Application of a basic demand & capacity modelling in unscheduled care

1. Application of a basic demand & capacity modelling in unscheduled care

2. Objectives Present an application of simple quantitative methodology we have used for understanding demand and optimising the use of resources in order to achieve timely flow in an unscheduled care setting

3. The results

4. Steps 1. Identify the resource within the pathway to test 2. Understand demand on this resource and its variability 3. Quantify the capacity we have available. 4. Compare demand with capacity

5. Step I - Identify the resource within the pathway to test • Do we have sufficient volumes of medical staff in acute medicine available to meet demand at all hours of the day and for all days of the week? • Currency for demand will need to be a proxy for patients requiring review

6. Step 2 - Understand demand on this resource and its variability Stage 1: Understanding the pathway and the timescales for its delivery – in this case we applied 2 simple pathways for demand based on access method: i) Time into A&E -- (2hrs) -- Start Jnr clerking -- (90 mins) -- Start Snr review ii) Time into MAU -- (0 mins) -- Start Jnr clerking -- (90 mins) -- Start Snr review Stage 2: Understanding the variables within the patient group that may affect the demand that patients place on medical staffing resource eg condition, acuity, history etc etc and that data is readily available for a sufficient volume of patients. In our example, due to the limitations of the data we agreed all patients were equal in terms of time required.

7. Step 2 - Understand demand on this resource and its variability Stage 3: Quantify the distribution of demand by time. - In our example used the timescales as to how the pathway flows in stage 1 to quantify by each 2 hour time band in the day, for each day of the week and each week of the year the volume of patients that would have presented for clerking and for senior review if demand had flowed as expected.

8. Step 2 - Understand demand on this resource and its variability Stage 4: Trend & seasonality analysis of the data using Statistical Process Control & Visual Least Squares trend line Stage 5: A Visual check as to distribution - in this case data was mainly normal although negatively skewed in the small hours Stage 6: If normal: Calculate Mean demand, mean demand plus 1 sd and 2 sd calculated for each of the 84 time bands (1 sd – 84% of time, 2 sd 97.7% of time)

9. Monday’s demand

10. Summary of demand

11. Step 3 - Quantify the capacity we have available. Stage 1: Understand what resources are designated to providing the service and any differentials between them – In our example we need to know the types of staff providing the reviews, what roles they fulfil and the time they take to complete the task. Stage 2: Quantify the number of each different group rostered to work for each two hour time band of the week.

12. The clinicians providing the service and the clinical time they take to clerk and review patients

13. Staffing rosters– Monday

14. Step 3 - Quantify the capacity we have available. Stage 3: Convert the rostered resource available into the same currency as used for quantifying demand. e.g. consultants can provide senior review to 6 patients per hour, whilst SpRs can review 2. Hence over a 2 hour slot if you had 1 consultant and 1 SpR present you would have the capacity to manage 16 patients. Stage 4: Map out the capacity available for each time slot

15. Rostered resource – number of patients who can be clerked every 2 hours

16. Step 4. Comparing demand with capacity

18. Over to you • Where can you apply this approach & where are the priorities at this time? • Social service demand • Community service demand • Do you have access to the necessary data? • Do you have the skills, or access to the skills, to apply the tool? • NLIAH training • How and when are you going to have a go?