Copyright © eContent Management Pty Ltd. Contemporary Nurse (2014) 47(1–2): 7–15.
Unequal staffing: A snapshot of nurse staffing in critical care units in New South Wales, Australia
Thomas Harding*,+ and Michael Wright! *School of Nursing, Midwifery and Paramedicine, Australian Catholic University, North Sydney, NSW, Australia; +Buskerud University College, Kongsberg, Norway; !New South Wales Nurses and Midwives’ Association, Sydney, NSW, Australia
Abstract: A growing body of research provides evidence of the link between nurse-to-patient ratios (NTPRs) and skill mix with adverse patient outcomes. This paper reports an investigation into nurse staffing patterns, skill mix and patient movement in critical care units in NSW, Australia. A ‘snapshot’ of staffing patterns and patient movement over 1 week in October 2012 was obtained by use of a cross-sectional design using retrospective survey and administrative data. A wide variation was found in NTPRs, skill mix and the number of nursing staff vacancies in coronary care and high dependency units. These variations suggest that the quality of patient care may vary between facilities in New South Wales.
Keywords: nurse-to-patient ratios, skill mix, critical care, patient movement
O
ver the last decade concern has been raised in Australia about impending nurse shortages and the prospective magnitude of the problem (Armstrong, 2004; Health Workforce Australia, 2012). In addition to the potential for nurse shortages to compromise patient care, inadequate skill mix, i.e., the proportion of registered nurses (RNs), has also been identified as a significant factor which can result in adverse patient outcomes (Armstrong, 2009; Berry & Curry, 2012; Kane, Shamliyan, Mueller, Duval, & Wilt, 2007). Following on from seminal work by Needleman, Buerhaus, Mattke, Stewart, and Zelevinsky (2002), there have been a number of studies which have investigated a number of key patient outcomes known as ‘outcomes potentially sensitive to nursing’ (OPSN), i.e., adverse events that lead to increased length of stay in hospital (LOS) and in hospital mortality. Numerous studies – both national and international – now describe the significant link between nurse-to-patient ratios/ nursing hours per patient day (NHPPD) and patient outcomes (for example: Aiken, Clarke, Cheung, Sloane, & Silber, 2003; Aiken, Clarke, Sloane, Sochalski, & Silber, 2002; Dall, Chen, Sifert, Maddox, & Hogan, 2009; Duffield et al., 2011; Hinno, Partanen, & Vehviläinen-Julkunen, 2012; Twigg, Duffield, Bremner, Rapley, & Finn,
2010). The growing body of evidence, over the last 15 years, clearly demonstrates that inadequate nurse staffing leads to an increase in negative outcomes for patients, and ultimately a greater burden of cost to both the healthcare budget and society. Given such findings, it is not surprising that some professional nursing organisations have adopted the position that there is ‘safety in numbers’ and have campaigned for either mandated nurse-to-patient ratios (NTPRs) or NHPPD. In 2001, Australia was the first country to introduce legislation mandating NTPRs when Victorian nurses successfully mounted a campaign that lead to the introduction of a model of 5 nurses to every 20 patients in acute medical and surgical wards in public hospitals (Gerdtz & Nelson, 2007). In 2010, the New South Wales Nurses and Midwives Association (NSWNMA) commissioned research on nurse staffing in NSW Public Hospitals. This project conducted by the Workplace Research Centre (WRC), University of Sydney and the Centre for Health Services Management (CHSM), University of Technology, Sydney informed discussions with the NSW Department of Health which, in 2011, lead to nurses in New South Wales achieving legally enforceable award based NHPPD/ratios in surgical and medical wards, palliative care, rehabilitation and in patient mental health units.
Volume 47, Issue 1–2, April/June 2014
CN
7
CN
Thomas Harding and Michael Wright
Outside of Australia, to date, only the State of California in the United States of America (USA) has legislated for minimum NTPRs. Although, the legislation to establish minimum NTPRs in acute care hospitals in California was passed in 1999, it was not implemented until 2004 (Tevington, 2011). Although, by 2010 there were 24 states in the USA actively considering staffing legislation, as yet no other state has introduced mandated nurse staffing levels (Brogan, 2012; Douglas, 2010). Nurses in two other countries, South Korea and the United Kingdom (UK), are now actively campaigning for legislated NTPRs. A ratios bill was introduced into the Korean Legislature in 2012, but passage of the bill has been delayed owing to the presidential elections in November 2012 (Brogan). In the UK, the Royal College of Nursing (RCN) and UNISON – the UK’s largest public-sector union – will be pursing mandated NTPRs in response to both the mounting research evidence and to the findings from the survey of nurses undertaken to provide a snapshot of ratios in the UK (RCN, 2012; UNISON, 2102). In 2012 the NSWNMA undertook research to gather a snapshot of current NTPRs in those areas not covered by the 2011 award. The work which follows reports on one aspect of this study, and describes the findings related to establishing: 1. The current NTPR, RN vacancy rate and skill mix in ‘critical care’ units; and 2. The patient movement in and out of these wards and units. The category ‘critical care’ in this study includes: intensive care (ICU), coronary care (CCU), high dependency (HDU), paediatric intensive care (PICU) and neonatal intensive care (NICU). Methods The study was a cross-sectional design that used retrospective survey and administrative data. Using a similar methodology to the previous work commissioned by the NSWNMA (Workplace Research Centre, School of Business, University of Sydney & Centre for Health Services Management, University of Technology, 8
CN
Sydney, 2010) a new tool was developed to collect information on: (1) the number of beds; (2) the current nursing establishment (RN, Enrolled Nurse [EN] and Assistant in Nursing [AIN]); (3) the actual staffing at 0300, 0900 and 2000 for each of the three census dates; (4) the midnight patient census and patients admitted and discharged over the 24-hour period for each of the three census dates; and (5) the number of patients in the ward/unit at 0300, 0900 and 2000 for each of the census dates. Retrospective data collection took place during a 2-week period in early November, 2012 for 3 days (Monday, Thursday and Saturday) of 1 week in the previous month. Data was collected either in face-to-face interviews with the Nurse Unit Managers (NUMs), or their delegates, or by telephone. Each NUM was sent an email pre-survey outlining the information that would be requested. No data was collected pertaining to patient demographics or reason for admission. Permission was granted by the Director General of NSW Health to collect retrospective statistical data for three historical census days of patient numbers and staffing levels. As this study was negligible risk research involving the use of existing data, which did not identify information about individual people no further level of ethical clearance was deemed necessary (National Health and Medical Research Council, 2007). Sample From a possible total of 63 units within the category ‘critical care’ in NSW, 60 were included in the final analysis. Useable data was collected from only one of the three PICU in NSW, so this was excluded from the analysis as no comparison between PICUs was possible. The composition of the sample by unit/ward type is presented in Table 1. Table 1: Composition of sample by unit type (N = 60) Ward/unit type
ICU
CCU
NICU
Number
31
15
7
Volume 47, Issue 1–2, April/June 2014
HDU Total critical care 7
60
© eContent Management Pty Ltd
Unequal staffing: A snapshot of nurse staffing in critical care units Geographically, the sample of critical care units was equally spread between metropolitan and regional health care facilities. The ‘metropolitan’ category included hospitals in Sydney, Wollongong and Newcastle. The sample was also collected and subdivided by the three broad categories of Hospital Peer Groupings (A, B and C). Peer Group A hospitals are principal referral and specialist w omen’s and children’s hospitals. Peer Group B hospitals are large hospitals, either major city acute hospitals with >10,000 acute casemix-adjusted separations per annum, or regional acute hospitals or remote hospitals treating >8000 or >5000 acute casemix-adjusted separations per annum respectively. Peer Group C consists of medium sized acute hospitals in regional and major city areas, which treat between 5000 and 10,000 acute casemix-adjusted separations per annum. The critical care sample consisted of 25, 36 and 9 units from Peer Group A, B and C respectively. Six of the critical care units in the sample were ‘multipurpose.’ This is a result of critical care units in smaller hospitals often providing various combinations of adult intensive care, CCU, paediatric and HDU beds. For the purpose of this study they have been included in the ICU category, as they are designated as such by the NSW Department of Health. Data analysis The data related to clinical staff numbers (RN, EN and AIN) were collected in full time equivalent (FTE) numbers whereas the patient data were collected by head count. The data were entered into a computerised database (FileMaker Pro 12.0v4™, FileMaker Inc., Santa Clara, CA, USA) and then summarised by the calculation of means and ranges to describe: (1) the NTPR and (2) the RN vacancy rate as a proportion of the nursing establishment; i.e., the total number of positions available both filled and unfilled. In addition calculation of the skill mix – the proportion of RNs providing patient care – was undertaken for unit, and summarised by type of critical care unit. Where
© eContent Management Pty Ltd
Skill mix (% RN) =
CN
RN FTE total nursing staff FTE
