nurse-patient ratio
5–20:a model of minimum nurse-to-patient ratios in Victoria, Australia
M.F.GERDTZ P h D,B N,R N,A&E C e r t,G D A E T1and S.NELSON P h D,B A(H o n s),R N2
1Lecturer and2Professor,School of Nursing.The University of Melbourne,Melbourne,Australia
Introduction
The size and the mix of nursing teams are critical elements of ef?cient health services management and workforce planning(Hurst2002).Among the many economic in-puts used to deliver health services to people,ef?ciency in health care requires?scal resource be correctly balanced. More speci?cally,imbalances between investment and recurrent expenditure,including human resources,rep-resent a substantial barrier to satisfactory performance (Buchan et al.1996).Health service provision by nature is labour intensive and human resources costs are esti-mated to account for as much as two-thirds of total expenditure(World Health Organisation2000). Accordingly,health systems worldwide are searching for new ways to contain expenditure while ensuring quality and managing risk.Within this context,staf?ng levels and skill mix are recognized as central elements of cost, and are now considered the primary determinants of quality(Buchan et al.2001).
Internationally,nurses represent the largest single professional group working within the health care industry.Currently,a chronic worldwide shortage of quali?ed nurses is contributing to industrial instability across the health sector and continues to raise both professional and public concern about the quality of
Correspondence
Marie Gerdtz
The School of Nursing
The University of Melbourne Level1
723Swanston Street
Carlton
Victoria3053
Australia
E-mail:gerdtzmf@https://www.wendangku.net/doc/c116257099.html,.au G E R D T Z M.F.&N E L S O N S.(2007)Journal of Nursing Management15,64–71
5–20:a model of minimum nurse-to-patient ratios in Victoria,Australia
Aim This study presents a critique of a new model of minimum nurse-to-
patient ratio and considers its utility alongside established Patient Dependency Systems.
Background Since2001legislation mandating minimum nurse-to-patient ratios has been enacted throughout large public hospitals in the state of Victoria,Australia. The Victorian model mandates minimum staf?ng of?ve nurses to20patients in acute medical and surgical wards.In conjunction with this approach,Patient Dependency Systems are employed to anticipate short-term resource needs.
Key issues Although this legislation has been successful in attracting nurses back into the public sector workforce,no published empirical evidence exists to support speci?c ratios.In addition,neither ratio nor Patient Dependency Systems approa-ches account for the critical in?uence of skill mix on hospital,employee,or patient outcomes.
Conclusion There is an urgent need for further research that speci?cally examines relationships between models of staf?ng,skill mix and quality outcomes. Keywords:Australia,nurse-to-patient ratios,patient dependency,skill mix,workload management
Accepted for publication:22December2005
Journal of Nursing Management,2007,15,64–71
care delivered to people in hospitals and the risks associated with the shortage of nurses(Buchan& Shocalski2004).In Australia,a national level analysis shows that the small increase in workforce participation by nurses from1996to2001will fail to keep pace with a projected shortfall of40000by the year2010(Aus-tralian Department of Health and Ageing2004).This persistent gap in the labour market has been attributed to a range of factors relating to the characteristics of the nursing workforce,which is both ageing and predom-inantly female,the stereotyped image of nursing,the nature of the work itself and the increasingly complex nature of health care where changing patient demo-graphics have resulted in older and sicker patients using services(Sorensen2001,Harris et al.2002,Creegan et al.2003,Buchan&Calman2004).Notwithstanding the impact of factors in?uencing supply,budget reduc-tions resulting in work overload are recognized as core elements contributing to the ongoing problem of recruitment and retention in nursing.On a macro-eco-nomic scale,levels of nurse staf?ng also in?uence the availability of services provided by a health care system. For instance,resources provided to care for the criti-cally ill(intensive care beds)and the running of hospi-tals?operating lists both depend on a continued supply of appropriately educated nurses(Shuldham2004). The purpose of this study was to critically review the research and related literature supporting the use of mandated nurse-to-patient ratios and automated Patient Dependency Systems(PDS)within Australian and inter-national contexts.In particular,the discussion will focus on factors known to affect estimates of staf?ng and skill mix and explore the ways each of these approaches is known to contribute to quality of care.For this review an electronic search was made of the literature published in English using the following indexes(1990to current): CINHAL,Medline,Social Science Citation Indexes, Australasian Medical Index,Australian Public Affairs Information Service,Expanded Academic ASAP,Coch-rane library.In addition,relevant literature was located by hand searching of specialist reports,papers and books cited in the publications.Search terms used included workload management,patient dependency,patient classi?cation systems.Subheadings and categories used in conjunction with the stem terms were,skill mix and nurse-to-patient ratios.
