To determine whether robot-assisted training is cost-effective compared with an enhanced upper limb therapy (EULT) programme or usual care.
Economic evaluation within a randomised controlled trial.
Four National Health Service (NHS) centres in the UK: Queen’s Hospital, Barking, Havering and Redbridge University Hospitals NHS Trust; Northwick Park Hospital, London Northwest Healthcare NHS Trust; Queen Elizabeth University Hospital, NHS Greater Glasgow and Clyde; and North Tyneside General Hospital, Northumbria Healthcare NHS Foundation Trust.
770 participants aged 18 years or older with moderate or severe upper limb functional limitation from first-ever stroke.
Participants randomised to one of three programmes provided over a 12-week period: robot-assisted training plus usual care; the EULT programme plus usual care or usual care.
Mean healthcare resource use; costs to the NHS and personal social services in 2018 pounds; utility scores based on EQ-5D-5L responses and quality-adjusted life years (QALYs). Cost-effectiveness reported as incremental cost per QALY and cost-effectiveness acceptability curves.
At 6 months, on average usual care was the least costly option (£3785) followed by EULT (£4451) with robot-assisted training being the most costly (£5387). The mean difference in total costs between the usual care and robot-assisted training groups (£1601) was statistically significant (p<0.001). Mean QALYs were highest for the EULT group (0.23) but no evidence of a difference (p=0.995) was observed between the robot-assisted training (0.21) and usual care groups (0.21). The incremental cost per QALY at 6 months for participants randomised to EULT compared with usual care was £74 100. Cost-effectiveness acceptability curves showed that robot-assisted training was unlikely to be cost-effective and that EULT had a 19% chance of being cost-effective at the £20 000 willingness to pay (WTP) threshold. Usual care was most likely to be cost-effective at all the WTP values considered in the analysis.
The cost-effectiveness analysis suggested that neither robot-assisted training nor EULT, as delivered in this trial, were likely to be cost-effective at any of the cost per QALY thresholds considered.
Our economic evaluation was designed and conducted following best practice methods which resulted in robust and generalisable results.
Sensitivity analyses exploring any uncertainties surrounding the level of resource use and their impact on the cost-effectiveness of the interventions add to the robustness of the results.
The unavailability of longer-term data for the within trial evaluation means that no robust inferences could be made on the long-term cost-effectiveness of the interventions.
Poor completion of arm rehabilitation therapy logs meant that detailed information on the delivery of usual care was obtained from the health service utilisation questionnaire.
The use of quality-adjusted life years based on responses to the EQ-5D-5L questionnaire as a generic outcome measure may not accurately capture changes in quality of life for this patient group.
Stroke is the fourth leading cause of death in the UK and a leading cause of disability. Almost two-thirds of patients who had a stroke leave hospital with a disability.
The Robot-Assisted Training for the Upper Limb after Stroke (RATULS) trial sought to evaluate the clinical effectiveness and cost-effectiveness of robot-assisted training (using the MIT-Manus robotic gym system) by comparing it with either an enhanced upper limb therapy (EULT) programme, or usual care.
After conducting a scoping review, we found little evidence of cost-effectiveness studies in the UK. The only economic evaluation we found in the literature assessed the cost-effectiveness of robot-assisted training therapy for upper limb rehabilitation within the USA based VA Robotics study.
The study was a three-arm RCT which recruited 770 participants from stroke units, day hospitals, outpatient clinics, primary care, community rehabilitation services and local stroke clubs in four study centres. The sample size calculation yielded a target sample size of 762 participants with 216 participants in each group required to provide 80% power at a significance level of 1.7%. The sample size was revised after protocol publication to 770 to allow for 15% attrition (rather than 10% as originally specified in the published protocol). Full details on sample size calculation and trial methodology have been reported elsewhere.
Participants were eligible for inclusion in the study if they were 18 years or older, had experienced a first-ever stroke between 1 week and 5 years prior to randomisation and, as a consequence of the stroke, had moderate or severe upper limb functional limitation as measured by the Action Research Arm Test (ARAT)
The clinical primary outcome of the study was upper limb function ‘success’ using (ARAT)
We conducted an economic evaluation consisting of a cost–utility analysis using the quality-adjusted life year (QALY) as the primary outcome measure following guidance for best practice in health technology appraisal.
