BMJ 1996;313:595-599 (7 September)

General practice

Influences of practice characteristics on prescribing in fundholding and non-fundholding general practices: an observational study

Robert P H Wilson, research pharmacist,a Juanita Hatcher, senior research fellow in epidemiology,a Stuart Barton, senior lecturer in primary care therapeutics,a Tom Walley, professor of clinical pharmacology a

a Department of Pharmacology and Therapeutics, University of Liverpool, Liverpool L69 3BX

Correspondence to Professor Walley.

Abstract

Objective: To investigate the variation in prescribing among general practices by examining the contribution to this variation of fundholding, training status, partnership status, and the level of deprivation in the practice population and to investigate the extent to which fundholding has been responsible for any changes in prescribing.
Design: Analysis of prescribing data (PACT) for the years 1990-1 (before fundholding) and 1993-4 (after fundholding). Use of multiple linear regressions to investigate the variation among practices in total prescribing costs (net ingredient cost per prescribing unit), prescribing volume (items per 1000 prescribing units), and mean cost per item in each of the two years and also the change in these variables between years.
Setting: Former Mersey region.
Subjects: 384 practices.
Results: The models developed explained the variation in cost per item (43% of variation explained for 1990-1, 38% for 1993-4) and prescribing volume (34% for 1990-1, 38% for 1993-4) better than the variation in total prescribing costs (3% for 1990-1, 7% for 1993-4). The models developed to explain the change in these variables between years did not explain more than 10% of the variation. Most of the explained variation in the change in total prescribing costs was accounted for by fundholding. Of the £3.71 saved by first wave fundholders compared with non-fundholders £3.57 was attributable to fundholding alone.
Conclusion: In neither year did fundholding make a major contribution to the variation in prescribing behaviour among practices, which was better explained by deprivation, training status, and partnership status, but it did seem largely responsible for differences in the rise of total prescribing costs between fundholders and non-fundholders.

Key messages

  • Much of the variation in prescribing practice remains unexplained.

  • Fundholding is the major contributor to the dif- ferences in the rise in prescribing costs between fundholders and non-fundholders.

Introduction

General practice fundholders contain prescribing costs more effectively than non-fundholders and have lower costs and a lower prescribing volume over the initial fundholding period,1 2 3 although this may not be maintained.4 5 In 1994 a minister of health stated to the parliamentary health committee that in 1992-3 "GP fundholders spent £57, non-fundholders spent £61 per patient...not only do fundholders have lower spend per head but these costs are rising less quickly than those of non-fundholders."6 Similar sentiments were expressed recently by the current minister.7

But how much of these differences is attributable to fundholding itself and how much to other factors in the practice? Fundholders tend to differ in the nature of their practice and the patients they serve,8 which may allow them less expensive prescribing and easier containment of costs. Demographics,9 10 deprivation,11 employment levels,12 and morbidity10 are important influences on variations in prescribing costs at the level of health authorities. Research at practice level has focused largely on practice demographics as the basis for the possible allocation of prescribing budgets.13 14 15 With one exception,16 research has not generally considered other factors which contribute to variation in prescribing at practice level, such as true morbidity, variation in doctors' perception of and response to diagnoses,17 socioeconomic factors, historical prescribing patterns, and patient expectations.

Our aim was to investigate the influence of deprivation, training, and partnership or fundholder status on variation in prescribing among practices and to investigate whether changes in prescribing after fundholding were attributable to fundholding alone or to these other factors. Observational studies of a population of practices combined with the use of multiple regression techniques are the most practical way to address these questions, since matching fundholding and non-fundholding practices for all of the possible confounders would be impossible.8

Methods

DATA AND STUDY POPULATION

The study primarily examined three general measures of prescribing (the dependent variables): total prescribing costs (net ingredient cost per prescribing unit; a prescribing unit is a crude measure intended to allow for increased drug use by the elderly: a patient aged under 65 counts as 1 unit, a patient aged 65 and over is 3), volume (items prescribed per 1000 prescribing units), and the average cost per item (net ingredient cost per item). Data about each measure were collected from PACTLINE for the years 1990-1 (as baseline before fundholding) and 1993-4 (after fundholding), as previously described,3 from 412 practices in the former Mersey region. We also examined the change in the dependent variables between 1990-1 and 1993-4.