Research in nurse staffing levels and skill mix in acute care
Inadequate levels of staf?ng(low nurse-to-patient ratios)and skill mix(experience,education and special training)affect quality of care in a range of ways,and the relationship between nursing workloads and quality care is well documented in the research literature(Lang et al.2004).In a systematic review of over two decades of published research papers in the United States on the effects of nurse staf?ng for patient,employee and hos-pital outcomes,Lang et al.(2004)identi?ed probable relationships between richer nurse staf?ng and lower failure to rescue rates in surgical patients,and lower inpatient mortality(deaths from complications within 30days)and length of stay in medical patients.In re-spect to employee outcomes,the reviewers found lim-ited evidence to support richer staf?ng and lower rates of needle stick injury and burnout(Lang et al.2004). In their seminal USA study,Aiken et al.(2002) sought to determine associations between patient-to-nurse ratio and mortality,failure to rescue and a range of factors related to nurse retention(n?10184)gen-eral,orthopaedic and vascular surgery patients (n?232342).The study involved a cross-sectional analysis of linked data from168non-federal adult general hospitals in the state of Pennsylvania.The data analysis indicated that patient mortality increased by 7%for each patient added to an average hospital nur-se’s workload(Aiken et al.2002).When more patients were assigned to a nurse,unit productivity increased (Aiken et al.2002).
In addition to numerical calculations based on mini-mum nurse-to-patient ratios or nursing hours per patient day(HPPD),the combination of categories of health workers involved in direct patient care has been the subject of studies in nursing(McGillis Hall2004,2005). Skill mix is a broad term used to describe any one of the following factors in?uencing the labour force:
?…the mix of posts in the establishment;the mix
of employees in a post;the combination of skills
available at a speci?c time;or the combinations of
activities that comprise each role(Buchan et al.
2001,p.233)?.
Contained within this de?nition of skill mix are both empirical and contextual dimensions.The quanti?able elements of skill mix consist of proportions of licensed and unlicensed workers,appointment level,years of experience and levels of formal education and training. Theoretically,these elements are easily measurable. However,less readily quanti?able elements of skill mix include individual expertise,nursing knowledge and technical skills.In respect to this latter dimension, research commissioned by the World Health Organi-sation(Buchan et al.1996)involving analysis of over 400papers on skill mix noted a lack of consideration
Nurse-to-patient ratio
regarding the effect organizational context plays in in?uencing decision-making about workload generally, and skill mix speci?cally.In fact,little work has been underwent in nursing management outside North America that evaluates the relationships between skill mix decisions and quality outcomes.In examining relationships between one element of skill mix North American researchers Aiken et al.(2003)found that the educational preparation of nurses was a signi?cant factor in?uencing patient mortality.
