Randomised controlled trials in primary care: case study

Doctor Sue WilsonUniversity of Birmingham

United Kingdom

Full Reference

Randomised controlled trials in primary care: case study .

Wilson S, Delaney BC, Roalfe A, Roberts L, Redman V, Wearn A, Hobbs FDR. British Medical Journal. 2000;321:24 – 27 (1 July).

About the Author….• Senior Research Fellow

• Public Health / Cancer Epidemiology background

• Interested in design and conduct of high quality research within Primary Care

Learning Objectives

• To understand the importance of research in Primary Care

• To develop an awareness of issues surrounding randomised controlled trials in a primary care setting

Performance Objectives• To demonstrate awareness of some

of the difficulties associated with research in Primary care (e.g. patient / practice recruitment and randomisation)

How will we address this topic?

This lecture will discuss some of the issues that must be considered when conducting and interpreting the results of trials in primary care using examples generated during a trial of the management of dyspepsia.

Background to the Lecture

Why choose Dyspepsia?• Chronic disease

• Largely managed in primary care• Requires high quality evidence

from randomised trials

Background continued

The Research QuestionIs open access endoscopy more

effective and efficient than routine out patient referral for

the management of dyspepsia?

Birmingham Open Access Endoscopy Study

• Eligible subjects–Dyspeptic patients (age 18+)

• Randomised by sealed envelope–Control: usual management - NOT

open access–Study: intervention depends on age

Why do trials in Primary Care?

• Over 90% of patient contacts in NHS occur in Primary Care

• Relevance of research undertaken in secondary or tertiary care is questionable

Recruitment Bias• Amount of Practitioners vs. time /

cost of recruitment / maintenance of practitioners

• Number of patients with relevant condition vs. total consultations

• Participation of Practices / Practitioners in a defined area

Success in recruiting practices N %

Practices contacted 90

Practices expressing interest 59 65

Practices ‘recruited’ 43 48

Practices recruiting a patient 31 34

Practices recruiting 5+ patients 23 26

Practice Characteristics

Active practices (n=31)

Eligible, not participating (n=216)

Wilcoxon rank sum test

No. of partners

Median (IQR) 3 (2 to 6) 2 (1 to 3)

Mean (SD) 3.8 (2.2) 2.2 (1.6)

Townsend score:

Median (IQR) 1.8 (-0.9 to 4) 4.4 (1.0 to 6.3) Z = -3.2, P<0.01

Mean (SD) 1.5 (2.8) 3.8 (7.4)

Z = 4.4, P<0.0001

Recruitment Bias (patients)• Eligible patients not asked /not

prepared to enter study• Differences in prevalence /

presentation rates• Differences in proportion of

eligible patients recruited

Factors affecting recruitment rates

• Interest in trial may wane after initial period

• Eligible cases will be restricted to incident disease once pool of prevalent cases have been recruited

Case definition: Standardised monthly recruitment rate by

duration of participation

00.5

11.5

22.5

33.5

44.5

0 10 20 30 40Time since practice recruited (months)

Rec

ruitm

ent R

ate

per 1

0,00

0 po

pula

tion

Ethical Issues and recruitment

• Patient may feel obligated to participate• Financial implications to GP• Conflict between randomisation options

and preferred course of management• Patient acceptance of randomisation or

outcome of randomisation

Selective recruitment of patients

• Impact of Randomisation process on results

• Complexities in randomisation / reduced patient recruitment

• Recruitment levels and Practice workload

Selective recruitment of patients continued

• Practice commitment• Use of research staff for

recruitment

Practice Recruitment Rate & Symptom Score at time of recruitment

02468

1012141618

0 5 10 15 20Mean Symptom ScoreM

onth

ly R

ecru

itmen

t Rat

e pe

r 10,

000

popu

latio

n

Does representativeness matter?

• Not at all?–Trials have always been selective–Its up to others to determine local

applicability• Very much?

–Raison d’etre of primary care trial

Does representativeness matter?(continued)

• To some extent?–Balance to be achieved–Modelling helps generalise and

particularise

References