Nurse Staffing Levels and Teamwork: A Cross-Sectional Study of Patient Care Units in Acute Care Hospitals

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1 HEALTH POLICY AND SYSTEMS Nurse Staffing Levels and Teamwork: A Cross-Sectional Study of Patient Care Units in Acute Care Hospitals Beatrice J. Kalisch, PhD, RN, FAAN 1 & Kyung Hee Lee, MPH, RN 2 1 Rho, Titus Distinguished Professor of Nursing and Director, Nursing Business and Health Systems, University of Michigan, School of Nursing, Ann Arbor, MI 2 Rhoand Lambda Alpha-at-Large, Research assistant and PhD candidate, University of Michigan, School of Nursing, Ann Arbor, MI Key words Teamwork, staffing, nursing Correspondence Dr. Beatrice J. Kalisch, Titus Professor and Director, Nursing Business and Health Systems, University of Michigan, School of Nursing, 400 N. Ingalls Street, Ann Arbor, MI bkalisch@umich.edu Accepted: September 16, 2010 doi: /j x Abstract Purpose: To determine if nurse staffing predicts teamwork. Design: A cross-sectional, descriptive design with a sample of nursing staff (N = 2,545) on 52 patient care units in four hospitals was utilized. Methods: The Nursing Teamwork Survey was utilized to collect data on the level of perceived nursing teamwork on each of the study units. In addition, nursing staffing data were collected for each study unit. Findings: Higher levels of nurse staffing were related to better teamwork. Specifically, the greater the hours per patient day, the higher the level of overall teamwork on the unit (β = 0.417, p =.033). Also the greater the skill mix, the higher the level of overall teamwork on the unit (β = 0.436, p =.009). Conclusions: Adequate levels of staffing are needed to ensure nursing teamwork. Clinical Relevance: The ability to provide quality and safe care is associated with teamwork, which in turn requires adequate staffing. In recent years, the importance of teamwork in achieving patient safety (Clark et al., 2009; Firth-Cozens, 2001), quality of care (Kalisch, Curley, & Stefanov, 2007; Leppa, 1996; Morey et al., 2002), job satisfaction (Amos, Hu, & Herrick, 2005; Chang et al., 2009; Collette, 2004; Rafferty, Ball, & Aiken, 2001), and decreased turnover (Blegen, Vaughn, & Vojir, 2008) has been recognized. For example, higher self-identified teamwork in the intensive care unit was found to be related to lower mortality rates (Wheelan, Burchill, & Tilin, 2003). Blegen et al. found that lower vacancy rates and turnover were associated with a higher level of teamwork, and a study by Brewer (2006) showed that a group-type hospital culture predicted fewer patient falls with injury. Kalisch and colleagues compared selected outcomes before and after an intervention to improve teamwork and found a significant decrease in patient falls, turnover, and vacancy rates after the intervention (Kalisch & Begeny, 2005; Kalisch et al., 2007). In order to understand what leads to effective teamwork, studies have examined factors that are correlated with teamwork, such as interpersonal skills and selfmanagement (Stevens & Campion, 1994) and individual emotional intelligence (McCallin & Bamford, 2007). We uncovered only a few studies that focused on the relationship between workload or staffing levels and teamwork, and these were in fields outside of health care, such as organizational engineering and business (Sebok, 2000; Thomas, Sexton, & Helmreich, 2003). McComb, Green, and Dale Compton (2007) concluded that staffing quality (such as excellence in technical and professional skills and knowledge) is positively related to team members tendency to react flexibly within a team. In a previous study, we found that higher teamwork is associated with perceptions that staffing was adequate and fewer numbers of patients were assigned to the nurse on the previous shift (Kalisch & Lee, 2009). In order to better understand the relationship between workload and teamwork, the relationship between the actual level of staffing (as opposed to perceptions) and teamwork was examined in this study. 82 Journal of Nursing Scholarship, 2011; 43:1, c 2011 Sigma Theta Tau International