Canadian researchers McGillis Hall et al.(2004) sought to evaluate the in?uence of skill mix,focusing on the proportion of licensed and unlicensed workers,and on patient safety outcome measures including,medica-tion errors,wound and urinary tract infections.The study employed a descriptive,correlational design and involved a sample of medical and surgical units in19 urban teaching hospitals across the province of Ontario, Canada.The results of this study show that the lower the mix of professional nursing staff,the higher the incidence of medication errors and wound infections. The Australian health care system
Although the vocabulary of Australian health policy strongly resembles that used in the United States,major differences exist between health care systems(Peabody et al.1997).Unlike the largely privatized North American system,Australian health care is funded by a universal structure that has its origins in the United Kingdom’s National Health Service.Under the Austra-lian Medicare system,a national schedule guides the reimbursement of primary health care costs provided by private general practitioners who operate on a fee-for-service basis,but who are indemni?ed by Medicare.For hospital-based care,a mix of private,public and char-itable services operate in tandem,with almost three quarters of the hospital industry funded directly by government(Buchan2004).In the public system, inpatient costs are?nanced from global hospital bud-gets and scheduled remuneration is provided for public medical services.In addition,the federal government encourages participation in private health insurance by providing substantial taxation incentives(Peabody et al.1997).
Adding complexity to this model of health care delivery is its administration through seven separate states and territories.Although public hospital funding in Australia is derived from federal tax revenue,the management of hospital-based care is the responsibility of the state and territory governments(Whitehead et al. 1993).Not surprisingly,the involvement of two levels of government in the administration of the health sys-tem has resulted in a highly complex structure in which there is a considerable overlay of government regulation (Gibb1998).
Within this convoluted structure,the nursing work-force is regulated at a state level by a series of Acts of Parliament,which support the function of seven boards of nursing responsible for monitoring nurse training, examination and dealing with issues of reciprocity of registration in Australia and overseas.Legislation also exists to protect the title of?registered nurse?in Aus-tralian hospitals and precludes the recruitment of unquali?ed staff into nursing roles(Nurses Board of Victoria2004).
Minimum nurse-to-patient ratios and the5–20 model
The current5–20nurse-to-patient ratio model oper-ating in the state of Victoria,Australia has at its genesis a series of disputes between the Australian Nursing Federation(ANF)and the Victorian state government that were brought before The Australian Industrial Relations Commission some4years ago(Victorian Auditor General2002).Throughout the early1990s, the state was experiencing substantial cost reductions in health care.By the end of the decade,these extreme ?scal measures coupled with national and global shortfalls in the nursing labour market,had resulted in an acute statewide crisis in the nursing labour force.In addition,legacy-staf?ng methods,using either profes-sional judgement approaches or?nurses-per-occupied-bed?,were widely regarded as poor measures of patient acuity,and nursing resources within both public and private sectors were obviously stretched.At this time, many nurses resigned from the public work force,un-able to come to terms with their professional and legal responsibilities to provide safe care in the face of unyielding workloads(Barnett et al.2004).Because of this crisis in the nursing workforce,the public sector nurse labour market contracted and the casual work-force expanded,resulting in high levels of agency use and an expediential increase in the cost of nursing care across the acute care sector(Creegan et al.2003). The issue of nurse recruitment,retention and educa-tion in Victoria was brought into focus by the?nal re-port of the Nurse Recruitment and Retention Committee.The?Bennett Report?was commissioned by the Minister for Health,and the Australian Industrial Relations Commission(AIRC)arbitration hearing before Commissioner Blair in August2000.The out-come of the latter dispute between the ANF and the
M.F.Gerdtz and S.Nelson
Victorian Hospitals Industrial Association(VHIA)was the Head of Agreement(HOA),which was?nally handed down on23August2001(Barnett et al.2004). This landmark decision for Victorian nurses represents a world?rst,in essence,enabling the implementation of set nurse–patient ratios throughout Victorian public hospitals and residential aged care facilities.Originally, nurse-to-patient ratios were set at1–4on both morning and afternoon shifts in major metropolitan hospital medical and surgical wards.Modi?ed ratios were also in place for some speciality units.In2004,the ANF was successful in improving and extending minimum level staf?ng though its enterprise bargaining agreement with the state government.In short,ratio staf?ng was moved from the patient level(1–4)to the ward level(5–20). Known locally as the?5–4–20?,this approach to mini-mum staf?ng which uses a?exible ratio model is a world?rst(ANF2004a).