As well, the data collected allowed calculation of patient movement, using the formula Patient movement Patients at midnight + patients admitted = patients at midnight Results Table 2 presents the NTPRs. It can be seen that for each of the different types of critical care unit, the mean NTPR ratio across the different time periods (0300, 0900, 2000) was generally consistent, with little difference between NTPRs throughout the day. The CCU group had the greatest difference in mean NTPRs, but even this was only a relatively modest difference between a NTPR of 2.8 and 2.3 at 0300 and 0900 hours, respectively. The range of NTPR within each category and shift, however, was marked: With a wide variation in NTPR found in NICUs and CCUs. The lowest mean NTPR value was found at 2000 hours in ICU, and the highest mean value was seen at 0300 hours in CCU. With respect to the mean RN skill mix, for all types of units within this category, RNs comprised more than 90% of the total nursing skill mix. There was, however, considerable variation within and between the different types of critical Table 2: Critical care nurse–patient ratios by shift (N = 60) Mean NTPR per shift
ICU Range CCU Range NICU Range HDU Range
0300
0900
2000
1.3 0.9–2.3 2.8 1.2–4.7 2.3 1.5–4.0 1.6 0.3–2.7
1.3 0.3–2.6 2.3 0.8–3.1 2.0 0.9–4.2 1.5 0.3–2.3
1.3 0.9–2.0 2.4 0.8–4.0 2.1 1.1–4.1 1.5 0.3–2.6
Volume 47, Issue 1–2, April/June 2014
Overall mean
CN
1.3 2.5 2.1 1.5
9
CN
Thomas Harding and Michael Wright
care units. From Table 3, it can be seen that the smallest range of RN skill mix as a percentage of the total nursing workforce was found in ICU (94–100%). The greatest range was found in HDU (63–100%) with a wide variation in RN skill mix also found in the CCUs (75–100%). The mean percentage of RN positions that are currently unfilled as proportion of the total nursing establishment lies in a narrow band of approximately 5–8%. It can be seen from Table 3, however, that there is a HDU and a CCU at the extreme end of the range with vacancy rates of 29 and 45% respectively. Table 4 presents the range and average figures of patient movement across the three sample days in the critical care units. Patient movement ranged from one patient per unit bed per day across all the categories of critical care to 2.25 in one HDU. Discussion This study set out to provide a snapshot of staffing patterns and patient movement in NSW critical care units across shifts for 3 days in 1 week in late 2012. The results reveal considerable variation in the NTPRs, skill mix and patient turnover. Nurse-to-patient ratios According to Pilcher et al. (2001) a 1:1 NTPR has been the gold standard in intensive care since Table 3: RN skill mix and vacancies in NSW critical care units
Skill mix Range (%) Average (%) RN vacancies Range (%) Average (%)
ICU
NICU
CCU
94–100 99.5
93–100 97
0–14 6.3
3–10 4.7
HDU
75–100 63–100 95 94 0–45 4.0
0–29 7.7
Table 4: Patient movement in NSW critical units Range Average
10
CN
ICU
NICU
1.0–2.12 1.29
1.0–1.32 1.08
CCU
HDU
1.0–1.47 1.08–2.25 1.32 1.58
the British Medical Association first advocated it in 1967 and this is the standard recommended by the Australian Health Workforce Advisory Committee (AHWAC, 2002), and the Australian College of Critical Care Nurses (ACCN, 2001). Therefore it was not unexpected to find that the mean NTPR in ICU across all shifts of 1:1.3 was close to the recommended ratio. The fact that this was slightly higher than the recommended ratio can be explained by the fact that the sample was not filtered by the level of ICU. Three levels of intensive care exist in Australia (AHWAC, 2002) and only Level 3 ICUs are required to provide a minimum of 1:1 for ventilated and other critically ill patients. In Level 2 units some patients may require less that 1:1 nursing. The lowest NTPR of 0.3 was found at 0900. This low NTPR could be a reflection of several factors: (1) staffing in a Level 3 ICU, where it is recommended that enough nurses should be available for >1:1 nursing for patients requiring complex management (AHWAC, 2002); (2) staffing models based on ‘open’ bed numbers rather than occupancy and acuity; and (3) the census having occurred during a particularly quiet period with respect to patient admissions. In HDUs the overall mean NTPR was 1.5, and the range was 0.3–2.5, which is consistent with the recommendations in both Australia and New Zealand. The ACCN (2001) position statement was that HDU patients require a standard NTPR of at least 1:2. In New Zealand, the same standard is suggested for HDU patients, with the recommendation that this ratio needs to be lower at times (Morley, 2005). The ACCN (2001) position statement does not specifically refer to CCU; however, the New Zealand guidelines for acute CCU patients recommend a standard NTPR of 1:2, with the flexibility to lower this in response to patient need (Morley, 2005). In this study, the average NTPR in CCU across the 3 days was 2.5; however, from the range of NTPR presented in Table 2 it is evident that there are units with higher NTPRs, with one recording a NTPR of 4.7 overnight. There are few studies which specifically investigate the impact of nurse staffing on patient outcomes in CCU; however, a study conducted in
Volume 47, Issue 1–2, April/June 2014
© eContent Management Pty Ltd
Unequal staffing: A snapshot of nurse staffing in critical care units one unit in India determined that a NTPR of 1:2 was required during the day, with a NTPR of 1:3 during the night (Deepti Sharma & Sharma, 2010). The authors of that study did not specify why a lower ratio is required at night, it might be inferred that this relates to the division of day versus night-time nursing activity. While patient acuity will not be less at night, activities such as patient hygiene care, counselling and education, relative education and support, and invasive diagnostic procedures are less likely to be undertaken. Merkouris et al. (2003) put forward a case for a low NTPR in CCU. In their study of Greek CCUs, they observed that the specific needs of patients with cardiac disease means that the nurse may be intensely involved in the technical management of life sustaining devices and titration of IV medications within narrow therapeutic levels. Therefore, a lower NTPR is required with the employment of highly skilled nurses who can operate with a high degree of autonomy. They found that poorer patient outcomes were found in units with low staffing levels and a high rate of substitution of RNs with less skilled personnel. Rothschild, Bates, Franz, Soukup, and Kaushal (2009) noted that the level of experience of nursing staff is often lower during the after hours’ shifts, i.e., weekends and evenings/nights. In their study of two CCU in the US, those were the shifts with the highest NTPRs and also were the shifts which were more likely to use pool or agency staff. They also suggest that less experienced staff, agency nurses or those drawn from the nursing pool may be less effective in preventing adverse events. Similarly, it was found by Pham et al. (2011), in the emergency department context, that medication errors associated with temporary or agency staff were more harmful than those associated with permanent staff. With respect to staffing in NICU, the RCN (2003) and the British Association of Perinatal Medicine (BAPM, 2010), hold the position that the appropriate NTPR is 1:1. The BAPM also contend that at times the neonate may be so unwell as to require a ratio of care >1:1. A study undertaken in two NSW NICUs (Spence et al., 2006) over a 5-month period found that there was a shortfall of the nurses required, which lead to:
© eContent Management Pty Ltd
CN
This shortfall being taken up by clinical educators, managers or sometimes by the use of relief staff. The effect on the patient care can mean that things do not get done, for example components of care such as comfort, support and teaching patients. (p. 232)
Given that this study has found an average NTPR of 2.1 in the seven NICUs included in the study and that for all shifts the range of NTPRs went as high as four, it would appear that there has been no improvement in NTPRs since the study undertaken by Spence et al. (2006). Further research is required to investigate the impact of the current NTPR on patient outcomes. It is suggested in the literature that inadequate staffing leads to poorer outcomes for infants in intensive care. For example, a population-based comparative study, between Australia and the UK, of NICU found that there was lower adjusted neonatal mortality in Australia (International Neonatal Network, Scottish Neonatal Consultants, Nurses Collaborative Study Group, 2000). Several factors were put forward by the authors to account for the difference; one of which was the recommendations for nurse:infant ratios for ventilated patients (1:1 in Australia compared to 1:2 in the UK at that time). The present study did not specifically investigate the ratio of nurse to ventilated patient, but if the 1:1 ratio found in the earlier study is being maintained then it can be inferred that the NTPR for non-ventilated patients is likely higher than the average of 2.1 found in NICUs. Skill mix In addition to the nursing intensity, i.e., NTPR, the experience of the nurses is important to patient safety and the prevention of adverse events. As noted by Rothschild et al. (2009): Characteristics of experienced nurses that increased the likelihood of recovering near misses included confidence, assertiveness, patient advocacy skills, surveillance skills, strong critical thinking skills, and a strong knowledge base. (Rothschild et al., 2009, p. 471.e5)
It is arguable that the competencies they describe are those more likely to be exhibited by RNs as a consequence of their educational preparation for entry into the profession through the
Volume 47, Issue 1–2, April/June 2014
CN
11
CN
Thomas Harding and Michael Wright
