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From Ambition to Reality – Delivering Services in Lean Times

From Ambition to Reality – Delivering Services in Lean Times. Mental Health/Learning Disability (MH/LD) Service Workforce Planning and Development (WP&D) - the Challenges Ahead Keith Hurst k.hurst1@ntlworld.com +44 (0)1623 477418. Presentation Objectives.

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From Ambition to Reality – Delivering Services in Lean Times

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  1. From Ambition to Reality – Delivering Services in Lean Times Mental Health/Learning Disability (MH/LD) Service Workforce Planning and Development (WP&D) - the Challenges Ahead Keith Hurst k.hurst1@ntlworld.com +44 (0)1623 477418

  2. Presentation Objectives • Define healthcare workforce planning and development (WP&D). • Briefly describe five staffing methods; notably their strengths and weaknesses. • Staff a case-study psychiatric unit using at least three methods. • Discuss outcomes emerging from these main methods, notably their clinical, educational and financial implications. • Help service managers select appropriate staffing methods. • Take a look at what’s round the corner, notably Safer Care and DRG-based WP&D.

  3. Defining Workforce Planning and Development (WP&D) Workforce planning and development - the five ‘rights’: Getting service quality right – enough staff with the right skills in the right place at the right time at the right price. However, it’s hard to remember your aim is to drain the swamp when you’re up-to-your backside in alligators!

  4. The Nursing WP&D Context • Rising workload: older, sicker inpatients and rapid throughput; e.g., elderly care (including dementia) ward staff face the fastest rising workload – currently equivalent to nine Dep.1 patients in each bed - yet it remains a Cinderella service. • Hospital staffing is historical and irrational at best. Are staffing differences between best and worse staffed wards justifiable? Consequently, some ward costs are double the average with no discernible service-quality differences. • New policies and practices such as ‘Productive Wards’; e.g., in some wards 20 RNs in 100 do nothing more than document care and handover to nurses on the next shift. Should we sustain that?

  5. Context ... • New WP&D demand and supply issues; e.g., Service-Line Reporting. • Nursing time-out is challenging; i.e., 1 in 4 staff is away from the ward at any time, but should we reward a 6% sickness–absence rate? • Ward design isn’t counted as a staffing factor, yet single-room wards need a 7% staffing uplift - a price worth paying for better privacy and dignity? • Are mandatory-minimum staffing approaches stalling? • Safer Care, Diagnostic Related Groups (DRGs) and E-rostering are gaining momentum.

  6. Classifying WP&D Methods Macro, top-down, population-based methods: • The NHS Benchmarking database, which covers: (i) Primary and community care; (ii) Acute; (iii) Maternity; (iv) Psychiatry/Learning Disabilities; (v) Private hospitals; (vi) Ambulance services; and (vii) Social Services. Micro, bottom-up or workload-driven approaches (from simple to sophisticated): • Professional judgment (consensus) methods; i.e., Telford. • Full-time equivalent (FTE) to bed ratios; e.g., CQC, Dr Foster, UK Best-practice Nursing Database, DRG. • Workload-quality; e.g., UK Best-practice Nursing Database, Safer Care. • Timed-task, e.g., GRASP. • Regression, e.g., Teamwork, Kaplan, Aberdeen. Triangulation opportunities.

  7. Staffing methods – horses for courses Inpatient Community • Benchmarking database. • Professional judgment. • Staff to bed ratios. • Workload-quality. • Timed-task. • Regression.

  8. Using the Benchmarking Database for Community Staffing (Data are from 61 MH/LD disability trusts) A. Mean B. Lwr 95% CI C. Uppr 95% CI 1. MHLD FTEs/bed 13 11 14.9 2. CPN 14.8% 12.9% 16.6% 3. CPHCSW 3.2% 2.1% 4.4% What to do: • Multiply your total establishment by 0.1476 to give the CPN establishment. • Multiply your total establishment by 0.0323 to give the community psychiatric support worker establishment. These multipliers may need converting to staff per capita. They also need weighting according to: (a) service quality; (b) ethnicity; (c) rural vs. urban, etc.

