Does quality affect patients’ choice of doctor? Evidence from the UK

Rita Santos* Hugh Gravelle* Carol Propper**

*Centre for Health Economics, University of York **Imperial College, London; CMPO, University of Bristol

Competition and market mechanisms in health care.workshop. Nuffield Trust, 13 September 2013

Motivation

• Governments increasingly adopting policies to create/enhance choice in health care (and other public services)

• Improve match of patients and providers

• Encourage providers to compete on quality in fixed price regime

• Competition will improve quality only if demand is responsive to quality – But

• Noisy quality measures

• Consumers may not value quality

• Does quality affect patients’ choice of provider?

2

Our Research Question

• Do English patients respond to differences in quality when choosing a general practice?

• England is a good “test bed” – Patients register with a single general practice

– GPs are gatekeepers for elective hospital care

– Care is tax funded and free at point of use, so choice should be driven only by clinical quality, distance and other practice attributes

– Government actively promotes provision of information to patients eg NHS Choices website

– Rich set of quality measures for general practice

3

What we do

• Data on the choices of 3.4M patients in 2874 small areas (LSOAs) from amongst nearly 1000 general practices

• Focus on quality, distance, and practice attributes

• Consider appropriate measure of quality, patient heterogeneity, endogeneity of quality

• We find – Patients more likely to choose practices which have higher clinical quality

as measured by published data on performance (QOF points)

– Robust across age and gender, socio-economic status

– Quality has small effect on probability patient chooses particular practice

– But large number of potential patients for a practice mean that quality has large effect on total demand

• 1 SD increase in QOF points would increase demand for a practice by 20%

4

Literature on health care quality, demand, and competition

• Quality and demand • Hospital sector – quality affects choice of hospital

– Extensive US literature – Recent UK studies: Sivey 2011; Beckert et al 2012, Gaynor et al 2012

• General practice: few studies of impact of quality on choice because of lack of good measures of quality – UK: Dixon et al, 1997 – Norway: Biorn & Godager, 2010); Iversen and Luras 2011

• Competition and quality • Hospital sector: competition improves quality in fixed price systems • UK hospital sector: Cooper et al (2011); Gaynor et al (2013) • UK general practice: Pike (2010) - practices with more rivals within

500m have higher patient satisfaction, smaller ACSC admission rate

5

Outline of talk

• Institutional setting

• Data

• Model

• Results

• Conclusions

6

Institutional setting: English NHS

• No charges to patients for hospital or primary care

• List system (patient registration) for general practices

• GPs as gatekeepers for elective hospital care

• 8300 practices with 4.2 GPs and 6600 patients

• Practice contracts with NHS

– GMS – mix of capitation, lump sum, quality related payments

– PMS - paid as if GMS plus uplift to reflect additional services negotiated with local PCT

– Quality and Outcomes Framework – payment for achievement of quality indicators

– Both contracts link total revenue closely to number of patients

7

Institutional background: policy

• Abolition of national body controlling entry (2002) • Devolution of entry control to local health authorities • Removal on restrictions on ownership of practices • Encourage new entry (Darzi health centres) • NHS Choices website with data on practices • Patients to be given right to register with any practice

8

9

ONS Neighbourhood Statistics Socio economic data at LSOA level

General Medical Services Statistics Practice and GP characteristics

General Practice Patient Survey Patient satisfaction by practice

Quality and Outcomes Framework Clinical quality indicators by practice

Hospital Episode Statistics ACSC emergency admission rates by practice

Attribution Data Set Patient registered with each general practice LSOA by age by gender by practice cells

Data sets

Sample • Unit of analysis: LSOA

• Population: mean 1500, min 1000

• Attribution Data Set • Number of patients in each of 8300 practices resident

in each of 32,482 LSOAs in 36 age/gender bands

• At 1 April 2010

• East Midlands Strategic Health Authority • Mix of urban, rural areas; high proportion of non-UK

qualified GPs; relatively high proportion of pop of Asian origin

• Not adjacent to Wales or Scotland

• 2875 LSOAs, 3.372M individuals aged ≥25

• 994 practices with 1235 surgeries

10

11

Data: practice QOF quality • Quality and Outcomes Framework

– National P4P scheme introduced 2004

– Points awarded (max 1000) for achievements of indicators

• Clinical domain

• Organisational domain

• Patient experience domain

• Additional services

• Holistic care

– £125 per point

– Data extracted from practice electronic patient records

• Main quality measure: (lagged) total QOF points in 2006/7

• Also use – total QOF points 2009/10

– average QOF points 2006/7-2009/10

– domain points

– other measures derived from clinical indicators

12

Data: non-QOF quality measures

• Emergency hospital admissions for Ambulatory Care Sensitive Conditions

• Patient satisfaction

• General Practice Patient Survey 2009: 5% sample of all patients on lists

• “In general, how satisfied are you with the care you get at your GP surgery or health centre?”