attainment of a bachelor’s degree in nursing. Since 1994, RN education in Australia is undertaken in the higher education sector (Grealish & Smale, 2011). A key component of such nursing education is the development of critical thinking and the identification of complex clinical phenomena (Simpson & Courtney, 2002). In line with the proposition but forward by Rothschild et al. (2009) with respect to the importance of nursing experience, a number of studies have found that increased RN staff as a proportion of the nursing hours is associated with better patient outcomes (for example: Aiken et al., 2002, 2003; Blegen, Goode, Spetz, Vaughn, & Park, 2011; Duffield et al., 2011). The study c onducted by Duffield et al. (2011) used data from 80 wards in 19 NSW hospitals and found that increasing the RN skill mix was associated with decreased rates of a number of OPSN, including decubitus ulcers, pneumonia, gastrointestinal bleeding, sepsis, shock, and physiological/metabolic derangement. The highest mean RN skill mix found in this study was in the (99.5%), with a narrow range of 94–100%. In contrast, the average RN skill mix in the CCUs in this study was 95%, however, with a broader range of 75–100% across the 15 units in the sample it can be inferred that nursing expertise for this complex group of patients is inconsistent and that some units may be providing a better level of care through employment of a higher proportion of RNs. The RN skill mix in the HDUs was lower, with an average of 94% and a skill mix of 63% was observed in one unit. Once again, it could be inferred from these results that the level of nursing expertise, care provided and patient outcomes might vary across the HDUs in NSW. The average RN skill mix in NICU was 97%, with a range of 93–100%. This suggests that even though absolute staffing may be inadequate in some cases that the workforce consists, for the most part, of RNs. What this study has not determined is the numbers of neonatal nurses who have specialist neonatal qualifications. A longer period of neonatal nurse training (12 months in Australia versus 6 months in the UK) was another factor posited by the International Neonatal Network et al. (2000) for the better outcomes for Australian infants. A more recent study 12
CN
conducted in 54 UK NICUs described an inverse relationship between survival in neonatal care for very low birth weight or preterm infants and the proportion of nurses with neonatal qualifications per shift (Hamilton, Redshaw, & Tarnow-Mordi, 2007). They found that increasing the ratio of nurses with neonatal qualifications in intensive care and HDU to 1:1 was associated with a 48% decrease in risk-adjusted mortality. RN vacancies The AHWAC (2002) reported that in 1999– 2000 the RN vacancy rate in ICU was 8.48%, so the average RN vacancy rates of 4.7–7.7% found in this study would imply that there has been some – albeit relatively slight – improvement in terms of recruitment and retention. The AHWAC reported that the gap in the intensive care workforce was not just a result of the overall shortage of nurses, but also reflected the ‘disenchantment of nurses in the permanent workforce with working conditions’ (p. 67). The range of RN vacancies found in this study, with 29 and 45% found at the extreme end of the range in HDU and CCU, respectively suggests that there are units where issues of recruitment and retention need to be addressed. In units with such high vacancy rates there is likely to be heavy reliance on agency, casual RNs and permanent staff working overtime to meet normal staffing requirements, not just in times of peak demand for beds or high patient acuity. As noted earlier pool or agency staff may be less effective in preventing adverse events (Rothschild et al., 2009); as well, there is evidence that nurse overtime is positively linked to adverse patient outcomes. A study of 1358 nurses in Taiwan (Liu, Lee, Chia, Chi, & Yin, 2012) found a positive association between nurses’ overtime and a variety of nurse-sensitive patient outcomes including patient falls, medication errors, hospital-acquired pneumonia, hospital-acquired urinary tract infections and unplanned extubations. Stone et al. (2007) examined working conditions on patient safety outcomes in 51 US adult intensive care units and found increased overtime was associated with higher rates of catheter-associated urinary tract infections and decubitus ulcers. Extended
Volume 47, Issue 1–2, April/June 2014
© eContent Management Pty Ltd
Unequal staffing: A snapshot of nurse staffing in critical care units shifts are also positively associated with patient dissatisfaction and nurse burnout (Stimpfel, Sloane, & Aitken, 2012); as the authors of this study note it is also linked to nurse dissatisfaction and intent to leave the profession. Patient movement According to Unruh and Fottler (2006) NTPRs alone are inadequate to describe nurses’ workloads; there must also be consideration of the movement of patients in and out of the healthcare facility. Also known as ‘churn,’ patient movement is a significant interruption to patient care and places additional demands on nurses’ workloads (Duffield, Diers, Aisbett, & Roche, 2009). For example, according to Joyce, Kielbaso, Lincks, Reuf, and Sizemore (2005) it can take, on average, 1 hour to admit a noncomplex patient and 2 hours or more for complex patients. A study of patient movement undertaken in 80 nursing wards in 27 NSW hospitals for the period 2005–2006 (Duffield et al., 2009) showed that ‘the number of patients flowing through the nursing wards was, on average, 1.25 the number of beds per day’ (p. 189). In the present study, the only area to have lower average patient movement than that found by Duffield et al., was NICU (1.08), however, given that Duffield and colleagues did not include the critical care areas in their study comparison of their results with those found in this study is not meaningful. However, apart from HDU it might have been expected to find lower patient turnover in the critical care environment given that this is the patient group who are most seriously ill and it might be expected that their mean LOS would be longer than that of a patient admitted for routine investigations or procedures. Another factor to be considered in the context of patient movement in and out of critical care is that of movement to and from procedures and diagnostics. As noted by Hendrich and Lee (2005) this compromises hospital resources as each patient transport adds to the workload index of both direct and indirect caregivers. Limitations It is acknowledged that the results could be influenced by problems inherent in the use of
© eContent Management Pty Ltd
CN
administrative databases, such as inadequate reporting and questions of data integrity. Additionally, the data with respect to staffing was also potentially subject to bias due to recall bias, as this relied on records kept on the wards/ units being accurate. The patient dataset is limited in that it was purely census data and did not account for other factors which are significant in the relationship between NTPRs and workload, such as patient diagnosis and acuity. As this study is a ‘snapshot’ of nurse staffing over 1 week in NSW it is possible that the findings here are not reflective of normal patient movement patterns and staffing. A longitudinal study would be required to account for factors that might influence staffing and patient m ovement, such as seasonal variations. Interestingly, a number of the NUMs commented that it was an ‘unusually quiet week’ that had been selected for the census. Conclusion The results presented in this study reveal considerable variation in staffing patterns, NTPRs and patient movement in critical care units in NSW. In particular, there was a wide range of NTPRs found in NICUs and CCUs. The CCUs, along with HDUs, are also an area of a wide range of skill mix and staff vacancies. While the employment of agency staff and the requirement for staff to work overtime was not investigated it can be assumed that this is most likely occurring in those wards/units where there are large numbers of staffing vacancies. There is evidence which links such staffing patterns to poorer patient outcomes. Given the plethora of research evidence which demonstrates the association between NTPRs and skill mix on patient outcomes it can be inferred from the results presented here that that is likely a wide variation in the quality of patient care in critical care units throughout NSW. What this study has not explored has been the extent to which the variation observed also reflects a differential in service provision between those critical care units based in large metropolitan areas and those in regional and rural centres. It is possible that the variation also reflects a metropolitan/
Volume 47, Issue 1–2, April/June 2014
CN
13
CN
Thomas Harding and Michael Wright
regional split and possible inequities in h ealthcare provision. This needs further investigation, but even so the findings of the present study must be of concern to health administrators and policy makers and require addressing. Insufficient staffing and inadequate skill mix are potentially compromising nurses ability to maintain the safety of those in their care, and to provide a level of care that is likely to satisfy either the nurses who provide the care or the patients who are the recipients of the care. 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: The Journal of the American Medical Association, 290(13), 1617–1623. Aiken, L. H., Clarke, S. P., Sloane, D. M., Sochalski, J., & Silber, J. H. (2002). Hospital nurse staffing and patient mortality, nurse burnout, and job dissatisfaction. JAMA: The Journal of the American Medical Association, 288(16), 1987–1993. Armstrong, F. (2004). Can you hear us? There’s a nursing shortage. Australian Nursing Journal, 12, 21–24. Armstrong, F. (2009). Ensuring quality, safety and positive patient outcomes: Why investing in nursing makes $ense. Melbourne, VIC: Australian Nursing Federation. Retrieved from http://anf.org.au/documents/reports/ Issues_Ensuring_quality.pdf Australian College of Critical Care Nurses. (2001). Position statement on intensive care nursing staffing. Australian Critical Care, 14(2), 48–49. Australian Health Workforce Advisory Committee. (2002). The critical care nurse workforce in Australia (AHWACC Report 20002.1). Retrieved from http:// www.ahwo.gov.au/documents/Publications/2002/ The%20 critical%20care%20nurse%20workforce%20in%20Australia.pdf Berry, L., & Curry, P. (2012). Nursing workload and patient care: Understanding the value of nurses, the effects of excessive workload, and how nurse-patient ratios and dynamic staffing models can help. Ottawa, ON: The Canadian Federation of Nurses Unions. Blegen, M. A., Goode, C. J., Spetz, J., Vaughn, T., & Park, S. H. (2011). Nurse staffing effects on patient outcomes. Safety-net and non-safety-net hospitals. Medical Care, 49(4), 406–414. British Association of Perinatal Medicine. (2010). Service standards for hospitals providing neonatal care (3rd ed.). London, England: Author.
