Missing data in trial-based cost-effectiveness analysis: the current state of play

Cost-effectiveness of providing university students with a mindfulness-based intervention to reduce psychological distress: economic evaluation of a pragmatic randomised controlled trial

OBJECTIVE

Increasing numbers of young people attending university has raised concerns about the capacity of student mental health services to support them. We conducted a randomised controlled trial (RCT) to explore whether provision of an 8 week mindfulness course adapted for university students (Mindfulness Skills for Students-MSS), compared with university mental health support as usual (SAU), reduced psychological distress during the examination period. Here, we conduct an economic evaluation of MSS+SAU compared with SAU.

DESIGN AND SETTING

Economic evaluation conducted alongside a pragmatic, parallel, single-blinded RCT comparing provision of MSS+SAU to SAU.

PARTICIPANTS

616 university students randomised.

PRIMARY AND SECONDARY OUTCOME MEASURES

The primary economic evaluation assessed the cost per quality-adjusted life year (QALY) gained from the perspective of the university counselling service. Costs relate to staff time required to deliver counselling service offerings. QALYs were derived from the Clinical Outcomes in Routine Evaluation Dimension 6 Dimension (CORE-6D) preference based tool, which uses responses to six items of the Clinical Outcomes in Routine Evaluation Outcome Measure (CORE-OM; primary clinical outcome measure). Primary follow-up duration was 5 and 7 months for the two recruitment cohorts.

RESULTS

It was estimated to cost £1584 (2022 prices) to deliver an MSS course to 30 students, £52.82 per student. Both costs (adjusted mean difference: £48, 95% CI £40-£56) and QALYs (adjusted mean difference: 0.014, 95% CI 0.008 to 0.021) were significantly higher in the MSS arm compared with SAU. The incremental cost-effectiveness ratio (ICER) was £3355, with a very high (99.99%) probability of being cost-effective at a willingness-to-pay threshold of £20 000 per QALY.

CONCLUSIONS

MSS leads to significantly improved outcomes at a moderate additional cost. The ICER of £3355 per QALY suggests that MSS is cost-effective when compared with the UK's National Institute for Health and Care Excellence thresholds of £20 000 per QALY.

TRIAL REGISTRATION NUMBER

Australian and New Zealand Clinical Trials Registry, ACTRN12615001160527.

Cost-effectiveness of closed incision negative pressure wound therapy in preventing surgical site infection among obese women giving birth by caesarean section: An economic evaluation (DRESSING trial)

BACKGROUND

There is growing evidence regarding the potential of closed incision negative pressure wound therapy (ci-NPWT) to prevent surgical site infections (SSIs) in healing wounds by primary closure following a caesarean section (CS).

AIM

To assess the cost-effectiveness of ci-NPWT compared to standard dressings for prevention of SSI in obese women giving birth by CS.

MATERIALS AND METHODS

Cost-effectiveness and cost-utility analyses from a health service perspective were undertaken alongside a multicentre pragmatic randomised controlled trial, which recruited women with a pre-pregnancy body mass index ≥30 kg/m2 giving birth by elective/semi-urgent CS who received ci-NPWT (n = 1017) or standard dressings (n = 1018). Resource use and health-related quality of life (SF-12v2) collected during admission and for four weeks post-discharge were used to derive costs and quality-adjusted life years (QALYs).

RESULTS

ci-NPWT was associated with AUD$162 (95%CI -$170 to $494) higher cost per person and an additional $12 849 (95%CI -$62 138 to $133 378) per SSI avoided. There was no detectable difference in QALYs between groups; however, there are high levels of uncertainty around both cost and QALY estimates. There is a 20% likelihood that ci-NPWT would be considered cost-effective at a willingness-to-pay threshold of $50 000 per QALY. Per protocol and complete case analyses gave similar results, suggesting that findings are robust to protocol deviators and adjustments for missing data.

CONCLUSIONS

ci-NPWT for the prevention of SSI in obese women undergoing CS is unlikely to be cost-effective in terms of health service resources and is currently unjustified for routine use for this purpose.