• “How satisfied are you with the hours that your GP surgery or health centre is open ?”

• “Would you recommend your GP practice or health centre to someone who has just moved to your local area?”

13

Data: LSOA - practice distances

• Practice locations • Main surgery – GMS statistics • Branch surgeries – NHS Choices

• LSOA population weighted centroids

• Linear distance from each LSOA centroid to nearest branch of each practice within 50km

• Dummy variable = 1/0 as practice located in different/same PCT as LSOA

14

Data: LSOA choice sets

• Practices with branch within 10km of LSOA centroid

– 99.3% patients choose practice within 10km

• If more than 30 such practices restrict choice set to 30 practices with largest number patients from LSOA

15

16

Characteristics of patients in LSOAs

Mean SD Min Max

Proportion female 0.507 0.022 0.276 0.618

Proportion in fair or good self-rated health 0.907 0.032 0.760 0.983

Proportion adults without qualification 0.231 0.071 0.035 0.430

Proportion non white 0.065 0.130 0.000 0.948

Income deprivation score 0.143 0.110 0.013 0.830

Urban 0.731 0.444

Proportion of LSOA registered at nearest

practice

0.399 0.263 0.001 0.998

Practice characteristics

17

Mean SD Min Max

Average GP age 47.9 6.7 31.5 72.5

Proportion female GPs 0.362 0.248 0 1

Proportion GPs trained outside Europe 0.267 0.354 0 1

Opted out of out of hours care 0.613 0.487

PMS contract 0.479 0.500

Dispensing practice 0.204 0.403

Patients aged ≥ 25 registered with

practice

4886 3063 653 24988

Practice quality measures

18

Mean SD Min Max

QOF 2006/7 total points 956.1 63.6 426.5 1000

QOF 2006/7 clinical points 632.8 36.4 330.5 655

QOF 2006/7 organisational points 166.5 21.0 13.2 181

QOF 2006/7 patient experience points 103.3 16.1 0 108

QOF 2006/7 additional services points 35.3 2.8 6 36

QOF 2006/7 holistic care points 18.3 3.1 0 20

QOF 2009/10 total points 940.5 46.9 545.5 1000

Average QOF total points 2006/7-2009/10 954.6 44.8 545.5 1000

ACSCs 2006/7 per 10,000 259 76 28 679

Overall patient satisfaction 2009 0.89 0.06 0.57 0.99

Satisfaction with opening hours 2009 0.80 0.06 0.45 0.97

Prop patients would recommend practice

2009

0.82 0.10 0.38 0.99

Distances

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Mean SD Min Max

Distance to practices in choice set (km) 4.83 1.65 0.35 9.89

Distance to chosen practice (km) 1.89 1.34 0.13 9.87

Distance to nearest practice (km) 1.20 1.16 0.02 9.81

Proportion practices in different PCT 0.27 0.45 0 1

Prop practices chosen in different PCT 0.19 0.39 0 1

Prop nearest practices in different PCT 0.05 0.22 0 1

Prop LSOA pop registered at nearest

practice

0.40 0.26 0.00 1

Distance to practices in choice set

Distance to practice chosen

20

Model: conditional logit

21

All patients in an LSOA have same choice set

All patients derive same utility from observed practice characteristics

unobserved utility iid type 1 extreme value distribution

P

a

iaj aj iaj

aj

iaj

a C

u

x β

x

1

1

1

robability patient in LSOA choose practice

exp( ) exp( )

Log likelihood ( patients in LSOA choose practice )

ln ln exp( ) exp( )

a

A

a a

iaj aj ajj C

aj

n

aj aj aja j C j C

i a j

P

n a j

L n

x β x β

x β x β

Model: sensitivity checks

• Alternative quality measures

• Distance specification

• Patient heterogeneity

• Restrictions on choice sets

• Endogeneity

22

Model: interpretation of results

• Report average of marginal effects

• AMEs small • Potential incentive for practice to increase quality

depends on change in demand for practice – Depends on change in probability patients will want to

join practice and number of patients in whose choice set practice falls • 75,000 individuals 25 yrs within 5 km of av practice • 25,000 individuals 25 yrs within 2km of av practice