14
CN
Brogan, G. (2012, November). Safety in numbers. National Nurse, pp. 10–21. Retrieved from http:// nurses.3cdn.net/a70aeebe6eccdff4bb_1rm6vtx0w.pdf Dall, T. M., Chen, Y. J., Sifert, R. F., Maddox, P. J., & Hogan, P. F. (2009). The economic value of nursing. Medical Care, 47(1), 97–104. Deepti Sharma, S., & Sharma, Y. P. (2010). An exploratory study on ‘nursing manpower’ requirements for coronary care unit of PGIMER, Chandigarh. Nursing and Midwifery Research Journal, 6(1), 14–23. Douglas, K. (2010). Ratios – If it were only that easy. Nursing Economic$, 28(2), 119–125. Duffield, C., Diers, D., Aisbett, C., & Roche, M. (2009). Churn: Patient turnover and case mix. Nursing Economic$, 27(3), 185–191. Duffield, C., Diers, D., O’Brien-Pallas, L., Aisbett, C., Roche, M., King, M., & Aisbett, K. (2011). Nursing staffing, nursing workload, the work environment and patient outcomes. Applied Nursing Research, 24, 244–255. Gerdtz, M. F., & Nelson, S. (2007). 5–20: A model of minimum nurse-to-patient ratios in Victoria, Australia. Journal of Nursing Management, 15(1), 64–71. Grealish, L., & Smale, L. A. (2011). Theory before practice: Implicit assumptions about clinical nursing education in Australia as revealed through a shared critical reflection. Contemporary Nurse, 39(1), 51–64. doi: 10.5172/conu.2011.39.1.51 Hamilton, K. E. S., Redshaw, M. E., & Tarnow-Mordi, W. (2007). Nurse staffing in relation to risk-adjusted mortality in neonatal care. Archives of Disease in Childhood. Fetal and Neonatal Edition, 92, F99–F103. doi:110.1136/adc.2006.102988 Health Workforce Australia. (2012). Health workforce 2025 – Doctors, nurses and midwives. Adelaide, SA: Author. Hendrich, A. L., & Lee, N. (2005). Intra-unit patient transports: Time, motion, and cost impact of hospital efficiency. Nursing Economic$, 23(4), 157–164. Hinno, S., Partanen, P., & Vehviläinen-Julkunen, K. (2012). Nursing activities, nurse staffing and adverse patient outcomes as perceived by hospital nurses. Journal of Clinical Nursing, 21(11–12), 1584–1593. International Neonatal Network, Scottish Neonatal Consultants, & Nurses Collaborative Study Group. (2000). Risk adjusted population based studies of the outcome for high risk infants in Scotland and Australia. Archives of Disease in Childhood. Fetal and Neonatal Edition, 82, F118–F123. Joyce, C., Kielbaso, M., Lincks, J., Reuf, D., & Sizemore, C. (2005). Discharge teams keep things moving. Nursing Management, 36(11), 36–39.
Volume 47, Issue 1–2, April/June 2014
© eContent Management Pty Ltd
Unequal staffing: A snapshot of nurse staffing in critical care units Kane, R. L., Shamliyan, T. A., Mueller, C., Duval, S., & Wilt, T. J. (2007). The association of registered nurse staffing levels and patient outcomes: Systematic review and meta-analysis. Medical Care, 45, 1195–1204. Liu, L. F., Lee, S., Chia, P. F., Chi, S. C., & Yin, Y. C. (2012). Exploring the association between nurse workload and nurse-sensitive patient safety outcome indicators. The Journal of Nursing Research, 20(4), 300–309. doi:10.1097/jnr.0b013e3182736363 Merkouris, A., Papathanassoglou, E. D. E., Pistolas, D., Papagiannaki, V., Floros, J., & Lemonidou, C. (2003). Staffing and organisation of nursing care in cardiac intensive care units in Greece. European Journal of Cardiovascular Nursing, 2, 123–129. Morley, A. (2005). Minimum guidelines for intensive care nurse staffing in New Zealand. Wellington, New Zealand: New Zealand Nurses’ Organisation. National Health and Medical Research Council, & Australian Research Council and Australian Research Council. (2007). National statement on ethical conduct in human research. Canberra, ACT: Australian Government. Needleman, J., Buerhaus, P., Mattke, S., Stewart, M., & Zelevinsky, K. (2002). Nurse-staffing levels and the quality of care in hospitals. New England Journal of Medicine, 346(22), 1715–1722. Pham, J. C., Andrawis, M., Shore, A. D., Fahey, M., Morlock, L., & Pronovost, P. J. (2011). Are temporary staff associated with more severe emergency department errors? Journal for Healthcare Quality, 33(4), 9–18. Pilcher, T., Odell, M., Bray, K., Clarke, S., Gardner, J., Orr, R., & Stirton, H. (2001). Nurse-patient ratios in critical care. Nursing in Critical Care, 6(2), 59–63. Rothschild, J. M., Bates, D. W., Franz, C., Soukup, J. R., & Kaushal, R. (2009). The costs and savings associated with prevention of adverse events by critical care nurses. Journal of Critical Care, 24, 471.e1– 471.e7. doi:10.1016/j/jere.2007.12.021 Royal College of Nursing. (2003). Defining staffing levels for children’s and young people’s services. London, England: Author. Royal College of Nursing. (2012). Mandatory nurse staffing levels. Policy Briefing 03/12. London, England: Author. Retrieved from http://www.rcn.org.uk/__data/assets/
CN
pdf_file/0009/439578/03.12_Mandatory_nurse_staffing_levels_v2_FINAL.pdf Simpson, E., & Courtney, M. (2002). Critical thinking in nursing education: Literature review. International Journal of Nursing Practice, 8, 89–98. Spence, K., Tarnow-Mordi, W., Duncan, G., Jayasuryia, N., Elliott, J., King, J., & Kite, F. (2006). Measuring workload in neonatal intensive care. Journal of Nursing Management, 14, 227–234. Stimpfel, A. W., Sloane, D. M., & Aitken, L. H. (2012). The longer the shifts for hospital nurses, the higher the levels of burnout and patient dissatisfaction. Health Affairs, 3(2), 2501–2509. doi:http:dx. org/10.13 77/hlthadd.2011.1377 Stone, P. W., Mooney-Kane, C., Larson, E. L., Horan, T. S., Glance, L. G., Zwanziger, J., & Dick, A. W. (2007). Nursing working conditions and patient safety outcomes. Medical Care, 45(6), 571–578. doi:10.1097/MLR.0b013e3180393667 Tevington, P. (2011). Mandatory nurse-patient ratios. Medsurg Nursing, 20(5), 265–268. Twigg, D., Duffield, C., Bremner, A., Rapley, P., & Finn, J. (2010). The impact of the nursing hours per patient day (NHPPD) staffing method on patient outcomes: A retrospective analysis of patient and staffing data. International Journal of Nursing Studies, 48(5), 540–548. UNISON. (2012). Care in the balance: A UNISON survey into staff/patient ratios on our wards. Retrieved from http://www.unison.org. uk/acrobat/20727.pdf Unruh, L. Y., & Fottler, M. D. (2006). Patient turnover and nursing staff adequacy. Health Services Research, 41(2), 599–612. doi:10.1111/j.1475-6773.2005.00496.x Workplace Research Centre, School of Business, University of Sydney & Centre for Health Services Management, University of Technology, Sydney. (2010, August). Nurse staffing NSW public hospitals. Report for the NSW Nurses Association. Sydney, NSW: University of Sydney & University of Technology, Sydney. Received 06 June 2013
Accepted 18 December 2013
R E N E W N O W F O R J u ly 2 0 1 4 – J une 2 0 1 5 Contemporary Nurse will publish Volumes 48–50 from July 2014 – June 2015 with special issues on: Nursing Innovation and Reform in Health Care Advances in Chronic Care, Ageing and Palliation Nursing Advances in Contemporary Nurse Education (3rd edn) Please ensure that your subscription has been renewed to retain access to Contemporary Nurse (ISSN 1037–6178) in print and online www.e-contentmanagement.com
© eContent Management Pty Ltd
Volume 47, Issue 1–2, April/June 2014
CN
15
Copyright of Contemporary Nurse: A Journal for the Australian Nursing Profession is the property of eContent Management Pty. Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.
