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Anthony J Avery a Division of General Practice, School of
Community Health Sciences, University Hospital, Nottingham NG7
2UH, b Enigma Medical Systems, Cleethorpes, North East Lincolnshire
DN35 0HF, c School of Economics, University of Nottingham, University
Park, Nottingham NG7 2RD, d Health Services Management Centre,
University of Birmingham, Park House, Birmingham B15 2RT, e Health
Management Group, School of Humanities and Social Sciences, City
University, London EC1V 0HB
Correspondence to: A Avery tony.avery{at}nottingham.ac.uk
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Abstract |
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Objective:
To identify how some general practices have low growth in prescribing costs relative to other practices.
In 1994 the Audit Commission estimated that the NHS
could save up to £425 million a year if general practitioners changed their prescribing habits by controlling the volume of prescribing, increasing rates of generic prescribing, and using expensive products more appropriately.1 The suggestions were based on
extrapolating the prescribing patterns of 50 selected practices to the
rest of the country. While the commission might have suggested some potentially useful strategies for cost control,1 however,
there was little evidence that practices actually used such
strategies to achieve low growth in their prescribing costs. Also,
while the commission commented on high cost prescribing patterns, they did not look at how some practices increased their prescribing costs.
Finding out how general practices change their prescribing costs is
important for the development of successful cost control strategies.
Previous studies have suggested that general practices can control
their prescribing costs by reducing the volume of
prescribing2-5 and the cost per unit of
volume
2 4
and by increasing their rates of generic
prescribing.2-6 Few studies, however, have looked in
detail at the range of cost control strategies suggested by the Audit
Commission.
7 8
We examined this issue by comparing three groups of practices
characterised by different rates of growth in prescribing costs to
identify how some general practices have low rates of growth of
prescribing costs relative to others.
The study was done with data from general practices in the
Trent region of England. This region is reasonably representative of
the rest of England and Wales in terms of general practice and
sociodemographic characteristics.9 We interviewed all
health authority advisers in the region at the beginning of the study and were satisfied that there were no unusual incentives schemes in
operation that might have biased the results.
We did an observational study of changes in prescribing costs between
two financial years using anonymised data from all general practices in
Trent (n=840). Using prescribing data (PACTLINE), obtained
electronically through the Prescription Pricing Authority, we ranked
the general practices in terms of their percentage changes in net
ingredient costs per prescribing unit (NIC/PU) between the financial
years April 1994 to March 1995 and April 1995 to March 1996. We
excluded practices with greater than 10% change in list size between
the two years and obtained our sample from the 776 remaining general practices.
We sampled practices from the top, middle, and bottom fifths for
percentage change in net ingredient costs per prescribing unit between
the two years. We calculated that we needed at least 36 practices in
each group to detect a 2.5% difference between groups in their change
in percentage of items prescribed generically, with a type I error of
0.01 and a power of 0.9. Having established this as a minimum sample
size, we decided that our resources were sufficient to allow a 50%
margin above this minimum. Accordingly, we took the 54 practices with
the lowest percentage growth in net ingredient costs per prescribing
unit (group 1). We then found the 54 closest matches for these
practices (on the basis of net ingredient costs per prescribing unit in
the financial year 1994-5) from practices in the middle fifth (group 2)
and from those in the fifth with the greatest percentage increase in
costs (group 3).
We analysed changes in overall prescribing variables using PACTLINE
data. To do more detailed analysis of prescribing patterns, however, we
obtained PACT (Prescribing Analysis and CosT) catalogues for each of
the study practices for each year of the study from the 10 health
authorities in the region. The catalogues were sent to a company
(Enigma Medical Systems) specialising in the analysis of prescribing
data for entry on a database.10 We took this approach
because we knew the database software (Optimise) to be extremely
flexible in terms of the analysis of changes in prescribing patterns.10
We concentrated our analysis on drugs and preparations within the
chapters of the British National Formulary that have the highest costs in general practice (chapters 1-6 and 10, see box for
details).11 Also, we looked at the chapter on drugs used for malignant disease (chapter 8) as we were interested in the costs of
expensive drugs that had probably been initiated during hospital
treatment. From these chapters we calculated the costs for each
practice for each year of the study where the Audit Commission had
suggested that savings might be made (see box and Appendix ). The drugs
and preparations included in each category were based on information in
the British National Formulary and were validated by members
of the research team and three independent pharmacists.
Variables obtained from PACTLINE data
Variables obtained from PACT catalogues The net ingredient costs (from BNF, chapters 1-6, 8, and 10) for the following variables were calculated:
Design:
Observational study.
