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HEALTH ECONOMICS Health Econ. 7: 711–722 (1998) ECONOMICS OF PRIMARY CARE GENERAL PRACTITIONERS’ REFERRAL THRESHOLDS AND CHOICES OF REFERRAL DESTINATION: AN EXPERIMENTAL STUDY STEPHEN C. EARWICKER a AND DAVID K. WHYNES b, * a General practitioner, Stapleford, Nottingham, UK b Department of Economics, Uni6ersity of Nottingham, Nottingham, UK SUMMARY General practitioners (GPs) exert a major impact on NHS resource use, both as providers of primary care and as referrers to secondary care. Referral rates are subject to wide variations, leading to the conjecture that certain GPs may have different ‘referral thresholds’ from those of others. In this paper, the authors describe an experiment designed both to test the referral threshold hypothesis and to illuminate the GP’s decision process with respect to choice over referral destination. Nottinghamshire GPs were provided with hypothetical case histories and a list of possible referral destinations, specifying a range of consultants, their specialist interests, plus the expected waiting times and costs for both out-patient investigation and in-patient treatment. For each case, respondents were requested to indicate whether or not they would refer the patient, and to whom. Respondents were also asked to indicate the extent to which their choices of consultants generally were governed by the specialist interest, the waiting time and the cost information. The responses of the sample support the referral threshold conjecture, with specialist interests and waiting time appearing to be far more important than cost in influencing choice of referral destination. The possibilities of influencing GPs’ referral behaviour are discussed, in the light of recent initiatives with respect to prescribing. © 1998 John Wiley & Sons, Ltd. KEY WORDS — general practitioners; referral rates INTRODUCTION With the exception of accident and emergency cases, direct access to hospitals on the part of patients is relatively uncommon in the UK. In- stead, the primary care physician, or general prac- titioner (GP), acts as the ‘gatekeeper’ to secondary care. Following a consultation with the patient, the GP will decide whether a referral to a specialist treatment centre is necessary and will offer advice on the choice of the appropriate specialist. Although the decision to admit the patient for investigation or treatment is formally the province of the hospital, evidence suggests a strong positive correlation between the rate of GP referrals and that of hospital inpatient admissions in all major specialties [1]. It accordingly follows, that GPs’ referral deci- sions form an important determinant of overall activity in the hospital sector, in terms of both the nature of cases investigated and treated and the costs of resources thereby entailed. In comparison with other countries, the average referral rate from primary to secondary care in the UK is low (the consultation:referral ratio is of the order of 20:1). Even so, observational studies consistently indicate the existence of wide variations in referral * Correspondence to: Department of Economics, University of Nottingham, Nottingham NG7 2RD, UK. Tel.: +44 115 9515463; fax: +44 115 9514159. CCC 1057–9230/98/080711 – 12$17.50 © 1998 John Wiley & Sons, Ltd. Recei6ed 13 February 1998 Accepted 16 June 1998

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Page 1: General practitioners' referral thresholds and choices of referral destination: an experimental study

HEALTH ECONOMICS

Health Econ. 7: 711–722 (1998)

ECONOMICS OF PRIMARY CARE

GENERAL PRACTITIONERS’ REFERRALTHRESHOLDS AND CHOICES OF REFERRALDESTINATION: AN EXPERIMENTAL STUDY

STEPHEN C. EARWICKERa AND DAVID K. WHYNESb,*a General practitioner, Stapleford, Nottingham, UK

b Department of Economics, Uni6ersity of Nottingham, Nottingham, UK

SUMMARY

General practitioners (GPs) exert a major impact on NHS resource use, both as providers of primary care and asreferrers to secondary care. Referral rates are subject to wide variations, leading to the conjecture that certain GPsmay have different ‘referral thresholds’ from those of others. In this paper, the authors describe an experimentdesigned both to test the referral threshold hypothesis and to illuminate the GP’s decision process with respect tochoice over referral destination. Nottinghamshire GPs were provided with hypothetical case histories and a list ofpossible referral destinations, specifying a range of consultants, their specialist interests, plus the expected waitingtimes and costs for both out-patient investigation and in-patient treatment. For each case, respondents wererequested to indicate whether or not they would refer the patient, and to whom. Respondents were also asked toindicate the extent to which their choices of consultants generally were governed by the specialist interest, thewaiting time and the cost information. The responses of the sample support the referral threshold conjecture, withspecialist interests and waiting time appearing to be far more important than cost in influencing choice of referraldestination. The possibilities of influencing GPs’ referral behaviour are discussed, in the light of recent initiativeswith respect to prescribing. © 1998 John Wiley & Sons, Ltd.