Unequal staffing: A snapshot of nurse staffing in critical care units in New South Wales, Australia
Thomas Harding*,+ and Michael Wright! *School of Nursing, Midwifery and Paramedicine, Australian Catholic University, North Sydney, NSW, Australia; +Buskerud University College, Kongsberg, Norway; !New South Wales Nurses and Midwives’ Association, Sydney, NSW, Australia
Abstract: A growing body of research provides evidence of the link between nurse-to-patient ratios (NTPRs) and skill mix with adverse patient outcomes. This paper reports an investigation into nurse staffing patterns, skill mix and patient movement in critical care units in NSW, Australia. A ‘snapshot’ of staffing patterns and patient movement over 1 week in October 2012 was obtained by use of a cross-sectional design using retrospective survey and administrative data. A wide variation was found in NTPRs, skill mix and the number of nursing staff vacancies in coronary care and high dependency units. These variations suggest that the quality of patient care may vary between facilities in New South Wales.
Keywords: nurse-to-patient ratios, skill mix, critical care, patient movement
O
ver the last decade concern has been raised in Australia about impending nurse shortages and the prospective magnitude of the problem (Armstrong, 2004; Health Workforce Australia, 2012). In addition to the potential for nurse shortages to compromise patient care, inadequate skill mix, i.e., the proportion of registered nurses (RNs), has also been identified as a significant factor which can result in adverse patient outcomes (Armstrong, 2009; Berry & Curry, 2012; Kane, Shamliyan, Mueller, Duval, & Wilt, 2007). Following on from seminal work by Needleman, Buerhaus, Mattke, Stewart, and Zelevinsky (2002), there have been a number of studies which have investigated a number of key patient outcomes known as ‘outcomes potentially sensitive to nursing’ (OPSN), i.e., adverse events that lead to increased length of stay in hospital (LOS) and in hospital mortality. Numerous studies – both national and international – now describe the significant link between nurse-to-patient ratios/ nursing hours per patient day (NHPPD) and patient outcomes (for example: Aiken, Clarke, Cheung, Sloane, & Silber, 2003; Aiken, Clarke, Sloane, Sochalski, & Silber, 2002; Dall, Chen, Sifert, Maddox, & Hogan, 2009; Duffield et al., 2011; Hinno, Partanen, & Vehviläinen-Julkunen, 2012; Twigg, Duffield, Bremner, Rapley, & Finn,
2010). The growing body of evidence, over the last 15 years, clearly demonstrates that inadequate nurse staffing leads to an increase in negative outcomes for patients, and ultimately a greater burden of cost to both the healthcare budget and society. Given such findings, it is not surprising that some professional nursing organisations have adopted the position that there is ‘safety in numbers’ and have campaigned for either mandated nurse-to-patient ratios (NTPRs) or NHPPD. In 2001, Australia was the first country to introduce legislation mandating NTPRs when Victorian nurses successfully mounted a campaign that lead to the introduction of a model of 5 nurses to every 20 patients in acute medical and surgical wards in public hospitals (Gerdtz & Nelson, 2007). In 2010, the New South Wales Nurses and Midwives Association (NSWNMA) commissioned research on nurse staffing in NSW Public Hospitals. This project conducted by the Workplace Research Centre (WRC), University of Sydney and the Centre for Health Services Management (CHSM), University of Technology, Sydney informed discussions with the NSW Department of Health which, in 2011, lead to nurses in New South Wales achieving legally enforceable award based NHPPD/ratios in surgical and medical wards, palliative care, rehabilitation and in patient mental health units.
Volume 47, Issue 1–2, April/June 2014
CN
7
CN
Thomas Harding and Michael Wright
Outside of Australia, to date, only the State of California in the United States of America (USA) has legislated for minimum NTPRs. Although, the legislation to establish minimum NTPRs in acute care hospitals in California was passed in 1999, it was not implemented until 2004 (Tevington, 2011). Although, by 2010 there were 24 states in the USA actively considering staffing legislation, as yet no other state has introduced mandated nurse staffing levels (Brogan, 2012; Douglas, 2010). Nurses in two other countries, South Korea and the United Kingdom (UK), are now actively campaigning for legislated NTPRs. A ratios bill was introduced into the Korean Legislature in 2012, but passage of the bill has been delayed owing to the presidential elections in November 2012 (Brogan). In the UK, the Royal College of Nursing (RCN) and UNISON – the UK’s largest public-sector union – will be pursing mandated NTPRs in response to both the mounting research evidence and to the findings from the survey of nurses undertaken to provide a snapshot of ratios in the UK (RCN, 2012; UNISON, 2102). In 2012 the NSWNMA undertook research to gather a snapshot of current NTPRs in those areas not covered by the 2011 award. The work which follows reports on one aspect of this study, and describes the findings related to establishing: 1. The current NTPR, RN vacancy rate and skill mix in ‘critical care’ units; and 2. The patient movement in and out of these wards and units. The category ‘critical care’ in this study includes: intensive care (ICU), coronary care (CCU), high dependency (HDU), paediatric intensive care (PICU) and neonatal intensive care (NICU). Methods The study was a cross-sectional design that used retrospective survey and administrative data. Using a similar methodology to the previous work commissioned by the NSWNMA (Workplace Research Centre, School of Business, University of Sydney & Centre for Health Services Management, University of Technology, 8
CN
Sydney, 2010) a new tool was developed to collect information on: (1) the number of beds; (2) the current nursing establishment (RN, Enrolled Nurse [EN] and Assistant in Nursing [AIN]); (3) the actual staffing at 0300, 0900 and 2000 for each of the three census dates; (4) the midnight patient census and patients admitted and discharged over the 24-hour period for each of the three census dates; and (5) the number of patients in the ward/unit at 0300, 0900 and 2000 for each of the census dates. Retrospective data collection took place during a 2-week period in early November, 2012 for 3 days (Monday, Thursday and Saturday) of 1 week in the previous month. Data was collected either in face-to-face interviews with the Nurse Unit Managers (NUMs), or their delegates, or by telephone. Each NUM was sent an email pre-survey outlining the information that would be requested. No data was collected pertaining to patient demographics or reason for admission. Permission was granted by the Director General of NSW Health to collect retrospective statistical data for three historical census days of patient numbers and staffing levels. As this study was negligible risk research involving the use of existing data, which did not identify information about individual people no further level of ethical clearance was deemed necessary (National Health and Medical Research Council, 2007). Sample From a possible total of 63 units within the category ‘critical care’ in NSW, 60 were included in the final analysis. Useable data was collected from only one of the three PICU in NSW, so this was excluded from the analysis as no comparison between PICUs was possible. The composition of the sample by unit/ward type is presented in Table 1. Table 1: Composition of sample by unit type (N = 60) Ward/unit type
ICU
CCU
NICU
Number
31
15
7
Volume 47, Issue 1–2, April/June 2014
HDU Total critical care 7
60
© eContent Management Pty Ltd
Unequal staffing: A snapshot of nurse staffing in critical care units Geographically, the sample of critical care units was equally spread between metropolitan and regional health care facilities. The ‘metropolitan’ category included hospitals in Sydney, Wollongong and Newcastle. The sample was also collected and subdivided by the three broad categories of Hospital Peer Groupings (A, B and C). Peer Group A hospitals are principal referral and specialist w omen’s and children’s hospitals. Peer Group B hospitals are large hospitals, either major city acute hospitals with >10,000 acute casemix-adjusted separations per annum, or regional acute hospitals or remote hospitals treating >8000 or >5000 acute casemix-adjusted separations per annum respectively. Peer Group C consists of medium sized acute hospitals in regional and major city areas, which treat between 5000 and 10,000 acute casemix-adjusted separations per annum. The critical care sample consisted of 25, 36 and 9 units from Peer Group A, B and C respectively. Six of the critical care units in the sample were ‘multipurpose.’ This is a result of critical care units in smaller hospitals often providing various combinations of adult intensive care, CCU, paediatric and HDU beds. For the purpose of this study they have been included in the ICU category, as they are designated as such by the NSW Department of Health. Data analysis The data related to clinical staff numbers (RN, EN and AIN) were collected in full time equivalent (FTE) numbers whereas the patient data were collected by head count. The data were entered into a computerised database (FileMaker Pro 12.0v4™, FileMaker Inc., Santa Clara, CA, USA) and then summarised by the calculation of means and ranges to describe: (1) the NTPR and (2) the RN vacancy rate as a proportion of the nursing establishment; i.e., the total number of positions available both filled and unfilled. In addition calculation of the skill mix – the proportion of RNs providing patient care – was undertaken for unit, and summarised by type of critical care unit. Where
© eContent Management Pty Ltd
Skill mix (% RN) =
CN
RN FTE total nursing staff FTE