Discontinuation and nonpublication analysis of chronic pain randomized controlled trials

Introduction

The primary objective of this cross-sectional analysis is to evaluate rates of discontinuation and nonpublication of Randomized controlled trials (RCTs) of therapeutic interventions to treat chronic pain.

Methods

Using ClinicalTrials.gov, a sample was obtained which included clinical trials pertaining to chronic pain. Trials were analyzed for publication status and completion status of each trial. If information was unavailable on the trial registry database, or could not be allocated through a systematic search, the corresponding trialist was contacted and data points were gathered.

Results

In our final analysis of the 408 RCTs, we found that 281 (68.9%) were published in a peer-reviewed journal and 127 (31.1%) were unpublished trials. Of 112 discontinued trials, 59 (52.7%) reached publication. In addition, 221 of 296 completed trials (74.7%) were published, and 75 (25.3%) remained unpublished after trial completion. The most common listed reason for trial discontinuation was administrative recommendations (41 of 71 trials [57.7%]), while not receiving an email reply to our standardized email from the corresponding trialist was the most common result for trial nonpublication (49 of 88 trials [55.7%]). Clinical trials funded by nonindustry sponsors were more likely to reach publication than industry-funded clinical trials (unadjusted odds ratio 1.86 [95% CI, 1.18-2.95]; adjusted odds ratio 3.01 [95% CI, 1.76-5.14]).

Conclusion

The rate of discontinuation of RCTs involving patients with chronic pain is concerning. Chronic pain affects many patients; thus, the importance of having quality data from clinical trials cannot be overstated. Our study indicates that chronic pain RCTs are frequently discontinued and their findings often go unpublished - all of which could provide crucial information to providers and patients regarding the treatment of chronic pain. We offer suggestions to enhance chronic pain RCT completion, thereby reducing the waste of resources in chronic pain research.

Econometric Issues in Prospective Economic Evaluations Alongside Clinical Trials: Combining the Nonparametric Bootstrap With Methods That Address Missing Data

Prospective economic evaluations conducted alongside clinical trials have become an increasingly popular approach in evaluating the cost-effectiveness of a public health initiative or treatment intervention. These types of economic studies provide improved internal validity and accuracy of cost and effectiveness estimates of health interventions and, compared with simulation or decision-analytic models, have the advantage of jointly observing health and economics outcomes of trial participants. However, missing data due to incomplete response or patient attrition, and sampling uncertainty are common concerns in econometric analysis of clinical trials. Missing data are a particular problem for comparative effectiveness trials of substance use disorder interventions. Multiple imputation and inverse probability weighting are 2 widely recommended methods to address missing data bias, and the nonparametric bootstrap is recommended to address uncertainty in predicted mean cost and effectiveness between trial interventions. Although these methods have been studied extensively by themselves, little is known about how to appropriately combine them and about the potential pitfalls and advantages of different approaches. We provide a review of statistical methods used in 29 economic evaluations of substance use disorder intervention identified from 4 published systematic reviews and a targeted search of the literature. We evaluate how each study addressed missing data bias, whether the recommended nonparametric bootstrap was used, how these 2 methods were combined, and conclude with recommendations for future research.

A scoping review of statistical methods for trial-based economic evaluations: The current state of play

The statistical quality of trial-based economic evaluations is often suboptimal, while a comprehensive overview of available statistical methods is lacking. Therefore, this review summarized and critically appraised available statistical methods for trial-based economic evaluations. A literature search was performed to identify studies on statistical methods for dealing with baseline imbalances, skewed costs and/or effects, correlated costs and effects, clustered data, longitudinal data, missing data and censoring in trial-based economic evaluations. Data was extracted on the statistical methods described, their advantages, disadvantages, relative performance and recommendations of the study. Sixty-eight studies were included. Of them, 27 (40%) assessed methods for baseline imbalances, 39 (57%) assessed methods for skewed costs and/or effects, 27 (40%) assessed methods for correlated costs and effects, 18 (26%) assessed methods for clustered data, 7 (10%) assessed methods for longitudinal data, 26 (38%) assessed methods for missing data and 10 (15%) assessed methods for censoring. All identified methods were narratively described. This review provides a comprehensive overview of available statistical methods for dealing with the most common statistical complexities in trial-based economic evaluations. Herewith, it can provide valuable input for researchers when deciding which statistical methods to use in a trial-based economic evaluation.