KEY WORDS — general practitioners; referral rates

INTRODUCTION

With the exception of accident and emergencycases, direct access to hospitals on the part ofpatients is relatively uncommon in the UK. In-stead, the primary care physician, or general prac-titioner (GP), acts as the ‘gatekeeper’ tosecondary care. Following a consultation with thepatient, the GP will decide whether a referral to aspecialist treatment centre is necessary and willoffer advice on the choice of the appropriatespecialist. Although the decision to admit thepatient for investigation or treatment is formally

the province of the hospital, evidence suggests astrong positive correlation between the rate of GPreferrals and that of hospital inpatient admissionsin all major specialties [1].

It accordingly follows, that GPs’ referral deci-sions form an important determinant of overallactivity in the hospital sector, in terms of both thenature of cases investigated and treated and thecosts of resources thereby entailed. In comparisonwith other countries, the average referral ratefrom primary to secondary care in the UK is low(the consultation:referral ratio is of the order of20:1). Even so, observational studies consistentlyindicate the existence of wide variations in referral

* Correspondence to: Department of Economics, University of Nottingham, Nottingham NG7 2RD, UK. Tel.: +44 1159515463; fax: +44 115 9514159.

CCC 1057–9230/98/080711–12$17.50© 1998 John Wiley & Sons, Ltd.

Recei6ed 13 February 1998Accepted 16 June 1998

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S.C. EARWICKER AND D.K. WHYNES712

rates between individual GPs, which may be asmuch as three- or fourfold [2]. By implication, it isevident that some GPs are initiating far higherlevels of hospital activity than are others, withcorresponding implications for cost [3,4].

Morbidity is known to be strongly associatedwith the socio-economic and demographic charac-teristics of patients, such as age, sex, social classand employment status. However, even whenthese contributory causes are controlled for in theobservational studies, variations in referral ratesbetween individual GPs appear to persist [5,6].Accordingly, the dispositions of the referring GPsthemselves have been taken to represent a sourceof the variation. In particular, it has been conjec-tured that each GP has an individual ‘referralthreshold’, i.e. an essentially subjective and ‘per-sonal level at which the stimulus of a consultationproduces a referral’ ([7], p. 1037). The thresholdmay be determined by the training and experienceof the GP and his/her attitude to uncertainty, andmay further be influenced by the GP’s sensitivityto that which is perceived as pressure exerted bypatients during consultations. GPs who perceivepressure or sense an expectation of referral on thepart of the patient appear to be more likely torefer [8–10].

In attempting to understand referral rate varia-tions between GPs, and the referral thresholdconjecture in particular, the observation of prac-tice possesses certain limitations as an analyticalmethod. First, confounding variables, such as pa-tient-specific characteristics and the dynamics ofthe individual consultation, are inevitably presentin all real world observed data and may provedifficult to allow for, in even the biggest samples.Second, it can be demonstrated that, when al-lowance is made for random fluctuations in ob-served data, referral rate variations might well beexplicable simply in terms of statistical ‘noise’ inthe system [11]. Finally, and perhaps most signifi-cantly, each actual referral is usually the result ofa decision made by a single and particular GP. Itis accordingly impossible to assess how other GPsmight have reacted, had they been confrontedwith that particular decision. Indeed, if it were tobe based on observational data, a ‘completely faircomparison of doctor referral rates would requirethe impossible—that the same patient consultevery doctor’ ([7], p. 1039).

There are two additional approaches to theanalysis of referral variation and the first involves

the use of external, expert opinion to judge thequality or appropriateness of GPs’ referral deci-sions. One might anticipate that a higher propor-tion of referrals from the high-referral rate GPswould be deemed by the experts to be of lowerquality. Evidence to date fails to support thisprediction, however, the extent of inappropriate-ness appearing not to vary with referral rate[12,13]. Second, one might approach the analysisof variation in a purely experimental fashion, byconfronting GPs with identical, and thereforecontrolled, case data and asking, were such apatient to present, whether the evidence availablewould justify a referral.

METHOD

In this paper, the authors describe an experimentdesigned, first, to test the referral threshold con-jecture. They present this as a hypothesis with twovariants. In its weak form, the hypothesis simplysuggests that when confronted with the same setof nominal patients, some GPs will refer morecases than others, based on their own individual,subjective criteria. In the stronger variant, how-ever, the hypothesis suggests that GPs operate onthe basis of a consistent hierarchy or ranking ofcases in terms of ‘relative need for referral’, yetselect different absolute cut-off points. Perfectadherence to the strong hypothesis would requirethat, when GPs are given, say, three cases—X, Yand Z—on which to make referral judgements,some would choose to refer none. Those choosingonly one referral would all select, say X, thosechoosing two referrals would all select X and, sayY, whilst the remainder would, obviously, selectall three. GPs might thus be characterised as‘harder’ or ‘softer’ when evaluating the evidencesurrounding the potential referral. All the GPs areagreeing that the relative need ranking is X\Y\Z, whilst differing in the subjective estimateof the absolute need required to trigger thereferral.

