calculating the global sum and mpig payments - nhs wales · 2015. 10. 27. · v.31/01/04 annex b...

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Annex B Global Sum MPIG Final - 1 -

ANNEX BCALCULATING GLOBAL SUM AND MPIG PAYMENTS

Introduction

B1. This annex:

(i) explains the detailed steps involved in calculating the global sum and MPIG

(ii) illustrates and describes the different spreadsheet tables that LHBs will receive for each contractor along with theirallocations in January 2004. It uses worked examples to show how each table works.

B2. LHB finance departments should read this annex very carefully in order to finalise the construction of indicative contractorbudgets and deal with any queries from their contractors.

Global sum and MPIG calculation method

B3. Table B1 describes each of the steps, the information sources and the calculation method.

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TABLE B1 – CALCULATING THE GLOBAL SUM AND MPIG

Part Step Activity Information Source/Calculation Method

1. Calculating

the global sum

1 Take raw data for each contractor from

the Exeter Attribution Data Set and other

sources provided by the BSC

LHBs will be given a global sum allocation for its GMS

practices in February . This will be based on data from

the April 2003 Attribution Dataset (ADS).

Along with the financial allocation, LHBs will be given

their normalised weighted population, their crude

population and their normalising factor.

The normalising factor is the ratio of the normalised

weighted population to the crude population.

The normalising factor remains constant throughout the

year, and each quarter as the population changes, the

crude population should be multiplied by the

normalising factor to get the new weighted population.

For each quarter, the practice populations should be

normalised against this updated LHB weighted

population.

Practice allocations will be based on the latest quarterly

LHB level Exeter ADS information and information

provided by the Assembly

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2 Calculate the adjustments for:

(i)age and sex of patients on practice list

(ii) patients in nursing and residential

homes

(iii) list turnover for new patients

(iv) additional needs

(i) Table B details the age and sex breakdown of the two

practices after the numbers of patients in each category

have been adjusted to the LHB weighted population.

Table C then weights the patients by the relevant

age/sex weighting factor, as set out in the SFE.

(ii) Table D Nursing and Residential Homes adjustment.

Patients in a nursing or residential home receive a

weighting of 1.43 compared with other patients that

receive a weighting of 1. The nursing and residential

homes patient information is planned to be available

from the Exeter system.

(iii) Table E List Turnover. Patients in their first year of

registration at a practice receive a weighting of 1.46

compared with patients not in their first year. The new

patient count will be available through the Exeter

system.

(iv) Table F Additional Needs. The measure of

standardised limited long-standing illness and the

standardised mortality ratio are used to weight the

practice population for additional needs. These scores

for these will be provided at ward level, and will be

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(v) staff market forces

(vi) rurality

attributed to practices using the patient postcodes from

the Exeter system.

(v) Table G Unavoidable Costs (MFF). This adjustment

takes account of geographical variations in staff costs.

The market forces factor (MFF) is determined by

estimating the unavoidable variation in employment

costs in different parts of the country. Scores for each

of the NES zones will be matched to practices using the

practice postcode.

(vi) Table H Unavoidable Costs (rurality). The distance

of the population from a practice and the density of

that population influence the costs of delivering GMS

services. Information on the distance and density of the

population will be provided through the Exeter system.

3 Create indices for each adjustment so

that they carry equal weight by:

(i) Scaling the weighted populations back

to derive a share of the LHBs weighted

population

(ii) Create an index for each adjustment

by dividing the scaled back weighted

practice population by the crude practice

population

For each of the indices above in Table C to H, the

calculated weighted populations of the two practices

are normalised back to the weighted population of the

LHB

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4 Calculate the Contractor’s Weighted

Population by applying the six indices

simultaneously to the Contractor

Registered Population (CRP) and

normalising to the LHB weighted

population

Table I: each of the index listed in Tables B to G are

multiplied together to generate the contractor

weighting for each practice. This is then multiplied by

the raw practice list size to produce the weighted

population for each practices and then is normalised

back to the LHB’s weighted population

5 Calculate the Initial Global Sum by

multiplying the Weighted population by

£50 per patient in 2004/05, and adding

the London weighting adjustment.

