
Among surgical patients, a higher proportion of registered-nurse–hours (model 1) was associated with a lower rate of urinary tract infection. A greater number of registered-nurse–hours per day (model 2) was associated with a lower rate of failure to rescue; a greater number of licensed-nurse–hours per day was also associated with a lower rate of failure to rescue (incidence-rate ratio, 0.98; 95 percent confidence interval, 0.97 to 1.00; P=0.02). Because most licensed-nurse–hours are provided by registered nurses, these associations are consistent. Among both medical and surgical patients, we found no evidence of an association between in-hospital mortality and the proportion of registered-nurse–hours, the number of registered-nurse–hours per day, or the number of licensed-nurse–hours per day.
Measures of Staffing by Other Nurses
In addition to the association with a lower rate of failure to rescue among surgical patients, a greater number of licensed-nurse–hours per day was associated with a shorter length of stay among medical patients (regression coefficient, –0.08; 95 percent confidence interval, –0.12 to –0.05; P<0.001). Measures of staffing by aides and licensed practical nurses had either nonsignificant associations with lower rates of the adverse outcomes we studied or significant associations with higher rates of the adverse outcomes (data not shown). Thus, whereas there was evidence that greater numbers of registered-nurse–hours or licensed-nurse–hours were associated with a shorter length of stay among medical patients and lower rates of failure to rescue among surgical patients, there was no evidence of an association between lower rates of the outcomes we studied and a greater number of licensed-practical-nurse–hours or aide-hours per day or a higher proportion of aide-hours.
Discussion
In a large sample of hospitals from a diverse group of states, after controlling for differences in the nursing case mix and the patients' levels of risk, we found an association between the proportion of total hours of nursing care provided by registered nurses or the number of registered-nurse–hours per day and six outcomes among medical patients. These were the length of stay and the rates of urinary tract infections, upper gastrointestinal bleeding, hospital-acquired pneumonia, shock or cardiac arrest, and failure to rescue (the death of a patient with one of five life-threatening complications — pneumonia, shock or cardiac arrest, upper gastrointestinal bleeding, sepsis, or deep venous thrombosis). The evidence was weaker for failure to rescue than for the other five measures. As in other studies,32,57 higher levels of staffing by registered nurses were associated with lower rates of failure to rescue among surgical patients, among whom we also found an association between a higher proportion of registered-nurse–hours and lower rates of urinary tract infections.
The fact that fewer outcomes among surgical patients than among medical patients were found to be associated with the level of staffing by registered nurses may have several explanations. Surgical patients may be healthier than medical patients and therefore have a lower risk of adverse outcomes. The smaller size of the samples of surgical patients may also have made it more difficult to detect associations.
Our findings clarify the relation between the levels of staffing by nurses and the quality of care. We found consistent evidence of an association between higher levels of staffing by registered nurses and lower rates of adverse outcomes, but no similar evidence related to staffing by licensed practical nurses or aides. Our findings may reflect the actual contribution of these different members of the nursing staff to patients' outcomes in general, or they may be specific to the outcomes we examined. It is possible that the outcomes for which we found significant associations may be more sensitive to the contribution that the skills and education of registered nurses, in particular, make to patient care.
A higher proportion of total hours of nursing care provided by registered nurses was more frequently associated with lower rates of adverse outcomes than was a greater number of registered-nurse–hours per day. This difference may reflect a real effect, or it may simply indicate that we could measure differences in the mix of staff among hospitals with greater precision than we could nurse-hours adjusted for case mix.
We tested the association between staffing levels and 25 outcomes in medical and surgical patients and found an association for 8 of these outcomes. With the exception of failure to rescue among medical patients, these results were consistent across alternative regression models. Because of the large number of comparisons, however, it is possible that some of the associations we found may be false positive findings. In addition, differences among hospitals may be caused not by the staffing level of nurses per se but by other unmeasured factors associated with higher levels of staffing by registered nurses or other unmeasured characteristics of the hospitals' nursing work force. The level of staffing by nurses is an incomplete measure of the quality of nursing care in hospitals. Other factors, such as effective communication between nurses and physicians and a positive work environment, have been found to influence patients' outcomes.58,59
Other limitations of our study arise from weaknesses of currently available data. Constructing a data base on the staffing levels of nurses for inpatient care from the diverse data sets of multiple states required substantial efforts to standardize the data and to determine what proportion of a hospital's nursing staff was allocated to inpatient care. Because of the absence of reliable coding indicating whether secondary problems were present when the patient was admitted or developed later, constructing measures of quality from discharge abstracts involved defining appropriate coding and exclusion rules for each adverse outcome. These outcomes are likely to be underreported, and the degree of underreporting may be higher where staffing levels are low. Each of these limitations weakened our ability to observe associations between outcomes and staffing levels. We studied only adverse outcomes. Furthermore, not all outcomes among patients that are important to examine (for example, falls or medication errors) can be studied on the basis of discharge data. The outcomes for which we found associations with the levels of staffing by nurses should be viewed as indicators of quality rather than as measures of the full effect of nurses in hospitals.
