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Modelling the Impact of Workforce Change in Social Services

Modelling the Impact of Workforce Change in Social Services. Sally Brailsford 1 , Pei Shan Ang 1 and Peter Knight 2 1 School of Management, University of Southampton, UK 2 Hampshire Social Services, UK. ORAHS 32, Wroc ł aw, Poland, 23-28 July 2006. Basingstoke. Portsmouth.

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Modelling the Impact of Workforce Change in Social Services

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  1. Modelling the Impact of Workforce Change in Social Services Sally Brailsford1, Pei Shan Ang1 and Peter Knight 2 1 School of Management, University of Southampton, UK 2 Hampshire Social Services, UK ORAHS 32, Wrocław, Poland, 23-28 July 2006

  2. Basingstoke Portsmouth

  3. Hampshire Social Services • One of the biggest Departments in England: over 5,000 staff, annual turnover over £300M • Serves population of over 1.2 million people • Divided into 7 regions • Proportion of people over 85 is higher than the national average and is continuing to grow • Nationally, people over 65 use around 40% of the NHS budget and 50% of the Social Services budget

  4. Equipment services • HCC SSD provides services to enable elderly and disabled people to maintain independence and autonomy in their daily lives • Professional assessment service and the loaning of special equipment • Equipment provision service run by the Integrated Community Equipment Service • Two centres in the Hampshire region: • Hampshire Joint Equipment Store (JES) in Basingstoke • Portsmouth Community JES

  5. Current process • Client’s needs assessed by Occupational Therapist (OT) • OT orders equipment from JES or substore • Equipment delivered by van • OT makes second visit to demonstrate equipment and train client in its use: may involve some reassessment

  6. Start OT (or district nurse) visit client Client phones OT Direct Sub-store has inadequate stock OT (or district nurse) assesses client and orders equipment Yes Self assessment? Sub-store makes order/ System shows that certain stocks are below standard level No More than 3 items selected? Yes Staff arranges for OT visit No OT assesses and orders equipment OT Direct (trained staff) processes order JES receives order (via fax, e-form, post, hand) Yes Self collection? JES allocate equipment No Client collects items Delivery and collection tickets being printed Client waits Drivers receive tickets in the afternoon Normal delivery: Within 7-10 working days Urgent delivery : Within 3 working days Collection : Within 2 weeks Assessment through OT Direct/ Equipment collection? Yes No OT visit clients and demonstrate equipment End

  7. Current Problems • Shortage of OTs • Even the most basic equipment currently has to be demonstrated by an OT • Long waiting times between assessment by an OT and receiving the equipment and being able to use it • Inappropriate use of the OTs’ expert skills • Problem likely to get worse in future

  8. Potential Solution • Train van drivers to install and demonstrate equipment • Implications: costs of training and temporary cover for van drivers; need to recruit additional drivers; possible resistance from OT’s • Key question: which specific equipment (of the 900 – 1000 types held in the JES) would it be safe for drivers to demonstrate?

  9. Study Objectives • To determine the optimum number of additional drivers that need to be recruited to maintain the current level of performance and to take on these additional duties • To obtain the overall cash value of the time saving to OT’s from adopting this approach which enables them to focus their time and skills more appropriately

  10. Modelling approach • Discrete-event simulation • Need to allow for variability of input variables. • Allows users to forecast the impact of different scenarios by asking ‘what if’ questions. • Graphical interface as a better communication tool . • Determine number of drivers needed after implementing the proposal. • Spreadsheet model • Convenient “front end” for user to experiment with Simul8 model • To carry out the cost benefit analysis of this proposal.

  11. Data Requirements • Equipment groups • Demand (order arrival rate) • Client numbers • Travel time • Demonstration time • Proportion of clients with special conditions • Maximum hours drivers available for delivery/ collection • Sub-stores replenishment • Costs

  12. Equipment Groups • Different categories for each JES • Categorized, after discussions with OTs, by the following criteria: • Equipment in the same group should have similar demonstration time • Desirable to have equipment of a similar function in the same group

  13. Equipment Groups – Portsmouth JES * (OT): Still requires OT demonstration (Driver): Driver can demonstrate * _xx-yy mins: Estimated demonstration time for equipment in the corresponding group

  14. Demand and Travel Time • Demand data • obtained from the Primary Care Trust Group Reports and Store Activity Reports • analysed based on each group • distributions fitted using BestFit • Travel time from work place to client or from client to client limits the maximum number of clients that a driver or OT can reach in a day

  15. Demonstration time • Vital in deciding the additional task time required from drivers and time saved in OTs • Drivers will be up to 25% quicker than OTs (on average) in demonstration time, as they will not be reassessing the clients

  16. Other data • Clients with special conditions • Drivers might be less suitable to demonstrate to certain clients, e.g. amputees, or clients with terminal conditions, Parkinsons disease etc • Maximum hours drivers available for delivery/ collection • A main determinant of the total duties that can be performed by a driver. • Training and staffing costs

  17. The Simul8 model

  18. Three scenarios • Permanent drivers do not cross-task (swap jobs with other drivers); No agency drivers • Permanent drivers do not cross-task; Agency drivers will be employed when needed • Permanent drivers cross-task; No agency drivers

  19. Results – Basingstoke JES

  20. Results – Portsmouth JES

  21. Cost Benefit Analysis

  22. Payback Period

  23. Conclusions • Both JES need additional drivers if drivers are taking over part of the demonstration tasks from OTs • This proposal will save OT time equating to a cash value of approx £9200 per month • The payback period is less than two months

  24. Thanks are due to • Frances Farrar, Kevan Dyne and Richard Jarczyk from the Portsmouth JES • Dr. Maxwell Chipulu and Korina Katsaliaki from the University of Southampton • Many other HSS staff (OTs and drivers) who were involved directly or indirectly in this project

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