The £50 per patient rate may be subject

to amendment in the light of the on-

formula superannuation indexation

increase

Table J calculates the initial global sum and correction

factor by taking the Normalised Weighted Population

from Table I column J and multiplying it by £50.

6 Calculate the Temporary Patients

Adjustment (TPA) – an off-formula

adjustment. This is described in annex C

of the SFE

This annual sum is based on a five-year average of costs

7 Deduct any monies for additional service

and out of hours opt-outs

This deduction is a percentage of the initial global sum

which is the addition of steps 5,6 and 7 above

8 The result of this is the contractors

Global Sum

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2. Calculating the Global Sum

Equivalent

9 Extract global sum equivalent fees and

allowances plus staff reimbursement

data) between 1st July 2002 and 30th June

2003 from Exeter System uplifted to

2003/04 prices

The next three steps are described in annex D of the SFE

10 Calculate adjusted GSE by taking account

of:

(i) GP vacancies

(ii) practice mergers

(iii) practice splits

(iv) staff vacancies if agreed locally

(v) changes in the list size between the

GSE data collection period and April 2004

The rules are set out in paragraphs 8-19

of annex E of the SFE

For the first calculation in April 2004, LHB’s will need to

adjust the GSE to take account of list size changes. See

annex E MPIG Guidance in the Statement of Fees and

Allowances

11 Calculate the Global Sum Equivalent

(GSE) by uplifting the to 1st April 2004

value

3. Calculating the Correction

Factor

12 Calculate the correction factor by

subtracting global sum from global sum

equivalent after taking account of

historic opt outs from global sum. If

amount is positive, this is the correction

factor before adjustment.

Divide by 12 to give monthly correction

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factor. This together with the monthly

global sum) constitutes the monthly

entitlement under the global sum/MPIG.

13 Adjust the monthly correction factor

where need be to take account of:

(i) to take account of practice mergers

and splits after 1st April 2004.

(ii)to take account of contract

termination.

These are payable only in respect of

number of days for which the contract

runs

The rules are set out in paragraphs 3.8-3.12 of the SFE.

4. Paying and revising the

Global Sum Monthly Payment

and Correction Factor

14 Ensure the payment of the monthly sum

and correction factors where need be by

the end of each month

15 Revise quarterly the:

(i) global sum (expressed monthly) for

changes in both composition and size of

contractor registered population taking

account of mergers and splits.This must

be done on the same day for all

contractors – the 1st day of each quarter

(ii) Monthly correction factor only to take

account of contractor mergers or splits

The information to undertake this calculation will be

derived from the Exeter system.

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16 Revise annually the Temporary Patients

Adjustment (TPA)

In accordance with the guidance

17 Adjust annually the first Global Sum

Monthly Payment of each year to take

account of contractors with QOF

achievement points of less than 100 in

the previous year

18 Uplift annually the price of the

registered patient for the calculation of

the Global Sum Monthly Payment in line

with any changes to the SFE.

As set out in the joint John Chisholm/Mike Farrar letter

of 30th May 2003, as part of the MPIG deal there will be

no uplift in 2005/06

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Worked example for calculation of indicative contractor budgets

B4. This section of the annex illustrates how the method described in the table is put into practice. 12 different spreadsheet tableare used. These are as follows:

Table A - Converting the raw data for each of the practices into a weighted population for the LHBTable B - The raw data for each of the practices scaled by the weighting factor for the LHBTable C - An adjustment for the age and sex structure of the practice listsTable D - A nursing and residential home indexTable E - An adjustment for list turnoverTable F - An adjustment for the additional needs of the patients on the practice listsTable G - An adjustment for the unavoidable costs related to location of the practiceTable H - An adjustment for the unavoidable costs related to the rurality of the practiceTable I - Combining each of the indices – the total weighting for each of the practicesTable J - Calculating the initial Global Sum monthly payment and the correction factorTable K - Adjusting the initial Global Sum monthly payments to take account of opt-outsTable L - Defining the Historic opt-outs adjustment.

B5. Each table is described in turn.