In response to declining patient care caused by understaf?ng of registered nurses and an increase in the use of Unlicensed Assistive Personnel(UAP),the state of California,USA,introduced legislation man-dating minimum nurse–patient ratios(Seago2000a, Spetz2004).Signed by former Governor Gray Davis in1999,the California AB394limits to six,the number of patients per nurse.In addition,California AB394demands staf?ng be based on severity of ill-ness,need for specialized equipment and technology, complexity of care and the patients?ability to provide self-care.Moreover,this legislation prohibits hospitals from assigning nursing work to technical assistants or care attendants.Since that time,a number of other USA states have indicated nurse staf?ng ratios are a prime legislative priority,with at least two bills developed in Hawaii(HB2921,S2735)and one in Missouri(HB2080)based on the Californian legis-lation(Habgood2000).A key difference between the USA ratio models and the Victorian5–20is that the latter is iterative in so much as it permits a degree of ?exibility based on patient acuity and,depending on unit work load can be increased,at the discretion of the nurse in charge.
A second difference between the Victorian and the Californian models relate to the way in which the industry has responded to the legislation mandating minimum nurse-to-patient ratios.While in the USA acute care facilities have increased overall hours of care, the increase in care has largely been achieved using unlicensed workers(Schafer Mourek&Colbert2004). In Victoria,increases in staf?ng the acute care sector have,by law,come from an entirely regulated work-force of registered nurses.
At the time of writing,mandated nurse–patient ratios exist in only two states:Victoria,Australia and Cali-fornia,USA.Despite strong local support for minimum staf?ng levels in Victoria and in many USA states,there is a dearth of research to support the ratios currently in use,and Australian studies are yet to examine the impact of ratio variability on quality of care(Bolton et al.2001).
Static vs.responsive ratio models
A de?ning feature of the Victorian5–20ratio model is that the nurse-to-patient ratio is set at a minimum number of nurses per ward,not per patient,thus allowing for staf?ng levels to be increased and therefore sensitive to changes in patient acuity(ANF2004a).One of the appeals of this model for working nurses is that it is responsive to?uctuations in patient status,unit work?ow and emergencies.For example,if a sudden change in patient acuity necessitates reallocation of work,the ratio of one nurse to four patients may change;however,the ratio of5:20is still maintained at the unit level.A second,but under-discussed issue is that the5–20ratio model returns the decision-making authority to the unit manager to allocate patient load according to skill mix and staf?ng needs.Thus,the 5–20ratio model reasserts the team basis of nursing work–where dif?cult patient loads are acknowledged and the burden is shared by colleagues.
The contextual in?uence of unit skill mix and the ?exibility afforded by the5–20ratio model seems critical to its success in practice.While the in?uence of nurses?quali?cations,education,years of experi-ence and special training can be readily identi?ed and measured using well-designed systems–the situa-tional aspects of skill mix are more dif?cult to cap-ture using workforce management systems.In particular,the ability to deploy staff with a speci?c set of skills or technical knowledge to a patient group at any time over the duration of a shift permits the timely delivery of care and the ef?cient use of resources.
The ability of the5–20ratio model to respond to contextual in?uences within the workplace may explain,at least in part,its success within the State of Victoria.Recently,however,there is no evidence to support such an assertion,and it is apparent that research into the5–20ratio model must explore the relationship between ratios,skill mix and clearly de?ned quality indicators.