2 Kalisch and Lee Nurse Staffing and Teamwork Hospital characteristic Bed size Unit characteristics Case mix index Nursing staffing (HPPD, RN HPPD, skill mix) Figure. Conceptual framework staffing and teamwork. Conceptual Framework Nursing teamwork The framework for this study is illustrated in the Figure. It postulates that staffing levels predict teamwork when unit level case mix index (CMI) and size of hospital are controlled. CMI values for patients were averaged across each study unit as an indicator of the acuity of patients. We also hypothesized that the size of the hospital may have an impact on teamwork. Size of hospitals has been found, in previous studies, to be negatively associated with teamwork (El-Jardali, Jamal, Dimassi, Ammar, & Tchaghchaghian, 2008; Meterko, Mohr, & Young, 2004). Over 100 studies have shown that the level and type of nurse staffing impacts patient outcomes (Aiken, Clarke, Cheung, Sloane, & Silber, 2003; Friese, Earle, Silber, & Aiken, 2010), yet we are not clear about how or why this relationship exists. Teamwork has been associated with patient safety (Clark et al., 2009; Firth-Cozens, 2001), a reduction in patient fall rates (Brewer, 2006; Kalisch et al., 2007), clinical error reduction, performance improvement, improved end of life care (Hewison, Badger, Clifford, & Thomas, 2009), and better patient outcomes (Wheelan et al., 2003). Taken together, it is hypothesized that level of staffing may impact teamwork, which in turn leads to patient outcomes. Teamwork would be one process variable that would at least partially explain the relationship between level of staffing and patient outcomes. Teamwork in this study is based on work by Salas, Sims, and Burke (2005), who identified five core elements (team orientation, team leadership, back up, mutual performance, and adaptability) and three coordinating functions of teamwork (communication, shared mental models, and trust). Using the Salas conceptual framework as a basis, the Nursing Teamwork Survey (NTS) was developed and tested for its psychometric properties (Kalisch, Lee, & Salas, 2010). This testing resulted in five of the eight elements of teamwork being descriptive of nursing teams in inpatient hospital settings: team orientation (i.e., the emphasis is on what is in the best interest of the total team, not the desires of individual team members), team leadership (i.e., direction and support provided by a formal leader [e.g., charge nurse] or members of the team), back up (i.e., members move in to assist and provide feedback when another team member is overwhelmed or does not know how to complete the work), shared mental models (i.e., members have the same conceptualization about what work is to be completed and when and who will do it), and trust (i.e., confidence in team members that they will complete their part of the work in a quality way). Research Questions The aim of this study was to examine the relationship of staffing levels to nursing teamwork. The research questions were as follows: 1. Controlling for hospital size and CMI, does the level of staffing predict nursing teamwork? 2. Controlling for hospital size and CMI, does the level of staffing predict subscales of teamwork (trust, team orientation, back up, shared mental model, and team leadership)? METHOD Sample and Setting This study utilized a cross-sectional, descriptive design, and a purposive sample was used. The setting for this study was four hospitals located in the Midwestern United States. Hospital bed size ranged from 300 to 900 beds. Unit participation within hospitals ranged from 7 to 18 units. All units within the hospitals eligible for inclusion (i.e., medical, surgical, intermediate care, intensive care, rehabilitation, maternal-child, and psychiatric in patient units) participated. A total of 52 units in these four hospitals made up the study sample. There were 2,545 respondents, of whom 1,741 were registered nurses (RNs), 41 were licensed practical nurses (LPNs), 502 were nursing assistants (NAs), and 191 were unit secretaries (US). The overall return rate was 55.7% with a range of 43.1% to 71.8% by patient care unit. Study Variables Teamwork. The NTS was utilized in this study. The NTS was specifically designed to measure nursing teamwork in inpatient settings among the individuals who are permanent members of the unit staff, namely RNs, LPNs, NAs, and USs. Providers and other staff members 83

