Overall Evidence Table Reference Hugonnet et al., 2007a [1] Sample and Setting Sample: 1,883 Setting: Medical ICU in Geneva Hugonnet et al., 2007b [2] Mark et al., 2007 [3] Stone et al., 2007 [4] Berney & Needleman, Sample: 2,470 patients Setting: Medical ICU in Geneva Sample: 3.65 million pediatric patients Setting: 286 general and children’s hospitals in California Sample: 15,846 patients in 51 adult ICUs in 31 hospitals 1095 nurses Setting: NNIS hospitals Sample: 161 hospitals Design and Unit of analysis Design: Prospective cohort Unit of analysis: Patient Design: Prospective cohort Unit of analysis: Patient Design: Retrospective longitudinal Unit of analysis: Hospital Design: Observational study Unit of analysis: Unit Design: Longitudinal Adjustment for confounding Demographic characteristics, admission diagnosis and severity score, comorbidities, daily exposure to devices and selected drugs Staffing variable(s) Staffing variable: Nurse to patient ratio Infection and Operational definition Infection: ICU acquired infection Operational Definition: CDC criteria Patient characteristics, admission diagnosis, severity of illness, commorbidities, exposure to invasive devices Staffing variable: Nurse to patient ratio Resource demand scale, which includes ages, sex, comorbid conditions, emergency admission Size, teaching status, metropolitan area, inpatient days, presence of pediatric and neonatal ICU, Fixed effect analytic model Severity of illness, comorbidity, gender, age, socioeconomic status, hospital size and teaching status Staffing variable: HPPD (RN, LPN, aides) Staffing variable: RN HPPD Infection: Early on-set VAP Late on-set VAP Operational Definition: CDC criteria Infection: Postoperative infections Postoperative pneumonia Postoperative UTI Operational Definition: ICD-9-codes Infection: CLBSI VAP CAUTI Operational Definition: CDC definition Diagnostic related groups, age, payer, comorbidity, Staffing variable: RN HPPD Infection: Urinary tract infection 2006 [5] Setting: New York State hospitals Cimiotti et al., 2006 [6] Sample: 2,675 patients Dancer et al., 2006 [7] Setting: 2 level III-IV neonatal ICUs Sample: 174 patients Halwani et al., 2006 [8] Geubbels et al., 2005 [9] Setting: United Kingdom ICU Sample: 430 patients and 3947 patient-days Setting: Adult ICU of a tertiary care hospital in the United Kingdom Sample: 13,680 patients Setting: 36 acute care Unit of analysis: Hospital Design: Prospective cohort Unit of analysis: Patient Design: Retrospective investigation Unit of analysis: Patient Design: Longitudinal urban or rural hospital, size, teaching status, unionization and margin. Patient acuity, birth weight, Staffing variable: use of devices, surgery RN HPPD Not reported Staffing variable: Nurse staffing levels for trained, agency and auxiliary nurses and weekly workload Hospital acquired pneumonia Hospital acquired sepsis Operational Definition: ICD-9 codes Infection: BSI Operational Definition: CDC criteria Infection: MRSA Operational Definition: Microbiologic data Not reported Staffing variable: Infection: Understaffing: less than Nosocomial pathogen one nurse per patient during a 24h period Operational Definition: CDC definition Patient characteristics including: age, American Society of Anasthesiologists score, duration of postoperative Staffing variable: Full time-equivalent employees per 250 beds for prevention and control of infection Unit of analysis: Patient Design: Prospective, multi-center cohort study Overtime as percent of RN HPPD Infection: Surgical-site infection Operational Definition: CDC definition Sujijantararat et al., 2005 [10] The UK Neonatal Staffing Study Group, 2005 [11] Mark et al., 