The handling of missing data in trial-based economic evaluations: should data be multiply imputed prior to longitudinal linear mixed-model analyses?

INTRODUCTION

For the analysis of clinical effects, multiple imputation (MI) of missing data were shown to be unnecessary when using longitudinal linear mixed-models (LLM). It remains unclear whether this also applies to trial-based economic evaluations. Therefore, this study aimed to assess whether MI is required prior to LLM when analyzing longitudinal cost and effect data.

METHODS

Two-thousand complete datasets were simulated containing five time points. Incomplete datasets were generated with 10, 25, and 50% missing data in follow-up costs and effects, assuming a Missing At Random (MAR) mechanism. Six different strategies were compared using empirical bias (EB), root-mean-squared error (RMSE), and coverage rate (CR). These strategies were: LLM alone (LLM) and MI with LLM (MI-LLM), and, as reference strategies, mean imputation with LLM (M-LLM), seemingly unrelated regression alone (SUR-CCA), MI with SUR (MI-SUR), and mean imputation with SUR (M-SUR).

RESULTS

For costs and effects, LLM, MI-LLM, and MI-SUR performed better than M-LLM, SUR-CCA, and M-SUR, with smaller EBs and RMSEs as well as CRs closers to nominal levels. However, even though LLM, MI-LLM and MI-SUR performed equally well for effects, MI-LLM and MI-SUR were found to perform better than LLM for costs at 10 and 25% missing data. At 50% missing data, all strategies resulted in relatively high EBs and RMSEs for costs.

CONCLUSION

LLM should be combined with MI when analyzing trial-based economic evaluation data. MI-SUR is more efficient and can also be used, but then an average intervention effect over time cannot be estimated.

Assessing Alternative Imputation Strategies for Infrequently Missing Items on Multi-item Scales

Health-science researchers often measure psychological constructs using multi-item scales and encounter missing items on some participants. Multiple imputation (MI) has emerged as an alternative to ad-hoc methods (e.g., mean substitution) for handling incomplete data on multi-item scales, appealingly reflecting available information while accounting for uncertainty due to missing values in a unified inferential framework. However, MI can be implemented in a variety of ways. When the number of variables to impute gets large, some strategies yield unstable estimates of quantities of interest while others are not technically feasible to implement. These considerations raise pragmatic questions about the extent to which ad-hoc procedures would yield statistical properties that are competitive with theoretically motivated methods. Drawing on an HIV study where depression and anxiety symptoms are measured with multi-item scales, this empirical investigation contrasts ad-hoc methods for handling missing items with various MI implementations that differ as to whether imputation is at the item-level or scale-level and how auxiliary variables are incorporated. While the findings are consistent with previous reports favoring item-level imputation when feasible to implement, we found only subtle differences in statistical properties across procedures, suggesting that weaknesses of ad-hoc procedures may be muted when missing data percentages are modest.

A Scoping Review of Item-Level Missing Data in Within-Trial Cost-Effectiveness Analysis

OBJECTIVES

Cost-effectiveness analysis (CEA) alongside randomized controlled trials often relies on self-reported multi-item questionnaires that are invariably prone to missing item-level data. The purpose of this study is to review how missing multi-item questionnaire data are handled in trial-based CEAs.

METHODS

We searched the National Institute for Health Research journals to identify within-trial CEAs published between January 2016 and April 2021 using multi-item instruments to collect costs and quality of life (QOL) data. Information on missing data handling and methods, with a focus on the level and type of imputation, was extracted.