Four main explanatory variables were investigated: (a) whether a practice became fundholding during the study period, and the wave of fundholding, (b) whether the practice was a training practice (defined as having a general practice registrar at any time during the period of the study), (c) partnership status (multipartner or singlehanded in 1990-4), and (d) the level of deprivation in the practice population. To illustrate the relative importance of these factors compared with historical prescribing, we also used an additional explanatory variable for 1993-4: the value of each prescribing measure in the year 1990-1.

Details of the first three explanatory variables were obtained from health authority data. As a measure of deprivation at practice level, we used the low income scheme index (LISI(C)92).11 This index is based on the percentage of items dispensed that were exempt from prescription charges under the low income scheme in 1992; more deprived practice populations are associated with higher scores. LISI(C)92 scores were available for 94% of practices in the former Mersey region.

Practices which started or ceased during the study period or for which a LISI(C)92 score was unavailable were excluded. The final study population was 384 practices, roughly 85% of the practices in the region in March 1994.

ANALYSIS

The median and interquartile range for the primary dependent variables were calculated for each quartile of the LISI(C)92 index and for each level of the other explanatory variables for both the first period (1990-1, before fundholding) and the last (1993-4, after fundholding). The differences between the years were also calculated. Data for intervening periods were also examined but added no new information and so are not given here.

Stepwise multiple linear regressions, using SPSS, examined the relations between dependent and explanatory variables. The natural logarithms of all the dependent variables except for the changes between years were used to normalise the residuals. In analysing the changes between years arithmetic differences were used. First order interactions of the explanatory variables were also examined. A significance level of 0.05 was used for both inclusion and exclusion of variables in the analysis.

Results DISTRIBUTION OF PRACTICE CHARACTERISTICS.

Early waves of fundholders had proportionately more training practices, fewer singlehanded practices, and lower LISI(C)92 scores than later waves or non-fundholders. Similarly, training practices were more likely to have multiple partners and lower LISI(C)92 scores than non-training practices. Singlehanded practices tended to have higher LISI(C)92 scores (table 1). 


Table 1--Distribution of practice characteristics. Values are numbers (and percentages)
-------------------------------------------------------------------------------------------------------------------------------------------------
                                                            Fundholding                               Training                 Partners
-------------------------------------------------------------------------------------------------------------------------------------------------
                                             First         Second        Third        Non-
                                             wave           wave         wave      fundholders                   Non-       Multi-      Single-
                                            (n = 18)       (n = 27)     (n = 48)    (n = 291)      Training     training    partner     handed
-------------------------------------------------------------------------------------------------------------------------------------------------
Training
Training (n = 62)                           13 (21)          7 (11)     11 (18)      31 (50)
Non-training (n = 322)                       5 (2)          20 (6)      37 (12)     260 (81)
Partners
Multipartner (n = 301)                      18 (6)          24 (8)      40 (13)     219 (73)       60 (20)       241 (80)
Singlehanded (n = 83)                        0 (0)           3 (4)       8 (10)      72 (87)        2 (2)         81 (98)
Deprivation
LISI(C)92 quartile 1 (0, 8.9) (n = 98)      12 (12)          8 (8)      16 (16)      62 (63)       31 (32)        67 (68)     83 (85)     15 (15)
LISI(C)92 quartile 2 (9, 16.3) (n = 95)      4 (4)           9 (10)     12 (13)      71 (74)       11 (12)        84 (88)     81 (85)     14 (15)
LISI(C)92 quartile 3 (16.4, 23.9) (n = 97)   1 (1)           7 (7)       9 (9)       80 (83)       11 (11)        86 (87)     74 (76)     23 (24)
LISI(C)92 quartile 4 (24, 59.6) (n = 94)     1 (1)           3 (3)      11 (12)      79 (84)        9 (9)         85 (90)     63 (67)     31 (33)

TOTAL PRESCRIBING COSTS (NET INGREDIENT COST PER PRESCRIBING UNIT)

Median total prescribing costs increased over the study period (table 2). The median cost was lower for first wave fundholders than for other groups, for which costs were broadly similar. Training practices had a lower median cost than non-training practices for both years. Costs for single and multipartner practices were similar. Costs for practices in the lowest quartile of the LISI(C)92 scores were lower than for other practices for both years. 


