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- 2. Dentistry Workforce planning ‐ impact
- By illustrating various policy options with the model simulation for 15 years, the author
was able to convince the Ministry of Higher Education and the Ministry of Health, that if the status quo continues, the dental workforce supply dynamics over the next 15 years will be almost the same as today. There will be around 250 dental surgeons seeking government employment throughout the simulation period from 2010 to 2025. Furthermore, although the waiting time to secure government employment will improve, it will be more than three and a half years, throughout the above period.
- Based on this model illustration, the Ministry of Higher Education decided not to increase
the intake of dentistry students for the next ten years. Moreover, the Ministry of Health also accepted the study results and was convinced, based on the advice and recommendations of the author, of the long‐term adverse consequences of having unemployed dental surgeons.
- The Ministry decided to obtain special Cabinet approval to create 400 additional
vacancies in the Ministry of Health within the next three years. With the implementation
- f this proposal, most of the country‟s dental treatment needs could be met, while
harnessing the potential of trained dental manpower in a productive manner to enhance the country‟s health development.
Emergency ncy and and on
demand health health ca care
Brailsford S, Lattimer VA, Tarnaras P, Turnbull C. Emergency and on‐demand health care: Modelling a large complex system. J Oper Res Soc 2004; 55:34‐42 Emergency Care On Demand (ECOD) project, focused on the at the time increasing pressure on emergency medical service use and consequent increasing number of hospital admissions in Nottingham. The project posed four main research questions, based around identifying the current configuration of the system, more precisely defining the present level of demand, how the system could be developed, and to what extent community preferences were driving use of Accident and Emergency (A&E).
Emergency ncy and and on
demand health health ca care
Emergency ncy and and on
demand health health ca care
- Outputs
- Projections from the model suggested that if emergency admissions continued to rise at
the rates experienced, average bed occupancy levels would be unmanageably high within two to three years. The most promising intervention was found to be the diversion of selected elderly patients to specialist investigation centres.
- Impact
- The model was used to investigate patient flows and bottlenecks and as a tool for
provoking and facilitating discussion. The Nottingham steering group for ECOD used the model to test and evaluate different scenarios of care. However, the primary use of the model was for promoting greater understanding of the dynamics of the system rather than in generating numerical outputs.
- The essentially generic framework adopted and the model’s use of routinely collected
data means that this approach can readily be adapted elsewhere.
Factors tha that influence uence ambul bulance ance deman demand
ISSUES:
- Daily, Weekly, Monthly and Seasonal
Fluctuations well understood
- Increasing year‐on‐year demand for
ambulance services
- Recent changes (e.g. introduction of 111
Service) affecting demand, but annual increases before this
- Studies typically look at A & E demand
with ambulance as one factor
- Potential national application
Literature Search Literature Review Build Influence Map Discuss and Amend Map Agree Final Map
4.
Factors tha that influence uence amb ambulan ance deman demand
Sys System em Dynam Dynamics cs Model Model
People who have not yet called an ambulance People calling for an ambulance Proximal Cause 1 Distal Cause 1 Proximal Cause 2 People who have called an ambulance