RESULTS

A total of 87 trial-based CEAs were included in the review. Complete case analysis or available case analysis and multiple imputation (MI) were the most popular methods, selected by similar numbers of studies, to handle missing costs and QOL in base-case analysis. Nevertheless, complete case analysis or available case analysis dominated sensitivity analysis. Once imputation was chosen, missing costs were widely imputed at item-level via MI, whereas missing QOL was usually imputed at the more aggregated time point level during the follow-up via MI.

CONCLUSIONS

Missing costs and QOL tend to be imputed at different levels of missingness in current CEAs alongside randomized controlled trials. Given the limited information provided by included studies, the impact of applying different imputation methods at different levels of aggregation on CEA decision making remains unclear.

Linear mixed models to handle missing at random data in trial-based economic evaluations

Trial-based cost-effectiveness analyses (CEAs) are an important source of evidence in the assessment of health interventions. In these studies, cost and effectiveness outcomes are commonly measured at multiple time points, but some observations may be missing. Restricting the analysis to the participants with complete data can lead to biased and inefficient estimates. Methods, such as multiple imputation, have been recommended as they make better use of the data available and are valid under less restrictive Missing At Random (MAR) assumption. Linear mixed effects models (LMMs) offer a simple alternative to handle missing data under MAR without requiring imputations, and have not been very well explored in the CEA context. In this manuscript, we aim to familiarize readers with LMMs and demonstrate their implementation in CEA. We illustrate the approach on a randomized trial of antidepressants, and provide the implementation code in R and Stata. We hope that the more familiar statistical framework associated with LMMs, compared to other missing data approaches, will encourage their implementation and move practitioners away from inadequate methods.

Local Instrumental Variable Methods to Address Confounding and Heterogeneity when Using Electronic Health Records: An Application to Emergency Surgery

Background

Electronic health records (EHRs) offer opportunities for comparative effectiveness research to inform decision making. However, to provide useful evidence, these studies must address confounding and treatment effect heterogeneity according to unmeasured prognostic factors. Local instrumental variable (LIV) methods can help studies address these challenges, but have yet to be applied to EHR data. This article critically examines a LIV approach to evaluate the cost-effectiveness of emergency surgery (ES) for common acute conditions from EHRs.

Methods

This article uses hospital episodes statistics (HES) data for emergency hospital admissions with acute appendicitis, diverticular disease, and abdominal wall hernia to 175 acute hospitals in England from 2010 to 2019. For each emergency admission, the instrumental variable for ES receipt was each hospital’s ES rate in the year preceding the emergency admission. The LIV approach provided individual-level estimates of the incremental quality-adjusted life-years, costs and net monetary benefit of ES, which were aggregated to the overall population and subpopulations of interest, and contrasted with those from traditional IV and risk-adjustment approaches.

Results

The study included 268,144 (appendicitis), 138,869 (diverticular disease), and 106,432 (hernia) patients. The instrument was found to be strong and to minimize covariate imbalance. For diverticular disease, the results differed by method; although the traditional approaches reported that, overall, ES was not cost-effective, the LIV approach reported that ES was cost-effective but with wide statistical uncertainty. For all 3 conditions, the LIV approach found heterogeneity in the cost-effectiveness estimates across population subgroups: in particular, ES was not cost-effective for patients with severe levels of frailty.

Conclusions

EHRs can be combined with LIV methods to provide evidence on the cost-effectiveness of routinely provided interventions, while fully recognizing heterogeneity.

Highlights

Surveying Over the Counter and Prescription Only Medication Misuse in Treatment Services During COVID-19

Background:

A greater understanding of Over the Counter (OTC) and Prescription Only Medication (POM) misuse amongst adults accessing substance misuse services (SMS) during COVID-19 is required to identify how SMS can better meet the needs of the people who require treatment.

Aim:

To use a questionnaire to explore OTC/POM misuse during COVID-19 in adults accessing community SMS in England.