Table 2--Median and interquartile range for total prescribing costs (net ingredient cost (£) per prescribing unit) for all
explanatory variables in both years and for the difference between years
------------------------------------------------------------------------------------------------------------------------------------------
                                                                Median (interquartile range) cost (£)
------------------------------------------------------------------------------------------------------------------------------------------
                                                     1990-1                    1993-4
                                  No of             (before                    (after                                   Difference
Practice type                   practices         fundholding)              fundholding)                              between years
------------------------------------------------------------------------------------------------------------------------------------------
First wave fundholder               18          34.46 (31.22-37.60)       44.97 (43.54-48.69)                        10.89 (9.92-13.67)
Second wave fundholder              27          38.02 (34.61-41.84)       51.45 (47.26-55.08)                        12.41 (10.42-14.21)
Third wave fundholder               48          38.05 (34.94-40.39)       52.83 (49.49-55.15)                        14.83 (11.28-17.60)
Non-fundholder                     291          39.25 (34.70-43.62)       54.44 (48.85-60.59)                        15.08 (11.84-18.14)
Training                            62          36.09 (33.37-39.77)       49.23 (45.96-55.48)                        13.68 (11.20-16.49)
Non-training                       322          39.40 (34.86-43.37)       54.26 (49.43-59.35)                        14.69 (11.14-17.81)
Multiple                           301          38.53 (34.69-42.20)       53.82 (48.38-58.77)                        14.79 (11.81-17.81)
Singlehanded                        83          39.61 (33.43-45.65)       53.75 (47.56-58.34)                        13.16 (9.98-17.40)
LISI(C)92 quartile 1 (0, 8.9)       98          36.72 (33.26-40.47)       49.94 (45.30-54.92)                        12.79 (10.79-16.00)
LISI(C)92 quartile 2 (9, 16.3)      95          39.57 (35.66-43.53)       54.05 (49.76-59.17)                        14.06 (11.03-17.34)
LISI(C)92 quartile 3 (16.4, 23.9)   97          39.61 (35.06-43.76)       54.93 (49.44-59.90)                        15.15 (11.16-17.70)
LISI(C)92 quartile 4 (24, 59.6)     94          39.32 (36.65-44.08)       55.78 (49.89-62.08)                        16.90 (12.64-19.65)

In 1990-1 only 3% of the variation in prescribing costs could be explained by our explanatory variables (table 3). The models that explained most variation included fundholding wave alone or training status alone. There was no difference between the fit of the two models. None of the other explanatory variables contributed significantly to either model. For 1993-4 only 7% of the variation in prescribing costs could be explained by any model based on the four main explanatory variables (table 3). With the inclusion of prescribing costs for 1990-91 as an additional explanatory variable, the percentage of variation explained increased to 67% (not shown). 


Table 3--Regression equation for model explaining variation in total prescribing costs (net ingredient cost per prescribing unit)
-------------------------------------------------------------------------------------------------------------------------------------------------------------
                                                    1990-1 (loge)                         1993-4 (loge)          Arithmetic difference
                                                (before fundholding)                        (after fundholding)                 between years
-------------------------------------------------------------------------------------------------------------------------------------------------------------
                                                      r2 = 0.025                        r2 = 0.067                     r2 = 0.095
                                           Coefficient             SE        P     Coefficient             SE      P    Coefficient             SE       P
-------------------------------------------------------------------------------------------------------------------------------------------------------------
Constant                                     3.591                0.023              3.965               0.017            14.09                0.59
First wave fundholders v non-fundholders                                            -0.145               0.039   0.002    -3.57                1.34    0.008
Second wave fundholders v non-fundholders                                           -0.071               0.032   0.026    -3.30                1.09    0.003
Third wave fundholders v non-fundholders                                            -0.032               0.025   0.192    -0.39                0.85    0.645
Single-handed v multiple partners                                                                                         -2.87                0.69   <0.001
Non-training v training                      0.078                0.025    0.001
LISI(C)92                                                                            0.002               0.001   0.045     0.093               0.027   0.001

The median differences in prescribing costs between 1990-1 and 1993-4 (table 2) increased with increasing LISI(C)92 score and with wave of fundholding. Only 10% of the variation in these differences was explained by any model based on the four main explanatory variables (table 3).