– Small changes in individual probabilities can translate into large demand increases

23

ˆˆ ˆ ˆ/ (1 )aj kaj k aj ajP x P P

Results: preferred model

Average Marginal

Effect

z

QOF 2006/7 Total points 0.00013 6.87

Distance (cubic) -0.06778 -14.18

Practice in different PCT -0.04751 -10.12

GP age -0.00144 -13.31

Prop female GPs 0.01508 6.12

Prop GPs non Europe trained -0.03029 -10.36

Opted Out 0.00543 2.49

PMS contract 0.00564 2.95

BIC 11714907

McFadden R2 0.3955

N LSOA 2,870

N GP practices 987

N patients 3,364,263

Increase 10 QOF pts increase pr(choice) by 0.0013 Mean QOF points = 957, sd = 64. 24

Results: other quality measures

• 2006/7 total QOF points performs at least as well as – domains of QOF – 2009/10 QOF total points – av 2006/7-2009/10 total QOF points

• QOF clinical measures adjusted for exceptions and thresholds have no explanatory power given covariates

• Patient satisfaction – Overall patient satisfaction insignificant when practice characteristics

and QOF 2006/7 total points included – Patient satisfaction summarises effect of practice characteristics

(Robertson et al, 2008)

• ACSC admission rates – Negatively correlated with QOF quality but no additional explanatory

power

25

Results: distance

• Cubic preferred to other polynomial specifications and to log distance

• Distance effects similar (except linear)

26

Plot of the average marginal effects of distance for linear (km), quadratic (km2), cubic (km3), quartic (km4), and quintic (km5) specifications for baseline model specification.

Average marginal effects of distance

27

Linear specification

Model estimation: patient heterogeneity

• Baseline models assume patients homogenous

• Test for observed and unobserved patient preference heterogeneity

– estimating models for each age and gender group

– stratify LSOAs (separately) by characteristics of the proportion of pop who are non-white, deprived etc.

– estimate random coefficient model (mixed logit model)

28

Results: patient heterogeneity

Separate estimates for 10 age and gender groups

• Young men (25-35) less sensitive to quality

Separate estimates for LSOAs stratified by patient characteristics (rurality, income deprivation, education deprivation, self assessed health, ethnicity; top vs other quintiles)

• Rural areas: less sensitive to distance and quality, ratio similar

• More deprived LSOAs more affected by distance and less by quality (marginal rate of substitution halves)

Unobserved heterogeneity (mixed logit model)

• Similar means, only significant variance in distance and quality

29

Mixed logit Conditional logit

Mean of

coefficients

z Coefficient z

QOF 200607 Total points 0.0029 11.55 0.00224 14.58

Practice in different PCT -0.891 -10.55 -0.826 -19.00

Distance -1.556 -38.51 -1.563 -40.06

Distance squared 0.109 9.06 0.121 10.55

Distance cubed -0.00417 -4.58 -0.00432 -4.88

GP age -0.0254 -15.52 -0.025 -15.68

Proportion female GPs 0.262 7.77 0.262 7.85

Proportion GPs non Europe trained -0.522 -18.95 -0.527 -19.33

Opted out 0.0998 2.73 0.0943 2.61

PMS 0.104 3.28 0.098 3.13

Standard deviation of coefficients QOF 200607 Total points 0.00317 7.02

LSOAs from different PCTs -0.478 -1.76

Distance 0.214 8.28

Distance squared km -0.00439 -1.56

Distance cubic km 0.000341 1.98

GP age 0.00633 1.23

Female GPs 0.0071 0.20

GPs trained outside Europe -0.048 -0.85

Opted out 0.308 2.09

PMS 0.0759 0.34

30

Catchment areas and closed lists • Do data reflect patient or practice choices?

• GPs have obligation to make home visits if medically required. Higher costs to practices if patient lives further away.

