This article discusses the economic benefits of increased levels of nursing care and reports the findings of a study that assessed the cost-effectiveness of increased nursing care on health outcomes. It builds on previous analysis (Twigg et al. 2011, 2012) by examining the cost-effectiveness of the staffing method and by ‘incorporating a more complex individual measure of patient risk aggregated by hospital’ (Twigg et al. 2011). To date an economic evaluation has not been undertaken in an Australian setting.
The recent downturn in world economies has increased pressure on public and private health services to increase efficiency in an environment where advancing technology and increased availability of treatment interventions are increasing the demand for health care. Seventy-two percent of the recurrent cost per ‘case-mix-adjusted’ separation is staff related (medical and non-medical labour) (Australian Institute for Health & Welfare 2010) and as nursing is the largest workforce in health, nurse managers are increasingly forced to make difficult decisions. Nurse managers must decide the number and mix of nursing staff needed to optimize safe patient care within the limitations of budgetary constraints (Twigg & Duffield 2009). In a recent report, the Australian Nursing Federation (2009) observed that excessive workloads are common in the Australian healthcare setting. Nursing workloads and patient outcomes are inextricably linked (Aiken et al. 2002). Simply put: ‘If there are not enough nurses, the workload for each nurse is increased’ (Australian Nursing Federation 2009). Inadequate time reduces nurses' ability to deliver adequate patient care and forces nurses to leave work undone which directly has an impact on patient outcomes (Kalisch 2006, Duffield et al. 2011).
Higher nurse staffing levels and a richer skill mix [a higher proportion of registered nurse (RN) hours] have been linked with improved patient outcomes in many studies (Aiken et al. 2003, 2002, b, Rafferty et al. 2007, Tourangeau et al. 2007, Kane et al. 2007). Fifteen states and one district in the USA have enacted regulations or legislation aimed at improving nurse staffing. California was the first state to do so in 1999 and numerous studies about the impact of these changes have been undertaken (Donaldson & Shapiro 2010). A synthesis of these studies found that the nurse-to-patient ratio fell and the nursing hours per patient day increased. However, the authors did not establish any significant impact on patient safety indicators (Donaldson & Shapiro 2010) although they noted that adverse outcomes did not increase despite the case-mix index suggesting a sicker patient group. On the other hand, Aiken et al. (2010) found the mandated ratios in California were associated with lower mortality when compared with two states (Pennsylvania and New Jersey) without legislation. The continuous (24 hour 7 days a week) surveillance provided by RNs is key to early detection and prompt intervention for deteriorating patients (Aiken et al. 2002, b, Estabrooks et al. 2005). Nurses also have the capacity to proactively minimize adverse events and subsequent negative patient outcomes (Aiken et al. 2003). This function, however, depends on adequate nurse staffing levels in terms of both the volume of nursing and the mix of nurses (Aiken et al. 2003, Needleman et al. 2011).
Two Australian studies found similar results (Duffield et al. 2011, Twigg et al. 2011). The first study, undertaken in New South Wales found a higher proportion of RNs was associated with a statistically significant decrease in pressure ulcers, gastrointestinal bleeding, sepsis, shock, physiologic/metabolic derangement, pulmonary failure, and failure to rescue (Duffield et al. 2011). The same study found increased rates of deep vein thrombosis with improved skill mix (Duffield et al. 2011). The second study, undertaken in Western Australia (WA) over 4 years, evaluated implementation of the Nurse Hours per Patient Day (NHPPD) staffing method (Twigg et al. 2011). Twigg et al. (2011) found decreased rates of nine nursing-sensitive outcomes (NSOs), including mortality, at hospital level and significant decreased rates of five NSOs at ward level, following implementation of NHPPD.
This research evidence has put hospitals on notice to implement appropriate nurse staffing levels and a better skill mix (Clarke & Aiken 2006) as illustrated by the mandated staffing changes described previously. However, budgetary constraints and the labour market often limit the ability of hospitals to implement higher levels of nurse staffing and administrators have expressed concerns about the cost implications (Needleman & Buerhaus 2003). In response, several papers modelled the potential impact of fewer or additional nursing hours, given the association with NSOs. Many have argued that significant financial savings are to be gained by improving nurse-to-patient ratios (Rothberg et al. 2005, Needleman et al. 2006, Newbold 2008). Needleman et al. (2006) used data from the landmark 2002 study of 799 hospitals to argue the economic and social case for increasing nurse staffing levels. They found improving the RN mix (higher proportion of RN hours) to the 75th percentile while maintaining the total hours of care resulted in significant cost savings via reductions in length of stay and/or adverse outcomes. Although increasing total hours of care (RNs and licensed practical nurses) to the 75th percentile produced a larger reduction in length of stay, improvements in adverse outcomes were not so great and did not offset the increased hours of care. Needleman et al. (2006) estimated 6700 inpatient deaths could be avoided by increasing nursing staffing, mostly by a richer RN mix.
Newbold (2008) used production theory techniques to suggest staffing profiles that maximized patient outcomes and minimized costs. Reinterpreting Aiken et al.'s (2003) data, Newbold (2008) suggested increasing the number of graduate RNs as a percentage of the workforce was the most cost-effective way to improve patient outcomes. Thungjaroenkul et al. (2007) found that the proportion of RNs (skill mix) was inversely related to costs. More recently, Weiss et al. (2011) found that units with higher RN non-overtime staffing had lower odds of readmission. Their projected total savings was $409·59 per hospitalized patient per standard deviation increase in RN non-overtime staffing. For the 16 units studied, this represented US$11·64 million total savings.
Staffing at the nurse-to-patient level has also been examined from the context of a patient safety intervention (Rothberg et al. 2005). Rothberg et al. estimated that decreasing the patient-to-nurse ratio from 8:1–4:1 would reduce patient mortality and cost US$136,000 per life saved. This cost compares favourably to, for example, thrombolytic therapy in acute myocardial infarction at US$182,000 per life saved (Catillo et al. 1997 cited in Rothberg et al. 2005) or routine cervical cancer screening at US$432,000 per life saved (Charny et al. 1987 cited in Rothberg et al. 2005). This is supported by another study (Dall et al. 2009) that found the economic value of each additional full time RN ranged from US$58,100 to US$62,500 because of an associated reduction in nosocomial complications and therefore reduced medical costs. These analyses (Rothberg et al. 2005, Needleman et al. 2006, Dall et al. 2009, Weiss et al. 2011) indicate there is also an economic argument to improve nurse staffing.