The mean difference in prescribing costs between fundholders and non-fundholders and its implications are calculated for first wave fundholders in the box.

PRESCRIBING VOLUME (ITEMS PER 1000 PRESCRIBING UNIT)

The median prescribing volume increased over the study period (table 4). In 1990-1 fundholders had a lower median volume than non-fundholders; early wave fundholders had a lower volume than later waves. A similar pattern was seen in 1993-4. Median volumes were lower in training and multipartner practices, while they increased with increasing LISI(C)92 score. 


Table 4--Median and interquartile range for prescribing volume (items per 1000 prescribing units) for all explanatory
variables in both years and for the difference between years
---------------------------------------------------------------------------------------------------------------------
                                                           Median (interquartile range)
---------------------------------------------------------------------------------------------------------------------
                                                         1990-1                1993-4
                                       No of            (before                (after             Difference
Practice type                        practices        fundholding)          fundholding)        between years
---------------------------------------------------------------------------------------------------------------------
First wave fundholder                    18         5806 (4764-6428)      6608 (5639-7099)       705 (607-1042)
Second wave fundholder                   27         6442 (5490-7430)      7439 (6344-7804)       749 (265-1020)
Third wave fundholder                    48         7073 (5936-7956)      7844 (6746-8769)       885 (405-1190)
Non-fundholder                          291         7376 (6287-8355)      8223 (7038-9427)       850 (469-1338)
Training                                 62         6078 (5395-7066)      7017 (6176-7931)       891 (625-1215)
Non-training                            322         7414 (6345-8347)      8250 (7005-9430)       817 (385-1305)
Multiple                                301         6894 (5983-7890)      7748 (6658-8845)       825 (472-1216)
Singlehanded                             83         8096 (7205-9166)      8992 (7876-10197)      763 (249-1436)
LISI (C)92 quartile 1 (0, 8.9)           98         6000 (5222-6787)      6706 (5991-7546)       705 (300-1008)
LISI(C)92 quartile 2 (9, 16.3)           95         6826 (6119-7713)      7734 (6687-8702)       746 (457-1148)
LISI(C)92 quartile 3 (16.4, 23.9)        97         7567 (6734-8448)      8420 (7485-9349)       881 (469-1269)
LISI(C)92 quartile 4 (24, 59.6)          94         8060 (7309-9126)      9374 (8456-10145)     1165 (494-1561)

Thirty four per cent of the variation in prescribing volume in 1990-1 could be explained (table 5). The best model included the LISI(C)92 score, the training status of the practice, and the partnership status of the practice. For 1993-4 these same variables explained 38% of the variation (table 5). With the inclusion of the prescribing volume for 1990-1 as an additional explanatory variable the percentage of variation explained increased to 85% (not shown). Fundholding status did not contribute significantly to these models. 


Table 5--Regression equation for model explaining variation in prescribing volume (items per 1000 prescribing units)
--------------------------------------------------------------------------------------------------------------------
                                              1990-1 (loge)                         1993-4 (loge)
                                          (before fundholding)                        (after fundholding)
--------------------------------------------------------------------------------------------------------------------
                                                  r2 = 0.343                       r2 = 0.382
                                     Coefficient            SE        P     Coefficient            SE         P
--------------------------------------------------------------------------------------------------------------------
Constant                               8.582               0.026              8.707               0.021
Singlehanded v multiple partners       0.114               0.024    <0.001    0.083               0.022    <0.001
Non-training v training                0.112               0.027    <0.001    0.079               0.024     0.001
LISI(C)92                              0.009               0.001    <0.001    0.011               0.001    <0.001

The largest increases in median volume between 1990-1 and 1993-4 were seen in third wave fundholders, training practices, and multipartner practices. The differences increased with increasing LISI(C)92 score (table 4). No simple model with any of our explanatory variables could explain the variation in these changes.

