BOX 1. SIX COMMONLY USED WORKFORCE PLANNING AND DEVELOPMENT METHODS

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1 KEYWORDS WORKFORCE PLANNING STAFFING LEVELS SKILL MIX QUALITY Evaluating the strengths and weaknesses of NHS workforce planning methods Nursing is a trust s most expensive resource. Workforce planning methods help managers estimate how many nurses they need, and the skills they should have AUTHOR Keith Hurst, PhD, is an independent analyst, Nottinghamshire. ABSTRACT Hurst K (2010) Evaluating the strengths and weaknesses of NHS workforce planning methods. Nursing Times; 106: 40, This article examines the different methods used in NHS workforce planning and development and their strengths and weaknesses. It is a summary and update of the nurse staffing study commissioned by the Department of Health (Hurst, 2003). The article is designed to help nurse managers select and apply methods for reviewing or estimating their staffing needs, and looks at the future for workforce planning and development. BOX 1. SIX COMMONLY USED WORKFORCE PLANNING AND DEVELOPMENT METHODS Macro, top down, population based methods: l Benchmarking databases (Skills for Health Workforce Projects Team, 2010b). Micro, bottom up or workload driven methods from simple to sophisticated: l Professional judgement or consensus methods (Telford, 1979); l Staff to bed ratios, for example Leeds University Nursing Database (SfH WPT, 2010a); l Workload quality, for example by the Safer Nursing Care tool (Smith et al, 2009); l Timed task, for example GRASP (Anderson, 1997); l Regression (Kaplan, 1975). INTRODUCTION Daily nursing costs for one patient in an elderly care ward is estimated to be 116 and this rises to 525 for patients in critical care units (Skills for Health Workforce Planning Team, 2010a). Nurses and healthcare support workers are the NHS s largest and therefore most expensive workforce and it is important that nurses time is used efficiently and effectively. There are six methods used for estimating the size of ward and department teams and skill mix. These fall into two broad approaches: one top down method and five bottom up. Each has strengths and weaknesses, so it is wise to plan staffing recommendations using at least two methods. The commonly used methods for workforce planning and development are outlined in Box 1. Examples are provided in this article to show how all six methods are used in practice. WHAT IS NHS WORKFORCE PLANNING AND DEVELOPMENT? Effective workforce planning and development supports service quality by ensuring that a sufficient number of workers with the right skills are in the right place at the right time at the right price. Health workforce planning and development is usually presented as scales, as illustrated in Fig 1. These emphasise how ward based workforce planning and development cannot be viewed in isolation. It is likely that staffing reviews will involve clinical staff and managers as well as personnel, commissioning and education colleagues. BENCHMARKING DATABASES All four UK countries maintain data warehouses from which NHS staffing and related data can be obtained. These are listed in Box 2. There are currently around 1,350 workforce related datasets and these are being aggregated into dedicated sites (SfH WPT, 2010b), which makes benchmarking easier. The SfH WPT (2010b) benchmarking BOX 2. UK HEALTH SERVICE DATA WAREHOUSES Site Department of Health The NHS Information Centre (NHS IC) Scotland Information Service Department (Scotland ISD) StatsWales Department of Health, Social Services and Public Safety (DHSSPSNI) URL tinyurl.com/departmentofhealthgovernment tinyurl.com/statisticsanddatacollections tinyurl.com/scotlandinformationservice tinyurl.com/statisticswales tinyurl.com/governmentindexstatistics 10

2 THIS ARTICLE HAS BEEN DOUBLE-BLIND PEER-REVIEWED FIG 1. BALANCING WORKFORCE PLANNING AND DEVELOPMENT BOX 3. PROFESSIONAL JUDGEMENT METHOD: l Enduring l A springboard to using other methods l Handles complex issues l Clinician views l Free software to help with calculations A balanced workforce Staff supply Recruitment and retention methods BOX 4. PROFESSIONAL JUDGEMENT CALCULATIONS This calculation of staffing is based on a seven day, three shift ward with a funded shift overlap. Three nurses are allocated per shift (two at night) with 22% additional time out to cover sickness, holidays, maternity, compassionate leave and study leave. Time out may differ between trusts as a result of Agenda for Change, so it is important to use the correct local figure. The process should be repeated for HCAs to set the ward s establishment (total staffing). Free software (SfH WPT, 2010a) is available to help with these calculations. Shift Length (hours) Nurses Days Staff hours x 3 x 7 = x 3 x 7 = x 2 x 7 = 140 Total = 455 Add 22% time out (455 hrs x 1.22 = 555.1hrs), divide by 37.5hrs = 14.8 full time equivalents (FTEs) It is useful to know how to reverse the professional judgement formula: Demand for staff Top-down Bottom-up methods to estimate team size and skill mix l No built in service quality measure l Selected a more sophisticated method l Workload insensitive l Manager views l Awkward to calculate staffing manually l Each ward has 21 shifts a week; l Each full time nurse or HCA works five shifts; l Therefore, 21 shifts/5 staff