As well, the data collected allowed calculation of patient movement, using the formula Patient movement Patients at midnight + patients admitted = patients at midnight Results Table 2 presents the NTPRs. It can be seen that for each of the different types of critical care unit, the mean NTPR ratio across the different time periods (0300, 0900, 2000) was generally consistent, with little difference between NTPRs throughout the day. The CCU group had the greatest difference in mean NTPRs, but even this was only a relatively modest difference between a NTPR of 2.8 and 2.3 at 0300 and 0900 hours, respectively. The range of NTPR within each category and shift, however, was marked: With a wide variation in NTPR found in NICUs and CCUs. The lowest mean NTPR value was found at 2000 hours in ICU, and the highest mean value was seen at 0300 hours in CCU. With respect to the mean RN skill mix, for all types of units within this category, RNs comprised more than 90% of the total nursing skill mix. There was, however, considerable variation within and between the different types of critical Table 2: Critical care nurse–patient ratios by shift (N = 60) Mean NTPR per shift
ICU Range CCU Range NICU Range HDU Range
0300
0900
2000
1.3 0.9–2.3 2.8 1.2–4.7 2.3 1.5–4.0 1.6 0.3–2.7
1.3 0.3–2.6 2.3 0.8–3.1 2.0 0.9–4.2 1.5 0.3–2.3
1.3 0.9–2.0 2.4 0.8–4.0 2.1 1.1–4.1 1.5 0.3–2.6
Volume 47, Issue 1–2, April/June 2014
Overall mean
CN
1.3 2.5 2.1 1.5
9
CN
Thomas Harding and Michael Wright
care units. From Table 3, it can be seen that the smallest range of RN skill mix as a percentage of the total nursing workforce was found in ICU (94–100%). The greatest range was found in HDU (63–100%) with a wide variation in RN skill mix also found in the CCUs (75–100%). The mean percentage of RN positions that are currently unfilled as proportion of the total nursing establishment lies in a narrow band of approximately 5–8%. It can be seen from Table 3, however, that there is a HDU and a CCU at the extreme end of the range with vacancy rates of 29 and 45% respectively. Table 4 presents the range and average figures of patient movement across the three sample days in the critical care units. Patient movement ranged from one patient per unit bed per day across all the categories of critical care to 2.25 in one HDU. Discussion This study set out to provide a snapshot of staffing patterns and patient movement in NSW critical care units across shifts for 3 days in 1 week in late 2012. The results reveal considerable variation in the NTPRs, skill mix and patient turnover. Nurse-to-patient ratios According to Pilcher et al. (2001) a 1:1 NTPR has been the gold standard in intensive care since Table 3: RN skill mix and vacancies in NSW critical care units
Skill mix Range (%) Average (%) RN vacancies Range (%) Average (%)
ICU
NICU
CCU
94–100 99.5
93–100 97
0–14 6.3
3–10 4.7
HDU
75–100 63–100 95 94 0–45 4.0
0–29 7.7
Table 4: Patient movement in NSW critical units Range Average
10
CN
ICU
NICU
1.0–2.12 1.29
1.0–1.32 1.08
CCU
HDU
1.0–1.47 1.08–2.25 1.32 1.58
the British Medical Association first advocated it in 1967 and this is the standard recommended by the Australian Health Workforce Advisory Committee (AHWAC, 2002), and the Australian College of Critical Care Nurses (ACCN, 2001). Therefore it was not unexpected to find that the mean NTPR in ICU across all shifts of 1:1.3 was close to the recommended ratio. The fact that this was slightly higher than the recommended ratio can be explained by the fact that the sample was not filtered by the level of ICU. Three levels of intensive care exist in Australia (AHWAC, 2002) and only Level 3 ICUs are required to provide a minimum of 1:1 for ventilated and other critically ill patients. In Level 2 units some patients may require less that 1:1 nursing. The lowest NTPR of 0.3 was found at 0900. This low NTPR could be a reflection of several factors: (1) staffing in a Level 3 ICU, where it is recommended that enough nurses should be available for >1:1 nursing for patients requiring complex management (AHWAC, 2002); (2) staffing models based on ‘open’ bed numbers rather than occupancy and acuity; and (3) the census having occurred during a particularly quiet period with respect to patient admissions. In HDUs the overall mean NTPR was 1.5, and the range was 0.3–2.5, which is consistent with the recommendations in both Australia and New Zealand. The ACCN (2001) position statement was that HDU patients require a standard NTPR of at least 1:2. In New Zealand, the same standard is suggested for HDU patients, with the recommendation that this ratio needs to be lower at times (Morley, 2005). The ACCN (2001) position statement does not specifically refer to CCU; however, the New Zealand guidelines for acute CCU patients recommend a standard NTPR of 1:2, with the flexibility to lower this in response to patient need (Morley, 2005). In this study, the average NTPR in CCU across the 3 days was 2.5; however, from the range of NTPR presented in Table 2 it is evident that there are units with higher NTPRs, with one recording a NTPR of 4.7 overnight. There are few studies which specifically investigate the impact of nurse staffing on patient outcomes in CCU; however, a study conducted in
Volume 47, Issue 1–2, April/June 2014
© eContent Management Pty Ltd
Unequal staffing: A snapshot of nurse staffing in critical care units one unit in India determined that a NTPR of 1:2 was required during the day, with a NTPR of 1:3 during the night (Deepti Sharma & Sharma, 2010). The authors of that study did not specify why a lower ratio is required at night, it might be inferred that this relates to the division of day versus night-time nursing activity. While patient acuity will not be less at night, activities such as patient hygiene care, counselling and education, relative education and support, and invasive diagnostic procedures are less likely to be undertaken. Merkouris et al. (2003) put forward a case for a low NTPR in CCU. In their study of Greek CCUs, they observed that the specific needs of patients with cardiac disease means that the nurse may be intensely involved in the technical management of life sustaining devices and titration of IV medications within narrow therapeutic levels. Therefore, a lower NTPR is required with the employment of highly skilled nurses who can operate with a high degree of autonomy. They found that poorer patient outcomes were found in units with low staffing levels and a high rate of substitution of RNs with less skilled personnel. Rothschild, Bates, Franz, Soukup, and Kaushal (2009) noted that the level of experience of nursing staff is often lower during the after hours’ shifts, i.e., weekends and evenings/nights. In their study of two CCU in the US, those were the shifts with the highest NTPRs and also were the shifts which were more likely to use pool or agency staff. They also suggest that less experienced staff, agency nurses or those drawn from the nursing pool may be less effective in preventing adverse events. Similarly, it was found by Pham et al. (2011), in the emergency department context, that medication errors associated with temporary or agency staff were more harmful than those associated with permanent staff. With respect to staffing in NICU, the RCN (2003) and the British Association of Perinatal Medicine (BAPM, 2010), hold the position that the appropriate NTPR is 1:1. The BAPM also contend that at times the neonate may be so unwell as to require a ratio of care >1:1. A study undertaken in two NSW NICUs (Spence et al., 2006) over a 5-month period found that there was a shortfall of the nurses required, which lead to:
© eContent Management Pty Ltd
CN
This shortfall being taken up by clinical educators, managers or sometimes by the use of relief staff. The effect on the patient care can mean that things do not get done, for example components of care such as comfort, support and teaching patients. (p. 232)
Given that this study has found an average NTPR of 2.1 in the seven NICUs included in the study and that for all shifts the range of NTPRs went as high as four, it would appear that there has been no improvement in NTPRs since the study undertaken by Spence et al. (2006). Further research is required to investigate the impact of the current NTPR on patient outcomes. It is suggested in the literature that inadequate staffing leads to poorer outcomes for infants in intensive care. For example, a population-based comparative study, between Australia and the UK, of NICU found that there was lower adjusted neonatal mortality in Australia (International Neonatal Network, Scottish Neonatal Consultants, Nurses Collaborative Study Group, 2000). Several factors were put forward by the authors to account for the difference; one of which was the recommendations for nurse:infant ratios for ventilated patients (1:1 in Australia compared to 1:2 in the UK at that time). The present study did not specifically investigate the ratio of nurse to ventilated patient, but if the 1:1 ratio found in the earlier study is being maintained then it can be inferred that the NTPR for non-ventilated patients is likely higher than the average of 2.1 found in NICUs. Skill mix In addition to the nursing intensity, i.e., NTPR, the experience of the nurses is important to patient safety and the prevention of adverse events. As noted by Rothschild et al. (2009): Characteristics of experienced nurses that increased the likelihood of recovering near misses included confidence, assertiveness, patient advocacy skills, surveillance skills, strong critical thinking skills, and a strong knowledge base. (Rothschild et al., 2009, p. 471.e5)
It is arguable that the competencies they describe are those more likely to be exhibited by RNs as a consequence of their educational preparation for entry into the profession through the
Volume 47, Issue 1–2, April/June 2014
CN
11
CN
Thomas Harding and Michael Wright
