The use of system dynamics in a strategic review of the English dental workforce
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The Center for Workforce Intelligence (CfWI) conducted a strategic review of the English dental workforce using system dynamics modeling to inform decisions about dental student intake levels. The model segmented the dental workforce by age, gender and career stage to project supply and demand through 2040 under different scenarios. Testing showed the projections indicated a risk of oversupply, leading ministers to recommend lowering 2014 intake levels. CfWI was also commissioned to review dental care professionals. The study demonstrated how system dynamics modeling can support robust workforce planning.
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The use of system dynamics in a strategic review of the English dental workforce
- 1. The use of system dynamics in a strategic review of the English dental workforce 32nd International Conference of the System Dynamics Society The CfWI produces quality intelligence to inform better workforce planning that improves people’s lives Dr Graham Willis – CfWI Head of Research and Development Dr Siôn Cave - Decision Analysis Services Ltd Hannah Darvill – CfWI Head of health (medical) Daniele Gioe’ – CfWI Principal Data Modeller Paru Patel – CfWI Senior Analyst
- 2. Contents 1. Introduction 2. Robust workforce planning 3. Purpose of the strategic review of the English dental workforce 4. The English dental workforce 5. The System Dynamics model 6. Impact of the study
- 3. Introductions • The national authority on workforce planning, providing advice and information to the NHS and social care system. • Independent business unit within Mouchel, wholly funded by the Department of Health • Workforce planning is ensuring “The right people, with the right skills, in the right places, at the right time” • Decision Analysis Services Ltd (DAS) is a strategy consultancy based in Basingstoke and Bristol, UK • We are experts in the application of systems modelling and simulation methods in the analysis of policy and strategy
- 4. Contents 1. Introduction 2. Robust workforce planning 3. Purpose of the strategic review of the English dental workforce 4. The English dental workforce 5. The System Dynamics model 6. Impact of the study
- 5. The scale of the health and social care workforce Planned expenditure for 2013/14 is £110bn 55% to 75% is spent on the workforce The English National Health Service employs: 1.4 million people 140,000 Doctors, 370,000 Nurses Similar numbers for social care sector: 1.6 million people employed 22,000 employers 6.4 million unpaid carers
- 6. Robust workforce planning (RWP) Focal question Understand the system Stories about the future Qualitative and quantitative System mapping Explore the future Stakeholder workshops Checked for consistency Expert elicitation of uncertain quantities Probability distributions Simulate the possibilities Supply complicated Demand complex Sensitivity and uncertainty analysis Make robust decisions Test policies against scenarios Decision-makers don’t like uncertainty!
- 7. Contents 1. Introduction 2. Robust workforce planning 3. Purpose of the strategic review of the English dental workforce 4. The English dental workforce 5. The System Dynamics model 6. Impact of the study
- 8. Project purpose CfWI were commissioned to undertake a review to inform the 2014 dental student intake. The objectives of the dental student intake review was to: • support the provision of training for the right blend of dental workforce to meet the needs of the population • inform investment decisions on dental student intake
- 9. Contents 1. Introduction 2. Robust workforce planning 3. Purpose of the strategic review of the English dental workforce 4. The English dental workforce 5. The System Dynamics model 6. Impact of the study
- 10. The dental workforce 0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000 Headcount Workforce, Headcount NHS Dentists Total GDC registered dentists 0 50 100 150 200 250 300 350 400 450 500 20 25 30 35 40 45 50 55 60 65 70 75 80 Workforce age profile Men Women Headcount
- 11. Training to become a dentist 850 860 870 880 890 900 910 920 930 940 2007 2008 2009 2010 2011 Undergraduatesadmitted Year Student intake 0 500 1,000 1,500 2,000 2,500 3,000 UndergraduatestudentsFTE Number of undergraduates Women Men
- 12. Contents 1. Introduction 2. Robust workforce planning 3. Purpose of the strategic review of the English dental workforce 4. The English dental workforce 5. The System Dynamics model 6. Impact of the study
- 13. SD Modelling in relationship to the RWP Horizon scanning Scenario generation Workforce modelling Policy analysis
- 14. Our rigorous approach to SD modelling Workforce Modelling Horizon Scanning Scenario Generation Policy Analysis Model scoping Model construction Model documentation Model testing