2004 [12] hospitals in the Dutch surveillance network for Nosocomial infections (PREZIES) Unit of analysis: Sample: 10 medical and 9 surgical wards; 389 patients and 513 full-time nursing personnel Design: Prospective, descriptive correlational research design Setting: Thai University hospital Sample: 13334 infants Setting: 54 NICUs in the UK Sample: Hospitalized patients Setting: 422 hospitals in hospital care); Hospital characteristics: including wound contamination class, type of surgery, duration of surgery, whether surgery was emergent of elective); teaching status Not reported Full time-equivalent employees per 250 beds for prevention and control of SSIs Number of surgeons Staffing variable: Nursing HPPD and percentage of RNs (of each ward) Infection: UTI Staffing variable: Presence of an appointed NICU infection control nurse or a link NICU infection control nurse at the unit Infection: Nosocomial bacteremia Staffing variable: RN FTE per 1,000 patient days LPN FTE per 1,000 patient days Non-nurse FTE per Infection: Pneumonia complication UTI complication Operational Definition: Other: urine culture Unit of analysis: Unit Design: Prospective, observational study Illness severity Unit of analysis: patient Design: Longitudinal Unit of analysis: Hospital Hospital characteristics including: high technology services, region, calendar year, ownership, payer mix, HMO penetration, patient risk adjustment Operational Definition: Other Operational Definition: 11 states McGillis et al., 2004 [13] AlonsoEchanove et al., 2003 [14] Cho et al., 2003 [15] Needleman et al., 2003 [16] Sample: 77 adult medical, surgical, and obstetric units Setting: 19 urban hospitals in Ontario, Canada Sample: 4,535 patients Setting: 8 ICUs Sample: 124,204 patients in 20 surgical diagnosis related groups Design: Cross sectional Unit of analysis: Unit Design: Cohort Unit of analysis: Patient Design: Cross sectional Unit of analysis: Patient Setting: California Sample: Design: Medicare patients Cross sectional Setting: Hospitals in 11 states Patient complexity and age Unit of analysis: Hospital Patient age, gender, weight, height, diagnosis, comorbidity 1,000 patient days Interactions among these variables Staffing variable: Staffing models defined as: RN/RPN staff mix All RN staff mix Proportion of regulated to unregulated staff RN/RPN/URW staff mix Staffing variable: Patient cared for by float nurse day > 60% Age, sex, race, primary payer, diagnosis related group, number of diagnoses at admission, scheduled admission, hospital ownership, size, teaching status, Staffing variable: All nursing hours RN hours RN proportion Diagnosis, age, sex, comorbidity, emergency admission, hospital location, size, occupancy rate, teaching status, casemix Staffing variable: Nursing HHPD (RN, LPN, Aide, licensed and total) Proportion of total hours of care by RN Proportion of total hours by LPN ICD-9 codes Infection: Wound infections UTI Operational Definition: Not stated in report Infection: CVC-associated BSI Operational Definition: CDC criteria Infection: Pneumonia Urinary tract infection Sepsis Wound infection Operational Definition: ICD-9-codes Infection: Urinary tract infection Hospital acquired pneumonia Hospital acquired sepsis Operational Definition: Richet et al., 2003 [17] Unruh, 2003 [18] Yang, 2003 [19] Sample: 90 healthcare facilities Setting: Hospitals from 30 countries participating in the International Network for the Study and Prevention of Emerging Antimicrobial Resistance (INSPEAR) Sample: 211 hospitals Setting: Acute care hospitals in Pennsylvania Sample: 21 medicalsurgical nursing units Setting: 1394-bed medical center in Design: Cross-sectional RN hours