3 Nurse Staffing and Teamwork Kalisch and Lee who care for patients or manage systems on multiple units, such as physicians, physical therapists, and dieticians, were not included in the definition of a patient unit team for this study. The NTS is a 33-item questionnaire with a Likerttype scaling system ranging from rarely to always. The survey items were generated from the literature and from focus groups with staff nurses and managers (Kalisch, Weaver, & Salas, 2009). The results of the psychometric evaluation of the NTS are published elsewhere (Kalisch et al., 2010). Construct validity, tested with exploratory factor analysis, resulted in a five-factor solution: trust (i.e., shared perception that members will perform actions necessary to reach interdependent goals and act in the interest of the team; seven items), team orientation (i.e., cohesiveness, individuals see the team s success as taking precedence over individual needs and performance; nine items), back up (i.e., helping one another with their tasks and responsibilities; six items), shared mental models (i.e., mutual conceptualizations of the task, roles, strengths-weaknesses, and processes and strategy necessary to attain interdependent goals; seven items), and team leadership (i.e., structure, direction, and support provided by the formal leader or the other members of the team, or both; four items). These five factors explained 53.11% of the variance. The result from the Bartlett test indicated that the correlation matrix is not an identity matrix (χ 2 = 12, , degrees of freedom = 528, p <.01), and the Kaiser-Meyer-Olkin measure supported the fact that sampling adequacy was excellent (0.961). Confirmatory factor analysis demonstrated that the five-factor model fits the data well. A comparative fit index of the model was 0.884, the root mean square error of approximation index was 0.055, and the standardized root mean residual fit index was Test-retest reliability was 0.92, and the coefficients on each subscale ranged from 0.77 to The overall internal consistency of the survey was 0.94, and the α coefficients on each subscale ranged from 0.74 to Intraclass correlation coefficients and index of agreement (r wg(j) ) were also calculated to estimate interrater agreement for each unit staff group. These analyses demonstrated that members of the same unit responded similarly to the NTS and that staff from different units responded differently (Kalisch et al., 2010). Staffing. Staffing data were obtained for this study, including three widely utilized nurse staffing indicators (hours per patient day [HPPD], RN hours per patient day [RN HPPD], and skill mix) as well as unit level CMI from administrative databases at the four hospital sites. To ensure that data were comparable among the four sites, we calculated these indicators from raw data provided by the hospital. HPPD refers to the overall time expended by the RNs, LPNs, and NAs working on a given patient unit per patient day. For this study, HPPD values were computed as the sum of total nursing hours worked by nursing staff (RN, LPN, and NA) with direct patient care responsibilities divided by number of patient days. RN HPPD is the time spent by the RNs only per patient day. RN HPPD was calculated as total RN hours per day divided by patient days. Skill mix is defined as the proportion of RNs, LPNs, and NAs providing direct patient care on a given unit. The patient s skill mix value was calculated as the number of productive hours worked by the RNs with patient care responsibilities divided by the total number of productive hours worked by nursing staff (RN, LPN, and NA) with direct patient care responsibilities. CMI is the average diagnosis-related group (DRG) weight for all of a hospital s Medicare patients. CMI is calculated by adding the relative weights for all patient admissions and then dividing that number by the total number of admissions during the same time frame (Steinwald & Dummit, 1989). It reflects the expected total resource utilization for all patients within a DRG grouping and thus is a proxy for patient acuity. Hospital size was measured as the number of beds. Procedures Data collection was conducted over a 4-week period of time in each facility in and included two study phases: (a) administration of the NTS to staff members on the study units, and (b) collection of staffing data (i.e., HPPD, RN HPPD, skill mix) and unit level CMI for each of the study units. Phase 1 began after internal review board approval and support was received to conduct the study at each hospital. The NTS survey was placed in a large envelope with a cover letter explaining the study, informing