B6. It is worth noting that the steps used to produce the weighted population for the contractor follow a similar pattern:(i) the rawdata is multiplied by a weighting factor, then (ii) each of contractor lists is scaled back so that the sum of contractor lists isequal to the LHB’s weighted population. This scaling process at each of the steps is known as normalisation. It is necessary toensure there is an equal impact for each of the steps in the formula. For example, without the normalisation process, theimpact of the list turnover adjustment may completely dominate all the other adjustments.

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Table A - Converting the raw data for each of the practices into a weighted population for the LHB

B7. The weighted population for the LHB is derived by multiplying the most up-to-date raw population of the LHB by the LHBnormalising index.

B8. The normalising index for each financial year is calculated by the Assembly from data underpinning the allocations. It isderived by dividing the weighted population for the LHB by the raw population for the LHB. Where a LHB has contractorlists with a relatively high weighting, the LHB normalising index will be greater than 1. This means that the weightedpopulation is higher than the raw population count. Whereas for LHBs whose contractors have a low global sum weighting,the LHB normalising index will be less than 1.

B9. In table A, the weighted population is determined by multiplying the raw population count by the LHB normalising index. Theraw population is the sum of all the contractor lists in the LHB and that is shown at the bottom of column H.

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Table A: Practice list and age/sex breakdown (UNWEIGHTED)

LHB normalising

index*

Weighted population this quarter

LHB raw population

in this Quarter

ALL LHB 1.23 14,407 11,750

A B C D E F G H MALES

Age groups 0-4 5-14 15-44 45-64 65-74 75-84 85+ TotalContractor A 100 250 1,000 750 350 150 100 2,700 Contractor B 125 325 1,300 750 350 100 25 2,975

All Males LHB 225 575 2,300 1,500 700 250 125 5,675

FEMALES Age groups 0-4 5-14 15-44 45-64 65-74 75-84 85+ Total

Contractor A 125 250 1,025 700 500 200 200 3,000 Contractor B 125 350 1,300 750 350 100 100 3,075

All Females LHB 250 600 2,325 1,450 850 300 300 6,075

TOTAL Age groups 0-4 5-15 15-44 45-64 65-74 75-84 85+ Total

Contractor A 225 500 2,025 1,450 850 350 300 5,700 Contractor B 250 675 2,600 1,500 700 200 125 6,050

ALL LHB 475 1,175 4,625 2,950 1,550 550 425 11,750

* Provided by the Assembly, by dividing the registered population by the weighted population at a national level

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Table B - The raw data for each of the practices scaled by the weighting factor for the LHB

B10. For the next stages in the calculation, the contractor lists adjusted by each index are normalised back to the weightedpopulation calculated in Table A. This means that the contractor lists by age and sex are scaled so that the aggregate of the allthe contractor lists in the LHB sums to the weighted population of the LHB.

B11. In the example, all the age and sex categories for both of the contractors is increased by 23%. This process ensure that theweighting given to the contractors in each LHB is relative to all contractors in Wales, not just the contractors within the LHB.

B12. Columns A to G of Table B identify the weighted age and sex breakdown of the two contractors. The raw list sizes have beenweighted by taking the lists sizes under each age category from Table A and multiplying them by the LHB's normalising indexof 1.23 *(LHB weighted population [14,407] divided by LHB raw population [11750]).

B13. For example, in Table B the weighted list size for Contractor A in respect of males between 0 and 4 (column A) is derivedfrom multiplying the number of males on Table A within that age band by the LHB's normalising index (100 x 1.23*) to give aweighted population of 123.*

B14. This calculation is followed for each of the categories in turn. At the end it is totalled to give the weighted populations forboth contractors within the LHB.

