Financial forecasting helps commissioners and providers with financial planning.
The forecast out-turn is a forecast of the spend for each practice for the current financial year, calculated using the expected profile of expenditure for England.
Calculating the forecast out-turn (FO)
Calculation
The FO calculation assumes that each month's expenditure for a practice is in line with the national trend for proportionate spend. This means it's assumed that a practice's cumulative spend to date is the percentage of total spend defined by the national trend. The percentages used are updated each year to reflect the latest trend information.
The FO formula for an existing practice is:
(Cumulative actual cost x 100) ÷ cumulative proportionate spend figure
The FO will not be shown for the first 2 months of the financial year (relating to April and May dispensing) due to the volatility of forecasting over the beginning of the year. The first month that this will be shown, for each financial year, will be for June dispensing.
The profile received in July 2023 will be used to calculate forecast out-turns for 2023 to 2024 prescriptions.
The profile:
- excludes drugs costs met centrally
- includes practice, out of hours, and community nurse prescribing
- is subject to change
The method used to calculate the forecast of primary care prescribing expenditure:
- considers monthly expenditure data from the last five years
- removes the effect of policies (reductions due to PPRS and Category M) from last year's expenditure
- looks at the effect of the number of dispensing days, the position of the month in the year and the year of expenditure
This is collated to predict the monthly expenditure for this year.
The percentage is then applied to data from the monthly Prescribing Monitoring Document.
Revision to the in-year forecast of primary care prescribing expenditure
The profile for 2023 to 2024 is subject to change and is based on the best information available at the time. The profiles will be revised accordingly as further information becomes available.
The Department of Health and Social Care (DHSC) receive a number of queries about our data that we're unable to answer, for example, the treatment of price concessions.
These queries should be directed to those responsible for the data collection or the relevant SICBL policy contact in the NHS.
Forecast out-turn 2023 to 2024
|
Month |
Forecast Profile |
Cumulative Profile |
|---|---|---|
|
April 2023 |
8.88% | 8.88% |
|
May 2023 |
9.64% | 18.52% |
|
June 2023 |
8.15% | 26.67% |
|
July 2023 |
7.78% | 34.45% |
|
August 2023 |
7.96% | 42.41% |
|
September 2023 |
8.29% | 50.70% |
|
October 2023 |
8.30% | 59.00% |
|
November 2023 |
8.32% | 67.32% |
|
December 2023 |
8.33% | 75.65% |
|
January 2024 |
8.49% | 84.14% |
|
February 2024 |
7.80% | 91.94% |
|
March 2024 |
8.06% | 100% |
|
Total |
100% |
|
Forecast out-turns for previous years
Forecast outturn 2022-23 (Word: 14KB)Forecast outturn 2021-22 - Updated (Word: 16KB)Forecast outturn 2021-22 (Word: 20KB)Forecast outturn 2020-21 Revised January 21(Word: 24KB)Forecast outturn 2020-21 (Word: 14KB)Forecast turnout 2019-20 update (Word: 20KB) Forecast turnout September 2019 (Word: 17KB)Forecast turnout April 2019 (Word: 25KB)Forecast turnout April 2018 (Word: 18KB)Forecast turnout April 2017 (Word: 18KB)Forecast turnout November 2016 (Word: 18KB)Forecast turnout April 2016 (Word: 18KB)Forecast turnout November 2015 (Word: 18KB)Forecast turnout April 2015 (Word: 47KB)Forecast turnout December 2014 (Word: 46KB)Forecast turnout October 2014 (Word: 45KB)Forecast turnout April 2014 (Word: 44KB)Forecast turnout December 2013 (Word: 45KB)Forecast turnout November 2013 (Word: 44KB)Forecast turnout April 2013 (Word: 44KB)Forecast turnout August 2012 (Word: 44KB)Forecast turnout April 2012 (Word: 44KB)Forecast turnout August 2011 (Word: 43KB)Forecast turnout April 2011 (Word: 42KB)Forecast turnout September 2010 (Word: 42KB)Forecast turnout April 2010 (Word: 39KB)
Forecast template
Produced by the Department of Health and Social Care (DHSC), the forecast template is intended to support PCOs with their primary care drug spend planning. The output doesn’t state the position of ourselves or DHSC.
View the amended forecast template 2023 to 2024 (Excel: 60KB)
The template uses 5 years of historic data to calculate a forecast spend for each month of the current financial year, taking into consideration:
- the number of dispensing days
- and the month in the year (seasonality)
It can also make adjustments for any policies and local initiatives that will affect prescribing spend.
The template allows organisations to input their own historical data and policy changes/local initiatives.
This forecasting methodology uses similar background data as the forecast out-turn provided in the Prescribing Monitoring Documents, however the forecasts are based upon local data rather than national level profiles applied to local data.
SICBL Prescribing Model Full Write Up (Word: 908KB)SICBL Prescribing Model Overview (Word: 36KB)
Dispensing days
View the number of dispensing days by financial year (Excel: 8KB)
It includes the number of dispensing days per month for the current, future and the previous three financial years.
Dispensing days excludes Sundays and bank holidays.
National average discount percentage
The National Average Discount Percentage is used to calculate actual cost shown in NHS Prescription Services prescribing and financial reports.