Methods:

In 2020 to 2021 anonymous self-administered online/paper questionnaires which collated quantitative and qualitative data were completed. They were piloted for suitability and ethical approval was obtained. Thematic analysis was conducted for qualitative data and chi-square tests used to assess the relationship between quantitative variables.

Results:

Participants were Caucasian (94.6% British), majority male (58.9%), aged 18 to 61 years. Most were prescribed medication for problematic substance use, with a 92.5% self-reported adherence rate. The misuse of benzodiazepines (22.2%) codeine products (30.8%) and pregabalin (14.5%) predominated and 37.5% misused 2 or more medicines. Administration was usually oral and concomitant use of other substances was common: alcohol 44.6% (52% daily), tobacco/vaping 73.2% and illicit substances 58.9%. There were statistically significant associations identified, including between changes during COVID-19 to OTC/POM misuse and illicit use. Only 56 questionnaires were included in the analysis: we believe this low number was because of infection control measures, limited footfall in services, pressures on staff limiting their capacity to distribute the paper questionnaires and reliance upon telephone consultations limiting online distribution. Increasing OTC/POM misuse and obtaining illicit supplies were reported when access to usual supplies were restricted; however, changes to doses/dispensing arrangement liberalisation in response to COVID-19 were positively viewed.

Conclusion:

OTC/POM misuse, including polypharmacy and concomitant use of other substances occurred during COVID-19: SMS need to be vigilant for these issues and mitigate the associated risks for example with harm reduction interventions. Further qualitative research is required to explore the issues identified.

Retrospectively Collected EQ-5D-5L Data as Valid Proxies for Imputing Missing Information in Longitudinal Studies

OBJECTIVES

Studies face challenges with missing 5-level EQ-5D (EQ-5D-5L) data, often because of the need for longitudinal EQ-5D-5L data collection. There is a dearth of validated methodologies for dealing with missing EQ-5D-5L data in the literature. This study, for the first time, examined the possibility of using retrospectively collected EQ-5D-5L data as proxies for the missing data.

METHODS

Participants who had prospectively completed a 3rd month postdischarge EQ-5D-5L instrument (in-the-moment collection) were randomly interviewed to respond to a 2nd "retrospective collection" of their 3rd month EQ-5D-5L at 6th, 9th, or 12th month after hospital discharge. A longitudinal single imputation was also used to assess the relative performance of retrospective collection compared with the longitudinal single imputation. Concordances between the in-the-moment, retrospective, and imputed measures were assessed using intraclass correlation coefficients and weighted kappa statistics.

RESULTS

Considerable agreement was observed on the basis of weighted kappa (range 0.72-0.95) between the mobility, self-care, and usual activities dimensions of EQ-5D-5L collected in-the-moment and retrospectively. Concordance based on intraclass correlation coefficients was good to excellent (range 0.79-0.81) for utility indices computed, and excellent (range 0.93-0.96) for quality-adjusted life-years computed using in-the-moment compared with retrospective EQ-5D-5L. The longitudinal single imputation did not perform as well as the retrospective collection method.

CONCLUSIONS

This study demonstrates that retrospective collection of EQ-5D-5L has high concordance with "in-the-moment" EQ-5D-5L and could be a valid and attractive alternative for data imputation when longitudinally collected EQ-5D-5L data are missing. Future studies examining this method for other disease areas and populations are required to provide more generalizable evidence.

Social recovery therapy for young people with emerging severe mental illness: the Prodigy RCT

BACKGROUND

Young people with social disability and non-psychotic severe and complex mental health problems are an important group. Without intervention, their social problems can persist and have large economic and personal costs. Thus, more effective evidence-based interventions are needed. Social recovery therapy is an individual therapy incorporating cognitive-behavioural techniques to increase structured activity as guided by the participant's goals.

OBJECTIVE

This trial aimed to test whether or not social recovery therapy provided as an adjunct to enhanced standard care over 9 months is superior to enhanced standard care alone. Enhanced standard care aimed to provide an optimal combination of existing evidence-based interventions.