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TABLE B:Practice list and age/sex breakdown WEIGHTED)

ALL LHB

A B C D E F G HMALES

Age groups 0-4 5-14 15-44 45-64 65-74 75-84 85+ TotalContractor A 123 307 1,226 920 429 184 123 3,310 Contractor B 153 398 1,594 920 429 123 31 3,648

All Males LHB 276 705 2,820 1,839 858 307 153 6,958

FEMALES Age groups 0-4 5-14 15-44 45-64 65-74 75-84 85+ Total

Contractor A 153 307 1,257 858 613 245 245 3,678 Contractor B 153 429 1,594 920 429 123 123 3,770

All Females LHB 307 736 2,851 1,778 1,042 368 368 7,448

TOTAL Age groups 0-4 5-15 15-44 45-64 65-74 75-84 85+ Total

Contractor A 276 613 2,483 1,778 1,042 429 368 6,989 Contractor B 307 828 3,188 1,839 858 245 153 7,418

ALL LHB 582 1,441 5,671 3,617 1,900 674 521 14,407

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Table C - An adjustment for the age and sex structure of the contractor listsB15. The number of patients in each of the age and sex bands is then multiplied by the weighting for each of the bands. So, for

example, a male in the 5-14 age band receives a weighting of 1, compared with a weighting of 6.72 for a female over 85 years.

B16. The contractor lists are then summed. Each of the contractor lists are then normalised so that on aggregate they equal the LHBweighted population. The age/sex index for the contractor is its weighted list size divided by its unweighted list size.

B17. Columns A to G of Table C show the age band weighting as determined by the global sum allocation formula. The weightedlist sizes for each contractor by age and sex are multiplied by the age band weightings to produce an adjusted weightedpopulation. That is then scaled back to the LHB weighted population in order to derive an age band index.

B18. For example, in Table C:

(i) the adjusted weighted population for contractor A in respect of females over 85 years is derived by multiplying theweighted population for this group in Table B by 6.72 (245 x 6.72) to give a figure of 1646

(ii) the same calculation is made for males in this age group (123 x 6.27 = 771) and this is added to the figure for femalesto give a contractor total of 2,417

(iii) the figures for all age groups are totalled to provide a contractor total of 20,314 (column H)

(iv) this is scaled down to derive contractor A’s share of the total weighted population of the LHB of 7,530 (column I).

(v) the scaled down contractor population is then divided by its pre-indexed weighted population to give the age/sex indexfor contractor A of 1.08 (column J).

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TABLE C: Age/sex i d A B C D E F G H I J

Age 0-4 5-14 15-44 45-64 65-74 75-84 85+ Total NormalisedAge/sex i dMale 3.97 1 1.02 2.15 4.19 5.18 6.27

Female 3.64 1.04 2.19 3.36 4.9 6.56 6.72

(Table B * Table C

A)

(Table B B *

col

(Table B C *

col ETContractor A

1,045 625 4,003 4,861 4,802 2,561 2,417 20,314 7,530 1.08 Contractor B

1,166 845 5,116 5,067 3,901 1,439 1,016 18,551 6,877 0.93

Total LHB 2,211 1,470 9,119 9,928 8,703 4,001 3,433 38,864 14,407 1.00

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Table D - A nursing and residential home index

B19. Patients in a nursing or residential home receive a weighting of 1.43 compared with other patients that receive a weighting of1.

B20. In the table below, contractor A has 40 patients in a nursing and residential home (column B), so these are given a weight of1.43 (column D). The remaining patients are unweighted. The weighted and unweighted patients are then added together toderive a weighted population for the practice. This is then normalised, and an index derived.

B21. For example, in Table D:

(i) contractor A has a weighted population (from Table B) of 6989 (column A) and 40 patients in a nursing or residentialhome (column B)

(ii) this figure is multiplied by the common weighting of 1.43 to give an adjusted weighting of 57 (column D)

(iii) the remaining patients of contractor A (column C) are then added to this adjusted number to derive a weighted patientnumber of 7006 (column E)

(iv) this is scaled down to derive contractor A’s share of the total weighted population of the LHB of 6,993 (column F)

(v) the scaled down contractor population is then divided by its pre-indexed weighted population to give the nursing andresidential home index for contractor A of 1.001 (column G).

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TABLE D: Nursing and residential home i d A B C D E F G

Practice population

Patients in residental or nursing home Other patients

Weighted patients in res or nurs home

Total weighted patients Normalised

Nurs & resindex

Weights 1.43 1.00col A - col B B4 * col B col C + col D col F/ col A

Contractor A 6,989 40 6,949 57 7,006 6,993 1.001 Contractor B 7,418 20 7,398 29 7,426 7,413 0.999

Total LHB 14,407 60 14,347 86 14,432 14,407 1.000

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Table E - An adjustment for list turnover

B22. Evidence has shown that in the first year of registration patients require 1.46 times more care than other patients. In theexample below, therefore, the patients within their first year of registration receive a weighting of 1.46. The remaining patientsreceive a weighting of 1. The weighted and unweighted patients are added together, and then the values are normalised to theLHB weighted population.