We conducted all analyses adopting the perspective of the UK National Health Service (NHS) and personal social services setting.
The costs included in the analysis comprised the intervention costs for the robot-assisted training and EULT programmes, no intervention costs were directly associated with usual care and we assumed that any rehabilitation received had been reported in the health service utilisation questionnaire. We also included use of health and social services over the 6-month follow-up period for all randomised groups. For the intervention costs we assumed, as per the protocol,
We developed a health service utilisation questionnaire, informed by previous data collection tools including the Client Service Receipt Inventory
To estimate the cost at 6 months for each participant we combined data on use of care and services with unit costs obtained from routine data sources. We applied NHS national reference costs
We used the information collected at 6-month follow-up in addition to the intervention costs to derive the total mean cost per participant per each randomised group. All costs are reported in pounds Sterling and converted to 2018 prices, when appropriate, using the Bank of England inflation calculator.
The quality of life outcome measures used for the economic evaluation were the summary utility scores derived from the EQ-5D-5L questionnaires.
For the main (base-case) cost-effectiveness analysis we only included those participants for whom we had some data on costs. Once we determined that missing cost data were missing at random, we explored in the sensitivity analyses the effect on cost-effectiveness of applying multiple imputation to missing total costs controlling for age, sex and baseline ARAT score.
We explored the patterns of missing utility data. Once we established that information was missing at random, we used multiple imputation methods to estimate the missing utility values at 3 months and 6 months. This involved applying truncated normal regression while controlling for age, sex and baseline ARAT score in order to generate the missing utility value.
We calculated mean costs and effects along with corresponding SD. Where we report differences in mean costs and effects between all three randomised groups we used 98.33% CIs, as this was a three-arm comparison. We conducted all pairwise comparisons using 95% CIs. Using seemingly unrelated regression modelling methodology
In the analysis if a comparator was both more costly and less effective than the others it was dropped from any further cost-effectiveness comparisons because it was less cost-effective than the other comparator.
We created cost-effectiveness acceptability curves in order to assess the imprecision surrounding the estimates of costs, effects and cost-effectiveness. This approach involved drawing bootstrapped samples, with replacement, of the mean costs and mean QALYs from the original trial data. We repeated this process increasing the number of replications until the results were stable. This was achieved at 1000 replications. After using the new values generated from the bootstrapping exercise to calculate the difference in costs and effects between groups, we combined this information with a range of willingness to pay (WTP) values (£0, £10 000, £20 000, £30 000, £50 000) per QALY gained. This involved using the net benefit statistic
We conducted deterministic sensitivity analyses in order to assess the robustness of the cost-effectiveness results for three scenarios.
First, we examined the impact of assigning a value of zero to missing total healthcare costs.
Second, we examined the possibility that those participants with missing total healthcare costs may have used some services and hence incurred some costs. Under this scenario, once we established that information was missing at random, we applied truncated normal regression methods excluding total costs values below zero and above £25 000 (as the highest observed value for total costs) and used age, sex and baseline ARAT as covariates.
Finally, we investigated whether increasing the life span of the MIT-Manus robotic gym system from 5 to 7 years would affect the cost-effectiveness of the interventions.
In order to explore the impact of time since stroke on the cost-effectiveness of the interventions, we conducted an exploratory analysis for the subgroups outlined in the protocol.
A secondary per-protocol cost-effectiveness analysis removing from the data set those participants who did not receive at least 20 sessions of therapy in the robot-assisted training and the EULT programme groups was also conducted. The cut-off point of 20 sessions was based on clinical evidence that an additional 20 hours of therapy compared with control interventions leads to improvements on functional outcome.
We combined each sensitivity, subgroup and per-protocol analyses with bootstrapping in order to reflect the imprecision surrounding the cost-effectiveness results.