- 15. Our rigorous approach to SD modelling Workforce Modelling Horizon Scanning Scenario Generation Policy Analysis Model scoping Model construction Model documentation Model testing
- 16. Model Requirement • Calculate supply and demand for the dental workforces to 2040 • Segment the workforce by age and gender • Represent the training pipeline from entering university through to delivering service as fully qualified dentists • Represent the complex career paths for doctors and dentist following qualification • Execute rapidly and produce outputs that can be readily analysed • Be fully tested and documented, with an audit trail for all assumptions Data Availability Scenario / Policy Questions Specification Model scoping
- 17. Stakeholders • Health Education England • Department of Health • Schools of clinical dentistry • UCAS • NHS • British Dental Association • Dental project reference group • National road shows…. Model construction Dental school Dental foundation training 1 Staff grade Dental core training 1 (includes OMFS) Specialty training - specialist General dental practitioners, salaried dentists and DwSI Additional training Consultant practice Specialist practice Clinical academic training Dental core training 2 2011 stock =4,558 2010 intake =1,013 2012 = 893 2009 = 555 2012 = 22,920 2011 = 142 2012 = 523 2010 = 43 2012 = 36 2012 = 2706* 2012 = 787 2010 = 20
- 18. Model construction segmented by age and gender can include country of origin/qualification, skill and competences includes attrition, delays, exits and returns, migration Include full/part-time working
- 19. Testing included: 1. Independent CfWI testing 2. Comparison with other models 3. Review of the results with relevant stakeholders 4. Sensitivity analysis Testing
- 20. Contents 1. Introduction 2. Robust workforce planning 3. Purpose of the strategic review of the English dental workforce 4. The English dental workforce 5. The System Dynamics model 6. Impact of the study
- 21. Impact The projections produced with the Dental Workforce Model indicated that there was a significant risk of a future oversupply of dentists for England Ministers have agreed to a recommendation from the Chief Dental Officer to change dental school intake. This change will be implemented in the 2014 intake. CfWI has been commissioned to undertake a stocktake of Dental Care Professionals (DCP).
- 23. The use of system dynamics in a strategic review of the English dental workforce 32nd International Conference of the System Dynamics Society The CfWI produces quality intelligence to inform better workforce planning that improves people’s lives Dr Graham Willis – CfWI Head of Research and Development Dr Siôn Cave - Decision Analysis Services Ltd Hannah Darvill – CfWI Head of health (medical) Daniele Gioe’ – CfWI Principal Data Modeller Paru Patel – CfWI Senior Analyst
Editor's Notes
- S. Taylor, People and Organisations, Employee Resourcing (1998) Medical means doctors in this work
- CfWI were commissioned to undertake a review to inform the 2014 dental student intake. This follows the CfWI’s 2012 review of medical and dental student intakes, and HENSE’s recommendation to revisit dental intakes. The objectives of the dental student intake review are to: support the provision of training for the right blend of dental workforce to meet the needs of the population, including exploring the wider use of all members of the dental team and what impact that will have on the need for trained dentists inform investment decisions on dental student intake
- Dental services in the UK are provided by a multi-professional workforce that includes dentists, dental nurses, dental hygienists, dental therapists, orthodontic therapists, dental technicians and clinical dental technicians. The focus of this project was dentists. Dentists currently make up 37% of the total dental workforce (General Dental Council, 2013). In the UK, dentists must be on the General Dental Council (GDC) register in order to practise. In 2013 there were 38,832 UK registered dentists. Dentist may also provide non-NHS services. The Health and Social Care Information Centre’s Dental Statistics for England 2011-12 (HSCIC, 2013a) reported that were 22,920 dentists providing primary care NHS dental services in 2012. There has been a gradual, but steady growth in the number of dentists since 2006/2007, as shown in Figure 1. In addition there have been significant changes to the composition of the dentist workforce. For example, there has been an increase in the number and proportion of women in the workforce. Figure 2 gives the composition of dentists on the 2013 register in terms of age and gender. Understanding the workforce composition is important as workforce attributes, such as attrition, retirement and part-time working vary significantly by age and gender.
