The main study design and interventions are described in detail in our associated
paper.
5 Briefly, we conducted a randomised
controlled trial using a 4×2 factorial design, in which participants from 64 general
practices were randomised to one of eight groups. A short course of six lessons in the
Alexander technique, a longer course of 24 lessons, and six sessions of massage were
compared with normal care—half with and half without a doctor’s prescription for home based
general exercise and a practice nurse’s behavioural counselling.
We carried out the economic evaluation 12 months after randomisation of participants,
conducting it from the perspectives of the NHS, participants, and society. We included costs
to the NHS, personal costs to participants, and time off work and unpaid activities. NHS
costs included the intervention, primary care contacts, outpatient appointments, inpatient
hospital stays, and medication. Personal costs included travel associated with back pain
treatment, any private treatment and over the counter preparations, prescription charges,
loss of earnings, and expenditure on domestic help and care giving. Societal costs included
the value of time off work or unpaid activities and the value of informal care.
We analysed the data in two ways. Individual group analysis was used to provide the most
relevant information for policy makers, and we carried out marginal analysis in line with
the convention for a factorial design.
6 In both
cases we compared each intervention group with the most appropriate comparator group as
shown in table 1.
| Table 1 Interventions for chronic or recurrent low back pain in 579 patients recruited from
primary care and comparisons between the trial groups |
We estimated cost to the NHS and patients separately, and conducted a cost effectiveness
analysis that compared cost to the NHS with the primary outcome of the Roland-Morris
disability questionnaire,
7 the number of days in
pain,
8 and the QALY gain estimated from the
European quality of life instrument EQ-5D.
9 We
estimated cost effectiveness acceptability curves for the individual treatment groups to
indicate the level of uncertainty around the point estimates of cost per QALY.
Data collection
Table 2 shows the data sources and unit costs used in
this study. We collected resource use data prospectively during the trial. We recorded the
number of intervention sessions attended, extracted details of primary care visits and
prescribed drugs for back pain from practice records, and took other information from
participants’ self completed questionnaires conducted at three-monthly intervals. The
EQ-5D was conducted at baseline, three months, and 12 months.
| Table 2 Data sources and unit costs used in costing interventions for chronic or recurrent
low back pain |
We used unit costs in pounds sterling at 2005 prices. We based primary care costs on
Curtis and Netten,
10 secondary care costs on the
Department of Health national tariff,
11 and drug
costs on the
British National Formulary.
12 The exercise prescription, which included both general practitioner and
practice nurse time, was costed as primary care consultations, and the Alexander technique
and massage interventions were costed at the rate paid to teachers and therapists during
the trial. A charge was made for a missed appointment but not after a patient dropped out
of the trial. Personal costs were self reported except for travel by car, for which we
used the AA schedule of motoring costs.
13 No
adjustment for inflation was necessary.
Data analysis
Data extracted from primary care records were available for all participants. Some
questionnaire data, including the EQ-5D responses, were missing because of some
participants dropping out or failing to answer all the questions. Complete personal cost
data were available for 62% of patients, and the overall proportion of missing data points
was 35%. We had complete EQ-5D data for 306 (53%) patients: the data were complete for 92%
of participants at baseline, 72% at three months, and 62% at 12 months, giving a total of
25% missing data points. The level of completeness declined to 68% for the period from
baseline to three months and to 55% for the time from three months to 12 months, giving an
overall level of 62%.
We filled in the missing data points by means of imputation by chained equation using
STATA, release 9.
15 This method imputes missing
values using an iterative multivariable regression technique. Any number of variables can
be used in the regression, and any number of complete imputations may be created. In this
study we used all available EQ-5D data, plus the intervention group variable; we used 20
cycles of five imputations.
The EQ-5D data were used to estimate QALY gain per patient over the 12 month period using
the published social tariff for EQ-5D.
16 We used
the “area under the curve approach,” adjusted for baseline differences across the groups,
to calculate QALY gain.
17Uncertainty in assumptions or estimates made during the analysis were addressed in a
series of one-way sensitivity analyses. We estimated uncertainty around the incremental
cost effectiveness ratios of cost per QALY using the bootstrapping technique. We generated
1000 replications of each incremental cost effectiveness ratio and used them to derive
cost effectiveness acceptability curves.
It was not necessary to discount the costs and outcomes, as the time horizon of the study
was one year. All analyses were carried out using Microsoft Excel and STATA 9.
15