GMS Formula AnalysisGMS Formula AnalysisQRESEARCH 2005QRESEARCH 2005

09 Feb 200609 Feb 2006Julia Hippisley-CoxJulia Hippisley-Cox

Jon FordJon FordIan TrimbleIan Trimble

Aims of presentationAims of presentation

–Brief overview of methodsBrief overview of methods

–Present key results from analysisPresent key results from analysis

–Comparison of modelsComparison of models

–Hand over to Jon FordHand over to Jon Ford

Overall aim of the analysisOverall aim of the analysis

• To derive a regression model linking To derive a regression model linking workload to patient and practice workload to patient and practice characteristicscharacteristics

• To inform revision of the funding To inform revision of the funding formula for essential and additional formula for essential and additional servicesservices

Sampling: PracticesSampling: Practices

Practice inclusion criteria for analysisPractice inclusion criteria for analysisEngland and Wales onlyEngland and Wales only At least 1000 patientsAt least 1000 patientsAt least 2 consultations/person-yearAt least 2 consultations/person-yearComplete data for period in questionComplete data for period in question Decided not to sample Decided not to sample

proportionately by regionproportionately by region

Patient inclusion criteriaPatient inclusion criteria

• Patient level analysisPatient level analysis

• Study period 01 April 2003- 31 March Study period 01 April 2003- 31 March 20042004

• Included if registered at any point Included if registered at any point during study periodduring study period

• Included temporary residents, new Included temporary residents, new patients and patients who diedpatients and patients who died

• Person days denominator for rates Person days denominator for rates

Principal outcomePrincipal outcome

• Number of consultations (GP + nurse) Number of consultations (GP + nurse) in study yearin study year

• Regardless of settingRegardless of setting

• Excluding community/district nursesExcluding community/district nurses

Patient level variablesPatient level variables

• SexSex

• Ageband: standard as in Carr HillAgeband: standard as in Carr Hill• Registration period Registration period (6+ months; <6 or new)(6+ months; <6 or new)

• Temporary patients (yes/noTemporary patients (yes/no))

• New GMS diseases (yes/no for each)New GMS diseases (yes/no for each)

• Townsend score/IMDSTownsend score/IMDS

• % white/non white% white/non white

Practice level variablesPractice level variables

• List size List size

• Number of GP principalsNumber of GP principals

• Townsend scoreTownsend score

• RuralityRurality

• White/non whiteWhite/non white

• Mean prevalence of QOF diseasesMean prevalence of QOF diseases

• RegionRegion

Patient level analysisPatient level analysis

• Variables included at patient or Variables included at patient or at practice levelat practice level

• Both person years and registered Both person years and registered population were usedpopulation were used

QRESEARCH practicesQRESEARCH practices

Compared with UK averageCompared with UK average– Similar size– Similar distribution– Similar prevalence– Similar age-sex– Comparable consultation rate

LARGE Representative sampleLARGE Representative sample

Results generalisableResults generalisable

Results: study practicesResults: study practices

• 454 practices in England and Wales454 practices in England and Wales

• 3.8 million patients registered at any 3.8 million patients registered at any point in study yearpoint in study year

• 33,727 deaths33,727 deaths

• 319,435 new patients 319,435 new patients

• 97,239 temporary residents97,239 temporary residents

Summary of comparisonSummary of comparison

QRESEARCH practicesQRESEARCH practices

• Slightly biggerSlightly bigger

• More in East Midlands and fewer in More in East Midlands and fewer in LondonLondon

• Otherwise similar w.r.t. age-sex and Otherwise similar w.r.t. age-sex and disease prevalencedisease prevalence

Prevalence of diabetes in patients over 15Prevalence of diabetes in patients over 15 0

50

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15

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20

00

nu

mb

er

of

pra

ctice

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0 10 20 30 40 50 60 70 80 90 100

Diabetes prevalence per 1000 registered patients

per 1000 registered patientsQMAS figures for England

020

40

60

80

nu

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of

pra

ctice

s

0 10 20 30 40 50 60 70 80 90 100

Diabetes prevalence per 1000 registered patients

per 1000 registered patientsQRESEARCH figures for England

per 1000 registered patientsInter-practice variation in prevalence of Diabetes

Consultation rates by age and sexConsultation rates by age and sex

0

1

2

3

4

5

6

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8

9

0-4 years 5-14 years 15-44 years 45-64 years 65-74 years 75-84 years 85 plus

Ageband

Consu

ltat

ion r

ate

Males Females

ModelsModels

• We fitted a series of ‘a priori’ We fitted a series of ‘a priori’ statistical models specified in our statistical models specified in our protocol and then were asked to fit protocol and then were asked to fit additional onesadditional ones

• ‘‘a priori’ models included a priori’ models included patient patient levellevel assigned data where available assigned data where available (eg QOF diseases, Townsend score)(eg QOF diseases, Townsend score)

• Supplementary models included Supplementary models included practice level datapractice level data (QOF disease (QOF disease prevalence, mean Townsend score)prevalence, mean Townsend score)

Results: A priori Model 7biResults: A priori Model 7bi(person years denominator)(person years denominator)