We carried out a modelling exercise designed to extrapolate the mean QALYs at 6 months to 12 months based on the results of the trial, for this, we made a number of assumptions. First, we assumed that participants across all groups maintained the same utility levels reported at 6 months postrandomisation. Second, we considered all intervention costs and therapy-related costs (physiotherapy, occupational therapy, and speech and language therapy) as sunk costs, since they were deemed not to continue beyond the 6-month trial period. However, we assumed that all other levels of healthcare resource use remained constant from 6 to 12 months postrandomisation.
We calculated the difference in mean costs and effects between the randomised groups with differences across groups not being formally tested. We used seemingly unrelated regression
We have designed and reported our research with input from stroke survivors. Members from the North East Stroke Research Network Patient and Carer Panel provided input to the design and content of trial documents, including health economics questionnaires.
Most participants (96%) across all groups completed the health service utilisation questionnaire at baseline. There was a progressive increase in non-responses to the health service utilisation questionnaires over the 6-month follow-up period. The pattern of responses was similar across the intervention groups; however, the loss to follow-up was more pronounced in the usual care group. While completion rates were 83% for the robot-assisted training group and 85% for the EULT group, this decreased to 70% of usual care participants. Completion rate of EQ-5D-5L at baseline was 99% across all of participants. This decreased to 88% at 3 months and 82% at 6 months. The highest number of non-responders belonged to the usual care group with response rates of 81% at 3 months and 75% at 6 months.
Reported health service resource use was broadly similar across all randomised groups at 6 months (
Reported health service resource use at 6 months
Area of resource utilisation | Robot-assisted training (n=257) | EULT (n=259) | Usual care (n=254) | |||
Respondents n* | Mean contacts (SD) | Respondents n* | Mean contacts (SD) | Respondents n* | Mean contacts (SD) | |
GP surgery | 205 | 1.80 (3.88) | 208 | 1.49 (2.08) | 168 | 1.83 (2.17) |
GP home | 209 | 0.37 (1.08) | 213 | 0.27 (0.73) | 174 | 0.38 (1.29) |
GP phone | 207 | 0.53 (1.22) | 207 | 0.39 (0.96) | 172 | 0.30 (0.77) |
Nurse surgery | 203 | 0.61 (1.39) | 210 | 0.49 (1.19) | 169 | 0.90 (5.58) |
Nurse home | 206 | 0.47 (2.07) | 213 | 0.45 (1.65) | 170 | 5.39 (44.63) |
Nurse phone | 211 | 0.08 (0.56) | 212 | 0.52 (0.31) | 174 | 0.04 (0.25) |
NHS direct | 211 | 0.11 (0.44) | 213 | 0.08 (0.35) | 174 | 0.03 (0.32) |
Physiotherapy hospital | 210 | 2.18 (6.10) | 211 | 2.99 (9.23) | 171 | 2.64 (7.72) |
Physiotherapy home | 205 | 2.76 (8.76) | 207 | 3.10 (8.04) | 170 | 4.35 (11.87) |
Physiotherapy at general practice surgery | 213 | 0.13 (1.16) | 212 | 0.40 (2.63) | 176 | 0.50 (3.85) |
Physiotherapy elsewhere | 212 | 0.23 (1.45) | 213 | 0.21 (1.82) | 175 | 0.62 (4.63) |
Occupational therapy hospital | 211 | 0.64 (3.14) | 211 | 1.23 (7.23) | 174 | 0.57 (3.53) |
Occupational therapy home | 210 | 1.56 (5.39) | 209 | 1.27 (4.28) | 173 | 1.95 (7.23) |
Occupational therapy at general practice surgery | 213 | 0.00 (0.07) | 211 | 0.01 (0.14) | 176 | 0.02 (0.23) |