Second, the experiment was designed to exploredecisions relating to the choice over referral desti-nation. Existing evidence suggests that GPs’ deci-sions in this respect are dominated by personalknowledge of, and confidence in, the hospitalconsultant and by his or her physical proximity,i.e. locality and patient convenience effects [14–16]. By constructing an experiment that controlled

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for these particular choice variables, the authorshoped to gain further insights into the referraldestination decision process, in particular, the ex-tent to which consultant specialism, waiting timeand expected treatment cost were influentialfactors.

The experiment required Nottinghamshire GPsto complete an anonymous postal questionnaire.Respondents were provided with brief histories or6ignettes of eight hypothetical cases, four ortho-paedic and four gastroenterology. These 6ignetteswere constructed, by the author with general prac-tice experience (Earwicker), to represent medicalproblems familiar to GPs, and of which manycould be expected to have had direct experience.Respondents received a list of possible referraldestinations, specifying a range of anonymisedconsultants, their specialist interests, plus the ex-pected waiting times and costs for both out-pa-tient investigation and in-patient treatment.Whilst the data provided for consultant costs,waiting times and specialisms were constructed toallow for variations in characteristics between al-ternative destinations, all data were required torepresent plausible approximations to the realworld circumstances prevailing in the Notting-hamshire hospitals. The 6ignettes and details ofthe potential referral destinations appear in Ap-pendices A and B.

For each case, respondents were requested toindicate whether or not they would refer thepatient, and to whom. With respect to the latter,the option was provided for single or multiplepreferences, multiple preferences indicating indif-ference between two or more consultants. Re-spondents were instructed to assume that, in eachcase, the practice had already carried out all theappropriate tests, that patients were already tak-ing the appropriate medication and that patientinconvenience was identical for all referral desti-nations. The authors also asked respondents toindicate the extent to which their choices of con-sultants generally were governed by the specialistinterest, the waiting time and the costinformation.

Finally, they asked for age/sex data for therespondent and information about their practice.This comprised the number of partners, averagelist size and fundholding status. The normalbooking rate for consultations (patients per hour)was requested, as an indication of the time the GPnormally allocated to reaching treatment deci-

sions. Respondents were invited to make a subjec-tive assessment of the type of area served by theirpractice (inner city, urban, rural), on the groundsthat such a characteristic could influence the typesof patients actually seen in practice. Space wasprovided for additional, written comments at theend of the questionnaire.

In the case of the orthopaedic referrals, corrob-oration of the GP views was sought by obtainingdata from the orthopaedic consultants in the Not-tinghamshire hospitals. Each surgeon was pro-vided with the four orthopaedic 6ignettes only,and was asked to judge, for each case, whetherthey would consider such a referral as appropri-ate. They were given the options of ‘inappropri-ate’ (scored 1 for analysis purposes), ‘reasonable’(2) and ‘very appropriate’ (3). They were alsoasked to assess whether, in their judgement, anoperation would eventually prove likely in eachcase, recorded as ‘not likely’ (1), ‘possible’ (2) and‘very likely’ (3).

RESULTS

Of the 509 questionnaires sent out, 225 werereturned in a form amenable to analysis. Theimplied response rate of 44.2% is perhaps slightlybetter than that which can be expected of GPsurveys being conducted at present [17]. Table 1presents data pertaining to the respondents andthe characteristics of their practices. For compari-son, data are also presented for the Notting-hamshire GP population (obtained, whereavailable, from the two health authorities servingthe county, Nottingham and North Notting-hamshire) and for GPs in England as a whole[18]. There appears to be a strong similarity be-tween the age–sex distribution of respondents andthat of GPs in England, whilst the sample’s part-nership composition is close to that of both Not-tinghamshire and England. Historically, thepenetration of fundholding into Nottinghamshirewas slow. The sample proportion is extremelyclose to that of the county, and both are consider-ably smaller than the proportion for England.There is evidence that GPs with larger mean listsizes are over-represented in the sample, as arethose from Nottingham, as opposed to NorthNottinghamshire. Of the two authorities, the lat-ter has far fewer conurbations and all but one ofthe GPs assessing their practice as ‘inner city’were from the Nottingham authority.