Setting:
Trent region of England.
Participants:
162 general practices: 54 with low
growth in prescribing costs, 54 with average increases in costs, and 54 with large increases in costs.
Main outcome measures:
Changes in prescribing costs in
therapeutic categories in which it has been suggested that savings can
be made.
Results:
There were significant differences between the three groups of practices in terms of their changes in prescribing costs for almost all the variables studied. For the group of practices with lowest growth in costs the most important factors were reducing numbers of prescription items and costs per item; relatively low growth
in the costs of "new and expensive" drugs; increasing generic prescribing; and reducing costs for modified release products. This
group of practices did not increase costs as much as the others for
lipid lowering drugs (P=0.012) and hormone replacement therapy
(P=0.007). The practices with the greatest increases in costs had
particularly large increases for proton pump inhibitors, selective
serotonin reuptake inhibitors, and modified release products. Compared
with the other groups these practices had larger increases in costs for
"expensive hospital initiated drugs" (P=0.009).
Conclusion:
General practices vary in their growth in prescribing costs in many ways, with growth in costs for "new and
expensive" drugs being particularly important.
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Introduction
Top
Abstract
Introduction
Method
Results
Discussion
Appendix
References
![]()
Method
Top
Abstract
Introduction
Method
Results
Discussion
Appendix
References
Drug categories used in the analysis
Proton
pump inhibitors (BNF section 1.3.5)
Lipid lowering
drugs (section 2.12)
Selective serotonin reuptake inhibitors
(section
4.3.3)
Oestrogens and hormone replacement
therapy
(section 6.4.1.1)
"Other drugs" (these were
considered together
in the analysis): long acting
2 stimulants;
fluticasone preparations;
sumatriptan
preparations
Analysis
For the analysis of overall prescribing variables we used
prescribing units as the denominator (these give a triple weighting to
patients aged 65 years and older and were available with the PACTLINE
data).1 For the analysis of specific drug categories (see
box) we used "net ingredient costs per 1000 patients" as the
denominator, given that prescribing units and
ASTRO-PUs
4 12
have not been validated for use across many
of these categories.
2 tests to compare
the groups of practices. For continuous data we assessed normality
using the Kolmogorov-Smirnov test with the Lilliefors significance
correction and examined normality plots. For variables derived from
PACTLINE data we compared groups of practices using parametric methods
(analysis of variance and analysis of covariance). Some variables
derived from the PACT catalogues, however, were not normally
distributed. We therefore used Kruskal-Wallis tests to compare the
groups of practices in terms of their costs in 1994-5 and their changes
in costs between 1994-5 and 1995-6.
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Results |
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Practice characteristics
In 1995-6, in groups 1, 2, and 3 respectively, there were
20 (37%), 21 (38%), and 14 (26%) fundholders7 and eight, five, and seven dispensers13 (
2
P=0.31 and P=0.67, respectively). Table 1 shows that there were no
significant differences in list size between the groups of practices in
1994-5 or 1995-6.
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Analysis of prescribing variables
Table 1 shows that there were no significant differences
between the groups in terms of net ingredient costs per prescribing
unit, items per prescribing unit, and cost per item in 1994-5. The
practices with lowest growth in costs, however, had a lower generic
prescribing rate in this year. When we used analysis of covariance to
take account of baseline values there were significant differences
between the groups of practices for changes in prescribing variables
between the financial years 1994-5 and 1995-6.
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Discussion |
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Principal findings
This study has shown that general practices with low growth
in prescribing costs changed their prescribing patterns in ways that
the Audit Commission suggested might bring about savings without
detriment to patient care.1 These practices were also
conservative in their uptake of lipid lowering drugs and hormone
replacement therapy.
Strengths and weaknesses of the study
This was a large study that looked at changes in
prescribing costs in much greater detail than in previous
studies.
2-4 6
Also, the study was not limited to
observing changes in particular groups of practices such as
fundholders
2 3 5 6 8 14
or
dispensers.
13 15
Comparison with other studies
Nevertheless, our findings are similar to those of
studies that have shown that low growth in prescribing costs is
associated with a reduction in the overall volume of prescribing,2-8 a reduction in costs per unit of
volume,
2 4
and an increase in generic
prescribing.
2-6 8
One study showed that fundholders had
lower costs than non-fundholders in one financial year for some of the
therapeutic areas outlined by the Audit Commission.8 Our
study showed that general practices have low growth in costs in these
therapeutic areas when their overall growth in prescribing expenditure
is low.