Occupational therapy elsewhere | 212 | 0.16 (1.49) | 211 | 0.00 (0.00) | 176 | 0.00 (0.00) |
Speech and language therapy hospital | 213 | 0.57 (2.79) | 213 | 0.65 (3.74) | 173 | 0.94 (5.24) |
Speech and language therapy home | 210 | 0.47 (2.00) | 212 | 0.64 (3.97) | 175 | 2.22 (15.42) |
Speech and language therapy at general practice surgery | 212 | 0.00 (0.00) | 213 | 0.03 (0.42) | 176 | 0.02 (0.13) |
Speech and language therapy elsewhere | 213 | 0.05 (0.42) | 213 | 0.47 (0.68) | 175 | 0.03 (0.45) |
A&E visits | 213 | 0.33 (0.77) | 214 | 0.37 (0.98) | 178 | 0.24 (0.70) |
Outpatient appointments | 212 | 1.64 (3.14) | 215 | 1.42 (2.88) | 176 | 1.48 (4.24) |
Hospital nights after being admitted via A&E | 213 | 0.79 (4.77) | 215 | 1.83 (12.95) | 176 | 0.70 (3.59) |
Hospital nights NOT admitted via A&E | 213 | 0.28 (3.09) | 215 | 0.03 (0.19) | 176 | 0.25 (1.81) |
Day patient treatment (half day) | 205 | 0.08 (0.35) | 210 | 0.09 (0.46) | 175 | 0.06 (0.32) |
Day patient treatment (full day) | 199 | 0.03 (0.17) | 201 | 0.02 (0.18) | 169 | 0.06 (0.07) |
Residential care | 213 | 1.75 (14.65) | 215 | 2.08 (17.07) | 177 | 1.39 (10.72) |
Nursing home | 213 | 0.00 (0.00) | 216 | 0.83 (12.24) | 177 | 3.08 (23.51) |
Meals on wheels | 213 | 0.02 (0.27) | 213 | 0.04 (0.49) | 177 | 0.08 (1.05) |
Home help personal care | 211 | 2.89 (6.77) | 210 | 3.04 (7.42) | 173 | 3.17 (7.03) |
Home help household tasks | 213 | 0.74 (3.21) | 212 | 0.68 (3.87) | 175 | 1.06 (4.54) |
Home help shopping | 213 | 0.11 (0.74) | 212 | 0.07 (0.53) | 176 | 0.11 (0.76) |
Health visitor | 212 | 0.05 (0.45) | 213 | 0.09 (0.85) | 177 | 0.03 (0.28) |
Geriatrician | 212 | 0.03 (0.42) | 213 | 0.02 (0.23) | 177 | 0.00 (0.00) |
Psychiatrist | 212 | 0.13 (0.72) | 213 | 0.75 (0.54) | 175 | 0.01 (0.11) |
Psychologist | 209 | 0.45 (2.07) | 211 | 0.28 (1.14) | 176 | 0.44 (2.37) |
Chiropodist | 210 | 0.55 (1.19) | 210 | 0.39 (1.06) | 173 | 0.44 (1.02) |
Optician | 210 | 0.25 (0.56) | 212 | 0.23 (0.53) | 174 | 0.32 (0.64) |
Pharmacist | 211 | 0.66 (2.33) | 207 | 0.60 (2.28) | 174 | 1.16 (4.35) |
*n denotes the number of participants who completed all or part of the questionnaire.
A&E, accident and emergency; EULT, enhanced upper limb therapy; GP, general practitioner.
The mean total cost per participant for each randomised group is reported in
Total cost (£) over 6 months for all participants with full economic data
Area of resource utilisation | Robot-assisted training (n=257) | EULT (n=259) | Usual care (n=254) | |||
n | Mean (SD) | n | Mean (SD) | n | Mean (SD) | |
Intervention costs | 257 | 2872 (0) | 259 | 1399 (0) | 0 | – |
Primary care costs and community-based healthcare (including therapy services) | 213 | 743 (1031) | 215 | 777 (1262) | 177 | 1078 (1813) |
Social care | 213 | 1410 (3146) | 216 | 1541 (3943) | 178 | 1890 (4281) |
Secondary care | 213 | 733 (2247) | 216 | 988 (4486) | 178 | 668 (1880) |
Medication costs | 157 | 149 (302) | 162 | 154 (273) | 126 | 198 (347) |
Other NHS and social services | 11 | 727 (983) | 13 | 790 (946) | 9 | 307 (406) |
Deceased participants | 1 | 0 (0) | 3 | 13 953 (4516) | 0 | – |
Mean total cost | 257 | 5387 (4054) | 259 | 4451 (6033) | 178 | 3785 (5437) |
Mean difference between robot-assisted training and usual care with 95% CI; p value | 1601 (706 to 2496); <0.001 | |||||
Mean difference between EULT and usual care with 95% CI; p value | 665 (−444 to 1774); 0.239 |
EULT, enhanced upper limb therapy; n, randomised n; NHS, National Health Service.