© 1998 John Wiley & Sons, Ltd. Health Econ. 7: 711–722 (1998)

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Table 1. Sample characteristics

EnglandSample Nottinghamshire

64.5Males (%) 69.0

37.2 39.4Age distribution (%) B40 years40–49 years 36.7 33.7

26.1 27.0\49 years

Single handed 7.5 10.1 10.3Partnership size2 or 3 27.4 29.3(% of GPs) 28.6

29.733.5 34.54 or 527.8 24.9"6 or 7 26.66.03.8\7

25.6 25.1 46.5Fundholding GPs (%)

B1000 0.5 6.8Mean practice list size55.740.7(% of GPs) 1000–1999

51.9 35.22000–29993000 and above 7.0 2.3

61.173.0Health authority (% in Nottingham)

19.7Area type (%) Inner city62.0Urban

Rural 18.3

4 0.5Consultation rate44.86(bookings per hour;35.4% of GPs) 819.310

For the sample as a whole, the modal numberof total referrals was five, representing 36.2% ofrespondents. No GP referred less than two of theeight cases and only two GPs (0.9%) referred alleight. Two, three or four cases were referred by21.0%, whilst 42.0% referred six or seven. Foreach of the two specialities, there are 16 possiblecombinations of referral decision, ranging fromno referrals to the referral of all four cases. Table2 presents the two distributions of referral combi-nations as chosen by the sample, with case codenumbers corresponding to those of the 6ignettes.

Table 3 displays the overall frequency of refer-ral of each of the eight cases and the GPs’ ex-pressed preferences for the referral destination.These latter data have been constructed on thebasis of ‘share of the vote’, i.e. consultants receiv-ing a clear, single preference received a singlevote, whilst in cases where more than one consul-tant was indicated as being acceptable, each re-ceived an equal proportion of the single vote. Thedestination ‘any’ denotes referrals where GPs in-dicated that any of the consultants on the appro-priate list would be acceptable to them.

Table 4 displays the sample’s assessment of theoverall importance of information on consultantspecialist interest, expected patient waiting timeand cost in deciding on the referral destinations.

Of the orthopaedic consultants, 14 out of apossible 15 (93.3%) replied to the questionnaire.Table 5 presents summary statistics for their as-sessments of the appropriateness of each referraland the likelihood of an ensuing operation. Forconvenience of interpretation, the referral ratefrom the GP sample (Table 3) is included in thistable as well.

Of the full sample, 70 respondents (31.1%) en-tered written comments. Many were brief andmade reference to specific decisions, e.g. case 7‘would arrange urgent referral’ and case 4 ‘loseweight and then I’ll refer’. Of the responsesamenable to more general classification, 14 re-lated to testing for helicobacter pylori. All of theseGPs noted that such test results would be animportant additional consideration in their gas-troenterology referral decisions; at the time of thestudy, however, such testing was not available inall practices. A further ten of the responses recog-

© 1998 John Wiley & Sons, Ltd. Health Econ. 7: 711–722 (1998)

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Table 2. Referral combinations

No. of referrals Orthopaedic Gastroenterology

Numbers % Case codes Numbers %Case codes

0.0 1None 0 0.4

51.8 0.0041 16 2 0.92 0 0.0

0.9 7 143 2 6.20.4180 0.04

56 0 0.02 12 55 24.43.17574.0913

0.9 58 114 2 0.43.1 67 5323 7 23.6

2 0.9680.41240 0.0 78 27 12.034

36.9 567 113 123 4.9835685.3 0.4112124

2.2 578 7134 5 3.136.9836781.84234

18.2 5678 154 1234 41 6.7

225 100.0Total 225 100.0

nised the importance of two real world referralconsiderations necessarily omitted from the 6i-gnette information, namely, patient expectationsand familiarity with the consultant. Examples in-cluded: ‘we are not given any information aboutwhat the patient wants!’ and ‘I still refer people toconsultants I trust and whose skills, personal andtechnical, I am aware of’. Six respondents notedthat the real world waiting time data routinelyavailable were invariably out-of-date and/or inac-curate. Four commented that the exercise, whichinvolved choice, was of limited relevance to them,contractual obligations binding them to specificproviders.

ANALYSIS

From Table 2, it is evident that the distribution ofreferral combinations is far from uniform. For theorthopaedic cases, four of the 16 possible combi-nations of referrals—case codes 1, 12, 123 and1234—accounted for 81.3% of the responses. Forthe gastroenterology cases, five combinations—7,67, 78, 678 and 5678—accounted for 85.3%. In-deed, the hypothesis that, for a given number of

referrals, each case combination would be equallylikely to be chosen, is decisively rejected (x2=357.6 and 354.6 for orthopaedic and gastroen-terology, respectively, and pB0.001 in bothcases).