x 1.22 (at 22%) time out means 5.1 FTE staff provide one worker per shift; l Therefore, 15.3 (5.1 x 3) FTEs are needed to allocate three staff per shift. database, for example, shows that top rated trusts (based on Care Quality Commission ratings) employ 4.3 registered nurses and 2.5 healthcare assistants for each bed, compared with bottom rated trusts, which employ 0.9 and 1.9 respectively. WORKFORCE METHODS Professional judgement This involves expert, multidisciplinary groups which have local intelligence such as knowing about a move to new buildings agreeing a ward or department team s size and mix by consensus. This was first used in the 1970s and is one of the oldest methods for workforce planning and development (Telford, 1979). Box 3 highlights its strengths and weakness. It is the quickest and simplest method because precise information such as patient dependency data is not needed. Workforce planning teams often begin with this method but may run into difficulties if clinicians and finance managers cannot agree the former are often concerned with patient safety, the latter with affordability. An example of how it can be used is outlined in Box 4. The major criticism of the professional judgement method is that it is too subjective, especially if nurses alone decide the type and number of nursing staff that is needed. It is interesting to note that research updating the Department of Health Expert Working Group (2003) neonatal service report showed that the original professional judgement based staffing multipliers (the staffing value multiplied by occupied beds) were close to those determined later by fieldwork using cot occupancy, neonatal dependency and staff activity data. For example, the expert group using professional judgement decided a level 1 special care baby unit cot required 0.33 full time equivalent staff, whereas fieldwork indicated a 0.32 FTE was appropriate. Fieldwork determined multipliers are considerably more expensive and time consuming to generate than professional judgement calculations. Staff to bed ratios The staff per occupied bed method uses staff (by grade) to occupied bed ratios from best practice wards that pass a service quality test. The UK has staff to bed ratios for all services (SfH WPT, 2010a), but these have to be used with caution and the strengths and weaknesses of this method are outlined in Box 5 (overleaf). Unlike the professional judgement 11

3 BOX 5. STAFF TO BED RATIOS l Evidence based l Excellent benchmarks l Free software l Used with all care groups l Quality based method, the staff to bed ratio is evidence based, which makes it more expensive to establish and maintain. The ratios provide excellent benchmarks and are easy to use. However, the person calculating them should use occupied beds rather than total The example here details staff to occupied bed multipliers from 125 best practice general medical wards in the Leeds University Nursing Database (SfH WPT, 2010a). Wards average 25.7 occupied beds and 1.5 FTE senior ward sisters form part of the ward team, which we represent as 0.06 FTE per occupied bed (1.5 divided by 25.7). In practice, multiply the average occupancy by 0.06 FTE to estimate how many senior ward sisters are needed in your ward. The exercise is repeated for other grades. The time out allowance is set in this example at 22% (the best practice ward average) and the multiplier includes an allowance for temporary (bank) staff. l Accounts for most variables l Workload based l Flexible l Free software l Quality weighting l Measures throughput l Ward layout/housekeeper l E-rostering potential l Updating is costly l Use correct numerator (occupied beds)/ denominator (FTE) l Workload is fixed l Throughput is ignored l Open to manipulation such as adjusting ratios to produce lower costs l Hidden variables beds, and full-time staff rather than headcount, or this benchmark is useless. Occupied beds (the numerator) is divided by the number of full time staff (the denominator). An example of the calculation is provided in Box 6. This method assumes that patients generate the same workload; namely that all patients have similar dependency. Another failing is that throughput (how many times a bed empties and fills each shift) is not recognised, which makes it inappropriate for admission and assessment wards. Free software (SfH WPT, 2010a) can help convert occupied beds into a ward establishment. It is important to use the right care group for example, it would not be appropriate to use elderly care ward staffing ratios for children s wards. Finally, ratios from different ward designs are being developed as, for example, single rooms require different staffing configurations from Nightingale wards (Hurst, 2008). The time out allowance is set in this example at 22% (the best practice ward BOX 6. STAFF TO OCCUPIED BEDS A BEST PRACTICE GENERAL MEDICAL WARD Grade FTE x Beds = FTEs Snr WS (7+) 0.06 x 25.7 = 1.5 Jnr WS (6-7) 0.11 x 25.7 = 2.8 Snr SN (6) 0.34 x 25.7 = 8.7 Jnr SN (5) 0.51 x 25.7 = 13.1 Sr HCA (4) 0.1 x 25.7 = 2.6 Int HCA (3) 0.16 x 25.7 = 4.1 Jr HCA (2) 0.38 x 25.7 = 9.8 Total 1.65 x 25.7 = 42.5 Note: FTEs incorporate a 22% (best practice ward) time out allowance. Key: FTE (full time equivalent); Snr (senior); WS (ward sister); Jnr (junior); SN (staff nurse); HCA (healthcare assistant); Int (intermediate). BOX 7. WORKLOAD QUALITY METHOD: l Costly uses seven data sets l Adds to ward overheads l Not useful for small wards l Concerns abou t importing data l Auditing is not standardised l Poor forecaster of staffing l Data on this is currently limited l Competition average) and the multiplier includes an allowance for temporary (bank) staff. The workload quality method The workload (or acuity) quality method is popular in the UK. It is a sophisticated algorithm that uses occupancy, throughput, patient dependency, direct patient care times and ward overhead data from best practice wards. Its strengths and weakness are outlined in Box 7. This method is more expensive to set up, maintain and use than the two bottom up methods covered so far, because seven important datasets, such as patient dependency, are required to ensure that staffing estimations are workload based. Wards with sicker patients are therefore allocated more staff. Adopting more sophisticated methods means that busy ward staff have to collect data. This does not influence patient care directly and they may resent this, especially if staffing does not change as a result. The alternative is importing data from other wards, but borrowed data may not be from quality assured wards. This is a flexible method and there is excellent, freely available software for calculating your workforce (SfH WPT, 2010a). However, this staffing formula does not suit small wards (10 occupied beds or fewer) with low dependency patients because recommended establishments may be insufficient to place at least one RN on each shift. In this case, the professional judgement method is preferred. Perhaps the most significant workload quality method development in the last few years is the Safer Nursing Care multipliers (Smith et al, 2009; Hurst, 2008; Harrison, 2004). Safer Nursing Care s strength is that it combines the patient dependency definitions with empirically determined staffing requirements resulting in simple ward staffing formulas (Box 8). Patient dependency and staff activity used to generate the definitions were collected alongside ward quality data, ensuring that substandard wards were excluded from the main database. More detailed care level definitions (for example, of level 0) can be found in Hurst (2008). It is clear that workload quality methods are more sensitive to nursing workload than other methods and placing patients into the correct care level is crucial. Ward managers should check nurses are accurately assessing patient dependency (Hurst, 2009). In the future, it is likely that patient 12

4 BOX 8. SAFER NURSING CARE LEVELS AND MULTIPLIERS Care level Definition FTE multiplier 0 Needs met in general wards a Acutely ill patient or one likely to deteriorate b Patient is stable but more dependent on nurses for support Patient is unstable, likely to deteriorate, should not be in a general ward and likely to be transferred to a critical care unit. She or he may be managed in designated areas with appropriate staffing 3 Patient requires advanced therapeutic support for multiple organ problems FIG 2. STAFF TO BED RATIOS If an acute ward has 24 occupied beds, it needs 23 full time nurses/hcas (based on 22.5% time out) Patients Care level Multiplier 20 Level 0 patients x 0.79 = Level 1a x 1.7 = Level 1b x 1.86 = = 23 FTEs (rounded) dependency levels will be replaced by healthcare resource groups so that ward staffing levels are connected to payment by results (RCN, 2009). Supporting data and algorithms are emerging slowly but none are ready for general use. A recent and important development is the incorporation of patient turnover in busy wards to obtain more accurate workload indicators. Also under development are ward design sensitive staffing formulas. Eventually, separate algorithms for busy admission/assessment single room wards will be available. Ward staff rostering software, such as CareWare ( which combines electronic duty rostering with workload based staffing, are likely to become commonplace. Time task approaches Nursing care plans are commonplace in wards, so it makes sense to attach care times to nursing interventions so that ward staffing can be estimated. The GRASP approach (Anderson, 1997) attaches care times to interventions in patients care plans before adding ward overheads to cover indirect patient care activities. This can be used to estimate nursing hours per patient day. Box 9 outlines the strengths and weaknesses of this method. These systems are commercial and have licensing costs. They also add considerably to ward overheads since detailed, individual care plans are essential although computerising them reduces setting up and maintenance time significantly. Evidence based standard care plans (care pathways) and time task methods go hand in glove and, like healthcare resource groups, care pathways are an exciting development. Regression method The regression formula uses one main ward element such as theatre sessions (in surgery wards), complex nursing procedures (in critical care units) and escorts (in diagnostic wards), to predict how many staff are BOX 11. A REGRESSION EXAMPLE Listed here are 10 (from 138) best practice surgical wards, their weekly total theatre sessions (the independent variable or IV) and full time nurses in the surgical ward team (dependent