Step 7 Practical points / Lessons learnt
- 1. Public data can be mined and extrapolated to make initial PHM assumptions per cluster
- 2. Global trends in causes of mortality and morbidity across the Kingdom may have specific local variations which need to be kept in mind when modelling for interventions and demand- e.g. Sickle Cell disease in E1 or a Renal transplant centre in E1 will have imported cases from other cluster into E1
- 3. Cross boundary transfer of cases or migration of cases will some-times account for large number of care activities which has to be considered in defining the population needs
- 4. Accurate projection of the population size may be difficult and best managed through multiple methods including ELM registration, Abhser address, national ID, Census data etc
- 5. Look at what population-specific data is available within the organisation for analysis, including both healthcare data and non-healthcare data
- 6. Initiate and develop relationships with other local organisations with the aim of using their data for the purpose of PHM. These organisations do not necessarily need to operate in healthcare, as nonhealthcare data is also valuable (wider determinants of health)