B23. For example, in Table E:

(i) contractor A has a weighted population of 6,989 (column A) and new patients totalling 350 (column B)

(ii) the number of new patients is multiplied by the common factor of 1.46 to give an adjusted new patient number of 511(column D)

(iii) the remaining patients of contractor A (column C) are added to the adjusted number of new patients to give a revisedweighted population for the contractor of 7150 (column E)

(iv) this is scaled down to derive contractor A’s share of the total weighted population of the LHB of 7,037 (column F)

(v) the scaled down contractor population is then divided by its pre-indexed weighted population to give the list turnoverindex for Contractor A of 1.007 (column G).

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TABLE E: List turnover i d A B C D E F G

Practice l i

Patients within their fi year of

i iOther

i

Weighted registration

Total i h dpatient Normalise

d

List inde

Weight 1.46 1.00col A - col B4 * col col C + col col F / col

Contractor A

6,989

350 6,639

511 7,150

7,03 1.00 Contractor B

7,418

150 7,268

219 7,48 7,369

0.993

Total 14,40 500 13,90 730 14,63 14,40 1.00

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Table F - An adjustment for the additional needs of the patients on the contractor lists

B24. The measure of standardised limited long standing illness and the standardised mortality ratio are used to weight the contractorpopulation for additional need. These measures are derived for each contractor by linking the patients on the contractor listwith the ward in which they live using their postcode. The average value for all the patients on the practice list determines thevalue for the contractor. These values are multiplied by weights that have been determined based on empirical evidence of therelationship between the measures and the utilisation of primary care services.

B25. Again, the weighted populations are normalised and converted into an index for the contractor. For example, in Table F:

(i) the adjustment for contractor A multiplies the weighted population in Column A (from Table B) by the total of theconstant of 48.1198 (column B) and the result of multiplying the weights for long standing illness (column C) andmortality (column D) ratios by the relevant figures for each contractor

(ii) these calculations provide the Contractor’s Need weighted population figure of 341,200 (column E)

(iii) this figure is scaled down to derive contractor A’s share of the total weighted population of the LHB of 7,009 (columnF)

(iv) the scaled down contractor population is then divided by its pre-indexed weighted population to give the needs indexfor contractor A of 1.003 (column G).

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TABLE F: Needs index A B C D E F G

Practice population Constant

Standardised limited long

standing illness (SLLI)

Standardised mortality ratio

< 65 Population

weighted for need Normalised

Needsindex

Coefficients 0.26115 0.23676 col A * (col B + C5 * col C + D5 * col D) col F / col A

Contractor A 6,989 48.1198 1.60 1.20 341,200 7,009 1.003 Contractor B 7,418 48.1198 0.80 0.90 360,075 7,397 0.997

Total LHB 14,407 701,275 14,407 1.000

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Table G - An adjustment for the unavoidable costs related to the location of the contractor

B26. The adjustment in table G is to take account of geographical variations in staff costs. The market forces factor (MFF) isdetermine by estimating the unavoidable variation in employment costs in different parts of the country. The value given toeach contractor reflects the ‘MFF zone’ in which it sits which is mapped using the postcode of the surgery. On average,around 48% of the global sum is accounted for by staff costs, so this is the proportion of the contractor list weighted by theMFF factor.

B27. For example, in Table G:

(i) the adjustment for contractor A takes its weighted population in column A from (Table B) and multiplies it by thecontractor’s MFF for staff of 1.3 (column B) to derive a population weighted for MFF of 9,086 (column C)

(ii) this figure is then multiplied by 48% (the common staff costs percentage) to give the MFF weighted population for“MFF patients” of 4,361 (column D)

(iii) the remaining population unadjusted for MFF of 3,634 (column E) is added to the adjusted population in column D toprovide the overall MFF weighted population of 7,995 (column F)

(iv) this figure is scaled down to derive contractor A’s share of the total weighted population of the LHB of 7,305 (columnG)

(v) the scaled down contractor population is then divided by its pre-indexed weighted population to give the MFF index forcontractor A of 1.045 (column H).