- Dentists are highly skilled workforce that undergoes structured training in order to practise. Undergraduate dental education lasts five years. Completion of undergraduate training permits entry to the GDC Register. Following this, mandatory dental foundation training (formerly known as vocational training) is needed for new UK graduates wishing to work in NHS primary care. This training is a minimum of one year full-time (or a part-time equivalent). Training is spent in primary care, providing NHS general dental services. Post-foundation training is undertaken to develop basic skills and experience further, and (in some cases) prepare for specialist training (CfWI, 2013a). The numbers of students undertaking undergraduate training in dentistry has been increasing over recent years. Figure 3 provides the changes in student intake, and Figure 4 the changes in total numbers of undergraduates.
- System dynamics… Better understanding – dynamic behaviour of a system over time Simplify complexity – rich picture of causality, feedback and delays High stakeholder involvement–process provides as much value as end product Robust decisions – avoid policies and futures that lead to unexpected consequences
- S. Taylor, People and Organisations, Employee Resourcing (1998)
- S. Taylor, People and Organisations, Employee Resourcing (1998)
- The workforce models were required to: Calculate the supply and demand for the medical and dental workforces from now through to 2040 Segment the workforce by age and gender Represent the training pipeline from entering university through to delivering service as fully qualified doctors and dentists Represent the complex career paths for doctors and dentist following qualification Integrate with large datasets from a variety of NHS and other official data sources Use the data from the Delphi workshops that define the attributes of the four scenarios Enable policy analysis to be carried out to determine the impact of different policies on the different scenarios Execute rapidly and produce outputs that can be readily analysed Be fully tested and documented, with an audit trail for all assumptions Allow the sensitivity of the input assumptions to be determined. Due to the complexity of the model scope and scale it was decided that the system dynamics approach was best suited to meeting the modelling requirements. Not only does the method allow the complex processes to be represented and to integrate with the complex datasets, but as it based on a graphical representation of the system the stakeholders can be more readily involved in the model validation. Two models were developed, one for the medical workforce and the other for the dental workforce. The models were built using Vensim DSS and Excel. A user interface was developed using Excel to enable non-SD analysts to more easily use the model and carry out policy analysis. The model specification clearly defined the purpose of the model, and defined what was required in the model and equally importantly what was out of scope. The specification was based on the initial model requirement outline in Section 3 and ensured that the developed models only represented what was needed for the purposes of the HENSE review, thus preventing scope creep and mitigating against the risk of late delivery.
- The initial stages of model development were to map out the relevant processes of the training and career pathways with appropriate stakeholders from the medical and dental systems. The maps were created in Vensim and printed out to be shared with the stakeholders. In addition, the process maps were presented at a series of national road shows hosted by the CfWI, which enabled over 80 people to comment and amend the process maps. Numerous stakeholders helped to sense-check the accuracy of the models themselves or helped to provide or sense-check the data and modelling assumptions used. Key sources of help were the DH’s Workforce Data and Analysis Team, the Health and Social Care Information Centre, the BMA, GMC and specific deaneries, UCAS, NHS Pensions, and members of the medical project reference group. Annex A provides details of the stakeholders involved. The large degree of stakeholder engagement throughout the process mapping stage ensured high levels of stakeholder buy-in to the modelling process.