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What is already known on this topic
Low growth in prescribing costs in general practice is associated with increases in generic prescribing and reductions in prescribing volume and cost per unit of volume What this study addsGeneral practices with low growth in prescribing costs had low growth in the specific therapeutic categories in which the Audit Commission has suggested that savings might be made These practices had particularly low growth in costs for "new and expensive drugs" compared with other practices, including conservative uptake of lipid lowering agents and hormone replacement therapy General practices with large increases in prescribing costs showed relatively large increases for various categories of drugs, including expensive hospital initiated drugs |
Implications of the study
This study provides some support for the types of cost
control strategy suggested by the Audit Commission.1 Those
involved in managing prescribing costs in general practice should focus
on controlling the volume of prescribing, limiting the uptake of new
and expensive drugs, controlling the costs of modified release drugs,
and prescribing generically when this will result in savings.
Unanswered questions and future research
Two important questions arise from this research. Firstly,
what are the underlying reasons for observed changes in prescribing
costs? Secondly, what happens to the quality of prescribing when
general practitioners have low growth in their prescribing costs?
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Acknowledgments |
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We thank the health authority pharmaceutical and medical advisers in the Trent region of England who gave us useful comments on our study design and helped us to obtain PACT data, in particular Dr Peter Fitton, who gave invaluable advice in the early stages of the study. Dr John Wilson provided information on the use of "new and expensive" drugs in the region. Linda Stead and Helen Cornfield from Enigma Medical Systems were responsible for the accurate of data entry on the Optimise database. Steve Davies, Brigitte Nicholls, and Phil Dwyer carefully checked the drugs and preparations that we included in the categories shown in the Appendix . Lindsay Groom, Denise Kendrick, and Michael Dewey gave helpful comments on drafts of the paper.
Contributors: AJA conceived the study, wrote the protocol, managed the study on a day-to-day basis, developed the drug categories used in the study, liaised with the health authorities and Enigma Medical Systems, supervised the analysis, and wrote the paper. SR was the main contract researcher on the project on which this paper is based, and she did the statistical analysis together with TH. RC took the drug categories developed by AJA, incorporated these into the Optimise database, and helped with the data analysis. DW, MP, and RP were involved in the conception of the study; they actively contributed to project board meetings, advised on the analysis, and commented on drafts of the paper. DB made an active contribution to project board meetings, advised on the analysis, and commented on drafts of the paper. AJA is the guarantor.
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Footnotes |
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Funding: Department of Health (as part of the NHS Prescribing Research Initiative).
Competing interests: None declared.
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Appendix: Detailed definitions of drug categories used in the study |
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Drugs and preparations from the following drug categories (derived from chapters 1-6, 8, and 10 of issue 31 (1996) of the British National Formulary) were used in our analysis.
Combination products
All preparations containing two or more drugs,
excluding:
for example, co-codamol, migraleve (these preparations are
included in the "Over the counter" section)
Modified/sustained release preparations
All modified/sustained release preparations with the
exception of:
Drugs of limited therapeutic value
All drugs that the BNF suggests are of limited
clinical value, except those for which similar preparations could be
bought over the counter at a pharmacy (these appear in the "Over the counter" section).
Over the counter products
All drugs and preparations for which an equivalent could be
bought over the counter at a pharmacy excluding enemas, nitrates, and
topical non-steroidal anti-inflammatory drugs (these appear in their
own section).
Topical non-steroidal anti-inflammatory drugs
All topical non-steroidal anti-inflammatory drugs listed in
section 10.3.2 of the BNF.
New and expensive drugs
This section lists:
2
stimulants (salmeterol and eformoterol preparations); fluticasone preparations; sumatriptan preparations
Expensive hospital-initiated drugs
Drugs that the research team and three independent
pharmacists considered were probably hospital-initiated:
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References |
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| 1. | Audit Commission. A prescription for improvement: towards rational prescribing in general practice. London: HMSO, 1994. |
| 2. | Bradlow J, Coulter A. Effect of fundholding and indicative prescribing schemes on general practitioners' prescribing costs. BMJ 1993; 307: 1186-1189. |
| 3. |
Dowell JS, Snadden D, Dunbar JA.
Changing to generic formulary: how one fundholding practice reduced prescribing costs.
BMJ
1995;
310:
505-508 |
| 4. | Maxwell M, Heaney D, Howie JGR, Noble S. General practice fundholding: some observations on prescribing patterns and costs using the defined daily dose method. BMJ 1993; 307: 1190-1194. |
| 5. |
Wilson RPH, Buchan I, Walley T.