Despite the anecdotal evidence supporting the 5–20ratio model,minimum nurse-to-patient ratios of
Nurse-to-patient ratio
themselves cannot determine the precise number of nurses needed at a particular time in a particular setting (Shuldham2004).In addressing this limitation,ratio models in both Victoria and California run in tandem with PDS(Spetz2004).The most prominent PDS operating in Victoria is the Trend Care Patient Acuity and Care Management System TM(Trend Care Pty Ltd 2004).This system is currently in use in over80hos-pitals in Australia wide(Trend Care Pty Ltd2004). Patient Dependency Systems
On a micro-economic level,categorization of patients according to their level of acuity is a core principle used by managers to inform decisions about staf?ng(Alward 1983,Hlusko&Nichols1996).Based on principles derived from engineering and manufacturing,early PDS models aimed to predict demands for nursing resources according to the completion of speci?c nursing https://www.wendangku.net/doc/c116257099.html,ing original PDS models,staff requirements were represented as a function of the total number of tasks by the duration of time taken to perform those tasks(O’Brien-Pallas1988,Van Slyck2000).
Patient Dependency Systems can be categorized as task type(summative or criterion-based)or process-orientated(DeGroot1994a,b).Summative task type instruments aim to capture all of the nursing work that is performed for a patient in a given period of time (Seago2000b).Validation of summative task type sys-tems routinely involves work-measurement methodol-ogies that represent nursing work as a selected series of timed tasks,which may be condensed into critical indicators.Each indicator can then be assigned a numerical value that represents an approved time allo-cation for the performance of a speci?ed task(Van Slyck1991a).A major criticism of this approach is its representation of nursing work as a series of discrete time-limited tasks,rather than a process of delivering a service.Such an approach therefore fails to capture the essence and complexities of nursing care(Van Slyck 1991b,Buchan1993).
A second limitation that is linked to the summative task type instrument concerns the time taken for the nurses to record the necessary data for the system to work.Heslop et al.(2004)reported that on average nurses spend up to60%of their work time on docu-mentation and information management.The use of a summative task type approach to the measurement of nursing work is therefore problematic,due to the vol-ume of data entry required.Not surprisingly,sizable demands for data input using this type of PDS often result in high levels of non-compliance with documen-tation requirements and may threaten the interrater reliability of the data(Registered Nurses Association of Ontario2005).Because of this problem,summative PDS have the potential to produce widely inaccurate data,and therefore produce imprecise projections (Seago2000b).For example,in one analysis,time dif-ferences between estimates calculated by a range of PDS were as great as4.53hours/day for the same patient (O’Brien-Pallas et al.1992).In the context of practice, such variance is unacceptable because it is unlikely to support safe staf?ng practice(ANF2004a).In order to overcome the problem of excessive data entry some PDS systems link documentation systems,avoiding duplica-tion of information collected by clinical nurses(Regis-tered Nurses Association of Ontario2005).
To date,the application and utility of the myriad of PDS available to those managing the nursing workforce has been problematic,and while a PDS may facilitate retrospective recording of resource use,there is limited evidence to suggests that these systems are suf?ciently responsive to future changes in variables related to workload demand.This weakness occurs,in part, because projections using current models are based on the assumption that the number of nurses required to meet current workload demand will be suf?cient to meet future requirements.
Since the inception of the original PDS models more than60years ago,a range of other factors have been discovered that contribute to patient acuity in a sub-stantive way.Notably,these factors include risk,skill mix and complexity(Van Slyck1991a,b).
Third-generation PDS employ a process-based meth-od where all nursing provided to patients and their signi?cant others is not only measured according to time and frequency,but also according to risk,skill and complexity via the application of weighted measures. Theoretically,such a system considers in a more holistic way pertinent cognitive and emotional needs of the patient and family,the interdisciplinary coordination required to care for patients,and the complexity of patient care across a continuum from admission to discharge(Malloch et al.1999).
Van Slyck(2000)asserts that widespread dissatis-faction with many modern PDS can be attributed to its expected singular application that is satisfaction with staf?ng–when in fact patient acuity represents only one dimension of a staf?ng system.Other important dimensions in?uencing unit staf?ng include length of stay,the number of admissions,discharges and trans-fers,the managers?clinical judgement,staff competen-cies,unit geography and doctor practice patterns(Van Slyck2000).Van Slyck(2000)argues convincingly that
M.F.Gerdtz and S.Nelson
independence between micro-systems related to patient acuity and unit acuity levels is crucial in developing integrated macro-system applications for determining staf?ng requirements of a health service.