No significant association between the numberof referrals in the two specialisms was evident(x2=18.2, p=0.11). Analysis with respect toboth respondent and practice characteristics, aslisted in Table 1, revealed no significant differ-ences in the likelihood of referring any particularindividual case, with the following exception: forcases 2 and 8, referral was more likely if the GPwas female (x2=10.1 and 10.0, respectively, pB0.01).

The direction of referral (Table 3) appears tofollow a logical sequence, as determined by therelative importance of the factors that GPs indi-cate they take into account when choosing aconsultant (Table 4). Amongst the orthopaediccases, for example, it is only in case 2 whereconsultant A receives a sizeable proportion of thevotes. This consultant possesses the longest wait-ing time and the highest cost, but is the onlyconsultant specialising in the precise condition ofthe case 2 patient. Of those referring to A, 80.4%

© 1998 John Wiley & Sons, Ltd. Health Econ. 7: 711–722 (1998)

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Table 3. Referral frequencies and destinations

Case code number

84 6 751 2 3

28.9 18.6 73.9 96.4% Referred 60.693.8 90.2 67.1

To consultant (% of referrals)3.3A 0.5 62.5 1.4

11.4B 20.4 2.3 42.025.1C 27.3 11.8 18.113.3D 4.8 5.3 6.99.3E 23.3 4.5 11.9

24.1 15.7 27.717.1F2.4 1.8 0.0 0.7G

59.124.458.461.0H2.4 1.2 2.8 0.7I

0.6 33.4 0.00.0J0.0 1.8 3.0 0.0K

0.70.52.42.4L0.0 0.0 5.8M 0.00.0 0.0 2.5N 0.0

12.0 10.914.6 9.637.6Any 23.6 13.6 19.7

100.0 100.0 100.0 100.0100.0 100.0 100.0100.0

rated specialist interest as more or at least asimportant as waiting time. Of those using consul-tants C, D or E (shorter waiting times), 93.3%rated waiting time as more or at least as impor-tant as specialist interest. Again, three consultants(B, C and E) appear roughly equally favoured forcase 1, although the first mentioned possessed aconsiderably longer waiting time than the lasttwo. All those GPs referring case 1 to consultantB rated specialist interest as more or at least asimportant as waiting time, whereas 89.8% of thosereferring to C or E rated waiting time as more orat least as important as specialist interest.

For the gastroenterology cases, referral tosurgery as opposed to medicine was generallyuncommon. Referral to direct access endoscopy(consultant H) was universally popular for allcases, with consultant F being generally preferredto consultant G (same specialist interest butshorter waiting time). The geriatrician (consultantJ) was favoured only for case 7, the 70-year-oldpatient.

As is evident from Table 4, the distributions forwaiting time and specialist interest are broadlysimilar, and both differ radically from that ofcost. No significant associations between the as-sessment of importance of information and per-sonal and practice characteristics were detected,with one, perhaps unsurprising, exception: asmaller proportion of fundholders responded ‘notat all’ to the influence of cost on their decisions(46.2% compared with 64.2% for non-fundhold-ers, x2=7.2, p=0.03).

Table 5 indicates that, in the four orthopaediccases, the implied ‘need for referral’ rankingderived from the GP sample is entirely consistentwith the rankings resulting from the survey ofconsultants’ views. The finding would appear toindicate a communality of judgement betweendecision makers in the two health care sectors in

Table 4. Influences of information on referral deci-sions (%)

Waiting timeCost SpecialistInfluenceinterest

Not at all 59.4 5.0 7.9A little 37.1 46.0 40.4

51.749.03.5A lot

100.0 100.0 100.0

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Table 5. Orthopaedic consultants’ assessment

Mean consultant score

Likelihood of operationGP referral rate (%)Case Appropriateness

1 93.8 3.0 3.02.92.990.22

67.1 2.5 2.3328.9 2.2 1.94

Nottinghamshire. This having been said, evidencesuggests that the interregional variability in hospi-tal physicians’ conceptions of appropriateness, aswith GPs’ assessment of the need for referral, islikely to be high [19,20].

Given the identified referral destinations andthe cost information by specialist, it is possible toestimate the expected nominal costs of all thereferrals made by each GP. For GPs expressingindifference between a number of consultants, itseemed appropriate to select the cheapest destina-tions for this calculation. For out-patient visits,the mean expected cost of referrals was £850 (S.D.351), within a range of £160–£1860. Were it to beassumed that the referrals subsequently led tocourses of in-patient treatment at the indicatedcosts, the mean expected gross cost of the GPs’referrals becomes £13487 (S.D. 4593), within arange of £3580–£24530. In no instance did indi-vidual respondent and practice characteristicsproduce significant differences in means for out-patient or gross costs, including the case of fund-holders who had reported a higher degree ofsensitivity to cost. The mean costs of referralsincurred by those GPs indicating that cost dataexercised at least some influence on their decisionswere not significantly different to those who de-clared it exerted no influence (t-test, p=0.41 forout-patient referral costs and p=0.88 for grosscosts).