variable or DV). These data were entered into the regression formula. This predicts, for example, that if your ward has nine theatre sessions each week then you need almost 15 full time RNs. There is a separate regression model for HCAs and this approach can be used with other IVs, such as complex dressings in burns wards. BOX 9. TIME TASK METHOD l Evidence based l Updating is costly l Accurate l Costly, commercial l Easily computerised l Missing care groups l Easily updated l Overhead costly l Links to care l Task oriented nursing pathways BOX 10. REGRESSION METHOD l Best forecaster l Cheaper l Limited supporting literature l Commercial systems are costly l Importing data l Statistics off putting, specialist advice needed l Lacks ownership l Is data from quality assured wards? needed. The strengths and weaknesses of this method are outlined in Box 10. Although its weaknesses outnumber its strengths (Box 10), this method is recognised to be the best forecaster of staffing in areas with predictable workloads, such as planned waiting list theatre cases in the following week. It is simple and cheap to use, when software based, but the licence can be costly. The main weakness is that regression statistics and related language are off putting. Invariably, a statistician s help is needed to explain, for example, predicting beyond the range and its dangers. Theatre sessions (IV) Best practice ward RN FTEs (DV) etc 18 etc 13

5 Finally, some nurses are unhappy about importing data from wards; ownership is missing and imported data may not come from best practice wards. An example of the regression method is outlined in Box 11. CONCLUSION Nursing is a trust s most expensive resource. We know from the SfH WPT (2010b) database that nursing costs per bed vary significantly, and are not always related to service quality. It is therefore important that we systematically evaluate our ward and department staffing. Nurse managers have a choice ranging from methods that are quick, simple and easily used, such as professional judgement, to robust and more expensive time task approaches. Six common methods broadly classified as bottom-up or top-down can be combined so that results can be triangulated. Experienced managers do not aim for quick fixes they argue for staffing changes using reports incorporating results from at least two of the methods described. They should capitalise on the centrally held, free to use nursing data at their disposal. REFERENCES Anderson L (1997) The role and resources required for the introduction of ward assistants using the GRASP systems workload method: a quantitative study. Journal of Nursing Management; 5: Department of Health Expert Working Group (2003) Neonatal Intensive Care Services Report of the Department of Health Expert Working Group. London: DH. tinyurl.com/dhnicsreport Harrison J (2004) Addressing increasing patient acuity and workload. Nursing Management; 11: 4, Hurst K (2009) Gaming and up-coding. Nursing Management; 15: 9, Hurst K (2008) UK ward design, patient dependency, nursing workload, staffing and quality an observational study. International Journal of Nursing Studies; 45: Hurst K (2003) Selecting and Applying Methods for Estimating the Size and Mix of Nursing Teams. Leeds University: Nuffield Institute for Health. If fieldwork is commissioned in your hospital, ensure that data you collect supports all six workforce planning and development approaches. l Kaplan RS (1975) Approaches and techniques. Analysis and control of nurse staffing. Health Services Research; Fall: Royal College of Nursing (2009) Nursing and Payment by Results: Understanding the Cost of Care. London: RCN. tinyurl.com/aboutuspolicy Skills for Health Workforce Projects Team (SfH WPT) (2010a) The Nursing Workforce Planning Tool. tinyurl. com/nursework Skills for Health Workforce Projects Team (SfH WPT) (2010b) The NHS Benchmarking Database. tinyurl.com/ NHSbench Smith et al (2009) Developing, testing and applying instruments for measuring rising dependency-acuity s impact on ward staffing and quality. International Journal of Healthcare Quality Assurance; 22: 1, Telford WA (1979) A method of determining nursing establishments. Hospital Health Services Review; 5: 4, Learning INCREASE YOUR KNOWLEDGE Nursing Times Learning is a new, cost effective way to update your knowledge and skills. Our online units are written by experts and use case scenarios to relate your learning to practice. Our expanding range of units includes: l Conflict resolution: go to l Equality and diversity in the workplace: go to www. nursingtimes.net/equality l Nurse appraisal: go to l Learning and Studying Efficiently: go to net/studying Nursing Times subscribers get five units free activatenow Some of our other units cover: l Common oncological emergencies l Fatigue in cancer patients l Nausea in cancer and palliative care l Secondary lymphoedema in cancer patients l Childhood immunisation l Contraception l Dysphagia l Osteoporosis l Primary nocturnal enuresis l Urgency incontinence in women l Care of patients post myocardial infarction in primary care l Pneumonia l Cervical screening l Anaemia in chronic kidney disease l Non-invasive ventilation for acute hypercapnic respiratory failure l Diabetes in pregnancy l Arterial blood gas interpretation advanced l Leg ulcer management 14