Supporting Van Slyck’s(1991b)argument,Botter’s (2000)study,PDS in east Wisconsin,USA,identi?ed how PDS information was used by hospital personnel in the decision-making process.The?ndings of this research reveal that while PDS data are used by staff when making decisions about skill mix and minimal staf?ng,in practice,nurse managers frequently sought out a range of alternative data sources.The results of Botter’s(2000)work indicate the need to consider more broadly,how relationships between other information systems might be used to improve patient outcomes. In Victoria,criticisms of the Trend Care Patient Acuity and Care Management System TM echo those made of other PDS,i.e.that it consistently suggests less time is required for care than is needed in actual prac-tice,and that nurses lack con?dence in the ability of the PDS to adequately predict nursing workload(ANF 2004b).The Victorian branch of the ANF is critical of the use of PDS models on the basis that they promote ad hoc methods of rostering,draw heavily on a casual workforce and therefore increase the cost of care(ANF 2004a).The integrity of any workload measurement tool must also be called into question if it is not per-ceived to be politically neutral by its users(Needham 1997).Much of the criticism levelled at the Trend Care Patient Acuity and Care Management System TM in the state of Victoria has arisen because of the political cli-mate in which it was implemented and subsequently evaluated.
Notwithstanding these limitations,a critical element of any PDS model,and a feature currently lacking in the use of PDS in the state of Victoria is its capacity to link its outputs to patient,workforce and organizational outcome data(Rauhala&Fagerstrom2004).This dif-?culty has arisen,at least in part,because the use of software varies across organizations and therefore compatibility with related clinical and?nancial systems diverges.By virtue of these differences,the quality of the information drawn from Victorian PDS models is at best patchy.
Conclusions
Health services research in Australia with respect to staf?ng and patient outcomes is poorly developed.Yet, within the relatively well-resourced context of the Australian system,where the acute care sector is ser-viced by a highly regulated workforce of professional nurses–there exists a unique opportunity to study the effects of staf?ng and skill mix on a range of hospital and patient outcomes.
Measuring and valuing ways in which nursing work contributes to health status is critical to the allocation of resources in the acute care sector.Despite the ongoing debate related to the implementation of man-dated nurse-to-patient ratios and the utility of PDS in informing decisions about unit level staf?ng,little empirical work has been performed that links a speci?c programme of staf?ng,at macro-or micro-levels,to improvements in health outcomes.The dearth of research into relationships between nursing skill and positive patient outcomes also has implications for labour force planning.In particular,developing insights into how professionally administered care contributes to quality outcomes may contribute to the development of strategies to recruit and retain skilled practitioners within the health care work force(Clarke&Aiken 2003).
The State of Victoria has mandated minimum nurse-to-patient ratios.Globally,these conditions exist in only one other locale where very different economic condi-tions drive the labour market and ratios are not funded to the comparatively rich5–20level.In seeking to optimize resource utilization and quality outcomes for patients,there is an urgent need for further research that evaluates the costs and consequences of the Victorian5–20ratio model of staf?ng.In exploring the outcomes of the5–20ratio model consideration must be given to the valuation of economic consequences in terms of savings to both the health care sector and to the patient in terms of quality of life.This knowledge will provide a robust evidence base on which to develop local,national and international policy on nurse staf?ng and skill mix that is expressed in terms of improvements in overall health status.
References
Aiken L.F.,Clarke S.P.,Sloane D.M.,Sochalski J.&Silber J.H. (2002)Hospital nurse staffing and patient mortality,nurse burnout and job dissatisfaction.JAMA288,1987–1993. Aiken L.F.,Clarke S.P.,Cheung R.B.,Sloane D.M.&Silber J.H. (2003)Educational levels of hospital nurses and surgical patient mortality.JAMA290(12),1617–1623.