participants of the confidentiality of their responses and that their participation was voluntary. Also included was a candy bar as a token of appreciation and a letter size envelope in which the participants were to place their completed questionnaires and then seal the envelope and place it in a locked box on each patient care unit. For units who achieved a 50% return rate or greater, pizza was provided. The second phase of the study involved the retrospective collection of unit level administrative data. Data (i.e., HPPD, RN HPPD, skill mix, CMI) were obtained for each participating unit for the month prior to the time that the staff completed the NTS. Hospitals were asked to provide the data in raw form (i.e., numerator and denominator) in order to ensure consistency in computation. Administrative staff members of each hospital were given an Excel 84

4 Kalisch and Lee Nurse Staffing and Teamwork file with specific definitions and data requirements and were asked to input data into this template. Then the research team computed all variables of interest. Data Analysis The Statistical Package for the Social Science (SPSS), Version 16.0 (SPSS, Chicago, IL) was used for data analyses. The unit of analysis for this study was the patient care unit. The individual level teamwork mean score, which was collected via the NTS, was aggregated to a unit level teamwork score. The decision to use the unit level analyses was made based on the fact that staff working on the same unit (i.e., on the same team) are expected to be similar to each other, while those working on different unitsteams are predicted to be different. In addition, Smits, Wagner, Spreeuwenberg, van der Wal, and Groenewegen (2009) reported that the clustering of responses within units was conceptually better than individual attitudes about group culture. Statistical analyses also showed that unit level analyses were appropriate. Significant F statistic values inferred that the responses among nursing staff on the same unit were similar, while those of nursing staff on different units were not similar (F[51, 2,483] = 7.41, p <.001). The Intraclass correlation (ICC) 1 value was 0.12, indicating that staff within units had similar assessments of the unit s teamwork; the ICC2 value was 0.87, providing reliability that the unit s teamwork differentiates groups. Preliminary analyses of the data were completed using frequency, descriptive, and correlation methods according to the research questions. Correlation analysis was used to address the relationship between hospital bed size, staffing levels, and teamwork. Further analysis was completed using multiple regression to determine if staffing levels are predictive of the overall teamwork score. Hospital size and unit CMI were also included as independent variables to examine their impact on teamwork. In order to determine the predic- tive ability of staffing levels on the subscales of teamwork (trust, team orientation, back up, shared mental model, and team leadership), five separate multiple regression analyses were also performed. Findings Sample Characteristics In terms of the age of the staff, 60% were over 35 years and 46% of the staff held a bachelor s degree or higher. A majority of staff were female (89%), were RNs (70%), and worked full time (83%). The majority of units in the sample employed staff with greater than 2 years of experience in the role (74%; Table 1). HPPD values for participating units ranged from a low of 6.27 to a high of 21.30, with the mean being (SD ± 4.27). The average RN HPPD value was 8.91 (SD ± 4.48), with a range of 3.75 to The mean skill mix of staff on the units was 0.79 (SD ± 0.17), with a range of 0.53 to The mean CMI on the units was 2.28 (SD ± 1.36), with a range of 0.83 to Hospital and Unit Characteristics Pearson correlations were calculated to determine hospital characteristics and unit characteristics significantly related to teamwork scores. A positive relationship between hospital bed size and teamwork overall scores (r = 0.33, p <.05) was found. A positive correlation was also uncovered between teamwork and all three of the staffing variables: HPPD, RN HPPD, and skill mix. The higher the HPPD (r = 0.40, p <.01), RN HPPD (r = 0.53, p <.01), and skill mix value (r = 0.54, p <.01), the higher the levels of nursing teamwork. Predicting Teamwork Multiple regression analysis was conducted to determine the predictive ability of staffing levels on nursing Table 1. Hospital and Unit Characteristics of Study Unit characteristics Bed Units in Age Gender Education (BSN Experience Occupation Work hour (day Hospital size study (>35 yr) % (female)% or higher)% (>2 yr) % (RN) % Full-time% or rotating shift) % Total