attainment of a bachelor’s degree in nursing. Since 1994, RN education in Australia is undertaken in the higher education sector (Grealish & Smale, 2011). A key component of such nursing education is the development of critical thinking and the identification of complex clinical phenomena (Simpson & Courtney, 2002). In line with the proposition but forward by Rothschild et al. (2009) with respect to the importance of nursing experience, a number of studies have found that increased RN staff as a proportion of the nursing hours is associated with better patient outcomes (for example: Aiken et al., 2002, 2003; Blegen, Goode, Spetz, Vaughn, & Park, 2011; Duffield et al., 2011). The study c onducted by Duffield et al. (2011) used data from 80 wards in 19 NSW hospitals and found that increasing the RN skill mix was associated with decreased rates of a number of OPSN, including decubitus ulcers, pneumonia, gastrointestinal bleeding, sepsis, shock, and physiological/metabolic derangement. The highest mean RN skill mix found in this study was in the (99.5%), with a narrow range of 94–100%. In contrast, the average RN skill mix in the CCUs in this study was 95%, however, with a broader range of 75–100% across the 15 units in the sample it can be inferred that nursing expertise for this complex group of patients is inconsistent and that some units may be providing a better level of care through employment of a higher proportion of RNs. The RN skill mix in the HDUs was lower, with an average of 94% and a skill mix of 63% was observed in one unit. Once again, it could be inferred from these results that the level of nursing expertise, care provided and patient outcomes might vary across the HDUs in NSW. The average RN skill mix in NICU was 97%, with a range of 93–100%. This suggests that even though absolute staffing may be inadequate in some cases that the workforce consists, for the most part, of RNs. What this study has not determined is the numbers of neonatal nurses who have specialist neonatal qualifications. A longer period of neonatal nurse training (12 months in Australia versus 6 months in the UK) was another factor posited by the International Neonatal Network et al. (2000) for the better outcomes for Australian infants. A more recent study 12
CN
conducted in 54 UK NICUs described an inverse relationship between survival in neonatal care for very low birth weight or preterm infants and the proportion of nurses with neonatal qualifications per shift (Hamilton, Redshaw, & Tarnow-Mordi, 2007). They found that increasing the ratio of nurses with neonatal qualifications in intensive care and HDU to 1:1 was associated with a 48% decrease in risk-adjusted mortality. RN vacancies The AHWAC (2002) reported that in 1999– 2000 the RN vacancy rate in ICU was 8.48%, so the average RN vacancy rates of 4.7–7.7% found in this study would imply that there has been some – albeit relatively slight – improvement in terms of recruitment and retention. The AHWAC reported that the gap in the intensive care workforce was not just a result of the overall shortage of nurses, but also reflected the ‘disenchantment of nurses in the permanent workforce with working conditions’ (p. 67). The range of RN vacancies found in this study, with 29 and 45% found at the extreme end of the range in HDU and CCU, respectively suggests that there are units where issues of recruitment and retention need to be addressed. In units with such high vacancy rates there is likely to be heavy reliance on agency, casual RNs and permanent staff working overtime to meet normal staffing requirements, not just in times of peak demand for beds or high patient acuity. As noted earlier pool or agency staff may be less effective in preventing adverse events (Rothschild et al., 2009); as well, there is evidence that nurse overtime is positively linked to adverse patient outcomes. A study of 1358 nurses in Taiwan (Liu, Lee, Chia, Chi, & Yin, 2012) found a positive association between nurses’ overtime and a variety of nurse-sensitive patient outcomes including patient falls, medication errors, hospital-acquired pneumonia, hospital-acquired urinary tract infections and unplanned extubations. Stone et al. (2007) examined working conditions on patient safety outcomes in 51 US adult intensive care units and found increased overtime was associated with higher rates of catheter-associated urinary tract infections and decubitus ulcers. Extended
Volume 47, Issue 1–2, April/June 2014
© eContent Management Pty Ltd
Unequal staffing: A snapshot of nurse staffing in critical care units shifts are also positively associated with patient dissatisfaction and nurse burnout (Stimpfel, Sloane, & Aitken, 2012); as the authors of this study note it is also linked to nurse dissatisfaction and intent to leave the profession. Patient movement According to Unruh and Fottler (2006) NTPRs alone are inadequate to describe nurses’ workloads; there must also be consideration of the movement of patients in and out of the healthcare facility. Also known as ‘churn,’ patient movement is a significant interruption to patient care and places additional demands on nurses’ workloads (Duffield, Diers, Aisbett, & Roche, 2009). For example, according to Joyce, Kielbaso, Lincks, Reuf, and Sizemore (2005) it can take, on average, 1 hour to admit a noncomplex patient and 2 hours or more for complex patients. A study of patient movement undertaken in 80 nursing wards in 27 NSW hospitals for the period 2005–2006 (Duffield et al., 2009) showed that ‘the number of patients flowing through the nursing wards was, on average, 1.25 the number of beds per day’ (p. 189). In the present study, the only area to have lower average patient movement than that found by Duffield et al., was NICU (1.08), however, given that Duffield and colleagues did not include the critical care areas in their study comparison of their results with those found in this study is not meaningful. However, apart from HDU it might have been expected to find lower patient turnover in the critical care environment given that this is the patient group who are most seriously ill and it might be expected that their mean LOS would be longer than that of a patient admitted for routine investigations or procedures. Another factor to be considered in the context of patient movement in and out of critical care is that of movement to and from procedures and diagnostics. As noted by Hendrich and Lee (2005) this compromises hospital resources as each patient transport adds to the workload index of both direct and indirect caregivers. Limitations It is acknowledged that the results could be influenced by problems inherent in the use of
© eContent Management Pty Ltd
CN
administrative databases, such as inadequate reporting and questions of data integrity. Additionally, the data with respect to staffing was also potentially subject to bias due to recall bias, as this relied on records kept on the wards/ units being accurate. The patient dataset is limited in that it was purely census data and did not account for other factors which are significant in the relationship between NTPRs and workload, such as patient diagnosis and acuity. As this study is a ‘snapshot’ of nurse staffing over 1 week in NSW it is possible that the findings here are not reflective of normal patient movement patterns and staffing. A longitudinal study would be required to account for factors that might influence staffing and patient m ovement, such as seasonal variations. Interestingly, a number of the NUMs commented that it was an ‘unusually quiet week’ that had been selected for the census. Conclusion The results presented in this study reveal considerable variation in staffing patterns, NTPRs and patient movement in critical care units in NSW. In particular, there was a wide range of NTPRs found in NICUs and CCUs. The CCUs, along with HDUs, are also an area of a wide range of skill mix and staff vacancies. While the employment of agency staff and the requirement for staff to work overtime was not investigated it can be assumed that this is most likely occurring in those wards/units where there are large numbers of staffing vacancies. There is evidence which links such staffing patterns to poorer patient outcomes. Given the plethora of research evidence which demonstrates the association between NTPRs and skill mix on patient outcomes it can be inferred from the results presented here that that is likely a wide variation in the quality of patient care in critical care units throughout NSW. What this study has not explored has been the extent to which the variation observed also reflects a differential in service provision between those critical care units based in large metropolitan areas and those in regional and rural centres. It is possible that the variation also reflects a metropolitan/
Volume 47, Issue 1–2, April/June 2014
CN
13
CN
Thomas Harding and Michael Wright
regional split and possible inequities in h ealthcare provision. This needs further investigation, but even so the findings of the present study must be of concern to health administrators and policy makers and require addressing. Insufficient staffing and inadequate skill mix are potentially compromising nurses ability to maintain the safety of those in their care, and to provide a level of care that is likely to satisfy either the nurses who provide the care or the patients who are the recipients of the care. 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: The Journal of the American Medical Association, 290(13), 1617–1623. Aiken, L. H., Clarke, S. P., Sloane, D. M., Sochalski, J., & Silber, J. H. (2002). Hospital nurse staffing and patient mortality, nurse burnout, and job dissatisfaction. JAMA: The Journal of the American Medical Association, 288(16), 1987–1993. Armstrong, F. (2004). Can you hear us? There’s a nursing shortage. Australian Nursing Journal, 12, 21–24. Armstrong, F. (2009). Ensuring quality, safety and positive patient outcomes: Why investing in nursing makes $ense. Melbourne, VIC: Australian Nursing Federation. Retrieved from http://anf.org.au/documents/reports/ Issues_Ensuring_quality.pdf Australian College of Critical Care Nurses. (2001). Position statement on intensive care nursing staffing. Australian Critical Care, 14(2), 48–49. Australian Health Workforce Advisory Committee. (2002). The critical care nurse workforce in Australia (AHWACC Report 20002.1). Retrieved from http:// www.ahwo.gov.au/documents/Publications/2002/ The%20 critical%20care%20nurse%20workforce%20in%20Australia.pdf Berry, L., & Curry, P. (2012). Nursing workload and patient care: Understanding the value of nurses, the effects of excessive workload, and how nurse-patient ratios and dynamic staffing models can help. Ottawa, ON: The Canadian Federation of Nurses Unions. Blegen, M. A., Goode, C. J., Spetz, J., Vaughn, T., & Park, S. H. (2011). Nurse staffing effects on patient outcomes. Safety-net and non-safety-net hospitals. Medical Care, 49(4), 406–414. British Association of Perinatal Medicine. (2010). Service standards for hospitals providing neonatal care (3rd ed.). London, England: Author.