Consultation rates:Consultation rates:– Registered for 6+ months = baseline– Registered for < 6 months = 72% higher rate– Temporary residents = 86% higher rate

• Person years controls for length of registration Person years controls for length of registration periodperiod

• patients registered within 6 months before start patients registered within 6 months before start of study year or during study year have a 72% of study year or during study year have a 72% higher consultation rate compared to long higher consultation rate compared to long standing patientsstanding patients

A priori model: Townsend scoreA priori model: Townsend score

Fairly flat gradient with deprivationFairly flat gradient with deprivation

(Quintile 5 is deprived)(Quintile 5 is deprived)– Quintile 1 = baseline – Quintile 2 = 0.4% higher– Quintile 3 = 1.4% higher– Quintile 4 = 4.1% higher– Quintile 5 = 6.1% higher

A priori model:A priori model:Rurality and ethnicityRurality and ethnicity

Urban areas = baselineUrban areas = baseline

Rural areas = 1.7% higherRural areas = 1.7% higher

Ethnicity:Ethnicity:

99-100% white = baseline99-100% white = baseline

97-98.9% white = 0.5% lower97-98.9% white = 0.5% lower

90-96.9% white = 4.1% lower90-96.9% white = 4.1% lower

< 90% white = 11.6% lower< 90% white = 11.6% lower

A priori model: QOF diseasesA priori model: QOF diseases

For all diseases, people with the diseaseFor all diseases, people with the diseasehad higher consultation rates comparedhad higher consultation rates comparedto those without the diseaseto those without the disease

e.g.e.g.

CHD = 38% higherCHD = 38% higher

Diabetes = 54% higherDiabetes = 54% higher

Asthma = 63% higherAsthma = 63% higher

List size: List size: 2.2% lower rate for each additional2.2% lower rate for each additionalthousand patients for a given numberthousand patients for a given numberof GP principalsof GP principals

GP principals (head count not wte) GP principals (head count not wte) 1.4% higher rates for each additional1.4% higher rates for each additionalGP principal for a given list sizeGP principal for a given list size

A priori model: practice variablesA priori model: practice variables

ProcessProcess

• Undertook patient level modellingUndertook patient level modelling

• Then asked to do practice level Then asked to do practice level modelling for implementationmodelling for implementation

• Concerns about how well practice Concerns about how well practice level models can be applied at patient level models can be applied at patient levellevel

• Results were counter-intuitive Results were counter-intuitive (Ecological fallacy)(Ecological fallacy)

Ecological fallacyEcological fallacy

• Applying practice level variables to a Applying practice level variables to a patient population produces spurious patient population produces spurious and counter-intuitive resultsand counter-intuitive results

• Well described statistical Well described statistical phenomenonphenomenon

• Practice level models don’t workPractice level models don’t work

Additional model : Additional model : (practice level data)(practice level data)

Inclusion of all QOF disease prevalence Inclusion of all QOF disease prevalence values together in models showed somevalues together in models showed somenegative associations:negative associations:

e.g.e.g. CHD CHD = 4.7% lower rate= 4.7% lower rateThyroid disease = 1.1% lower rateThyroid disease = 1.1% lower rate

both for a 1% increase in practice both for a 1% increase in practice prevalence. prevalence.

Additional model: Additional model: Townsend scoreTownsend score

Inclusion of mean practice TownsendInclusion of mean practice Townsend

score showed a negative association:score showed a negative association:

Consultation rates were 2.9% lower forConsultation rates were 2.9% lower for

a 1 unit increase in mean practice a 1 unit increase in mean practice

Townsend scoreTownsend score

FRG reviewFRG review

• Requested additional patient level Requested additional patient level model WITHOUT prevalence (model model WITHOUT prevalence (model 18)18)

• Key comparison then is patient level Key comparison then is patient level with and without prevalencewith and without prevalence

Explanatory powerExplanatory powerAkaike Information criterionAkaike Information criterion

• AIC statistical test for explanatory AIC statistical test for explanatory powerpower

• Lower values indicator better modelsLower values indicator better models

• Absolute value increases with sample Absolute value increases with sample size size

• Relative difference more importantRelative difference more important

AIC resultsAIC results

Both models patient level, person years Both models patient level, person years denominator, age-sex, rurality, ethnicitydenominator, age-sex, rurality, ethnicity

Model 7b Model 7b AIC = 16,415,351AIC = 16,415,351– Townsend quintile

– Prevalence

– No region

Model 18 Model 18 AIC = 16,763,190AIC = 16,763,190– Townsend continuous

– No prevalence

– Region

SummarySummary

• Person years adjustment give better Person years adjustment give better fit for new registrations/TRsfit for new registrations/TRs

• Patient level analyses produce Patient level analyses produce intuitively acceptable resultsintuitively acceptable results

• Practice level analyses counter-Practice level analyses counter-intuitive results likely to lead to intuitive results likely to lead to controversy (ecological fallacy)controversy (ecological fallacy)

• Comparisons between patient level Comparisons between patient level models with and with and without models with and with and without prevalence are presented for prevalence are presented for Plenary’s considerationPlenary’s consideration