as a proportion of LPN hours Staffing variable: Number of infection control nurses per number of beds ICD-9 codes Patient age, gender, race, acuity, hospital ownership, board certified doctors, number of patients annually, capacity utilization Staffing variable: Licensed nurse FTE Total nurse FTE Proportion of licensed nurse FTE Infection: Pneumonia Post surgical infection Urinary tract infection Patient acuity level Staffing variable: Daily average hours of care, ratio of RNs to average patient census, skill-mix Not reported Unit of analysis: Hospital Design: Longitudinal Unit of analysis: Hospital Design: Correlational Unit of analysis: Unit Infection: MRSA Operational Definition: Laboratory reports of MRSA isolates Operational Definition: ICD-9 codes Infection: Respiratory and urinary tract infections Operational Definition: Other Barkell et al., 2002 [20] Taiwan Sample: 59 patients in staffing model A 37 patients in staffing model B Design: Retrospective pre-post test Not reported Staffing variable: Increase in budgeted ratio of RN to aide in staffing model B Unit of analysis: Patient Setting: Surgical unit Grundmann et al., 2002 [21] Kovner et al., 2002 [22] Sample: Design: 331 patients Cohort study followed for 3067 patient-days Unit of analysis: Patient Setting: Adult ICU in a tertiary-care hospital in the United Kingdom Design: Sample: Surgical patients Longitudinal Setting: Unit of analysis: 530-570 hospitals Hospital from 6 to 13 states depending on year Needleman et al., 2002 [23] Sample: 5,075,969 medical patients 1,104,659 Design: Cross sectional Unit of analysis: Infection: Pneumonia UTI Operational Definition: Pneumonia verified by chest x-ray UTI defined per CDC criteria Infection: MRSA Operational Definition: Microbiological identification Age, APACHE II scores Staffing variable: Relative staff deficit = a ratio of <1 of nurse staffing level/daily bed occupancy Hospital size, location, teaching status, affiliation with HMO or PPO, hospital owned nursing school, ownership, Medicare case-mix, proportion of Medicare and Medicaid, source of admission Diagnosis, age, sex, comorbidity, emergency admission, hospital location, size, occupancy Staffing variable: RN hours per adjusted patient day LPN hours per adjusted patient day Infection: Pneumonia UTI Staffing variable: Nursing HHPD (RN, LPN, Aide, licensed and total) Infection: Urinary tract infection Hospital acquired pneumonia Operational Definition: ICD-9 codes surgical patients Hospital rate, teaching status, casemix Setting: 799 hospitals in 11 states Stegenga et al., 2002 [24] Sample: 2929 patients Tucker, 2002 [25] Setting: General pediatrics ward of a Canadian hospital Sample: 13,334 infants Whitman et al., 2002 [26] Setting: 54 Neonatal ICUs in the United Kingdom Sample: 95 specialty units Dimick et al., 2001b [27] Setting: 10 adult acute care hospitals in eastern United States Sample: 569 patients Design: Retrospective descriptive study Not reported Proportion of total hours of care by RN Proportion of total hours by LPN RN hours as a proportion of LPN hours Staffing variable: Patient-to-nurse ratio and nursing HPPD Unit of analysis: Patient Design: Prospective cohort Unit of analysis: Patient Operational Definition: ICD-9 codes Infection: Nosocomial viral gastrointestinal infections Operational Definition: CDC definition Volume of neonatal ICU, consultant availability, birth weight, gestation, mode of delivery, mother had antenatal steroids, sex, Apgar scores Design: Not reported Secondary analysis of prospective, observational data Unit of analysis: Specialty unit Design: Cohort Study Hospital acquired sepsis Wound infection Patient age, sex, nature of