  9. Case Study Admission Ward Case Study Ward • Ward 1 is a dormitory-style, acute, admission ward. • Averages 23 inpatients each day (92% occupancy). • Three consultants admit patients. • Case conference sessions on Tue morning and Fri afternoon. • A named-nurse scheme operates, who run CBT sessions. • Current establishment: Grade FTE Mix Sr WS 1 (5%) Jr WS 1 (5%) Snr SN 6.75 (28%) Jnr SN 6.5 (27%) SWs 9 (37%)

  10. Case Study Ward cont… • Supernumerary students and 4th year interns regularly allocated. • Daily open-visiting from 1400-2100. • A three-shift system operates. • Official breaks are 15 minutes per shift (3.1% in 24 hours). • Annual time-out (sickness-absence, etc.) averages 21.6%.

  11. Professional Judgement (Prof-Jud) Method Expert groups (clinical, finance and personnel managers), armed with local intelligence, agree ward team size and mix by consensus. StrengthsWeaknesses Enduring method No quality measure Good springboard But where next? Handles complex variables Workload insensitive Clinicians vs. Managers Free software Awkward manually Staff-mix easy -

  12. Seven-day Ward Prof-Jud Staffing Formula Calculate how many working hours are required: ShiftLength(hrs)StaffDaysHours 0700-1430 7.5 x 3 x 7 = 157.5 1400-2130 7.5 x 3 x 7 = 157.5 2115-0715 10 x 2 x 7 = 140 Total = 455 Note the shift overlap, which means there are 25 nursing hours per patient day. Must add time-out: 455 hrs x 1.22 (22% time-out) = 555.1 hrs/37.5 hrs =14.8 FTE’s, otherwise there are 19.5 nursing hours per patient day. The software (on your disk) does these calculations automatically.

  13. Alternative Prof-Jud Method For a three-shift system: Twenty-one shifts need ‘staffing’ each week. Each full-time person works five shifts. Therefore: (21/5) x 22% time out = 5.1 FTEs, which provides 1 staff per shift. Therefore, 15.3 (5.1 * 3) FTE nurses/HCAs are needed to allocate three nurses/support workers per shift.

  14. Neonatal Staffing Multiplier Case Study How do ‘cheap’ professional judgment and ‘expensive’ empirical methods compare? • Note SCBU and HDU’s irrational staffing. • Prof-Jud and workload-quality methods equate remarkably well. • Therefore, do we need expensive ward-staffing methods?

  15. Time-out Details ElementAverage Annual leave = 13% Sickness = 6% Maternity leave = 1-6% Study leave = 2% Compassionate, unauthorised unknown Minimum allowance, therefore = 22% N.B., SWs – more sick leave but possibly less holidays. If time-out isn’t funded in your hospital then is that fair?

  16. FTEs per Occupied Bed (POB) Method Uses average FTEs (by grade) per bed from ‘high-quality’ wards: StrengthsWeaknesses Systematically derived Updating costly Excellent benchmarks Which numerator/denominator? - Assumes a fixed workload - Census not throughput Free software Unscrupulous manipulation Universal - all care groups - Accounts for grade-mix’ - Quality assured Unexplained, hidden variables Flexible time-out -

  17. Staff per Occupied Bed Method For example, using (fictitious)‘best practice’ ward averages: PostFTExBeds = Establishment (rounded) Sr WS 0.05 usually fixed at 1 FTE Jr WS 0.08 x 22 = 1.75 Sr SN 0.28 x 22 = 6 Jr SN 0.41 x 22 = 9 SW0.39 x 22 = 8.5 Total 1.21 x 22 = 26.5 FTEs The FTE multipliers include staff on leave and temporary replacements. The FTE multipliers include around 22% (best-practice ward) time-out.

  18. ‘Best Practice’ Psychiatric Wards – Base data Staffing VariableAcuteICUCAMHSCCEMI Wards 59 7 5 69 60 Patients 21 18 8 22 24 FTEs 2.03 2.91 3.52 1.38 2.06 Sr WS 0.08 0.11 0.15 0.06 0.06 Jr WS 0.16 0.19 0.41 0.11 0.08 Sr SN 0.44 0.87 0.9 0.42 0.33 Jr SN 0.49 0.35 1.32 0.22 0.38 SW 0.86 1.39 0.74 0.57 1.21 Time-out 24% 23% 25% 22% 24%