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TABLE G: Unavoidable cost A B C D E F G H

Practice Staff Population

for

Populatioweighted MFF x

Registerepopulation

52 Tota Normalis IndeWeight 0.4 0.5

col A * col B col G / col A

Contractor 6,98 1.3 9,08 4,36 3,63 7,99 7,30 1.04 Contractor 7,41 1.1 8,16 3,91 3,85 7,77 7,10 0.95

Total 14,40 17,24 8,27 7,49 15,76 14,40

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Table H - An adjustment for the unavoidable costs related to the rurality of the surgery

B28. Evidence has shown that the rurality of a practice also affects the cost of delivering services. This is measured in two ways: (i)distance of patients from the practice surgery. The value for the practice is the average distance between the surgery and thepatient’s home for all the patients on the contractor’s list; and (ii) by the average population density of the wards in which allthe contractor’s patients live. This is done by mapping patients to wards using the postcode of the patients on the list.

B29. The rurality weighting is applied to 58% of the practice list, so the other 42% of the practice list is given a weighting of 1. Forexample, in Table H:

(i) the adjustment for contractor A takes the difference between multiplying the weights for average distance (column B)and population density (column C) by the relevant figures for each contractor and multiplies the net figure by theweighted population in column A (from Table B) to arrive at the gross population for rurality of 414,304 (column D)

(ii) this figure is then multiplied by 58% (the common rurality weighting) to give the weighted population for “ruralitypatients” of 240,296 (column E)

(iii) the remaining population unadjusted for rurality of 2,935 (column F) is added to the adjusted population in column E toprovide the overall rurality weighted population of 243,331 (column G)

(iv) this figure is scaled down to derive contractor A’s share of the total weighted population of the LHB of 7,318 (columnH)

(v) the scaled down contractor population is then divided by its pre-indexed weighted population to give the rurality indexfor contractor A of 1.047 (column I).

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TABLE H: Unavoidable cost (rurality)i d A B C D E F G H I

PracticeLog average

distancLog popdensity

Populationweighted for

rurality

Populationweighted

for rurality x58%

Registeredpopulation x

42% Total Normalise RuralityCoefficient 0.05 0.06 0.58 0.42

col A * (col B * 0.05col C *0 06)

col H / colAContractor 6,989 1,200 12 414,30 240,29 2,935 243,23 7,318 1.047

Contractor 7,418 1,100 16 400,87 232,50 3,116 235,62 7,089 0.956

Total 14,407 815,17 472,80 6,051 478,85 14,407

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Table I - Combining each of the indices – the total weighting for each contractor

B30. The next step is to combine all of the indices mentioned above into a single “contractor weighting”. Each index, listed belowin columns B to G, are multiplied together to generate the contractor weighting for each practice. The contractor weighting isthen multiplied by the raw practice population to produce the weighted population, in column I. Finally, the weightedpopulation is normalised to produce the normalised weighted population in column J.

B31. For example, in Table I:

(i) the individual indices for contractor A in columns B to G are multiplied together to derive the contractor weighting of1.192 (column H)

(ii) this is then multiplied by the contractor’s weighted population in column A (from Table B) to produce the adjustedweighted population of 8,328 (column I)

(iii) finally, this figure is scaled down to derive contractor A’s share of the total weighted population of the LHB of 8,242(column J).

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TABLE I: Total practice weighting (combined index)A B C E D F G H I J

col B*C*D*E*F*G col A * Col H

Practice population

Age/sex index

Nursing & Residential

home index

List turnover

indexAdditional

need index MFF index Rurality

indexContractor weighting

Weighted population

Normalised Weighted

Population

Contractor A 6,989 1.077 1.001 1.007 1.003 1.045 1.047 1.192 8,328 8,242 Contractor B 7,418 0.927 0.999 0.993 0.997 0.957 0.956 0.840 6,229 6,165

LHB total 14,407 14,557 14,407

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Table J - Calculating the initial Global Sum Monthly Payment and the correction factor

B32. The next step is to calculate the initial global sum payment and the correction factor. Column D shows the global sum beforeany adjustments. This is calculated by multiplying the normalised weighted population (column C) by £50, taking £50 as anexample level of funding per weighted patient.