Further research is needed to refine the measurement of the nursing case mix on the basis of discharge data and to elucidate the factors influencing the staffing levels of nurses and the mix of nursing personnel in hospitals. Given the evidence that such staffing levels are associated with adverse outcomes, as well as the current and projected shortages of hospital-based registered nurses,60,61 systems should be developed for the routine monitoring, in large numbers of hospitals, of hospital outcomes that are sensitive to levels of staffing by nurses. Beyond monitoring, hospital administrators, accrediting agencies, insurers, and regulators should take action to ensure that an adequate nursing staff is available to protect patients and to improve the quality of care.
References (61)
1. Thomas L. The youngest science: notes of a medicine-watcher. New York: Viking Press, 1983.
2. Wunderlich GS, Sloan FA, Davis CK, eds. Nursing staff in hospitals and nursing homes: is it adequate? Washington, D.C.: National Academy Press, 1996.
3. President's Advisory Commission on Consumer Protection and Quality in the Health Care Industry. Quality first: better care for all Americans. Washington, D.C.: Government Printing Office, 1997. (Accessed May 6, 2002, at http://www.hcqualitycommission.gov/final.)
4. Lake E. The organization of hospital nursing. Philadelphia: University of Pennsylvania, 1999. (Dissertation.)
5. Schultz MA, van Servellen GA. A critical review of research on hospital mortality among medical-surgical and acute myocardial infarction patients. Nurs Health Sci 2000;2:103-112
6. Aiken LH, Clarke SP, Sloane DM, et al. Nurses' reports on hospital care in five countries. Health Aff (Millwood) 2001;20:43-53
7. Buerhaus PI, Donelan K, DesRoches C, Lamkin L, Mallory G. State of the oncology nursing workforce: problems and implications for strengthening the future. Nurs Econ 2001;19:198-208
8. Buerhaus PI, Staiger DO. Managed care and the nurse workforce. JAMA 1996;276:1487-1493
9. Buerhaus PI, Auerbach D. Slow growth in the United States of the number of minorities in the RN workforce. Image J Nurs Sch 1999;31:179-183
10. Kovner CT, Jones CB, Gergen PJ. Nurse staffing in acute care hospitals, 1990-1996. Policy Politics Nurs Pract 2000;1:194-204
11. Spetz J. Hospital employment of nursing personnel: has there really been a decline? J Nurs Adm 1998;28:20-27
12. Anderson GF, Kohn LT. Hospital employment trends in California, 1982-1994. Health Aff (Millwood) 1996;15:152-158
13. Aiken LH, Sochalski J, Anderson GF. Downsizing the hospital nursing workforce. Health Aff (Millwood) 1996;15:88-92
14. Hartz AJ, Krakauer H, Kuhn EM, et al. Hospital characteristics and mortality rates. N Engl J Med 1989;321:1720-1725
15. Manheim LM, Feinglass J, Shortell SM, Hughes EFX. Regional variation in Medicare hospital mortality. Inquiry 1992;29:55-66
16. Krakauer H, Bailey RC, Skellan KJ, et al. Evaluation of the HCFA model for the analysis of mortality following hospitalization. Health Serv Res 1992;27:317-335
17. Scott W, Forrest W, Brown B. Hospital structure and postoperative mortality and morbidity. In: Shortell SM, Brown M, eds. Organizational research in hospitals. Chicago: Blue Cross, 1976:72-89.