The mean utility scores across all randomised groups were similar at baseline, 3 months and 6 months as were mean QALYs (
Utility scores at baseline, 3 months and 6 months and QALYs at 6 months
Time period | Robot-assisted training (n*=257) | EULT (n*=259) | Usual care (n*=254) | |||
n | Mean | n | Mean | n | Mean | |
Baseline EQ-5D-5L score | 254 | 0.36 (0.26) | 259 | 0.39 (0.25) | 254 | 0.37 (0.26) |
3-month EQ-5D-5L score | 232 | 0.45 (0.27) | 236 | 0.48 (0.24) | 207 | 0.42 (0.29) |
6-month EQ-5D-5L score | 223 | 0.46 (0.29) | 222 | 0.50 (0.27) | 190 | 0.46 (0.27) |
QALYs at 6 months after multiple imputation | 254 | 0.21 (0.12) | 259 | 0.23 (0.10) | 254 | 0.21 (0.11) |
Mean difference in QALYs between robot-assisted training and usual care with 95% CI; p value | 0.00 (−0.20 to 0.20); 0.995 | |||||
Mean difference in QALYs between EULT and usual care with 95% CI; p value | 0.02 (0.00 to 0.35); 0.080 |
*n=number randomised.
EULT, enhanced upper limb therapy; QALY, quality adjusted life year.
The base-case cost-effectiveness analysis results (
Cost-effectiveness acceptability curve (base-case analysis)—adjusted bootstrapped replications for cost-effectiveness analysis. EULT, enhanced upper limb therapy.
Results from base-case cost-effectiveness analysis, subgroup analyses and longer-term economic model
Scenario | Robot-assisted training | EULT | Usual care | ICER | Probability of each therapy being cost-effective at the £20 000 WTP threshold | ||
Robot-assisted training | EULT | Usual care | |||||
Base-case analysis | |||||||
Cost—£, unadjusted, mean (CI)* | 5387 | 4451 | 5387 | – | – | – | – |
QALY—unadjusted, mean (CI)* | 0.21 | 0.23 | 0.21 | – | – | – | – |
ICER (£ per QALY)—adjusted EULT vs usual care† | – | – | – | 74 100 | 0.00 | 0.19 | 0.81 |
Subgroup analysis (less than 3 months—time since stroke) | |||||||
Cost—£, unadjusted, mean (CI) | 5485 | 3863 | 3328 | – | – | – | – |
QALY—unadjusted, mean (CI)* | 0.22 | 0.24 | 0.21 | – | – | – | – |
ICER (£ per QALY)—adjusted EULT vs usual care† | – | – | – | 31 400 | 0.00 | 0.41 | 0.59 |
Subgroup analysis (3 to 12 months—time since stroke) | |||||||
Cost—£, unadjusted, mean (CI)* | 5790 | 5084 | 4943 | – | – | – | – |
QALY—unadjusted, mean (CI) | 0.20 | 0.23 | 0.21 | – | – | – | – |
ICER (£ per QALY)—adjusted EULT vs usual care† | – | – | – | 79 400 | 0.04 | 0.37 | 0.59 |
Subgroup analysis (more than 12 months) | |||||||
Cost—£, unadjusted, mean (CI)* | 4822 | 3961 | 2823 | – | – | – | – |
QALY—unadjusted, mean (CI)* | 0.22 | 0.23 | 0.21 | – | – | – | – |
ICER (£ per QALY)—adjusted EULT vs usual care§ | – | – | – | 126 143 | 0.01 | 0.15 | 0.84 |
Per-protocol analysis | |||||||
Cost—£, unadjusted, mean (CI)* | 5595 | 4551 | 3785 | – | – | – | – |
QALY—unadjusted, mean (CI)* | 0.22 | 0.23 | 0.21 | – | – | – | – |
ICER (£ per QALY)—adjusted EULT vs usual care† | – | – | – | 68 000 | 0.00 | 0.17 | 0.83 |
Extrapolation to 12 months | |||||||
Cost—£, unadjusted, mean (CI)* | 7538 | 6892 | 6916 | – | – | – | – |
QALY—unadjusted, mean (CI)* | 0.44 | 0.48 | 0.45 | – | – | – | – |
ICER (£ per QALY)—adjusted EULT vs usual care† | – | – | – | 6095 | 0.10 | 0.55 | 0.35 |
*98.33% CI used throughout the analyses for the three-arm comparison.