B33. Column E then shows a payment of £2.18 for each weighted patient in practices within London PCTs. A London PCT isdefined as any PCT in any of the 5 London SHAs. In this example, just as an illustration, only one contractor in the PCT islocated in London. Contractor B is within a London PCT and so each patient on the raw registered list (6,050, rather than theweighted population of 6165) attracts £2.18 generating around £12,000 for the contractor. I have reinstated this by rejectingthe deletion rather than rewriting the whole thing.B29. Column F shows the historic opt-outs, taken from the global sum.If the contractor did not provide in the 2002-03 baseline period any services now defined as additional services then the valueof the opt-outs in 2002/03 is included here. If the contractor stopped providing the service after the 2002/03 baseline period,the value is kept in the global sum.

B34. In this example, Contractor A previously did not provide maternity services and contraceptive services in the baseline period.Contractor A has a historic opt-out equal to 4.5% of their Global Sum which is made up of a year of opt-outs for maternityservices (2.1%) and contraceptive services (2.4%). Contractor B has no historic opt-outs.

B35. Column G shows the total initial global sum, being the sum of columns D & E. Column H shows the Global Sum Equivalentfor each contractor. Column I shows the difference between the Global Sum Equivalent, and the total initial global sum afterthe historic opt-outs are subtracted (see below for description of historic opt-outs). Column J shows the value of theCorrection Factor for each contractor – if the value of column I is greater than zero, the contractor will receive this value as aCorrection Factor under the MPIG arrangements.

B36. Column K shows the adjustment for temporary patients, to reflect a contractor’s obligation to provide emergency treatment topeople not registered with them, and to provide treatment to temporary residents. This is based on the average annual amount

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claimed for these items over the last five full years, and is explained in detail in the SFE and chapter 5 of the guidance.Column L shows the total global sum (before opt-outs) and correction factor payments for the practice.

B37. Columns M and N simply show the Total Initial Global Sum and Correction Factor as monthly payments.

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TABLE J: Initial Global Sum monthly payment & Correction F t

Funding per 50.00 Funding per patient ( )

2.18 A B C D E F G H I J K L M N

Raw LHB List size

LHB List size weighted by PCT index

Weighted List Size Normalised

to LHBweighted

Global sum

AHistoric opt

outs

Initial Global Sum (Global

Sum GSEGSE-(initial global

sum-historic opt )

MPIG: Correction factor*

Temporary patients

adjustment**

Initial Global Sum and MPIG

payment + Temp patients

adjustment

Total initial Global Sum

monthly payment

Correction factor

monthly payment

(Col C * £50 patient

funding)

(Col A * £2.18 patient

funding)(Table L Col

K) (Col D + E) (Col H - (G - ))

(Col J if Col J > )

(Col G + Col J + Col K)

((Col G + Col K)/12) (Col J/12)

£'000s £'000s £'000s £'000s £'000s £'000s £'000s £'000s £'000s £'000s £'000s

Contractor A 5,700 6,989 8,242 412 0 13.6 412 333 -65 0 £0.00 412 34.34 0.00Contractor B ( )

6,050 7,418 6,165 308 13 0.0 321 340 19 19 £1.20 341 26.89 1.55

PCT total 11,750 14,407 14,407 720 13 734 673 -47 19 £1.20 753 61.23 1.55

* The correction factor is calculated in the first quarter of 2004-05. It is then fixed for the rest of 2004-05, but will be updated annually by a figure determined by the DH** Emergency treatment, immediate necessary treatment and care of temporary residents. Based on rules set out in the SFE

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Table K - Adjusting the initial Global Sum monthly payments to take account of opt-outs

B38. There are a range of services for which the practice can opt out of provision. The penalty for opt out is a percentage reductionin the global sum allocation, these percentages are described in chapter 2 of the guidance. The process for working out thereductions for opt outs is set out in table K. As the global sum is calculated quarterly, the calculation needs to adjust for thefact that opt outs may only apply for part of the quarter. For example, contractor B opted out of child health surveillance forone month of the quarter over which the payment is being calculated. Therefore the opt out penalty is scaled down to reflectthe fact that for only 31 days of the 91day quarter the service was opted out of.