admission, type of operation, comorbidity, Staffing variable: High and low nurse-topatient ratios Staffing variable: WHPPD Infection: Nosocomial bacteremia Operational Definition: First positive blood culture more than 48 hours after birth Infection: Central line infection Operational Definition: NNIS definition Staffing variable: Nurse to patient ratio Infection: Pneumonia Septicemia Dimick et al., 2001a [28] Setting: 25 hospitals in Maryland Unit of analysis: Patient Sample: 366 patients Design: Retrospective cohort Amaravadi et al., 2000 [30] Dorsey et al., 2000 [31] Postoperative Infection Unit of analysis: Patient Operational Definition: ICD-9 CM codes Infection: Complications after esophageal infection including pneumonia, septicemia, postoperative infection Sample: Abdominal Aortic surgery patients Setting: All nonfederal ICUs in Maryland Sample: 366 patients Design: Cross sectional Operational Definition: ICD-9 CM codes Infection: Septicemia Setting: 32 non-federal acute care hospitals in Maryland Sample: 52 patients in a SICU Unit of analysis: Patient Setting: 35 hospitals in Maryland Pronovost et al., 2001[29] hospital and surgeon volumes Unit of analysis: unit Design: Cohort study Design: Retrospective cohort study Patient case-mix and other hospital characteristics Staffing variable: Presence vs. absence of daily rounds by ICU physicians Patient age, sex, race, emergency admission, type of aneurysm, comorbid conditions, size of hospital, volume of surgery Staffing variable: Nurse to patient ratios of 1:1 or 1:2 Nurse to patient ratios of 1:3 or 1:4 Patient age, sex, nature of admission, type of operation, comorbid disease and hospital and surgeon volume, clustering of outcomes within a hospital Staffing variable: NNPR Monthly patient-days Staffing variable: Nurse to patient staffing ratio defined as: number of nurses- Operational Definition: ICD-9 codes Infection: Pneumonia Septicemia Postoperative infection Operational Definition: ICD9CM codes Infection: E. cloacae and S. marcescens Robert et al., 2000 [32] Harbarth et al., 1999 [33] Setting: Hospital in San Francisco, CA Sample: 28 cases and 99 randomly selected controls Setting: 20-bed surgical ICU Sample: 60 infants Setting: NICU of a 1500bed healthcare center in Geneva, Switzerland Lichtig et al., 1999 [34] Vicca, 1999 [35] Unit of analysis: Patient Design: Case-control Age, diagnosis, comorbidity, length of stay Unit of analysis: Patient Design: Retrospective cohort (outbreak) Unit of analysis: Patient Sample: 478 hospitals in 1992 426 hospitals in 1994 Design: Cross-sectional (Hospital cost reports) Setting: California and New York hospitals Sample: 50 new incident Unit of analysis: Hospital Design: Cohort Gender, birth weight, gestational age, length of stay in NICU and exposure factors including indwelling devices, medication and nutrition Nursing intensity weights based on patients’ characteristics, teaching status and location [(1:1 patients X 1)+(1:2 Operational Definition: patients X 0.5)] Microbiologic identification Staffing variable: Infection: Regular permanently Bloodstream infections assigned staff Pool staff Operational Definition: CDC criteria Nurse to patient ratio Staffing variable: Understaffing (lack of more than eight nursing staff per shift) Staffing variable: Nursing hours/ NIWs and RN hours as a percentage of total nursing hours Infection: E. cloacae infection at any site including: bacteremia, pneumonia, soft-tissue infection and respiratory colonization Operational Definition: CDC criteria Infection: Urinary tract infection Pneumonia Surgical wound infection Operational Definition: ICD-9 CM codes Not reported Staffing variable: Number