†Data adjusted for baseline costs, baseline utility score, study centre, randomised group and time since stroke.
EULT, enhanced upper limb therapy; ICER, incremental cost–effectiveness ratio; QALY, quality adjusted life year; WTP, willingness to pay.
The results from the subgroup analysis are also summarised in
Results from the per-protocol analysis did not change the direction of the cost-effectiveness results. Usual care remained the least costly option followed by EULT and robot-assisted training. The ICER for EULT and usual care was £68 000 and EULT only had a 17% probability of being cost effective at the £20 000 WTP threshold. The probability of robot-assisted therapy being considered cost-effective was very low.
The different scenarios explored in these analyses did not change the direction of the results from the base-case cost-effectiveness results. Robot-assisted training remained dominated on average by EULT in all instances. First, when we changed the missing costs to zero, the resulting ICER between EULT and usual care increased to £172 000. This increase is to be expected since all participants with missing total costs belong to the usual care group. By imputing zero for missing costs the mean costs for the usual care participants decreased and hence, when this was done, the ICER increased when compared with EULT.
Second, applying multiple imputation methods to missing costs resulted in an increase to the unadjusted mean usual care costs (£4451) compared with the base-case results (£3785). Consequently, the resulting ICER from the comparison between EULT and usual care decreased to £50 000 with the probability of EULT being cost-effective at £20 000 increasing to 27%.
Third, extending the life of the robotic gym system resulted in a reduction of the mean capital costs per patient and hence, in a lower mean total cost for the robot-assisted training group (£5085) compared with the base-case analysis (£5387). There were no changes to the utility scores across all groups nor to the mean costs for EULT and usual care, hence the resulting ICER for the comparison of EULT and usual care remained the same as in the base-case analysis (£74 100).
The RATULS trial found no evidence that robot-assisted training, as delivered in the study, improved upper limb function ‘success’ for patients who had a stroke with moderate or severe upper limb functional limitation when compared with a EULT programme or usual care.
Results from the base-case cost-effectiveness analysis suggested that, on average, robot-assisted training was more costly than both EULT and usual care and that robot-assisted training was slightly less effective than EULT. EULT was on average more costly and as effective as usual care in the unadjusted analyses and more costly and more effective in the adjusted analyses. The balance of probabilities favoured usual care as the preferred upper limb rehabilitation therapy over the range of WTP values considered. Focusing on the society’s WTP for a QALY, the bootstrapped analysis suggested that, EULT, as delivered in this trial, was unlikely to be cost-effective over any of the WTP values considered, despite being more effective than robot-assisted training and usual care. The subgroup, sensitivity and per-protocol analyses did not change the direction of the base-case cost-effectiveness results. Extrapolating within-trial results to 12 months produced the lowest ICER for the comparison between EULT and usual care overall, however, high uncertainty surrounds the assumptions made about how costs and utilities change beyond the trial follow-up.
The main strength of this economic evaluation is that it was conducted as part of a rigorously run RCT and followed guidelines for best practice throughout.
One of the main challenges in conducting the economic evaluation was the difficulty to ascertain the specific components of usual care therapy. Log books designed to capture detailed usual care information were completed by participants. The information gathered was to be used alongside the health service utilisation questionnaire. Completion rates, however, were very low and we were unable to incorporate these data into the economic evaluation. We overcame this by drawing on the information captured via our primary data collection tool, the healthcare service utilisation questionnaire, where participants recorded any therapy sessions received during the trial period.
