General Practice

Effective prescribing at practice level should be identified and rewarded

Trisha Greenhalgh, senior lecturer. 

Unit for Evidence Based Practice and Policy, Joint Department of Primary Care and Population Sciences, UCLMS/RFHSM, Whittington Hospital, London N19 5NF

p.greenhalgh{at}ucl.ac.uk

In the administrative corridors of the European Union there is no longer any talk of cows, sheep, or pigs but only of "grain consuming units" or GCUs. A similar level of bureaucratic jargon has come to surround what used to be known as patients in the British NHS, who, for the purposes of administering the funds that pay for their medication, are now known as "prescribing units" (PUs). Just as one cow consumes as much grain as three or four sheep and therefore counts as several GCUs, so a person over the age of 65, who is said to consume, on average, three times as many prescription items as someone aged under 65, is generally counted as three prescribing units.¹ Attempts by statisticians and health economists to explain and refine the prescribing unit^2-8 have generally been little read and poorly understood by those with most to gain or lose by the formulas produced. Yet the principle behind the jargon is simple, and the implications of an invalid model for capitation based drug budgets far reaching.

General practitioners in England and Wales are expected to keep the total cost of their drug prescribing within specified limits (indicative prescribing budgets⁹) allocated by their district health authority (previously the family health services authority) and generally calculated on the basis of their previous year's performance plus a small allowance for inflation and real cost increases (the much criticised "historical allocation formula"). Although there is currently no binding sanction against general practitioners who exceed their indicative prescribing budgets, there is, buried within the small print of the latest NHS white paper, the news that, from 1999, primary care groups will have a unified budget for commissioning, prescribing, and practice administrationin other words, general practitioners' prescribing will be cash limited.¹⁰ In the interim, many health authorities, encouraged by central office,¹¹ are introducing a variety of financial incentives for practices to remain within particular targets for total prescribing costs.¹²

Hence, there is considerable interest in developing a robust mathematical model that successfully predicts legitimate variation in prescribing costs and exposes (with a view to modifying or penalising) idiosyncratic variation. Given the number of potential influences on the total cost of a general practitioner's prescribing (see box) and the passion with which general practitioners have traditionally guarded their freedom to prescribe as they choose, it is small wonder that attempts to produce such a model have so far generated more heat than light.¹³

	Measures of prescribing cost

It is important to understand the principles behind the different types of research that have tried to unravel the complex influences on general practitioners' prescribing costs. If the focus of the research is the impact of doctor or patient factors on the decision to prescribe or the choice of drug, the unit of analysis must be the individual prescriber (and, perhaps, the individual consultation).¹⁴ If the focus is organisational factors (such as fundholding status or use of locum doctors), the unit of analysis must be the practice. If, however, the focus is a demographic variable (such as age or sex), aggregated data from a large geographical area (regional or national) must be used so that the effects of differences in local morbidity, practice organisation, and prescribing behaviour are smoothed out.

Demographic variables
A national sample of 90 practices drawn from 80 health authority areas was used to refine the crude prescribing unit (weighted only by a flat factor of 3 for patients aged over 65) to take account of sex, finer gradations of age, and the proportion of temporary residents (a highly mobile population increases prescribing costs, and patients often register as temporary residents simply because they forgot to bring their tablets on holiday with them).³ In another analysis, data from over 500 practices were used to determine average costs by different therapeutic group according to age and sex.⁷ The resulting ASTRO-PU (age, sex, and temporary resident adjusted prescribing unit, which used nine different age bands),⁴ the formula of which has recently been updated to take account of changing broad trends in general practitioner prescribing,¹⁵ and STAR-PU (specific therapeutic group age-sex related prescribing unit)⁷ provide more sophisticated weightings for legitimate variations in costs, especially in practices with unusual demographic or epidemiological features.

Individual variables
Once the unit of analysis is narrowed to practice level or below, variations in costs are less readily explainedprecisely because the effects of individual doctor and patient factors are unmasked. Adjustments for demographic variables with the ASTRO-PU probably account for about 25% of the variation between practices' costs,⁴ leaving most of the variation to be explained by local morbidity patterns, practice variables, and doctor-patient variables. Given that genuine variations in morbidity at the practice level are difficult to distinguish from variations in ascertainment of morbidity, patients' expectations, and individual doctors' threshold for reaching for the prescription pad, we should not be surprised when preliminary models seem to raise more questions than they answer.

Capitation based models
In an analysis of the prescribing behaviour of 131 general practitioners in a single health authority, Majeed et al recently attempted to derive a capitation based formula from demographic data and practice organisational factors (such as whether the practice was fundholding, computerised, had more than two partners, etc).²¹ They found poor correlation between most of these variables and net ingredient cost per patient, and found that a crude correction for age together with the generic prescribing rate explained only about a third of variability in costs between practices.

	Improving the formula for allocating prescribing budgets

In their wholesale rejection of a capitation formula, Majeed and Head fail to take account of many things that are known about prescribing at the micro-level as opposed to the macro-level. An independent report from the Audit Commission identified several factors that showed high variability between practices and through which, if the worst performing practices improved to the level of the best, substantial savings could be made and patient care improved (see box).²³ Using multiple regression modelling, Whynes et al found that two morbidity variablesproportion of certificates of payment exemption for prescriptions (a proxy for level of chronic illness) and number of night visits (possibly a proxy for deprivation)and one doctor related variable (proportion of items prescribed generically) explained 42% of variation between practices in costs per ASTRO-PU.⁸

Neither Majeed et al nor Whynes et al addressed other factors identified by the Audit Commission, but it would be potentially possible to develop proxy measures within existing data systems for non-use of formularies (such as number of different diuretics or non-steroidal anti-inflammatory drugs prescribed) and to identify marker drugs for prescription of products of low therapeutic efficacy (such as peripheral vasodilators or appetite suppressants) or those for which therapeutically equivalent cheaper alternatives exist. Practices that record diagnostic as well as prescribing data electronically would be amenable to scrutiny of their prescribing patterns for particular conditions, such as the frequency of antibiotic use for minor respiratory infections.

The British National Primary Care Research and Development Centre is currently undertaking preliminary research into the development of quality markers such as these for general practitioner prescribing (M Roland, personal communication). Ideally, a marker drug should have a single specific clinical indication and no clinical reason for differences between practices. In a recent region-wide survey, Roberts et al used specific marker drugs for prescribing of brand name drugs, those of low therapeutic efficacy, and those with cheaper therapeutic equivalents to monitor the impact of a regional prescribing incentive scheme.¹²

Valid standards for these and other hypothetical quality markers²⁴ in general practitioner prescribing must surely be determined externally (for example, by evidence assisted peer review) rather than simply by measuring what some or all general practitioners currently achieve. Only by directing analysis at particular compounds and therapeutic areas, and perhaps only by measuring health outcomes along with prescribing costs, will effective and efficient prescribing be distinguished from simple cost containment.

Given the variability in needs and expectations within and between practice populations, a truly equitable, all encompassing formula for allocating prescribing budgets is probably impossible. But indirect evidence suggests that it is theoretically possible for health authorities to identify an approximate band within which a practice's prescribing costs should remain. The time is surely ripe for a pilot study to test the feasibility of this notion.

	Acknowledgments

I thank Paul Wallace, Andy Haines, Mike Pringle, Martin Roland, and James Mason for advice on this article. The opinions expressed are mine alone.

	References

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