18. Flood AB, Scott WR, Ewy W. Does practice make perfect? II. The relation between volume and outcomes and other hospital characteristics. Med Care 1984;22:115-125
19. Flood AB, Scott WR. Hospital structure and performance. Baltimore: Johns Hopkins University Press, 1987.
20. Silber J, Rosenbaum PR, Ross RN. Comparing the contributions of groups of predictors: which outcomes vary with hospital rather than patient characteristics? J Am Stat Assoc 1995;90:7-18
21. Kovner C, Gergen PJ. Nurse staffing levels and adverse events following surgery in U.S. hospitals. Image J Nurs Sch 1998;30:315-321
22. Flood SD, Diers D. Nurse staffing, patient outcome and cost. Nurs Manage 1988;19:34-5, 38
23. Neidlinger SH, Bostrom J, Stricker A, Hild J, Zhang JQ. Incorporating nursing assistive personnel into a nursing professional proactive model. J Nurs Adm 1993;23:29-37
24. Fridkin SK, Pear SM, Williamson TH, Galgiani JN, Jarvis WR. The role of understaffing in central venous catheter-associated bloodstream infections. Infect Control Hosp Epidemiol 1996;17:150-158
25. Archibald LK, Manning ML, Bell LM, Banerjee S, Jarvis WR. Patient density, nurse-to-patient ratio and nosocomial infection risk in a pediatric cardiac intensive care unit. Pediatr Infect Dis J 1997;16:1045-1048
26. Pronovost PJ, Jenckes MW, Dorman T, et al. Organizational characteristics of intensive care units related to outcomes of abdominal aortic surgery. JAMA 1999;281:1310-1317
27. Blegen MA, Goode CJ, Reed L. Nurse staffing and patient outcomes. Nurs Res 1998;47:43-50
28. Lichtig LK, Knauf RA, Milholland KD. Some impacts of nursing on acute care hospital outcomes. J Nurs Adm 1999;29:25-33
29. Robert J, Fridkin SK, Blumberg HM, et al. The influence of the composition of the nursing staff on primary bloodstream infection rates in a surgical intensive care unit. Infect Control Hosp Epidemiol 2000;21:12-17
30. Iezzoni LI, Daley J, Heeren T, et al. Using administrative data to screen hospitals for high complication rates. Inquiry 1994;31:40-55
31. al-Haider AS, Wan TTH. Modeling organizational determinants of hospital mortality. Health Serv Res 1991;26:303-323
32. Silber JH, Rosenbaum PR, Schwartz JS, Ross RN, Williams SV. Evaluation of the complication rate as a measure of quality of care in coronary artery bypass graft surgery. JAMA 1995;274:317-323
33. Taunton RL, Kleinbeck SVM, Stafford R, Woods CQ, Bott MJ. Patient outcomes: are they linked to registered nurse absenteeism, separation, or work load? J Nurs Adm 1994;24:Suppl:48-55[Erratum, J Nurs Adm 1994;24:72.]
34. Iezzoni LI, Ash AS, Schwartz M, Daley J, Hughes JS, Mackiernan YD. Judging hospitals by severity-adjusted mortality rates: the influence of the severity-adjustment method. Am J Public Health 1996;86:1379-1387
35. Iezzoni LI, Ash AS, Schwartz M, Mackiernan YD. Differences in procedure use, in-hospital mortality, and illness severity by gender for acute myocardial infarction patients: are answers affected by data source and severity measure. Med Care 1997;35:58-71
36. Silber JH, Rosenbaum PR. A spurious correlation between hospital mortality and complication rates: the importance of severity adjustment. Med Care 1997;35:Suppl:OS77-OS92
37. Bradbury RC, Stearns FE Jr, Steen PM. Interhospital variations in admission severity-adjusted hospital mortality and morbidity. Health Serv Res 1991;26:407-424
38. Zimmerman JE, Shortell SM, Rousseau DM, et al. Improving intensive care: observations based on organizational case studies in nine intensive care units: a prospective, multicenter study. Crit Care Med 1993;21:1443-1451
39. Wan TTH, Shukla RK. Contextual and organizational correlates of the quality of hospital nursing care. QRB Qual Rev Bull 1987;13:61-64
40. Bryan YE, Hitchings KS, Fuss MA, Fox MA, Kinneman MT, Young MJ. Measuring and evaluating hospital restructuring efforts: eighteen-month follow-up and extension to critical care. J Nurs Adm 1998;28:21-27
41. Czaplinski C, Diers D. The effect of staff nursing on length of stay and mortality. Med Care 1998;36:1626-1638
42. CONQUEST: overview. Rockville, Md.: Agency for Health Care Policy and Research, 2001. (Accessed May 6, 2002, at http://www.ahrq.gov/qual/conquest/conqovr1.htm.)