It is calculated by: the sum of all discounts ÷ the sum of all basic price x 100.
2023 to 2024
| Used for Reports in | National Average Discount Percentage |
|---|---|
| March 2024 | 5.90 |
| February 2024 | 5.77 |
| January 2024 | 5.73 |
| December 2023 | 5.98 |
| November 2023 | 6.04 |
| October 2023 | 6.33 |
| September 2023 | 6.49 |
|
August 2023 |
6.34 |
| July 2023 | 6.32 |
| June 2023 | 5.91 |
| May 2023 | 5.83 |
| April 2023 | 5.87 |
2022 to 2023
| Used for Reports in | National Average Discount Percentage |
|---|---|
| March 2023 | 6.26 |
| February 2023 | 6.25 |
| January 2023 | 6.31 |
| December 2022 | 6.51 |
| November 2022 | 6.50 |
| October 2022 | 6.62 |
| September 2022 | 6.53 |
| August 2022 | 6.55 |
| July 2022 | 6.50 |
| June 2022 | 6.45 |
| May 2022 | 6.45 |
| April 2022 | 6.43 |
2021 to 2022
| Used for Reports in | National Average Discount Percentage |
|---|---|
| March 2022 | 6.48 |
| February 2022 | 6.38 |
|
January 2022 |
6.45 |
| December 2021 | 6.65 |
| November 2021 | 6.73 |
| October 2021 | 6.81 |
| September 2021 | 6.77 |
| August 2021 | 6.67 |
| July 2021 | 6.75 |
| June 2021 | 6.88 |
| May 2021 | 6.82 |
| April 2021 | 6.86 |
2020 to 2021
| Used for Reports in | National Average Discount Percentage |
|---|---|
| March 2021 | 6.95 |
| February 2021 | 6.86 |
| January 2021 | 6.92 |
| December 2020 | 7.00 |
| November 2020 | 6.98 |
| October 2020 | 7.17 |
| September 2020 | 7.14 |
| August 2020 | 7.02 |
| July 2020 | 7.11 |
|
June 2020 |
7.10 |
| May 2020 | 7.06 |
| April 2020 | 7.04 |
2019 to 2020
| Used for Reports in | National Average Discount Percentage |
|---|---|
| March 2020 | 7.11 |
| February 2020 | 6.92 |
| January 2020 | 7.02 |
| December 2019 | 7.05 |
| November 2019 | 7.07 |
| October 2019 | 7.14 |
| September 2019 | 7.15 |
| August 2019 | 7.16 |
| July 2019 | 7.04 |
| June 2019 | 7.07 |
| May 2019 | 7.13 |
| April 2019 | 7.09 |
2018 to 2019
| Used for Reports in | National Average Discount Percentage |
|---|---|
| March 2019 | 7.09 |
|
February 2019 |
7.14 |
| January 2019 | 7.19 |
| December 2018 | 7.18 |
| November 2018 | 7.23 |
| October 2018 | 7.31 |
| September 2018 | 7.20 |
| August 2018 | 7.22 |
| July 2018 | 7.13 |
| June 2018 | 7.22 |
| May 2018 | 7.19 |
| April 2018 | 7.26 |
2017 to 2018
|
Used for Reports in |
National Average Discount Percentage |
|---|---|
| March 2018 | 7.18 |
| February 2018 | 7.31 |
| January 2018 | 7.33 |
| December 2017 | 7.37 |
| November 2017 | 7.52 |
| October 2017 | 7.43 |
| September 2017 | 7.37 |
| August 2017 | 7.47 |
| July 2017 | 7.48 |
| June 2017 | 7.38 |
| May 2017 | 7.30 |
|
April 2017 |
7.42 |
2016 to 2017
|
Used for Reports in |
National Average Discount Percentage |
|---|---|
|
March 2017 |
7.28 |
|
February 2017 |
7.33 |
|
January 2017 |
7.42 |
|
December 2016 |
7.37 |
|
November 2016 |
7.44 |
|
October 2016 |
7.39 |
|
September 2016 |
7.35 |
|
August 2016 |
7.34 |
|
July 2016 |
7.34 |
|
June 2016 |
7.42 |
|
May 2016 |
7.45 |
|
April 2016 |
7.46 |
2015 to 2016
|
Used for Reports in |
National Average Discount Percentage |
|---|---|
|
March 2016 |
7.43 |
|
February 2016 |
7.46 |
|
January 2016 |
7.64 |
|
December 2015 |
7.54 |
|
November 2015 |
7.63 |
|
October 2015 |
7.54 |
|
September 2015 |
7.48 |
|
August 2015 |
7.56 |
|
July 2015 |
7.52 |
|
June 2015 |
7.48 |
|
May 2015 |
7.51 |
|
April 2015 |
7.52 |
2014 to 2015
|
Used for Reports in |
National Average Discount Percentage |
|---|---|
|
March 2015 |
7.43 |
|
February 2015 |
7.51 |
|
January 2015 |
7.70 |
|
December 2014 |
7.62 |
|
November 2014 |
7.77 |
|
October 2014 |
7.56 |
|
September 2014 |
7.53 |
|
August 2014 |
7.58 |
|
July 2014 |
7.52 |
|
June 2014 |
7.65 |
|
May 2014 |
7.58 |
|
April 2014 |
7.66 |