Hospital Use of Supplemental Nurses and Patient Mortality and Failure to Rescue Jingjing Shang, PhD, RN Columbia University School of Nursing Ying Xue, DNS, RN University of Rochester School of Nursing Linda Aiken, PhD, RN, FAAN University of Pennsylvania Center for Health Outcome and Policy Research 1

This study was funded by Council for the Advancement of Nursing Science (CANS) / American Nurse Foundation (ANF) grant (grant # ) 2

Background The nation has faced a cyclical nursing shortage for decades*; Hospitals have opted to use supplemental nurses (SRNs) as a temporary solution to maintain an adequate nurse workforce**; – SRN staffing is a $3.6 billion per year market*** The use of SRNs has been involved in a long- term debate. 3 * Buerhause et al. 2009; ** May et al. 2006; *** Gregorie 2011

Background Some studies show association between SRNs and adverse outcomes such as: needle-stick injury to nurses, bloodstream infection, and medication errors*; Other studies have found that SRNs work more efficiently on some clinical practices – patient evaluation, developing nursing diagnosis, therapeutic plans, and documentation, and were related to reduced patient falls**; 4 Aiken et al. 1997, Alonso-Echanove et al 2003, Roseman et al. ** Hughes et al. 1991, Strzalka et al. 1996, Bolton et al. 2007

Objectives To determine the association between the use of SRNs in hospital and patient mortality and failure-to-rescue (FTR); To the extent that a relationship is found between level of using SRNs and negative patient outcomes, to examine the effect of hospital nursing practice environments on the relationship between RSNs and patient outcomes. 5

Methods A secondary analysis of cross-sectional data in 4 states – CA, FL, NJ, & PA in 2006 – Nurse survey Random sample: 50% in NJ, 40% in PA, CA, 25% in FL – American Hospital Association (AHA) Annual Survey – Inpatient discharge data from state agencies 6

Methods General surgical, orthopedic, and vascular surgical patients, ages of Patient outcomes – 30-day inpatient mortality – 30-day inpatient failure to rescue (FTR) Patient death with 30 days of hospital admission after a postoperative complication 7

Methods SRNs: nurses employed by an external agency & involved in direct in-patient care; Surveyed nurses reported the number of SRNs, and number of RNs on duty on their unit on the last shift; Hospital use of SRN = total SRNs / total RNs 8

Methods Nurse practice environment: – Measured by Practice Environment Scale of the Nursing Work Index (PES-NWI) – Composite score – mean of the subscales scores Range from 1 to 4 Higher scores indicate better practice environment 9

Methods Descriptive statistics compare SRNs with Permanently employed RNs Multilevel logistic regression models to examine the relationship between SRNs & patient outcomes – Using a Huber White procedure to control for clustering within hospitals – Models were risk adjusted by patient characteristics (including age, sex, race, admission type, transfer status, insurance type, 27 Elixhauser comorbidities), hospital characteristics (teaching status, high-tech status, bed size, urban/rural location, ownership), & other nursing organizational factors (nurse staffing, nurse education, working environment). 10

Result The final analysis include 40,356 nurses, 1,295,068 patients from 665 hospitals; The utilization of SRNs in hospitals ranged 0% -- 56%, with an average of 9%. – 39.54% hospitals used less than 5% SRNs, – 42% hospitals used 5%-15% SRNs, – 19% hospitals used more than 15% SRNs Count of Hospitals by Proportion SRNs 11

Supplemental Nurses (n=2,750) Permanently Employed Nurses (37,606) P value Characteristic%SE% Age (mean) <0.01 Years of Experience as RN (mean) Male (%) <0.01 BSN or above (%) Certified (%) <0.01 Race/Ethnicity <0.01 White (%) <0.01 Filipino (%) <0.01 Other Asian (%) <0.01 Black (%) <0.01 Others (%) <0.01 Table 1. Characteristics of Supplemental Nurses and Permanently Employed Nurses Notes: RN = Registered Nurse, BSN = Bachelor of Science in Nursing ; T-tests and chi-squared tests were used for the group comparisons. 12

Odds Ratios Patient OutcomeSRN Effect 30-Day Mortality % SRNs 1.05 (1.01 – 1.09)** Nurse Staffing % BSN Nurses PES-NWI Failure-to-Rescue % SRNs 1.05 (1.01 – 1.09)* Nurse Staffing % BSN Nurses PES-NWI Notes: All models controlled for patient factors (including age, sex, admission type, transfer status, DRG group, and 27 Elixhauser comorbidities) and hospital characteristics (technology status, teaching status, bed size, urban/rural, and indicator variables for the states in which hospitals were located) † p<0.10,*p < 0.05, ** p < 0.01, *** p < Table 2. Associations between 30-day In-Hospital Surgical Mortality and Failure to Rescue and the Use of Supplemental Nurses (SRNs), Before and After Controlling for Other Characteristics of Nursing 13

Odds Ratios Patient OutcomeSRN Effect SRN and Staffing Effects 30-Day Mortality % SRNs 1.05 (1.01 – 1.09)**1.04 ( )* Nurse Staffing 1.05 ( )*** % BSN Nurses PES-NWI Failure-to-Rescue % SRNs 1.05 (1.01 – 1.09)* 1.04 ( ) † Nurse Staffing 1.05 ( )*** % BSN Nurses PES-NWI Notes: All models controlled for patient factors (including age, sex, admission type, transfer status, DRG group, and 27 Elixhauser comorbidities) and hospital characteristics (technology status, teaching status, bed size, urban/rural, and indicator variables for the states in which hospitals were located) † p<0.10,*p < 0.05, ** p < 0.01, *** p < Table 2. Associations between 30-day In-Hospital Surgical Mortality and Failure to Rescue and the Use of Supplemental Nurses (SRNs), Before and After Controlling for Other Characteristics of Nursing 14