14
CN
Brogan, G. (2012, November). Safety in numbers. National Nurse, pp. 10–21. Retrieved from http:// nurses.3cdn.net/a70aeebe6eccdff4bb_1rm6vtx0w.pdf Dall, T. M., Chen, Y. J., Sifert, R. F., Maddox, P. J., & Hogan, P. F. (2009). The economic value of nursing. Medical Care, 47(1), 97–104. Deepti Sharma, S., & Sharma, Y. P. (2010). An exploratory study on ‘nursing manpower’ requirements for coronary care unit of PGIMER, Chandigarh. Nursing and Midwifery Research Journal, 6(1), 14–23. Douglas, K. (2010). Ratios – If it were only that easy. Nursing Economic$, 28(2), 119–125. Duffield, C., Diers, D., Aisbett, C., & Roche, M. (2009). Churn: Patient turnover and case mix. Nursing Economic$, 27(3), 185–191. Duffield, C., Diers, D., O’Brien-Pallas, L., Aisbett, C., Roche, M., King, M., & Aisbett, K. (2011). Nursing staffing, nursing workload, the work environment and patient outcomes. Applied Nursing Research, 24, 244–255. Gerdtz, M. F., & Nelson, S. (2007). 5–20: A model of minimum nurse-to-patient ratios in Victoria, Australia. Journal of Nursing Management, 15(1), 64–71. Grealish, L., & Smale, L. A. (2011). Theory before practice: Implicit assumptions about clinical nursing education in Australia as revealed through a shared critical reflection. Contemporary Nurse, 39(1), 51–64. doi: 10.5172/conu.2011.39.1.51 Hamilton, K. E. S., Redshaw, M. E., & Tarnow-Mordi, W. (2007). Nurse staffing in relation to risk-adjusted mortality in neonatal care. Archives of Disease in Childhood. Fetal and Neonatal Edition, 92, F99–F103. doi:110.1136/adc.2006.102988 Health Workforce Australia. (2012). Health workforce 2025 – Doctors, nurses and midwives. Adelaide, SA: Author. Hendrich, A. L., & Lee, N. (2005). Intra-unit patient transports: Time, motion, and cost impact of hospital efficiency. Nursing Economic$, 23(4), 157–164. Hinno, S., Partanen, P., & Vehviläinen-Julkunen, K. (2012). Nursing activities, nurse staffing and adverse patient outcomes as perceived by hospital nurses. Journal of Clinical Nursing, 21(11–12), 1584–1593. International Neonatal Network, Scottish Neonatal Consultants, & Nurses Collaborative Study Group. (2000). Risk adjusted population based studies of the outcome for high risk infants in Scotland and Australia. Archives of Disease in Childhood. Fetal and Neonatal Edition, 82, F118–F123. Joyce, C., Kielbaso, M., Lincks, J., Reuf, D., & Sizemore, C. (2005). Discharge teams keep things moving. Nursing Management, 36(11), 36–39.
Volume 47, Issue 1–2, April/June 2014
© eContent Management Pty Ltd
Unequal staffing: A snapshot of nurse staffing in critical care units Kane, R. L., Shamliyan, T. A., Mueller, C., Duval, S., & Wilt, T. J. (2007). The association of registered nurse staffing levels and patient outcomes: Systematic review and meta-analysis. Medical Care, 45, 1195–1204. Liu, L. F., Lee, S., Chia, P. F., Chi, S. C., & Yin, Y. C. (2012). Exploring the association between nurse workload and nurse-sensitive patient safety outcome indicators. The Journal of Nursing Research, 20(4), 300–309. doi:10.1097/jnr.0b013e3182736363 Merkouris, A., Papathanassoglou, E. D. E., Pistolas, D., Papagiannaki, V., Floros, J., & Lemonidou, C. (2003). Staffing and organisation of nursing care in cardiac intensive care units in Greece. European Journal of Cardiovascular Nursing, 2, 123–129. Morley, A. (2005). Minimum guidelines for intensive care nurse staffing in New Zealand. Wellington, New Zealand: New Zealand Nurses’ Organisation. National Health and Medical Research Council, & Australian Research Council and Australian Research Council. (2007). National statement on ethical conduct in human research. Canberra, ACT: Australian Government. Needleman, J., Buerhaus, P., Mattke, S., Stewart, M., & Zelevinsky, K. (2002). Nurse-staffing levels and the quality of care in hospitals. New England Journal of Medicine, 346(22), 1715–1722. Pham, J. C., Andrawis, M., Shore, A. D., Fahey, M., Morlock, L., & Pronovost, P. J. (2011). Are temporary staff associated with more severe emergency department errors? Journal for Healthcare Quality, 33(4), 9–18. Pilcher, T., Odell, M., Bray, K., Clarke, S., Gardner, J., Orr, R., & Stirton, H. (2001). Nurse-patient ratios in critical care. Nursing in Critical Care, 6(2), 59–63. Rothschild, J. M., Bates, D. W., Franz, C., Soukup, J. R., & Kaushal, R. (2009). The costs and savings associated with prevention of adverse events by critical care nurses. Journal of Critical Care, 24, 471.e1– 471.e7. doi:10.1016/j/jere.2007.12.021 Royal College of Nursing. (2003). Defining staffing levels for children’s and young people’s services. London, England: Author. Royal College of Nursing. (2012). Mandatory nurse staffing levels. Policy Briefing 03/12. London, England: Author. Retrieved from http://www.rcn.org.uk/__data/assets/
CN
pdf_file/0009/439578/03.12_Mandatory_nurse_staffing_levels_v2_FINAL.pdf Simpson, E., & Courtney, M. (2002). Critical thinking in nursing education: Literature review. International Journal of Nursing Practice, 8, 89–98. Spence, K., Tarnow-Mordi, W., Duncan, G., Jayasuryia, N., Elliott, J., King, J., & Kite, F. (2006). Measuring workload in neonatal intensive care. Journal of Nursing Management, 14, 227–234. Stimpfel, A. W., Sloane, D. M., & Aitken, L. H. (2012). The longer the shifts for hospital nurses, the higher the levels of burnout and patient dissatisfaction. Health Affairs, 3(2), 2501–2509. doi:http:dx. org/10.13 77/hlthadd.2011.1377 Stone, P. W., Mooney-Kane, C., Larson, E. L., Horan, T. S., Glance, L. G., Zwanziger, J., & Dick, A. W. (2007). Nursing working conditions and patient safety outcomes. Medical Care, 45(6), 571–578. doi:10.1097/MLR.0b013e3180393667 Tevington, P. (2011). Mandatory nurse-patient ratios. Medsurg Nursing, 20(5), 265–268. Twigg, D., Duffield, C., Bremner, A., Rapley, P., & Finn, J. (2010). The impact of the nursing hours per patient day (NHPPD) staffing method on patient outcomes: A retrospective analysis of patient and staffing data. International Journal of Nursing Studies, 48(5), 540–548. UNISON. (2012). Care in the balance: A UNISON survey into staff/patient ratios on our wards. Retrieved from http://www.unison.org. uk/acrobat/20727.pdf Unruh, L. Y., & Fottler, M. D. (2006). Patient turnover and nursing staff adequacy. Health Services Research, 41(2), 599–612. doi:10.1111/j.1475-6773.2005.00496.x Workplace Research Centre, School of Business, University of Sydney & Centre for Health Services Management, University of Technology, Sydney. (2010, August). Nurse staffing NSW public hospitals. Report for the NSW Nurses Association. Sydney, NSW: University of Sydney & University of Technology, Sydney. Received 06 June 2013
Accepted 18 December 2013
R E N E W N O W F O R J u ly 2 0 1 4 – J une 2 0 1 5 Contemporary Nurse will publish Volumes 48–50 from July 2014 – June 2015 with special issues on: Nursing Innovation and Reform in Health Care Advances in Chronic Care, Ageing and Palliation Nursing Advances in Contemporary Nurse Education (3rd edn) Please ensure that your subscription has been renewed to retain access to Contemporary Nurse (ISSN 1037–6178) in print and online www.e-contentmanagement.com
© eContent Management Pty Ltd
Volume 47, Issue 1–2, April/June 2014
CN
15
Copyright of Contemporary Nurse: A Journal for the Australian Nursing Profession is the property of eContent Management Pty. Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.