• Practices can refuse to enrol patient only if

– patient lives outside catchment area agreed with PCT • If our LSOA choice set radius greater than radii of catchment areas

then zero patients registered with a practice may reflect catchment area not patient demand

– practice has notified PCT that its list is closed: it will not accept any more patients • List turnover averages 8% pa so no practice can have permanently

closed list

• Our data is patients on list at 1 April 2010: stock not flow 31

Results: choice set radius

32

Choice set

radius

QOF 2006/7

total points

Distance

(cubic)

10km AME 0.00013 -0.06778

z 6.87 -14.18

8km AME 0.00014 -0.07751

z 6.94 -14.2

6km AME 0.00019 -0.09964

z 7.07 -14.72

4km AME 0.00029 -0.15248

z 7.76 -16.76

2km AME 0.00044 -0.26363

z 7.98 -23.16

Quality effects increase as choice set shrinks

Results: choice sets only with practices with LSOA patients

33

Minimum patients from

LSOA in practice

QOF 2006/7

total points

Distance

(cubic)

0 patients AME 0.00013 -0.06778

z 6.87 -14.18

1 patient AME 0.00019 -0.0969

z 7.18 -15.6

5 patients AME 0.00026 -0.1268

z 7.47 -18.01

10 patients AME 0.00029 -0.14037

z 7.82 20.94

20 patients AME 0.00032 -0.14739

z 7.99 -24.43

50 patients AME 0.00031 -0.13713

z 7.07 -25.88

Endogeneity?

• Better educated patients care more about quality?

• Quality indicators easier to achieve with better educated patients?

• Implies quality AME biased upward

• Sicker patients care more about quality?

• Quality indicators harder to achieve with sicker patients?

• Implies quality AME biased downward

• Easier to achieve quality in larger practices (econ of scale)?

• Implies quality AME biased upward

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Endogeneity: two stage residual inclusion

• First stage

– Linear practice quality model

– IV: average quality of two nearest practices

– F statistic for IV: 18.5

• Second stage choice model

– Add residual from stage 1 quality model

– SEs : SD of second stage AMEs from 100 bootstrap samples LSOAs

35

Results: 2SRI model

36

Baseline model 2SRI model

AME z AME z

bootstrap

QOF 2006/7 points 0.00013 6.87 0.00074 4.35

QOF 2006/7 residuals -0.00044 -3.02

Different PCT -0.06778 -14.18 -0.10942 -9.85

Distance (cubic) -0.04751 -10.12 -0.11108 -18.82

GP age -0.00144 -13.31 -0.00281 -11.50

Female GPs 0.01508 6.12 0.03084 6.52

GPs non Europe trained -0.03029 -10.36 -0.06328 -10.26

Opted out 0.00543 2.49 0.00803 1.78

PMS 0.00564 2.95 0.01021 2.36

Quality AME larger when instrumented

Effects on demand

37

AME

Extra

metres

Patients

gained

Elasticity

2006/7 QOF points

(1/10th SD increase: 6.4 points ) 0.00082 12.4 103.6 1.44

SE 0.00012 0.9 9.4 0.06

Av age GPs

(1/10th SD increase: 0.7 yrs) -0.00096 -14.6 -120.6 0.003

SE 0.00007 0.9 5.3 0.00

Prop female GPs

(1/10th SD increase: 0.025) 0.00374 56.7 468.1 0.07

SE 0.00061 7.2 47.3 0.01

Prop non-European trained GPs

(1/10th SD increase: 0.035) -0.01072 -162.7 -1342.4 -0.08

SE 0.00103 -8.7 93.6 0.00

Conclusions

• Issue of whether choice will increase quality current and important

• A pre-requisite for increased competition to increase quality is that demanders are responsive to quality

• Find that this does appear to be the case for choice of GP

38

Thank you

39

Other QOF based quality measures

40

Table 3

QOF 2006/7 total

points

(1)

QOF 2006/7 total

points

(2)

QOF 2006/7

clinical points

(3)

AME z AME z AME z

QOF 2006/7 total points 0.00013 6.87

QOF 2006/7 clinical points 0.00015 2.71 0.00019 5.69

QOF 2006/7 organisational points 0.00018 4.90

QOF 2006/7 patient experience -0.00003 -0.78

QOF 2006/7 additional services 0.00139 4.12

QOF 2006/7 holistic care points -0.00020 -0.47

Distance (cubic) -0.06778 -14.18 -0.07626 -9.83 -0.06695 -12.00

BIC 11714907 11710963 11724753

Av 2006/7-09/10

total points

(4)

QOF 2009/10 total

points

(5)