of trained Infection: MRSA carriage cases Setting: Intensive therapy unit of a hospital in Leicestershire Blegen et al., 1998 [36] Sample: 42 general nursing units Setting: 1 hospital Kovner & Gergen, 1998 [37] Archibald et al., 1997 [38] Fridkin et al., 1996 [39] Sample: 589 hospitals Setting: Acute-care hospitals in 10 states Sample: 782 pediatric patients Setting: Cardiac intensive care unit Sample: 1760 patients Unit of analysis: Patient Design: Cross sectional Patient severity of illness Nursing acuity system Unit of analysis: Nursing unit Design: Cross-sectional nursing staff per 8 h shift, number of extra/agency staff per 8 h shift, number of patients per 8 h shift, dependency score per 8 h shift (number of nurses needed at bedside) Staffing variable: All HPPD Case mix (patient age, sex, and comorbidity), hospital teaching status, ownership, bed size, region Staffing variable: FTE RNAPD Operational Definition: Not defined, data abstracted from patient charts. Infection: Urinary tract infection pneumonia Operational Definition: ICD-9 diagnosis codes Not reported Staffing variable: Monthly nurse hours Nursing HPPD Unit of analysis: Monthly unit rates of infection Design: Case-control and Infection: Urinary tract and respiratory infections RN HPPD Unit of analysis: Hospital Design: Cross sectional Operational Definition: Not reported Infection: Nosocomial infection rate Operational Definition: CDC criteria Patient age, gender, length of stay, primary diagnosis, Staffing variable: Average monthly SICU Infection: CVC-BSI Setting: SICU in a Universityaffiliated VA medical center Grillo-Peck & Sample: Risner, 1995 71 patients [40] Setting: 1 neuroscience unit Haley et al., Sample: 1995 [41] NICU Taunton et al., 1994 [42] Setting: Public hospital in Dallas Sample: Hospitalized patients Setting: 4 large Midwestern urban hospitals cohort study (preand post- a protracted outbreak) Unit of analysis: Patient Design: Pre-post severity of illness Operational Definition: Laboratory-confirmed or CDC definition Not reported Unit of analysis: Patient Design: Outbreak investigation Unit of analysis: Unit Design: Cross sectional correlation study patient-to-nurse ratio Time and intensity of care Not reported Unit of analysis: Unit APACHE II = Acute physiology and chronic health evaluation II BSI = Bloodstream infections CAUTI- Catheter-associated urinary tract infections CDC = Center for Disease Control and Prevention Staffing variable: Change in staffing to increased aides and decreased RN Infection: Nosocomial infection Staffing variable: Daily infant to nurse ratio Daily work load to staffing ratio Infection: MRSA Staffing variable: RN absenteeism Required RN hours /actual RN hours Infection: UTI BSI Operational Definition: Not given Operational Definition: Microbiology results Operational Definition: CDC criteria CLBSI = Central line-related bloodstream infections CVC = Central venous catheter FTE = Full-time equivalent HMO = Health Maintenance Organization HPPD = Hours per patient day ICD-9 = International classification of diseases, 9th Edition ICD-9 CM = International classification of diseases, 9th Edition, Clinical Modification ICU = Intensive care unit LPN = Licensed practical nurse MRSA = Methicillin-resistant Staphylococcus aureus NICU = Nosocomial intensive care unit NIW = Nursing intensity weights NNIS = National Nosocomial Infections Surveillance System NNPR = Night-time nurse to patient ratio PPO = Preferred Provider Organization RN = Registered nurse RNAPD = RNs per adjusted inpatient day RPN = Registered Practical Nurse SICU = Surgical intensive care unit SSI = Surgical site infections URW = Unregulated Staff UTI = Urinary