43. Iezzoni LI, Mackiernan YD, Cahalane MJ, Phillips RS, Davis RB, Miller K. Screening quality of care using administrative data. Boston: Beth Israel Deaconess Hospital, 1999.
44. Karon SL, Sainfort F, Zimmerman DR. Stability of nursing home quality indicators over time. Med Care 1999;37:570-9.
45. Keyes MA. CONQUEST 2.0: an emerging clinical performance measurement tool. J Healthc Qual 2000;22:29-36
46. Palmer RH, Lawthers AG, Banks NJ, et al. CONQUEST 1.0: overview of final report and user's guide. Rockville, Md.: The Agency, 1996.
47. Silber JH, Williams SV, Krakauer H, Schwartz JS. Hospital and patient characteristics associated with death after surgery: a study of adverse occurrence and failure to rescue. Med Care 1992;30:615-629
48. Iezzoni LI, Foley SM, Heeren T, et al. A method for screening the quality of hospital care using administrative data: preliminary validation results. QRB Qual Rev Bull 1992;18:361-371
49. Iezzoni LI. Complications screening program for the Health Care Financing Administration (CSP-HCFA): CSP updated to FY 1993 coding guidelines. Boston: Beth Israel Hospital, 1994.
50. Healthcare cost and utilization project quality indicators (HCUPQIs). Rockville, Md.: Agency for Healthcare Research and Quality, 2000. (Accessed May 6, 2002, at http://www.ahrq.gov/data/hcup/qifact.htm.)
51. The AHA annual survey database: fiscal year 1997 documentation. Chicago: American Hospital Association, 1998.
52. Ballard KA, Gray RF, Knauf RA, Uppal P. Measuring variations in nursing care per DRG. Nurs Manage 1993;24:33-6, 40
53. The AHA annual survey database: fiscal year 1998 documentation. Chicago: American Hospital Association, 1999.
54. Greene WH. Econometric analysis. 4th ed. Upper Saddle River, N.J.: Prentice-Hall, 2000.
55. Stata reference manual: release 6. College Station, Tex.: Stata, 1999.
56. Needleman J, Buerhaus P, Mattke S, Stewart M, Zelevinsky K. Nurse staffing and patient outcomes in hospitals. Boston: Harvard School of Public Health, 2001. (Accessed May 6, 2002, at http://bhpr.hrsa.gov/dn/staffstudy.htm.)
57. Silber JH, Kennedy SK, Even-Shoshan O, et al. Anesthesiologist direction and patient outcomes. Anesthesiology 2000;93:152-163
58. Knaus WA, Draper EA, Wagner DP, Zimmerman JE. An evaluation of outcome from intensive care in major medical centers. Ann Intern Med 1986;104:410-418
59. Aiken LH, Smith HL, Lake ET. Lower Medicare mortality among a set of hospitals known for good nursing care. Med Care 1994;32:771-787
60. The hospital workforce shortage: immediate and future. TrendWatch. Vol. 3. No. 2. Washington, D.C.: American Hospital Association, June 2001:1-8.
61. Buerhaus PI, Staiger DO, Auerbach DI. Implications of an aging registered nurse workforce. JAMA 2000;283:2948-2954
Citing Articles (1293)
Letters
Figures/Media
- Appendix. Coding Rules for Adverse Outcomes.
Appendix. Coding Rules for Adverse Outcomes. - Table 1. Patient Outcomes and Characteristics of the 799 Hospitals.
Table 1. Patient Outcomes and Characteristics of the 799 Hospitals. - Table 2. Hours of Nursing Care.
Table 2. Hours of Nursing Care. - Table 3. Relation between Adverse Outcomes among Medical Patients and the Levels of Staffing by Registered Nurses (RNs).
Table 3. Relation between Adverse Outcomes among Medical Patients and the Levels of Staffing by Registered Nurses (RNs). - Table 4. Relation between Adverse Outcomes among Surgical Patients and the Levels of Staffing by Registered Nurses (RNs).
Table 4. Relation between Adverse Outcomes among Surgical Patients and the Levels of Staffing by Registered Nurses (RNs).