DISCUSSION

With little evidence of systematic bias in the sam-ple, the experimental approach to the referralthreshold conjecture controls for many of thecomplicating variables that are known to influ-ence real world referral decisions. As an analyticalresolution to the conjecture, this issue of controlis both a strength and a weakness. On the one

hand, the approach, in permitting the authors toconfront a large sample of GPs with identicalcases, has enabled them to evaluate an hypothesisthat, on the basis of real world observation,would have proved ‘impossible’ to test [7]. Theweak version of the hypothesis—when confrontedby the same nominal patients, some GPs refermore or fewer than others—is very clearly sup-ported by the experimental evidence. Moreover,the authors believe that the observed patterns ofreferral combinations (Table 2) provide consider-able support for the strong version also. For theorthopaedic 6ignettes, the general priority rankingappears to be 1\2\3\4 and, when the numberof referrals is increased, the next case selected isbroadly as predicted by this ordering. For gas-troenterology, the ordering is less rigid as thenumber of referrals increases from one to two,with the majority of such GPs adding case 6 tocase 7 and the minority adding case 8. Thereafter,the one of these two not chosen in the two-refer-ral case is typically added at the three-referralstage. As noted earlier, the responses of morethan four-fifths of the sample are consistent witheach of these orderings and the hypothesis ofrandomness in the referral combinations selectedis decisively rejected. There is evidence that refer-ral destinations are selected on the basis of therelative weightings given by GPs to specialist in-terest and waiting time, although the evidencethat respondent or practice characteristics system-atically influence referral decisions isinsubstantial.

On the other hand, it must be acknowledgedthat experimental studies of this nature necessarilypossess their own limitations. The desire to con-trol for extraneous variables necessarily causes theexperiment to depart from reality in some degree,as certain respondents noted in their written com-ments. Perhaps most significantly, a simple ques-tionnaire will fail to reproduce the emotionalcontext of a genuine referral, in which GPs will

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weigh up real risks, to both the patient and them-selves, in reaching a decision [21]. Were GPs tomake errors in this particular experiment, theywould be essentially costless; in reality, theywould not be. When in doubt in a real consulta-tion, GPs always possess the option of extendingthe session with a view to eliciting more informa-tion, an option explicitly denied to them by theexperiment. It is also possible that the hoped-forcontrol was imperfect, with GPs reading moreinto the 6ignette information than was originallyintended. For example, the hypothetical case his-tory may have caused a remembrance of an actualcase, and the referral decision may have beenmade on the latter basis.

In view of these potential limitations of themethod, do the experimental results offer genuineinsights into complex, real word processes? Itmust be appreciated that the problem of ‘paral-lelism’ between experiment and reality is endemicto all experimental sciences, not just economics.The development of medical treatments, for ex-ample, frequently entails exploring the hypothesisthat results achieved on animal subjects can bereproduced successfully in human populations. Inthe words of one leading experimentalist, ques-tions of parallelism ‘are not answered with specu-lations about alleged differences between theexperimental subject’s behaviour and (undefined)‘‘real world’’ behaviour’ ([22], p. 248). The resolu-tion lies in the conduct of more sophisticatedexperiments. Indeed, the potential for inconsis-tency between decisions based on hypothetical, asopposed to real, costs and benefits has been ex-plored frequently by experimental economists.Perhaps not surprisingly, a wealth of contradic-tory evidence has accumulated, some studies suc-cessfully demonstrating parallelism, with othersgoing some way towards refuting it [23]. At a bareminimum, however, the initial experimental resultbegins to shift the burden of proof.

Although it would have been informative tocompare the experimental results with actual re-ferral rates, this was impossible owing to theanonymity of the questionnaire respondents.Given the known variations in rates, and uncer-tainties with respect to the future organisation ofthe NHS, referral is presently a sensitive subjectamongst GPs. The authors opted for theanonymity approach on the grounds that it wouldbe more likely both to enhance questionnairecompliance and to reduce the incentives for bias

in response. Clearly, however, a comparison be-tween experimental and actual rates would repre-sent a logical next step for the researchprogramme.