Through the collection of self-reported quality of life information at three points during the study using the EQ-5D-5L questionnaire,
A noteworthy limitation of the economic evaluation is associated with the timeframe of the trial. The within-trial economic evaluation assessed the cost-effectiveness of the interventions at 6 months. A longer-term perspective was originally planned but due to limitations of the data, extrapolation to 12 months only was conducted. The results however, need to be interpreted with caution due to the assumptions made on both costs and utility values.
The economic evaluation fills a significant evidence gap with this being the first economic evaluation comparing robot-assisted training with usual care having been conducted in the UK NHS setting. This evaluation expands the analysis conducted on the cost-effectiveness of the MIT-Manus robotic system as part of the VA Robotics trial.
The use of multiple sites contributed to the generalisability of the economic evaluation. The analyses controlled for differences in sites hence minimising the chance of obtaining biased results from differences in costs and effects driven by location.
In conclusion, robot-assisted training was not found to be cost-effective in comparison to EULT and usual care. This economic evaluation suggested that usual care remained the most cost-effective type of upper limb rehabilitation compared with a EULT therapy programme and robot-assisted training for patients who had a stroke with moderate or severe functional limitation.
The results create opportunities for further research. In particular, further research could explore the potential effect on both costs and QALYs from reconfigurations to the delivery of EULT and robot-assisted training. It remains unclear, for example, whether delivering therapy in a group setting may first, be feasible in the NHS setting and second improve the quality of life and clinical outcomes. Further development of these interventions may increase their cost-effectiveness compared with usual care. Additionally, studies with a longer follow-up data may help establish whether the QALY gains derived from the interventions are sustained beyond the set timeframe of the trial, this can then lead to a robust assessment of their long-term cost-effectiveness.
We would like to thank Jenni Hislop for her input into the health economics analysis plan and the development of the data collection tools.
CF-G conducted the health economic evaluation. LV and LT are senior health economists and were involved in the main study design, delivery, analysis and interpretation of the data and drafting the manuscript. TMH contributed to the health economic evaluation and drafting of the manuscript. HR was the chief investigator of the study. HB, HIK, FVW, GF, LS, LA, TF, CP, DT, SW, JD were involved in the main study design, delivery, data management, data analysis and drafting the manuscript. NW, SA, DC, RF, NH contributed to study delivery, interpretation of the data and drafting the manuscript. SH was a coinvestigator and is a service user, he was involved in the main study design and delivery, interpretation of data. All authors have commented upon drafts of the manuscript and have given final approval to this version.
This work was supported by the National Institute for Health Research Health Technology Assessment Programme (reference: 11/26/05). The views and opinions expressed here are those of the authors and do not necessarily reflect those of the HTA programme, NIHR, the UK National Health Service (NHS) or UK Department of Health.
HR reports grants from NIHR, during the conduct of the study; personal fees from Bayer, outside the submitted work; and Member of NIHR HTA CET panel 2010–2014. GF reports grants from National Institute for Health Research, during the conduct of the study; personal fees from Amgen, personal fees from Daiichi Sankyo, grants and personal fees from Medtronic, personal fees from Stryker, personal fees from Pfizer, personal fees from Bayer, outside the submitted work. CP and LS report grants from National Institute for Health Research, during the conduct of the study. HIK reports other from Interactive Motion Technologies, other from 4Motion Robotics, outside the submitted work; in addition, HIK has a patent Interactive Robotic Therapist; US Patent 5466213; 1995; Massachusetts Institute of Technology issued, and a patent Wrist And Upper Extremity Motion; US Patent No. 7618381; 2009; Massachusetts Institute of Technology licensed to Bionik Laboratories.
Patients and/or the public were involved in the design, or conduct, or reporting, or dissemination plans of this research. Refer to the Methods section for further details.
Not commissioned; externally peer reviewed.
Data are available upon reasonable request. De-identified participant data will be made available to scientific researchers upon approval of their study protocol and analysis plan, by a committee of the RATULS team. Proposals should be directed to the corresponding author. A data sharing agreement will need to be signed by data requestors.
Not required.
Ethical approval was obtained for the clinical trial and the economic questionnaires. Approval was granted by the National Research Ethics Committee Sunderland (reference 12/NE/0274). The research here submitted is confined to the within trial economic evaluation.