Alward R.(1983)Patient classification systems:the ideal vs. reality.Journal of Nursing Administration13(2),14–19. Australian Department of Health and Ageing(2004)Health Ministers Conference.National Health Workforce Strategic Framework,AHMC,Canberra,Australia.
Australian Nursing Federation(ANF)(2004a)5200more Rea-sons to Commit to Nurse Patient Ratios.ANF,Victorian Branch Media Release,Victoria,Australia,12October2004.
Nurse-to-patient ratio
Australian Nursing Federation(ANF)(2004b)Patient Depend-ency System Pilot Evaluation.A Report prepared for the Department of Human Services,Victoria,by School of Nursing,Monash University,Victoria,Australia[An ANF (Victorian Branch)Alternative Executive Summary].
Barnett T.,Bird B.,Francis K.et al.(2004)Patient Dependency System Pilot Evaluation.Report prepared for Department of Human Services,Victoria,by School of Nursing,Monash University,Victoria,Australia,15March2004.
Bolton L.B.,Jones D.,Aydin C.E.et al.(2001)A response to California’s mandated nursing ratios.Image Journal of Nursing Scholarship33(2),179–184.
Botter M.(2000)The use of information generated by a Patient Classification System.Journal of Nursing Administration30 (11),544–551.
Buchan J.(1993)Posting notice about skill mix exercises.Nursing Standard7(21),37.
Buchan J.(2004)A Certain Ratio?Minimum Staf?ng Ratios in Nursing.A Report for the Royal College of Nursing,Australia. Buchan J.&Calman L.(2004)The Global Shortage of Registered Nurses:An Overview of Issues and Actions.International Council of Nurses,Geneva,Switzerland.
Buchan J.&Shocalski J.(2004)The migration of nurses:trends and policies.Bulletin of the World Health Organization82(8), 587–594.
Buchan J.,Ball J.&O’May F.(1996)A Review of Approaches to Determining Skill Mix in Health Care.World Health Organi-sation,Geneva,Switzerland.
Buchan J.,Ball J.&O’May F.(2001)If changing skill mix is the answer,what is the question?Journal of Health Service Research Policy6(4),233–238.
Clarke S.P.&Aiken L.F.(2003)Failure to rescue.American Journal of Nursing103,42–47.
Creegan R.,Duf?eld C.&Forester K.(2003)Casualisation of the nursing workforce in Australia:driving forces and implications. Australian Health Review26(1),201–208.
DeGroot H.A.(1994a)Patient classification systems and staffing: part1,problems and promise.Journal of Nursing Adminis-tration24(9),43–51.
DeGroot H.A.(1994b)Patient classification systems and staffing: part2,practice and process.Journal of Nursing Administration 24(10),17–23.
Gibb H.(1998)Reform in public health:where does it take nursing?Nursing Inquiry5(4),258–267.
Habgood C.(2000)New nurse-to-patient legislation and its effect on perioperative nursing.AORN71(6),1267–1268.
Harris M.,Gavel P.&Warwick C.(2002)Planning Australia’s hospital workforce.Australian Health Review25(5),62–77. Heslop L.,Deirs D.&Poh B.C.(2004)Using clinical data for nursing research and management in health services.Con-temporary Nurse17,8–18.
Hlusko D.&Nichols B.(1996)Can you depend on your patient classification system?Journal of Nursing Administration26 (4),39–44.
Hurst K.(2002)Selecting and Applying Methods for Estimating the Size and Mix of Nursing Teams.Nuf?eld Institute for Health.Leeds University,Leeds,UK.
Lang T.A.,Hodge M.,Olsen V.,Romano P.S.&Kravitz R.L. (2004)Nurse-patient ratios:a systematic review on the effects of nurse staffing on patient,nurse employee and hospital out-comes.Journal of Nursing Administration34(7–8),326–337.Malloch K.,Neeld A.P.,McMurrary C.et al.(1999)Patient classification systems:Part2.The third generation.Journal of Nursing Administration29(9),33–42.