tract infections VAP = Ventilator-associated pneumonia WHPPD = Worked hours per patient day Reference List (1) Hugonnet S, Chevrolet JC, Pittet D. The effect of workload on infection risk in critically ill patients. Crit Care Med 2007 Jan; 35(1):76-81. (2) Hugonnet S, Uckay I, Pittet D. Staffing level: a determinant of late-onset ventilator-associated pneumonia. Crit Care 2007; 11(4):R80. (3) Mark BA, Harless DW, Berman WF. Nurse staffing and adverse events in hospitalized children. Policy Polit Nurs Pract 2007 May; 8(2):83-92. (4) Stone PW, Mooney-Kane C, Larson EL, et al. Nurse working conditions and patient safety outcomes. Med Care 2007 Jun; 45(6):571-8. (5) Berney B, Needleman J. Impact of nursing overtime on nurse-sensitive patient outcomes in New York hospitals, 1995-2000. Policy Polit Nurs Pract 2006 May; 7(2):87-100. (6) Cimiotti JP, Haas J, Saiman L, Larson EL. Impact of staffing on bloodstream infections in the neonatal intensive care unit. Arch Pediatr Adolesc Med 2006 Aug; 160(8):832-6. (7) Dancer SJ, Coyne M, Speekenbrink A, Samavedam S, Kennedy J, Wallace PG. MRSA acquisition in an intensive care unit. Am J Infect Control 2006 Feb; 34(1):10-7. (8) Halwani M, Solaymani-Dodaran M, Grundmann H, Coupland C, Slack R. Crosstransmission of nosocomial pathogens in an adult intensive care unit: incidence and risk factors. Journal of Hospital Infection 2006 May; 63(1):39-46. (9) Geubbels EL, Wille JC, Nagelkerke NJ, Vandenbroucke-Grauls CM, Grobbee DE, de Boer AS. Hospital-related determinants for surgical-site infection following hip arthroplasty. Infect Control Hosp Epidemiol 2005 May; 26(5):43541. (10) Sujijantararat R, Booth RZ, Davis LL. Nosocomial urinary tract infection: nursing-sensitive quality indicator in a Thai hospital. J Nurs Care Qual 2005 Apr; 20(2):134-9. (11) The UK Neonatal Staffing Study Group. Relationship between probable nosocomial bacteraemia and organisational and structural factors in UK neonatal intensive care units. Qual Saf Health Care 2005 Aug 1; 14(4):264-9. (12) Mark BA, Harless DW, McCue M, Xu Y. A longitudinal examination of hospital registered nurse staffing and quality of care. Health Serv Res 2004 Apr; 39(2):279-300. (13) McGillis HL, Doran D, Pink GH. Nurse staffing models, nursing hours, and patient safety outcomes. J Nurs Adm 2004 Jan; 34(1):41-5. (14) Alonso-Echanove J, Edwards JR, Richards MJ, et al. Effect of nurse staffing and antimicrobial-impregnated central venous catheters on the risk for bloodstream infections in intensive care units. Infect Control Hosp Epidemiol 2003 Dec; 24(12):916-25. (15) Cho SH, Ketefian S, Barkauskas VH, Smith DG. The effects of nurse staffing on adverse events, morbidity, mortality, and medical costs. Nurs Res 2003 Mar; 52(2):71-9. (16) Needleman J, Buerhaus PI, Mattke S, Stewart M, Zelevinsky K. Measuring hospital quality: can medicare data substitute for all-payer data? Health Serv Res 2003 Dec; 38(6 Pt 1):1487-508. (17) Richet HM, Benbachir M, Brown DE, et al. Are there regional variations in the diagnosis, surveillance, and control of methicillin-resistant Staphylococcus aureus?. Infect Control Hosp Epidemiol 2003 May; 24(5):334-41. (18) Unruh L. Licensed nurse staffing and adverse events in hospitals. Med Care 2003 Jan; 41(1):142-52. (19) Yang KP. Relationships between nurse staffing and patient outcomes. J Nurs Res 2003 Sep; 11(3):149-58. (20) Barkell NP, Killinger KA, Schultz SD. The relationship between nurse staffing models and patient outcomes: a descriptive study. Outcomes Manag 2002 Jan; 6(1):27-33. (21) Grundmann H, Hori S, Winter B, Tami A, Austin D. Risk Factors for the Transmission of MethicillinīÇÉResistant Staphylococcus aureus in an