COST PER ITEM (NET INGREDIENT COST PER ITEM)

The median cost per item rose during the study period (table 6). In 1990-1 the median cost per item was higher in first and second wave fundholders than in third wave fundholders or non-fundholders. In 1993-4, however, there was little difference between any wave of fundholders or between fundholders and non-fundholders. Cost per item decreased with increasing LISI(C)92 score in both years and was higher in training or multipartner practices. 


Table 6--Median and interquartile range for cost per item (net ingredient cost (£) per items) for all explanatory vari-
ables in both years and for the difference between years
---------------------------------------------------------------------------------------------------------------------------------------
                                                           Median (interquartile range) cost (£)
---------------------------------------------------------------------------------------------------------------------------------------
                                                          1990-1                     1993-4
                                         No of           (before                     (after                  Difference
Practice type                          practices       fundholding)               fundholding)              between years
---------------------------------------------------------------------------------------------------------------------------------------
First wave fundholder                      18         5.85 (5.71-6.79)          6.91 (6.61-7.86)           1.04 (0.87-1.21)
Second wave fundholder                     27         5.86 (5.06-6.42)          7.07 (6.19-7.48)           1.19 (0.69-1.40)
Third wave fundholder                      48         5.48 (4.94-6.33)          6.87 (6.25-7.54)           1.23 (0.98-1.49)
Non-fundholder                            291         5.47 (4.96-6.02)          6.78 (6.01-7.43)           1.26 (0.91-1.58)
Training                                   62         5.91 (5.45-6.60)          7.18 (6.64-7.94)           1.24 (0.93-1.49)
Non-training                              322         5.46 (4.92-5.46)          6.75 (5.91-7.40)           1.21 (0.91-1.58)
Multiple                                  301         5.66 (5.13-6.17)          6.98 (6.41-7.58)           1.26 (0.97-1.59)
Singlehanded                               83         4.91 (4.45-5.47)          5.90 (5.37-6.81)           1.03 (0.68-1.43)
LISI(C)92 quartile 1 (0, 8.9)              98         6.12 (5.62-6.82)          7.55 (6.82-8.27)           1.28 (1.00-1.58)
LISI(C)92 quartile 2 (9, 16.3)             95         5.73 (5.31-6.21)          7.06 (6.47-7.66)           1.36 (0.92-1.63)
LISI(C)92 quartile 3 (16.4, 23.9)          97         5.36 (4.91-5.87)          6.66 (5.93-7.27)           1.17 (0.88-1.45)
LISI(C)92 quartile 4 (24, 59.6)            94         4.89 (4.34-5.27)          6.03 (5.34-6.72)           1.14 (0.81-1.53)

In 1990-1, 43% of the variation in the cost per item was explained (table 7). The best model included partnership status, LISI(C)92 score, and an interaction between partnership status and fundholding wave. In 1993-4 38% of the variation in cost per item was explained by a model including partnership status and LISI(C)92 score. Inclusion of cost per item data from 1990-1 as an additional explanatory variable increased the variation explained to 75% (not shown). 


Table 7--Regression equation for model explaining variation in cost per item (net ingredient cost per item)
----------------------------------------------------------------------------------------------------------------------------------------------------------
                                                    1990-1 (loge)                         1993-4 (loge)          Arithmetic difference
                                                (before fundholding)                        (after fundholding)                 between years
----------------------------------------------------------------------------------------------------------------------------------------------------------
                                                      r2 = 0.425                        r2 = 0.384                     r2 = 0.061
                                           Coefficient             SE        P     Coefficient             SE      P    Coefficient             SE     P
----------------------------------------------------------------------------------------------------------------------------------------------------------
Constant                                     1.878               0.0150              2.083               0.014             1.53                0.07
First wave fundholders v non-fundholders     0.025               0.033     0.449                                          -0.40                0.15  0.008
Second wave fundholders v non-fundholders    0.024               0.029     0.405                                          -0.23                0.12  0.063
Third wave fundholders v non-fundholders     0.011               0.023     0.607                                          -0.08                0.10  0.385
Singlehanded v multiple partners            -0.078               0.018    <0.001    -0.107               0.018  <0.001    -0.23                0.08  0.004
LISI(C)92                                   -0.009               0.001    <0.001    -0.009               0.001  <0.001    -0.01                0.00  0.006
Singlehanded/first wave fundholders
Single handed/second wave fundholders        0.031               0.084     0.713
Single handed/third wave fundholders        -0.155               0.055     0.005