B39. The following table then applies the opt out penalties to the practices total global sum payment (including the TemporaryPatients Adjustment). Column A shows the global sum monthly payment and columns B to I calculate the percentagereduction in the global sum income from outing out of services. Column J is the summed total of percentage opt outs. ColumnK and L then work out the total monetary penalty for the opt out services, and reduces this amount from the global sumcalculation. Column M then calculates the total global sum and MPIG entitlement, building on the GSE calculations in TableJ.

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TABLE K: Adjusted initial monthly payment Opt out of additional

servicesA B C D E F G H I

Cervical Screening

Child Health Serveillance

Minor surgery

Maternity Medical

ServicesContraceptive

services

Childhood immunisation and

pre-school boosters

Vaccinations and

immunisationsOut-of-hours

services% of Initial GSMP 1.1 0.7 0.6 2.1 2.4 1.0 2.0 6.0

Contractor A* 1 0 0 1 0 0 0 0Contractor B* 1 0.3406 0 0 0 0.3406 0 0

Funding implications of opt outsA B C D E F G H I J K L M

Total initial Global Sum

monthly payment

Cervical Screening


Minor surgery

Maternity Medical Services

Contraceptive services


pre-school boosters

Vaccinations and


servicesTotal percentage

opt outTotal value of

opt out

Adjusted Global Sum Monthly

Payment

Total adjusted Global Sum andMPIG monthly

payment (B5 * col B) (C5 * col C) (col B+C+D+E+F+G+H+I) (col A * col J) (col A - col K) (col L + Table J col N

£'000s £'000s £'000s £'000s

Contractor A £34 1.1000 0.0000 0.0000 2.1000 0.0000 0.0000 0.0000 0.0000 3.2000 £1.10 £33.24 £33.24Contractor B £27 1.1000 0.2384 0.0000 0.0000 0.0000 0.3406 0.0000 0.0000 1.6790 £0.45 £26.43 £27.98

Total LHB £61.23 £1.55 £59.68 £61.22

* Based on proportion of quarter for which opt out will be in place e.g. 31 days out of 91 days = 31/91 =

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Table L - Defining the Historic opt-outs adjustment

B40. The historic opt-outs are subtracted from the Initial Global Sum before the correction factor is calculated. It is based on thevalue of services that the practice opted-out of in the months covered by the Global Sum Equivalent. Since the funding forthese services will not be in the GSE, it should also be subtracted from the global sum.

B41. The historic opt-outs are calculated in a similar way to the future opt-outs. There is a fixed percentage reduction in the globalsum for each of the additional services. In this case the Temporary Patients Adjustment is not added to the Global Sum tocalculate the historic opt-out.

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TABLE L: Historic opt outs Opt out of additional services

A B C D E F G H I

Cervical Screening


Minor surgery

Maternity Medical

ServicesContraceptive

services


pre-school boosters

Vaccinations and


services% of Initial GSMP 1.1 0.7 0.6 2.1 2.4 1.0 2.0 6.0

Contractor A* 0 0 0 1 1 0 0 0Contractor B* 0 0 0 0 0 0 0 0

Funding implications of opt outsA B C D E F G H I J K

Initial Global Sum (Global

Sum + London)

Cervical Screening


Minor surgery

Maternity Medical Services

Contraceptive services


pre-school boosters

Vaccinations and


servicesTotal percentage

opt outTotal value of

opt out(B5 * col B) (C5 * col C) (col B+C+D+E+F+G+H+I) (col A * col J)

£'000s £'000s

Contractor A £34 0.0000 0.0000 0.0000 2.1000 2.4000 0.0000 0.0000 0.0000 4.5000 £1.55Contractor B £27 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 £0.00

Total LHB £61 £1.55

calculating the global sum and mpig payments - nhs wales · 2015. 10. 27. · v.31/01/04 annex b...

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