AME z AME z

Av QOF total points 2006/7-2009/10 0.00026 6.947

QOF 2009/10 total points 0.000017 2.569

Distance (cubic) -0.09046 -17.89 -0.03005 -7.334

BIC 11783137 11806537

Patient satisfaction

41

Table 4

Quality measure: overall satisfaction Quality measure: access satisfaction

(1) (2) (3) (4)

AME z AME z AME z AME z

QOF 2006/7 total points 0.00012 6.34 0.00012 6.32

Overall Satisfaction 0.24984 41.6 -0.00725 -0.89

Access Satisfaction -0.18348 -5.50 -0.01072 -1.57

Distance (cubic) -0.06504 -10.93 -0.06419 -11.37

BIC 19439563 11714835 19466172 11714636

Quality measure: would recommend

(5) (6)

AME z AME z

QOF 2006/7 total points 0.00013 6.70

Would recommend 0.27598 225.71 0.02226 3.12

Distance (cubic) -0.07284 -15.02

BIC 19374984 11713209

Distance specification

42

Linear Quadratic Cubic

AME z AME z AME z

QOF 2006/7 Total points 0.00019 7.89 0.00014 7.10 0.00013 6.87

Distance -0.07747 -16.36 -0.06962 -14.60 -0.06778 -14.18

BIC 11886627 11720567 11714907

Quartic Quintic Log distance

AME z AME z AME z

QOF 2006/7 Total points 0.00013 6.96 0.00013 6.94 0.00026 6.45

Distance -0.06914 -14.34 -0.06894 -14.24 -0.21689 -13.44

BIC 11713827 11713833 12363341

Table 7. Rurality, income deprivation

Socio-economic status stratified models

Rurality Income deprivation

Urban LSOAs Rural LSOAs Lowest 4 quintiles Top quintile

AME z AME z AME z AME z

QOF 2006/7 points 0.00017 7.98 0.00003 1.80 0.00014 6.10 0.00010 3.40

Distance (cubic) -0.08518 -16.35 -0.01548 -3.47 -0.06056 -12.19 -0.09852 -8.22

BIC 9447553 2247370 9039531 2648384

N LSOA 2100 770 2295 575

Table 7: Self assessed health, Asian ethnicity .

44

Proportion with poor self assessed health Proportion of Asian ethnicity

Lowest 4 quintiles Top quintile Lowest 4 quintiles Top quintile

AME z AME z AME z AME z

QOF

2006/7

Total

points 0.00016 6.51 0.00007 2.77 0.00011 5.18 0.00021 5.93

Distance

(cubic) -0.07075 -13.60 -0.06246 -6.06 -0.05234 -10.40 -0.12061 -13.22

BIC 9322153 2383773 8469297 3221563

N LSOA 2296 574 2294 576

Choice set restricted radii

45

Choice set radius 10km 8km 6km

AME z AME z AME z

QOF 2006/7 total points 0.00013 6.87 0.00014 6.94 0.00019 7.07

Distance (cubic) -0.06778 -14.18 -0.07751 -14.2 -0.09964 -14.72

BIC 11714907 11262610 10556052

McFadden R2 0.3955 0.3621 0.3094

N LSOA 2870 2806 2670

N GP practices 987 931 855

Choice set radius 4km 2km

AME z AME z

QOF 2006/7 total points 0.00029 7.76 0.00044 7.98

Distance (cubic) -0.15248 -16.76 -0.26363 -23.16

BIC 9096439 5279364

McFadden R2 0.2267 0.1056

N LSOA 2428 1925

N GP practices 729 605

Choice set with min nos patients

46

Minimum patients from

LSOA in practice

10 patients 20 patients 50 patients

AME z AME z AME z

QOF 2006/7 total points 0.00029 7.82 0.00032 7.99 0.00031 7.07

Distance (cubic) -0.14037 20.94 -0.14739 -24.43 -0.13713 -25.88

BIC 10056703 9195685 7367098

McFadden R2 0.1711 0.1284 0.0717

N LSOA 2802 2765 2670

N GP practices 774 751 719

N patients 3220697 3118525 2850124

Minimum patients from

LSOA in practice

0 patients 1 patient 5 patients

AME z AME AME z

QOF 2006/7 total points 0.00013 6.87 0.00019 7.18 0.00026 7.47

Distance (cubic) -0.06778 -14.18 -0.09690 -15.60 -0.12680 -18.01

BIC 11714907 11351519 10649668

McFadden R2 0.3955 0.2983 0.2126

N LSOA 2870 2865 2842

N GP practices 987 889 814

N patients 3364263 3353087 3298413