5 Nurse Staffing and Teamwork Kalisch and Lee Table 2. Predictors of Overall Teamwork Variable B SE β t p HPPD Skill Mix CMI Bed size R 2 R 2 = F(p) (.003) B,; SE, standard error; HPPD, hours per patient day; CMI, case mix index. teamwork. RN HPPD was dropped from the model due to a strong correlation between HPPD and RN HPPD (r = 0.94, p <.01). Choosing HPPD as opposed to RN HPPD was based on the fact that the study sample included all levels of nurse staffing (RNs, LPNs, and NAs). For overall teamwork,themodel(table 2) considered the following indicators: HPPD, skill mix, CMI, and bed size. The overall model accounted for 33.1% of the variation in overall teamwork (p =.003). HPPD and skill mix were moderately associated with overall teamwork after controlling for CMI and bed size; specifically, the greater the HPPD, the higher the level of overall teamwork on the unit (β = 0.417, p =.033), the greater the skill mix, the higher the level of overall teamwork on the unit (β = 0.436, p =.009). In order to determine the relationship between staffing levels and five subscales of teamwork (trust, team orientation, back up, shared mental model, and team leadership), five models were calculated using multiple regression analyses (Table 3). HPPD was strongly associated with a higher score on back up (β = 0.59, p <.01), shared mental model (β = 0.55, p <.01), and team leadership (β = 0.60, p <.01), but not on trust and team orientation. Skill mix was moderately associated with the higher scores on team orientation (β = 0.42, p <.05), back up (β = 0.33, p <.05), and team leadership (β = 0.50, p <.01), but not trust and shared mental model. Units with larger bed size hospitals showed moderately lower scores on team orientation (β = 0.46, p <.01), back up (β = 0.40, p <.015), and team leadership (β = 0.40, p <.01), but not trust and shared mental model. Discussion This study demonstrates that there is a relationship between the actual hours of nursing care (HPPD) and nursing teamwork. A higher proportion (skill mix) of nurse staffing (i.e., more RNs in the mix of staff) also results in better nursing teamwork. This finding substantiates previous research showing that nursing staff perceptions of staffing adequacy as well as number of patients they reported caring for on the previous shift was associated with a higher level of teamwork (Kalisch & Lee, 2009). The use of actual nurse staffing data in the current study adds substantial credibility and confidence to the previous findings. Teamwork in this study is made up of an overall score for each patient care unit as well as scores on the five subscales representing elements of nursing teamwork presented above under a conceptual framework: the higher the staffing level (HPPD), the better the back up. Back up can be either physical assistance (e.g., helping another staff member ambulate a patient) or verbal intervention (e.g., reminding a staff member to wash his or her hands). Having more staff would logically lead to more availability of other team members to monitor one another and help when the need arises. In other studies, we have found that when staff members feel overtaxed, they block out everything happening on the unit except the care of their own patients: There were three of us that night, and we each had eight patients. You couldn t help each other because you had eight of your own; I see a little of what the other staff are doing (Kalisch, Weaver, & Salas, 2009, p. 301). Shared mental model, which refers to staff having the same conception of what needs to be done and how, Table 3. Regression Analyses for Variables Predicting Subscales of Teamwork Model 1 Model 2 Model 3 Model 4 Model 5 Trust Team orientation Back up Shared mental model Team leadership B SE β B SE β B SE β B SE β B SE β HPPD Skill mix CMI Bed size R F(p) 1.74 (.16) 3.21 (.02) 5.22 (.00) 3.41 (0.02) (.00) p <.05; p <.01. B,; SE, standard error; HPPD, hours per patient day; CMI, case mix index. 86