Adult Intensive Care Unit: Fitting a Model to the Data. The Journal of Infectious Diseases 2002 Feb 4; 185(4):481-8. (22) Kovner C, Jones C, Zhan C, Gergen PJ, Basu J. Nurse staffing and postsurgical adverse events: an analysis of administrative data from a sample of U.S. hospitals, 1990-1996. Health Serv Res 2002 Jun; 37(3):611-29. (23) Needleman J, Buerhaus P, Mattke S, Stewart M, Zelevinsky K. Nurse-staffing levels and the quality of care in hospitals. N Engl J Med 2002 May 30; 346(22):1715-22. (24) Stegenga J, Bell E, Matlow A. The role of nurse understaffing in nosocomial viral gastrointestinal infections on a general pediatrics ward. Infect Control Hosp Epidemiol 2002 Mar; 23(3):133-6. (25) Tucker J. Patient volume, staffing, and workload in relation to risk-adjusted outcomes in a random stratified sample of UK neonatal intensive care units: a prospective evaluation. Lancet 2002 Jan 12; 359(9301):99-107. (26) Whitman GR, Kim Y, Davidson LJ, Wolf GA, Wang SL. The impact of staffing on patient outcomes across specialty units. J Nurs Adm 2002 Dec; 32(12):633-9. (27) Dimick JB, Swoboda SM, Pronovost PJ, Lipsett PA. Effect of nurse-to-patient ratio in the intensive care unit on pulmonary complications and resource use after hepatectomy. Am J Crit Care 2001 Nov; 10(6):376-82. (28) Dimick JB, Pronovost PJ, Heitmiller RF, Lipsett PA. Intensive care unit physician staffing is associated with decreased length of stay, hospital cost, and complications after esophageal resection. Crit Care Med 2001 Apr; 29(4):753-8. (29) Pronovost PJ, Dang D, Dorman T, et al. Intensive care unit nurse staffing and the risk for complications after abdominal aortic surgery. Eff Clin Pract 2001 Sep; 4(5):199-206. (30) Amaravadi RK, Dimick JB, Pronovost PJ, Lipsett PA. ICU nurse-to-patient ratio is associated with complications and resource use after esophagectomy. Intensive Care Med 2000 Dec; 26(12):1857-62. (31) Dorsey G, Borneo HT, Sun SJ, et al. A heterogeneous outbreak of Enterobacter cloacae and Serratia marcescens infections in a surgical intensive care unit. Infect Control Hosp Epidemiol 2000 Jul; 21(7):465-9. (32) 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 Jan; 2000 Jan;21(1):12-7. (33) Harbarth S, Sudre P, Dharan S, Cadenas M, Pittet D. Outbreak of Enterobacter cloacae related to understaffing, overcrowding, and poor hygiene practices. Infect Control Hosp Epidemiol 1999 Sep; 20(9):598-603. (34) Lichtig LK, Knauf RA, Milholland DK. Some impacts of nursing on acute care hospital outcomes. J Nurs Adm 1999 Feb; 29(2):25-33. (35) Vicca AF. Nursing staff workload as a determinant of methicillin-resistant Staphylococcus aureus spread in an adult intensive therapy unit. Journal of Hospital Infection 1999 Oct; 43(2):109-13. (36) Blegen MA, Goode CJ, Reed L. Nurse staffing and patient outcomes. Nurs Res 1998 Jan; 47(1):43-50. (37) Kovner C, Gergen PJ. Nurse staffing levels and adverse events following surgery in U.S. hospitals. Image J Nurs Sch 1998; 30(4):315-21. (38) 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 Nov; 16(11):1045-8. (39) 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 Mar; 1996 Mar;17(3):150-8. (40) Grillo-Peck AM, Risner PB. The effect of a partnership model on quality and length of stay. Nurs Econ 1995 Nov; 13(6):367-72, 374. (41) Haley RW, Cushion NB, Tenover FC, et al. Eradication of endemic methicillinresistant Staphylococcus aureus infections from a neonatal intensive care unit. J Infect Dis 1995 Mar; 171(3):614-24. (42) Taunton RL, Kleinbeck SV, Stafford R, Woods CQ, Bott MJ. Patient outcomes. Are they linked to registered nurse absenteeism, separation, or work load? J Nurs Adm 1994 Apr; 24(4 Suppl):48-55.