Alterations in prescribing by general practitioner fundholders: an observational study.
BMJ
1995;
311:
1347-1350 |
| 6. |
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:
1543-1547 |
| 7. | Baines DL, Tolley KH, Whynes DK. Prescribing, budgets and fundholding in general practice. London: Office of Health Economics, 1997. |
| 8. | Baines DL, Whynes DK, Tolley KH. General practitioner fundholding and prescribing expenditure control: evidence from a rural English health authority. Pharmacoeconomics 1997; 11: 350-358[Medline]. |
| 9. | Department of Health. General medical statistics: England and Wales. Leeds: NHS Executive, 1994. |
| 10. | Avery AJ. Analysis of PACT data using Optimise software. Prescriber 1999; 10: 109-113. |
| 11. | British Medical Association, Royal Pharmaceutical Society of Great Britain. British national formulary. London: BMA, RPS, 1996. (No 31.) |
| 12. | Roberts SJ, Harris CM. Age, sex and temporary resident originated pre-scribing units (ASTRO-PUs): new weightings for analysing prescribing of general practices in England. BMJ 1993; 307: 485-488. |
| 13. | Baines DL, Tolley KH, Whynes DK. The costs of prescribing in dispensing practices. J Clin Pharm Ther 1996; 21: 343-348[Medline]. |
| 14. |
Harris CM, Scrivener G.
Fundholders' prescribing costs: the first five years.
BMJ
1996;
313:
1531-1534 |
| 15. | Morton-Jones TJ, Pringle MA. Prescribing costs in dispensing practices. BMJ 1993; 306: 1244-1246. |
| 16. | Sibbald B, Wilkie P, Raftery J, Anderson S, Freeling P. Prescribing at the hospital-general practice interface. II: Impact of hospital outpatient dispensing policies in England on general practitioners and hospital consultants. BMJ 1992; 304: 31-34. |
| 17. | Rice N, Dixon P, Lloyd D, Roberts D. Derivation of a needs based capitation formula for allocating prescribing budgets. York: Centre for Health Economics, 1999. |
(Accepted 4 May 2000)
T J Cole Department of Paediatric Epidemiology
and Biostatistics, Institute of Child Health, 30 Guilford Street,
London WC1N 1EH
The study shows that prescribing costs increase over time
quite differently in general practices with low and high growth in such
costs. But how should we interpret this? To what extent are the
differences due to the individual practices and how much to random
variation? Or to put it another way, are the low growth practices
consistently low growth practices or were they just low growth
practices in this particular year?
Under the first interpretation the results for the observed year can be
generalised to other years and the differences in expenditure can be
considered to reflect policy decisions by individual practices. I will
call this the "policy" interpretation. The alternative or
"noise" interpretation is that prescribing costs increase over time
in a broadly random way and are unaffected by policy. The differences
in spending between low and high growth practices would therefore
represent no more than random noise.
The truth obviously lies somewhere between these extremes of policy and
noise, though it is hard to know exactly where. The authors acknowledge
this uncertainty and are careful to avoid any suggestion that the low
growth practices "control" their expenditure in any sense.
The key to interpretation is the association between baseline costs and
growth in costs. In the presence of random variation the two are
inversely related because of regression to the mean. Practices with
high costs at the start will tend to show the lowest growth in costs
and vice versa. Exactly the opposite pattern is to be expected under
the policy scenario, with low cost practices having both a low baseline
and low growth. If policy is the driving force, baseline and growth in
costs should be positively correlated.
In practice, the noise component is always likely to predominate. To
minimise its effect the study matches the practices for their baseline
net ingredient costs (NIC) per prescribing unit, though this adjusts
only partially for regression to the mean. Table 1 shows that in the
low growth practices two other facets of baseline costs are
consistently worse But against this, table 2 shows significant trends in the opposite
direction for baseline spending on new and expensive drugs, particularly selective serotonin reuptake inhibitors and proton pump
inhibitors. The low growth practices not only spend the least in
percentage terms, they also show by far the lowest growth (table 3),
and this fits clearly with a policy interpretation.
So on balance it looks as if the main policy difference between the
practices lies in their speed to embrace the classes of new and
expensive drugs. But these are drugs defined to have increased in cost
by more than 20% across the Trent region during the year of study. So
the slightly tautologous conclusion is this: that practices spending
relatively more on the fasting growing sector of the drugs market show
the highest growth in costs.
that is, net ingredient cost per item is higher and
percentage generic prescribing is lower. This looks more like
noise than policy, as the authors acknowledge.
© BMJ 2000
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