  19. Workload-quality Method Uses a sophisticated algorithm that combines patient dependency, direct care and ward overhead data from ‘best-practice’ wards. StrengthsWeaknesses Accounts for most variables Costly – seven data sets Workload-based Adds to ward ‘overhead’ Flexible system Small-ward problem Free software Importing data Quality-assured workforce - Grade-mix sensitive Skill-mix harder Handles throughput Poor forecaster Ward Layout/Housekeeper Thin data E-rostering software Competition

  20. Workload-quality Method Overview – Psychiatry 8. 247 wards 1. Patient dependency: 2. Nursing activity: ranked according 166k patients in 4 10.4k hrs, 709k to qualitydependency groups observations by grade 7. 12 ward 3. Competencies: layouts Software1k nurses survey 6. Nursing cost 5. Recommended 4. Actual per occupied establishments: establishments: bed: 247 wards 247 wards 247 wards by specialty

  21. Patient Dependency • Dependency classifies patients according to their nursing needs. • Methods are overwhelming. • Two main groups: (i) Medical (e.g., APACHE) vs. nursing (e.g., Safer Care) models; (ii) Long vs. short assessment methods: (a) Leeds acuity-quality – up to 28 criteria (b) Safer Care – 5 criteria • Recalibrating local dependency rating systems.

  22. Psychiatric Patient Dependency Rating Scale (précised) 1. Observation (LoO): Constant (unbroken) observation by at least one nurse (score = 5); Frequent observation (3); General observation (2); Nominal observation (1). 2. Personal Care (HRwPC): Total help and supervision (4); Assistance required (3); Verbal prompting only required.(2); Mainly independent but requires supervision (1). 3. Continence (C): Requires regular toileting/incontinent > 3 times per day (4); Requires regular toileting/incontinent <= 3 times per day (3); Requires regular toileting but is continent (2). 4. Escorting (E): Two or more nurses required (4); One nurse required (3); Ground parole (1). 5. Eating and Drinking (EaD): Patient requires feeding totally by nurses (4); Requires assistance from nurses (2); Requires prompting (include checking diets) (1). 6. Nursing Interventions (NI): Constant intervention by two or more nurses (5); Frequent intervention from one or more nurses (4); Occasional intervention (2); Nominal intervention (1). 7. Parents or Relatives (PoR): Parent/Relative needs constant explanation/reassurance/ support/help (4); Parent/Relative needs frequent help/support (3);Parent/Relative needs occasional help/support (2); Minimum help/support needed (1). Final Rating: > 18 =4; 13-17 = 3; 6-12 =2; <6 =1

  23. Safer Care Levels and Staffing Multipliers There is doubt that Level 1a is a viable group

  24. Service-specific Multipliers (no psychiatry ones to date) Key: AAU – admission and assessment units; CrCU = critical care units; PICU = paediatric intensive care unit; * PICU; ** PICU Multipliers per shift.

  25. Safer Nursing Care Multipliers - Example Our ward averages 23 patients each day, so: LevelPatients x Mtltplr = FTEs (rounded) 0 10 x 0.79 = 8 1a 2 x 1.7 = 3.5 1b 10 x 1.86 = 18.5 2 1 x 2.44 = 2.5 Total 32.5 = up to 6 staff per shift (32.6/5.1).

  26. Long Form Acuity-Quality (A-Q) Algorithm 1. Count dependency categories 1 to 4 patients: LowMediumHigh Dependency:1234 Patients 5 10 7 3 2. Apply average direct care times (see separate sheet): 1234 Daily time (minutes) 46 106 197 336 Times are form ‘custodial’ rather than ‘therapeutic’ wards 3. Convert times to ratios: 1234 Ratios 1 2.3 4.3 7.3

  27. A-Q Algorithm cont ... 4. Multiply ratios (from step 3) by patients (from step 1) to obtain workload index: Dependency:1234Total Ratios: 1 2.3 4.3 7.3 Patients: 5 10 7 3 25 Workload Index: 5 23 30 22 80 Workload index, ‘80’, is the equivalent Dep. 1 patients in the ward or 3.2 (80/25) Dep. 1 patients in each bed. The workload index is an excellent barometer.

  28. A-Q Algorithm cont ... 5. Direct care time for all patients is: 80 (WLI) x 46 minutes (from step 3) = 3680 minutes/60 = 61.3 hours a day. 6. Add indirect care (ward overhead): 61.3/42 x 100 = 146 hours per day x 7 days = 1022 hours per week. 7. Being hard-nosed, deduct (e.g., 10%) unoccupied time: 1022 hours - (1022 x 0.1) = 920 hours. 8. Being fair, add an agreed time-out allowance (e.g., 22%): 920 x 1.22 = 1122 hours a week. 9. Convert to FTEs: 1122/37.5 hours = 30 FTEs.