The median difference in cost per item between 1990-1 and 1993-4 was lower for first wave fundholders and singlehanded practices. The difference decreased with increases in LISI(C)92 score (table 6). Only 6% of the variation in the difference could be explained by a model which included fundholding status, partnership status, and LISI(C)92 score (table 7).

Discussion

VARIATIONS AMONG PRACTICES

The models described above explain the variations in cost per item and prescribing volume better than they explain the variation in total prescribing costs. Adding historical prescribing to the models greatly increased the amount of variation explained for 1993-4. "Historical prescribing" covers a multitude of factors which we have been unable to disentangle in this study, such as morbidity or perceived morbidity, factors pertaining to doctors and their readiness to prescribe, and patient expectations.

These findings do not support the suggestion that fundholders are less expensive prescribers simply because they have become fundholders.6 Even before fundholding, future fundholders, particularly future first wave fundholders, tended to have lower total prescribing costs and volumes than non-fundholders but a higher cost per item. A similar pattern was seen in training practices compared with non-training practices, in less deprived practices compared to more deprived practices, and, except for similar total prescribing costs, in multipartner practices compared with singlehanded practices.

There are clear links between these factors: fundholding practices tended to be multipartner practices, were more likely to be training practices, and were more likely to have low LISI(C)92 scores. Criteria for becoming fundholders included practice size (11 000 for the first wave, but since relaxed) and a high degree of organisation (also a requirement for training). Such practices may possibly be more in control of prescribing, but are also more likely to be in affluent areas.8 Conversely, non-fundholding practices were less likely to be training practices and more likely to be singlehanded than fundholders. They also often had higher LISI(C)92 scores and tended to be concentrated in less affluent areas.18

The pattern of high cost per item and low volume (and often lower total prescribing costs) is seen in practices with more affluent patients. This may be explained by these patients, who tend to be liable for prescription charges, buying relatively inexpensive but widely used drugs such as paracetamol over the counter. Less affluent patients, who may be exempt from prescription charges because of low income, might seek prescriptions for such drugs. Some of the difference in rates of prescribing will also be explained by higher morbidity in more deprived areas,19 but it is impossible in this study to separate deprivation and morbidity.

Such a pattern is also found between health authorities. For example, in 1994 relatively affluent Oxford had a prescribing cost/patient/year of £58.37; items/patient/ year of 7.2; cost/item of £8.06, and the sixth lowest LISI(C)92 score of the 90 family health service authorities in England, whereas the more deprived St Helens in Mersey had a prescribing cost/patient/year of £81.21, items/patient/year of 12.4, cost/item of £6.55, and the fourth highest LISI(C)92 score.11 20

VARIATION OVER TIME

Changes in prescribing volume between the years were not well explained by any of the variables studied. Changes in cost per item were explained to a very limited extent by factors including fundholding, deprivation, and partnership status.