McGillis Hall L.(2004)Nursing staff mix models and outcomes. Journal of Advanced Nursing44(2),217–226.
McGillis Hall L.(2005)Nurse staffing.In Quality Work Envi-ronments for Nurse and Patient Safety(L.McGillis Hall ed.) pp.9–37.In Jones and Bartlett,Massachusetts,USA. McGillis Hall L.,Dorna D.&Pink G.H.(2004)Nurse staffing models,nursing hours and patient safety outcomes.Journal of Nursing Administration34(1),41–45.
Needham J.(1997)Accuracy in workload measurement:a fact or fallacy.Journal of Nursing Management5,83–87.
Nurses Board of Victoria(2004)Nurses Board of Victoria.Our History.Available at:https://www.wendangku.net/doc/c116257099.html,.au/nbvonlinev1 [accessed9April2006].
O’Brien-Pallas L.(1988)An analysis of multiple approaches to measuring nursing workload.Canadian Journal of Nursing Administration1(2),8–11.
O’Brien-Pallas L.,Cockerill R.&Leatt P.(1992)Different sys-tems,different costs?An examination of the comparability of workload measurement systems.Journal of Nursing Adminis-tration22(12),17–22.
Peabody J.W.,Bickel S.R.&Lawson J.S.(1997)The Australian health care system.Are incentives down under right side up? JAMA276(24),1277–1278.
Rauhala A.&Fagerstrom L.(2004)Determining optimal nursing intensity.Journal of Advanced Nursing45(4),351–359. Registered Nurses Association of Ontario(2005)Nursing Workload Measurement Systems.A Discussion of the Issues.Available at:https://www.wendangku.net/doc/c116257099.html,/policy/discussion.asp [accessed on21March2005].
Schafer Mourek K.&Colbert K.(2004)Staffing ratios and patient outcomes:linkage,legislation and logic.Excellence in nursing knowledge.Honour Society Sigma Theta Tau. Available at:https://www.wendangku.net/doc/c116257099.html,/Portal/main. aspx[last accessed on13December2006].
Seago J.(2000a)The California experiment:alternatives for minimum nurse-to-patient ratios.Journal of Nursing Admin-istration32(1),48–58.
Seago J.(2000b)A comparison of two patient classification instruments in an Acute Care Hospital.Journal of Nursing Administration32(5),243–249.
Shuldham C.M.(2004)Nursing skill mix and staffing.Journal of Nursing Management12,385–387.
Sorensen E.M.(2001)Nursing workforce in practice and educa-tion:what can we learn from the current crisis?Journal of Perinatal Neonatal Nursing15(1),16–25.
Spetz J.(2004)California’s minimum nurse-to-patient ratios.The first few months.Journal of Nursing Administration34(12), 571–578.
Trend Care Pty Ltd(2004)Trend Care Patient Acuity and Care Management System.Available at:http://www.trendcare. com.au[accessed19April2006].
Van Slyck A.(1991a)A systems approach to the management of nursing services:Part 1.Introduction.Journal of Nursing Management22(3),16–19.
Van Slyck A.(1991b)A systems approach to the manage-ment of nursing services:Part II.Patient classification sys-tem introduction.Journal of Nursing Management22(4), 23–25.
M.F.Gerdtz and S.Nelson
Van Slyck A.(2000)Patient classification systems:not a proxy for nurse busyness.Nursing Administration Quarterly24(4),60–65.
Victorian Auditor General(2002)Report into Nurse Workforce Planning.Available at:https://www.wendangku.net/doc/c116257099.html,.au/reports_ par/agp78cv.html.Whitehead M.,Judge K.,Hunter D.,David J.,Maxwell R.& Scheuer M.A.(1993)Tackling inequities in health:the Aus-tralian experience.BMJ306(6880),783–787.
World Health Organisation(2000)The World Health Report. World Health Organisation,Geneva,Switzerland,pp.73–90.
Nurse-to-patient ratio