- Following process mapping the process maps were converted into a quantitative model. The model was developed using a combined Vensim and MS Excel architecture. MS Excel was used to create a user interface so that multiple scenarios and policies could be specified and then simulated with Vensim. The model was developed iteratively. As each functional area was completed the model results were shared with experts to determine whether the behaviour for that functional area was sensible and explainable. The medical and dental models contain similar calculation structures. In both models the future demand is calculated based on the current demand for service, future population projections, changes in levels of need and changes in productivity (for example through technological advances) and changes in service delivery. The demand calculation is based on a framework from the Canadian research programme on health human resources. In both models the future supply is calculated based on the simplified career pathways shown above in Figures 3 and 4. The actual career pathways represented within the models are in fact much more complicated, and include attrition from the stocks, exits out of system, inflows from overseas, workforce re-joiners and re-sits. The workforce levels are also broken out into more detailed career progression pathways. Figure 5 provides a more detailed view of the complexity of the medical training and career pathway as implemented in the Vensim SD model. In addition, the supply is segmented by age (from 16 to 80 years) and gender. This enables age and gender dependent impacts to be taken into account, for example attrition and participation rates. The models have been developed so that additional segmentation can be added if required. Finally, the models contain training allocation algorithms and capacity constraints at each stage of the training pipeline. These enable the preference between types of training to be included (for example there a female gender preference for GP Training). This allows the changes in future demography to be considered within the model. Birch, S. Kephart, G. Tomblin-Murphy, G., O’Brien-Pallas, L., Alder, R., MacKenzie, A. (2011) Human resource planning and the production of heath: a needs-based analytical framework, Canadian Public Policy, 33:S1-S16. The extent to which the workforce work full or part time The medical model contains 15 separate influence diagrams, 997 distinct variables and is initialised with 903,525 items of data. This model takes approximately 10 seconds to simulate. The dental model is of similar complexity Each Vensim System Dynamics model is linked to an MS Excel spread sheet. The MS Excel spread sheet contains all the input data used by the Vensim model, including all data references and a complete data audit trail. The table below provides a snapshot of some of the data integrated into the MDSI models: Type Historic range Source Accepted applicants to preclinical dentistry 2007 –11 UCAS Medical school intakes 2007–11 Higher Education Funding Council for England Foundation programme data 2011 Foundation Programme Annual Report Medical and general practice (GP) workforce census for England 2008–11 Health and Social Care Information Centre National population projections 2010 Office for National Statistics Hospital episode statistics for England 2010 –11 Health and Social Care Information Centre The MS Excel spread sheet also acted as a user friendly model interface and allowed the user to: Create, store and edit future scenarios Create, store and edit potential policies Select scenarios and policies to simulate Simulate the SD model Store the results of multiple simulations View and analyse the results of multiple scenarios
- The models were fully documented and tested prior to use for formal policy analysis. This was carried out to ensure that all model assumptions were formally documented and signed off, and that the model had been implemented correctly. Each model was documented in the following ways: A Technical Description was developed that described the model architecture, model assumptions and how the model is used for analysis The MS Excel spread sheet made extensive use of comments to describe the purpose of the cells and contained audit trail cells so that references could be included for each data item Each variable in the Vensim model was documented using the equation editor, and the units were fully defined. A robust, formalised approach to testing was adopted. The purpose of model testing was twofold: To ensure that the model design has been transformed into a simulation model with sufficient accuracy To ensure that the simulation model is sufficiently accurate for the required purpose A test specification was developed based on the model documentation. The test specification detailed all the tests to be carried out on the model, and included tests of the model structure, formulation and behaviour. The test specification ensured that the testing was carried out methodically, and that all areas of the model were tested. The testing was carried out by a CfWI modeller who was independent of the simulation development process. The results of the testing were captured in a spread sheet. The spread sheet identified when and by whom the test was carried out. The outcome of each test was also logged in the spread sheet. If the test resulted in a fail then the fault was corrected by the model developer. The test was then re-run by the model tester to ensure that it had been corrected, and also that the correction had had no wider implications on the model. The model tester also had the freedom to carry out additional tests on the simulation model, and these were also captured in the testing results spread sheet. In addition to the tests identified in the test specification the following analysis was carried out: The results of the model were compared with previous simulation models that represented the medical workforce The projections produced by the model for each stage of the training and workforce pipeline, along with the associated assumptions, were reviewed with relevant stakeholders (for example the chief dental officer) The sensitivity of the model outputs to the input data was tested. The sensitivity analysis was of particular importance. There were varying levels of confidence associated with the input data, and the sensitivity analysis was used to determine whether the model outputs were particularly sensitive to any low quality data. Figure 6 shows a sample sensitivity analysis output chart.
- The projections produced with the Dental Workforce Model indicated that there was a significant risk of a future oversupply of dentists for England Ministers have agreed to a recommendation from the Chief Dental Officer for cut to dental school intake. This reduction will be implemented in the 2014 intake. CfWI has been commissioned to undertake a stocktake of Dental Care Professionals (DCP). This is to ensure the future skill mix is right taking into account the slower growth of dentist workforce and the ability of other team members to undertake many dental care tasks.
- S. Taylor, People and Organisations, Employee Resourcing (1998) Medical means doctors in this work