Changes in total prescribing costs before and after fundholding were partly explained by models including fundholding wave, partnership status, and deprivation. Although our model explained only a small amount of the variation, fundholding was the major contributor to the model, with fundholding alone accounting for £3.57 of the £3.71 difference in increase in total prescribing costs between first wave fundholders and non-fundholders (see box). A similar pattern can be shown for second and third wave fundholders but is less marked because of their shorter time as fundholders up to 1993-4. Therefore at present it seems reasonable to attribute differences in the rate of rise of the drug bill between fundholders and non-fundholders to fundholding itself. Although fundholding is not yet making a significant contribution to differences in overall prescribing costs between practices, this may occur in the future unless non-fundholders become as successful as fundholders in restraining cost increases.4 A limitation of this study is that we looked at only four easily available practice characteristics to try to explain the variation in prescribing. Many other variables could have been considered, such as dispensing status or personal characteristics of general practitioners, and have been studied at both authority10 and practice level.16 Obviously such factors are not mutually exclusive. Other limitations to this study include the measures studied3: for instance, the LISI(C)92 index has not been validated at the practice level,21 22 although it correlates well with other measures of deprivation at health authority level.11 Similarly, the item is a poor measure of true prescribing volume23 and may further confuse effects of deprivation, since doctors may prescribe more drug in a single item to patients known to pay prescription charges (hence producing higher cost, lower volume prescribing). Furthermore, we have not considered important changes within specific therapeutic areas which may influence clinical outcomes.24 


How much influence has fundholding itself on changes in total
prescribing costs?
  Total prescribing costs are taken on net ingredient cost per prescribing unit (NIC/PU)
  The regression equation derived in table 3 is:
  Predicted mean change in NIC/PU between 1990-1 and 1993-4 = 14.09 -
  3.57 (fundholding wave 1) - 3.30 (fundholding wave 2) - 0.39 (fundholding
  wave 3) - 2.87 (partnership status: 0 for multipartner, 1 for singlehanded) +
  0.09LISI(C)92.
  Thus, for example, a first wave fundholding practice is predicted to have
increased its NIC/PU by £3.57 less than a similar non-fundholding
practice--that is, one with the same LISI(C)92 and partnership status.
  To calculate the mean predicted change for fundholders, for example, in the
first wave we can use this equation substituting the proportion of singlehanded
fundholders (none in wave 1) for partnership status and the mean LISI(C)92
score (9.07 for first wave fundholders).
   Thus for first wave fundholders:
   Predicted mean change in NIC/PU =
   14.09 - 3.57(1) - 3.30(0) - 0.39(0) - 2.87(0) + 0.09(9.07) = £11.34
                                                               (equation a)
that is, first wave fundholders are predicted by this model to increase their
NIC/PU by £11.34.
  The equation for non-fundholders, whose proportion of singlehanded
practices is 0.25 and whose mean LISI(C)92 is 18.65, is:
  Predicted mean change in NIC/PU =
  14.09 - 3.57(0) - 3.30(0) - 0.39(0) - 2.87(0.25) + 0.09(18.65 = £15.05
                                                                  (equation b)
that is, non-fundholders are predicted to increase their NIC/PU by £15.05.
  We are interested in the relative increase of first wave fundholders compared
with non-fundholders.
  Subtracting equation (b) from (a) gives the predicted mean change in NIC/PU
of first wave fundholders compared with non-fundholders:
   = (14.09 - 14.09) - 3.57(1 - 0) - 3.30(0 - 0) - 0.39(0 - 0)
     - 2.87(0 - 0.25) + 0.09(9.07 - 18.65)                         (equation c)
   = 0-3.57 + 0.72 - 0.86 = - 3.71
that is, first wave fundholders are predicted to save £3.71 per prescribing unit
compared with non-fundholders, and fundholding is the major contributor to
this, accounting for £3.57 of the predicted £3.71. The impact of LISI(C)92 and
partnership status largely cancel each other out.

Nevertheless, our conclusion is that ministerial suggestions that the less expensive prescribing of fundholders is due to their fundholding status are incorrect at present, but the claim that fundholding has affected the rate of rise of prescribing costs is supported by our data.

We thank the participating fundholding practices, and medical and pharmaceutical advisers in the family health services authorities of Mersey region for their cooperation and the Prescribing Research Unit, University of Leeds, for providing LISI(C)92 data.

Funding: North West Regional Health Authority.

Conflict of interest: None.