POLICY IMPLICATIONS

The experimental evidence suggests that, even un-der tightly controlled conditions, variability inreferral behaviour between GPs can be expected.From the point of view of the UK health caresystem as a whole, variable and unpredictablereferral behaviour at the local level poses bud-getary problems and raises concerns over equity.In the presence of variations in GP referral ratesbetween areas, budgets and planned service capac-ity allocated by capitation formulae will lead tointer-area variability in waiting times for sec-ondary care. Alternatively, if funding follows re-ferral rates, a disproportionate share of resourceswill be allocated to areas where the GPs are highreferrers [24]. At the level of the individual pa-tient, the ‘referral threshold’ results imply thatpatients who are referred by one GP might nothave been so referred, had they been assessed byanother. If one regards such equity issues as im-portant, one is led towards considering whetherthe levels of, and variations in, GP referrals couldbe influenced or controlled.

It is instructive here to consider recent eventssurrounding another major area of GP activity,namely the prescribing of drugs. As with referrals,inter-GP variations in prescribing behaviour havebeen regularly observed [25]. However, evidencesuggests that initiatives put into place over thepast decade have led to significant modificationsto prescribing behaviour on the part of individualpractices [26]. Examples include:

(i) the increased use of prescribing formularies,which requires the GP to consciously ratio-nalise his or her use of medicines, by pre-se-lecting from the broader list of the availablealternative candidates on cost effectiveness orother grounds;

(ii) fundholding and prescribing incentiveschemes, which provide tangible motives foreconomy in drug use;

(iii) the provision of prescribing activity and cost(PACT) data, which permit GPs to comparetheir own prescribing performance againstthat of others.

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All these have been shown to be cost- and vari-ance-reducing, although the impact upon patientcare and longer-term morbidity remains largelyunknown. Assuming it were deemed to be desir-able, would these prescribing models be transfer-able to referrals?

Perhaps the most obvious analogue of the pre-scribing formulary is the referral guideline. Bypre-specifying referral criteria, guidelines could beexpected to reduce the variability in confidence inclinical judgement between GPs, which has beensuggested as a fundamental cause of referral ratevariation [21]. The evidence to date suggests thatguidelines may be successful in improving consis-tency and in reducing variability in referral ratesto some degree [27]. In terms of the language ofthis paper, the guideline is attempting to signalthe absolute level of need, or to standardise thecut-off, within the ranking of the need for referral.Despite standardisation, however, there is no rea-son to expect the rate of referrals to decrease;indeed, it might well increase if the guidelinessucceed in identifying deserving cases formerlyexcluded from consideration for referral [13].

Translations of the remaining two prescribinginitiatives are more problematic. The success offundholding in restraining the growth in prescrib-ing costs arose from the imposition of ‘hard’budget constraints, in comparison with the ‘soft’prescribing budget constraints faced by non-fund-holders [28]. It is evident from the authors surveyresults that GPs are not at all ‘cost-conscious’with respect to referrals, largely because, the au-thors suggest, constraints in the past have eitherbeen soft or non-existent (in the case of non-fund-holders). Fundholders were not expected to meetthe costs of ‘expensive’ secondary care treatmentsfrom their budgets, nor did they have to pay forpatients referred as emergencies. This softness inthe fundholders’ referral budgets might accountfor the fact that the experiment failed to detectany major differences between the referral deci-sions of fundholders and those of non-fundhold-ers. It is only in the case of the more recentlyintroduced ‘total purchasing’ fundholders thatthese means of escape from budgetary constraintswould not necessarily exist, although it should benoted that many of nominal total purchasers exer-cised their rights to opt out of some purchasingareas [29]. At present, the future role of budgetsgenerally in the NHS remains unclear [30]. It isthus impossible to comment with authority on the

future hardness of constraints that are necessaryto engender changes in referral behaviour.

The collation and distribution of nationalPACT information is facilitated by the centralisa-tion of prescribing records with the PrescriptionsPricing Authority [31]. Nothing equivalentpresently exists for referral data (RACT?). Thishaving been said, collation at the local level wouldcertainly prove practicable. Being responsible forpayments with respect to the secondary care con-tracts of non-fundholders, each health authorityalready possesses full referral records for suchpractices. Fundholders have naturally adminis-tered their own accounts, although these too areavailable to the authority. On their own initiative,certain authorities in the Trent region have al-ready begun to assemble such materials, in orderto analyse local referral behaviour for planningpurposes. Evidence suggests that, to be of value inreferral management, such data will have to beseen to be both reliable and indicative to therelationship between referrals, need and the qual-ity of care [32].

ACKNOWLEDGEMENTS

An earlier version of this paper was presented at the HealthEconomics Study Group meeting, Sheffield, January 1998. Theauthors are grateful to the enthusiastic audience and to thediscussant, Hugh Gravelle, for the many helpful comments.The authors original submission was further improved bysuggestions from two anonymous referees.