Odds Ratios Patient OutcomeSRN Effect SRN and BSN Effects 30-Day Mortality % SRNs 1.05 (1.01 – 1.09)**1.05 ( )* Nurse Staffing % BSN Nurses 0.95 ( )*** PES-NWI Failure-to-Rescue % SRNs 1.05 (1.01 – 1.09)*1.04 ( )* Nurse Staffing % BSN Nurses 0.95 ( )*** PES-NWI Notes: All models controlled for patient factors (including age, sex, admission type, transfer status, DRG group, and 27 Elixhauser comorbidities) and hospital characteristics (technology status, teaching status, bed size, urban/rural, and indicator variables for the states in which hospitals were located) † p<0.10,*p < 0.05, ** p < 0.01, *** p < Table 2. Associations between 30-day In-Hospital Surgical Mortality and Failure to Rescue and the Use of Supplemental Nurses (SRNs), Before and After Controlling for Other Characteristics of Nursing 15

Odds Ratios Patient OutcomeSRN Effect SRN and PES- NWI Effects 30-Day Mortality % SRNs 1.05 (1.01 – 1.09)**1.03 ( ) Nurse Staffing % BSN Nurses PES-NWI 0.94 ( )*** Failure-to-Rescue % SRNs 1.05 (1.01 – 1.09)*1.02 ( ) Nurse Staffing % BSN Nurses PES-NWI 0.93 ( )*** Notes: All models controlled for patient factors (including age, sex, admission type, transfer status, DRG group, and 27 Elixhauser comorbidities) and hospital characteristics (technology status, teaching status, bed size, urban/rural, and indicator variables for the states in which hospitals were located) † p<0.10,*p < 0.05, ** p < 0.01, *** p < Table 2. Associations between 30-day In-Hospital Surgical Mortality and Failure to Rescue and the Use of Supplemental Nurses (SRNs), Before and After Controlling for Other Characteristics of Nursing 16

Odds Ratios Patient OutcomeSRN Effect SRN, Staffing, BSN and PES-NWI Effects 30-Day Mortality % SRNs 1.05 (1.01 – 1.09)**1.03 (0.99 – 1.06) Nurse Staffing 1.03 (1.01 – 1.05)** % BSN Nurses 0.96 ( )*** PES-NWI 0.95 (0.92 – 0.98)*** Failure-to-Rescue % SRNs 1.05 (1.01 – 1.09)*1.02 (0.98 – 1.06) Nurse Staffing 1.03 (1.01 – 1.05)** % BSN Nurses 0.96 ( )*** PES-NWI 0.94 (0.92 – 0.97)*** Notes: All models controlled for patient factors (including age, sex, admission type, transfer status, DRG group, and 27 Elixhauser comorbidities) and hospital characteristics (technology status, teaching status, bed size, urban/rural, and indicator variables for the states in which hospitals were located) † p<0.10,*p < 0.05, ** p < 0.01, *** p < Table 2. Associations between 30-day In-Hospital Surgical Mortality and Failure to Rescue and the Use of Supplemental Nurses (SRNs), Before and After Controlling for Other Characteristics of Nursing 17

Odds Ratios Patient OutcomeSRN Effect SRN and Staffing Effects SRN and BSN Effects SRN and PES- NWI Effects SRN, Staffing, BSN and PES-NWI Effects 30-Day Mortality % SRNs 1.05 (1.01 – 1.09)**1.04 ( )*1.05 ( )*1.03 ( )1.03 (0.99 – 1.06) Nurse Staffing 1.05 ( )***1.03 (1.01 – 1.05)** % BSN Nurses 0.95 ( )***0.96 ( )*** PES-NWI 0.94 ( )***0.95 (0.92 – 0.98)*** Failure-to-Rescue % SRNs 1.05 (1.01 – 1.09)* 1.04 ( ) † 1.04 ( )*1.02 ( )1.02 (0.98 – 1.06) Nurse Staffing 1.05 ( )***1.03 (1.01 – 1.05)** % BSN Nurses 0.95 ( )***0.96 ( )*** PES-NWI 0.93 ( )***0.94 (0.92 – 0.97)*** Notes: All models controlled for patient factors (including age, sex, admission type, transfer status, DRG group, and 27 Elixhauser comorbidities) and hospital characteristics (technology status, teaching status, bed size, urban/rural, and indicator variables for the states in which hospitals were located) † p<0.10,*p < 0.05, ** p < 0.01, *** p < Table 2. Associations between 30-day In-Hospital Surgical Mortality and Failure to Rescue and the Use of Supplemental Nurses (SRNs), Before and After Controlling for Other Characteristics of Nursing 18

Conclusions & Implications SRNs are equally or even more qualified than Permanently Employed Nurses ; Our findings suggest that deficient hospital work environments may explain the poor patient outcomes associated with higher use of SRNs rather than anything about SRNs themselves; Policymakers and administrators should invest resources in nursing to improve the aspects of the practice environment which have been linked to the attraction and retention of permanent nurses and the quality of patient care. 19

Limitations We may be lacking one or more critical explanatory variables that might alter our conclusion. The findings may not generalize to other patient outcomes or to patients other than surgical patients; 20