  29. A-Q Algorithm cont ... 10. Determine staff-mix: GradeMix MultiplierFTE Snr WS 4% (30 x 0.04) = 1 (usually fixed) Jnr WS 11% (30 x 0.11) = 3.25 Snr SN 21% (30 x 0.21) = 6.25 Jnr SN 33% (30 x 0.33) = 10 Snr SW 12% (30 x 0.12) = 3.5 Jnr SW 19% (30 x 0.19) = 5.75 Total = 30 Likely to be one ward leader (Sr WS/CNM II) only. FTEs have been adjusted to create realistic contracts. Senior and junior SWs can be combined, but look out for Band 4 assistant practitioners. Software does calculations automatically.

  30. Acuity Method - ‘Best Practice’ Psychiatric Wards Base Data Variable AcuteICU CAMHS CC EMI • Wards 59 7 5 69 60 • Patients 21 18 8 22 24 • Dep 1% 36 27 20 29 13 • Dep 2% 29 28 39 39 15 • Dep 3% 26 25 32 21 39 • Dep 4% 9 20 9 11 33 • Dep 1 mins 3.3 1.3 1.8 3.5 0.9 • Dep 2 mins 6.2 8.5 6 5.2 3.9 • Dep 3 mins 8 20 15 6 6 • Dep 4 mins 19 30 62 5.1 9.2 • Direct % 54 69 56 51 61 • Breaks % 10 8 9 10 9 • Time out % 24 23 25 22 22 • Snr WS % 4 4 4 4 3 • Jnr WS % 8 6 12 8 4 • Snr SN % 22 30 26 30 16 • Jnr SN % 24 12 38 16 19 • Snr HCA % 17 2 19 9 7 • Jnr HCA % 25 46 2 32 52 • Bed cost £ 81 125 165 60 59

  31. Diagnostic Related Groups – a Sea Change Diagnostic related groups have staffing, service-line reporting, reimbursement and benchmarking uses: DRGFTE per bedCost PbRLong Stay Alzheimer’s 0.81 £56 £104 £208 Palliative care 2.69 £196 £323 £201 Stroke 1.31 £95 £311 £171 Learning disability 1.04 £70 £462 £349 There are few psychiatric DRGs or multipliers.

  32. Timed-Task (T-task) Method Standard times are attached to interventions in the patient’s care plan. Nursing hours per patient day (NHPPD), therefore, are summed timed interventions plus a ‘ward overhead’. StrengthsWeaknesses More accurate Costly, commercial Easily computerised Missing care groups Easily updated Overhead costly Grade-mix sensitive Task-oriented - disliked Care pathways Complex algorithm

  33. Crude Timed-task Method Broad ActivityOne-off set up Maintain (mins) 1. Maintaining a safe environment 117 612 2. Physical/psychological comfort 199 571 3. Breathing 51 1592 4. Eating and drinking 35 485 5. Eliminating 95 388 6. Personal cleansing and dressing 240 253 7. Communicating 0 207 8. Controlling body temperature 33 114 9. Mobilising 16 122 10. Sleeping 0 16 11. Spiritual 0 30 12. Social care 41 20 13. Special needs and requests 40 140

  34. Regression Method The main workload driver, such as: theatre sessions; case mix; complex procedures; escorts, therapy sessions etc., are used to predict staffing. StrengthsWeaknesses Best forecaster Skimpy literature Cheap to maintain Set-up costs are high - Commercial systems costly - Do imported data come from quality- assured wards? - Statistics off-putting, specialist advice usually needed. - Lacking ownership - Predicting beyond the range - RN vs. SW workload drivers.

  35. Regression Example - Psychiatry CBT Sessions (IV) Best Practice Ward RNs (DV) 3 6 7 11 5 8 4 7 8 13 3 5 9 15 4 7 6 10 11… 18 … Constant = 0.64 (formula component) Standard error = 0.40 (sampling distribution standard deviation) R squared = 0.99 (variance explained by IV) Beta = 1.56 (predictor’s relative weight) CBT sessions = 9 = 14.7 FTEs

  36. Over to you … Questions and comments welcome …

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