6 Kalisch and Lee Nurse Staffing and Teamwork was found to be significantly associated with the level of staffing levels and skill mix. In other words, the better staffing and the higher proportion of RNs as a mix of staff, the greater the shared mental models. The reason for this finding might be due to having more time to communicate and conduct effective handoffs. Team leadership scores were also significantly associated with more staff and a greater number of RNs. The possible reasons for these findings might be either the greater amount of time available to lead and/or primarily because the charge nurse would be less likely to carry a patient load along with her leadership responsibilities. The three elements of teamwork team orientation, back up, and team leadership showing a significant relationship with skill mix correlates with other studies that have investigated RN and NA working relationships (Huber, Blegen, & McCloskey, 1994; Kalisch, 2009; Potter & Grant, 2004; Scott-Cawiezell et al., 2004). Apparently when there are more NAs, there are more teamwork problems than when the staff is made up of a greater proportion of RNs. Findings showing that teamwork is apparently more difficult to achieve in larger hospitals illustrates that perhaps the increasing complexity and the larger number of people one needs to interact with in larger institutions interferes with the creation and maintenance of effective teams even on a given patient care unit. Limitations This study is limited by the sample, which was in four hospitals. This does not allow for generalizability of the findings. The measure of teamwork in this study captures perceptions of teamwork. Direct observation studies would be needed to measure actual teamwork. However, observations can also have bias built in (e.g., observer bias). Implications The results of this study suggest that when nursing staff are stressed and overwhelmed by their work load due to insufficient staff, teamwork decreases. The need to ensure adequate staffing is obvious, but this finding also points to the importance of increasing the efficiency of care delivery in an effort to utilize staff more effectively. The fact that larger size hospitals have lower teamwork calls for creation of smaller working units within the larger hospital (hospitals within hospitals). Acknowledgments The authors acknowledge Hyunhwa Lee for her assistance with data analysis, and Bernadette Carroll, Courtney Andruszekiewicz, Cindy Weintraub, Deborah Mueller, and Therese Smith for their roles in data collection. This project was funded by the Blue Cross and Blue Shield Foundation and the Michigan Center for Health Intervention, University of Michigan School of Nursing, National Institutes of Health, National Institute of Nursing Research (P30 NR009000). Clinical Resources Agency for Healthcare Research and Quality. Hospital nurse staffing and quality of care. nursestaff.htm American Nurses Association. Safe staffing saves lives: ANA s national campaign to solve the nurse staffing crisis. saveslives.org/ References Aiken, L. H., Clarke, S. P., Cheung, R. B., Sloane, D. M., & Silber, J. H. (2003). Educational levels of hospital nurses and surgical patient mortality. JAMA, 290(12), Amos, M. A., Hu, J., & Herrick, C. A. (2005).The impact of team building on communication and job satisfaction of nursing staff. Journal for Nurses in Staff Development, 21(1), Blegen, M. A., Vaughn, T., & Vojir, C. P. (2008). Nurse staffing levels: Impact of organizational characteristics and registered nurse supply. Health Services Research, 43(1p1), Brewer, B. B. (2006). Relationships among teams, culture, safety, and cost outcomes. Western Journal of Nursing Research, 28(6), Chang, W. Y., Ma, J. C., Chiu, H. T., Lin, K. C., Lee, P. H., Chang, W.-Y., et al. (2009). Job satisfaction and perceptions of quality of patient care, collaboration and teamwork in acute care hospitals. Journal of Advanced Nursing, 65(9), Clark, E., Squire, S., Heyme, A., Mickle, M. E., Petrie, E., Clark, E., et al. (2009). The PACT Project: Improving communication at handover. Medical Journal of Australia, 190(11 Suppl.), Collette, J. E. (2004). Retention of nursing staff A team-based approach. Australian Health Review, 28(3), El-Jardali, F., Jamal, D., Dimassi, H., Ammar, W., & Tchaghchaghian, V. (2008). The impact of hospital accreditation on quality of care: Perception of Lebanese nurses. International Journal of Quality Health Care, 20(5),

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