APPENDIX A: VIGNETTES

Orthopaedic cases

Case 1. This 70-year-old widow has had pains inboth hips for several years. There is X-ray evi-dence of osteoarthritis in both hips. The pain,which she is now getting, is worst in her right hipand prevents her from walking more than 50 mwithout severe pain. This is despite taking regularpain-killers. She is also having difficulty gettingon the bus. She does not complain of pain atnight. She lives alone in a bungalow and is findingit increasingly difficult to cope with shopping.

Case 2. This 55-year-old, former professionalfootballer had a menisectomy of his left knee atthe age of 33. He now has severe pains fromosteoarthritis of this knee. This has been con-

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firmed by X-ray. He is now getting pain onwalking and at rest. He lives with his wife who isfit and healthy. They live in a detached house withtoilets upstairs and down. He has not worked nowfor 5 years.

Case 3. This 70-year-old woman has a pasthistory of alcoholism and has avascular necrosis ofher left femoral head. This causes her considerablepain both on walking and at rest. As a result ofthis, she is largely confined to a wheelchair, andcertainly cannot leave the house unaided. She hasnot touched alcohol for 3 years and her liverfunction tests have at long last returned to normal.Her X-rays, as well as showing avascular necrosis,also show generalised osteopenia. She also hassigns of peripheral vascular disease affecting bothlegs with no palpable pulses below her femorals.She is supported by her long-suffering husband intheir semi-detached house situated at the top of asteep hill.

Case 4. This 85-year-old woman has knownosteoarthritis affecting both hips and both knees.She is grossly obese, weighing 112 kg. She nowcomplains of pain, both on walking and at rest,and is woken at night with leg pain. This is despitetaking regular co-proxamol for pain relief. Shelives alone in a ground floor warden-aided flat.

Gastroenterology cases

Case 5. This 29-year-old man complains of a3-month history of epigastric pain, worse at night.He has been self-medicating with antacids, butwith only limited relief. He smokes 20 cigarettes aday and his alcohol consumption is 21 units perweek. He is of normal weight and this has notaltered recently. He works for the Benefits Agencyand finds this quite stressful. He is single and livesin a terraced house which he owns. He has not yethad any investigations.

Case 6. This 55-year-old woman has been com-plaining of symptoms of oesophageal reflux forthe past 9 months. She was initially treated withgaviscon, and has subsequently had a 4-weekcourse of omeprazole. The gaviscon providedsome short-term relief and the omeprazole pro-vided good relief of her symptoms, but these havereturned now that she has stopped taking it. Sheis a little overweight for her height (BMI 27)although her weight has not changed recently. Shedoes not smoke and consumes only trivialamounts of alcohol. She gets symptoms both dayand night. She works as the head teacher of a largecomprehensive school. She is married and lives ina detached house. She has not had any investiga-tions.

Case 7. This 70-year-old retired foundry workerhas had epigastric pain, mainly at night, for thepast 3 months. He has found that antacids havehelped to relieve this. He has also tried 2 weeks offamotidine, which he bought from the pharmacistand which also provided some relief. He is over-weight, but has noticed that his clothes are gettinglooser although he has not weighed himself foryears. He used to smoke over 20 cigarettes a dayuntil 3 years ago when he stopped smoking. Hedrinks about 18 units of alcohol a week. He hasnot had any investigations. He is married and livesin a semi-detached house.

Case 8. This 45-year-old financial advisor hashad epigastric pains on and off for 12 years. Thesehave previously responded to cimetidine. He hascome up to surgery this time because his medica-tion was due for review. He tells you that he stillgets epigastric pain and has to take cimetidinemost days. He had a barium meal in 1991, whichshowed a duodenal ulcer. He is a little overweightbut has lost some weight recently since taking upjogging. He is a non-smoker and drinks 12 units ofalcohol per week. He is separated from his wifeand lives in a flat in a large Victorian house.

APPENDIX B: CHOICE OF CONSULTANT

Waiting time Costs (£)Specialist interestName(weeks)

IPOPIPOP

Orthopaedics60 90 Hip, 4000Prof. A Knee 35

Knee, 5500

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45HipMr B 50 90 Hip, 4000Knee, 4500Hip, 3500804525GeneralMiss CKnee, 4500

Mr D General 30 40 80 Hip, 3500Knee, 4500

Mr E Hip, 350080General/hand 3025Knee, na

GastroenterologyMedicine

11 6 120Dr F 300Gastroenterology15 10 120Prof. G 300Gastroenterology

Dr H Gastroenterology 10 Direct access endoscopy 400Dr I General 9 na 110 na

13064GeriatricsDr J 300

SurgeryProf. K 8 6 90 350ThoracicMr L Oesophageal 12 10 90 350Mr M General 8 10 70 350

70 na4General naMr N

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