  1. Bradlow J, Coulter A. Effect of fundholding and indicative prescribing schemes on general practitioners' prescribing costs. BMJ 1993;307:1186-9.
  2. Maxwell M, Heaney D, Howie JGR, Noble S. General practice fundholding: observations on prescribing patterns and costs using the defined daily dose method. BMJ 1993;307:1190-4.
  3. Wilson RPH, Buchan I, Walley T. Alterations in prescribing by general practitioner fundholders: an observational study. BMJ 1995;311: 1347-50.
  4. Wilson RPH, Walley T. Prescribing costs in general practice fundholding. Lancet 1995;346:1710-1.
  5. Stewart-Brown S, Surender R, Bradlow J, Coulter A, Doll H. The effects of fundholding in general practice on prescribing habits three years after the introduction of the scheme. BMJ 1995;311:1543-7. [Abstract/Free Full Text]
  6. Department of Health. Evidence to the House of Commons Health Committee. Priority setting in the NHS: inquiry into the NHS drugs budget. London: HMSO, 1994.
  7. Prescribing gap widens in favour of fundholders. GP Magazine 1996; Feb.
  8. Audit Commission. What the doctor ordered. A study of GP fundholders in England and Wales. London: HMSO, 1996.
  9. Forster DP, Frost CEB. Use of a regression analysis to explain the variation in prescribing rates and costs between family practitioner committees. Br J Gen Pract 1991;41:67-71. [Medline]
  10. Morton-Jones, Pringle M. Explaining variations in prescribing costs across England. BMJ 1993;306:1731-4.
  11. Lloyd DCEF, Harris CM, Clucas DW. Low income scheme index: a new deprivation scale based on prescribing in general practice. BMJ 1995;310:165-70. [Abstract/Free Full Text]
  12. Pringle M, Morton-Jones A. Using unemployment rates to predict prescribing trends in England. Br J Gen Pract 1994;44:53-6. [Medline]
  13. Healey AT, Yule BF, Reid JP. Variations in general practice prescribing costs and implications for budget setting. Health Economics 1994;3:47-56. [Medline]
  14. Roberts SJ, Harris CM. Age, sex, and temporary resident originated prescribing units (ASTRO-PUs): new weightings for analysing prescribing of general practices in England. BMJ 1993;307:485-8.
  15. Wilson-Davis K, Stevenson WG. Predicting prescribing costs: A model of Northern Ireland general practices. Pharmacoepidemiology and Drug Safety 1992;1:341-5.
  16. Whynes DK, Baines DL, Tolley KH. Explaining variations in general practice prescribing costs per ASTRO-PU (age, sex, and temporary resident originated prescribing unit). BMJ 1996;312:488-9. [Free Full Text]
  17. Marinker M, Reilly P. Rational prescribing: how can it be judged? In: Marinker M, ed Controversies in health care policies: challenges to practice. London: BMJ, London 1994.
  18. Glennerster H, Matsanganis M, Owen P, Hancock S. GP fundholding: Wildcard or winning hand. In: Robinson R, LeGrand J, eds. Evaluating the NHS reforms London: Kings Fund, 1994.
  19. Eachus J, Williams M, Chan P, Davey-Smith G, Grainge M, Donovan J, et al. Deprivation and cause specific morbidity: evidence from the Somerset and Avon survey of health. BMJ 1996;312:287-92. [Abstract/Free Full Text]
  20. Government Statistical Service. Statistics of prescriptions dispensed in the Family Heath Services Authorities England 1984-94 Statistical Bulletin 1995/15. London: Department of Health, 1995.
  21. Britten N, Bartley M, Blane D. Proposed new deprivation index. BMJ 1995;310:1067-8. [Free Full Text]
  22. Lloyd DCEF, Harris CM, Clucas DW. Proposed new deprivation index. BMJ 1995;310:1068. [Free Full Text]
  23. Bogle SM, Harris CM. Measuring prescribing: the shortcomings of the item. BMJ 1994;308:637-40. [Abstract/Free Full Text]
  24. Griffiths C, Naish J, Sturdy P, Pereira F. Prescribing and hospital admissions in east London. BMJ 1996;312:481-2. [Free Full Text]
(Accepted 18 July 1996)


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Influences of practice characteristics on prescribing in practices
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