DESIGN

A pragmatic, single-blind, superiority randomised controlled trial was conducted in three UK centres: Sussex, Manchester and East Anglia. Participants were aged 16-25 years with persistent social disability, defined as < 30 hours per week of structured activity with social impairment for at least 6 months. Additionally, participants had severe and complex mental health problems, defined as at-risk mental states for psychosis or non-psychotic severe and complex mental health problems indicated by a Global Assessment of Functioning score ≤ 50 persisting for ≥ 6 months. Two hundred and seventy participants were randomised 1 : 1 to either enhanced standard care plus social recovery therapy or enhanced standard care alone. The primary outcome was weekly hours spent in structured activity at 15 months post randomisation. Secondary outcomes included subthreshold psychotic, negative and mood symptoms. Outcomes were collected at 9 and 15 months post randomisation, with maintenance assessed at 24 months.

RESULTS

The addition of social recovery therapy did not significantly increase weekly hours in structured activity at 15 months (primary outcome treatment effect -4.44, 95% confidence interval -10.19 to 1.31). We found no evidence of significant differences between conditions in secondary outcomes at 15 months: Social Anxiety Interaction Scale treatment effect -0.45, 95% confidence interval -4.84 to 3.95; Beck Depression Inventory-II treatment effect -0.32, 95% confidence interval -4.06 to 3.42; Comprehensive Assessment of At-Risk Mental States symptom severity 0.29, 95% confidence interval -4.35 to 4.94; or distress treatment effect 4.09, 95% confidence interval -3.52 to 11.70. Greater Comprehensive Assessment of At-Risk Mental States for psychosis scores reflect greater symptom severity. We found no evidence of significant differences at 9 or 24 months. Social recovery therapy was not estimated to be cost-effective. The key limitation was that missingness of data was consistently greater in the enhanced standard care-alone arm (9% primary outcome and 15% secondary outcome missingness of data) than in the social recovery therapy plus enhanced standard care arm (4% primary outcome and 9% secondary outcome missingness of data) at 15 months.

CONCLUSIONS

We found no evidence for the clinical superiority or cost-effectiveness of social recovery therapy as an adjunct to enhanced standard care. Both arms made large improvements in primary and secondary outcomes. Enhanced standard care included a comprehensive combination of evidence-based pharmacological, psychotherapeutic and psychosocial interventions. Some results favoured enhanced standard care but the majority were not statistically significant. Future work should identify factors associated with the optimal delivery of the combinations of interventions that underpin better outcomes in this often-neglected clinical group.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN47998710.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment Vol. 25, No. 70. See the NIHR Journals Library website for further project information.

Aspects and Challenges of Resource Use Measurement in Health Economics: Towards a Comprehensive Measurement Framework

BACKGROUND

While the methods for conducting health economics research in general are improving, current guidelines provide limited guidance regarding resource use measurement (RUM). Consequently, a variety of methods exists, yet there is no overview of aspects to consider when deciding on the most appropriate RUM methodology. Therefore, this study aims to (1) identify and categorize existing knowledge regarding aspects of RUM, and (2) develop a framework that provides a comprehensive overview of methodological aspects regarding RUM.

METHODS

Relevant articles were identified by enrolling a search string in six databases and handsearching the DIRUM database. Included articles were descriptively reviewed and served as input for a comprehensive framework. Health economics experts were involved during the process to establish the framework's face validity.

RESULTS

Forty articles were included in the scoping review. The RUM framework consists of four methodological RUM domains: 'Whom to measure', addressing whom to ask and whom to measure; 'How to measure', addressing the different approaches of measurement; 'How often to measure', addressing recall period and measurement patterns; and 'Additional considerations', which covers additional aspects that are essential for further refining the methodologies for measurement. Evidence retrieved from the scoping review was categorized according to these domains.

CONCLUSION

This study clustered the aspects of RUM methodology in health economics into a comprehensive framework. The results may guide health economists in their decision making regarding the selection of appropriate RUM methods and developing instruments for RUM. Furthermore, policy makers may use these findings to review study results from an evidence-based perspective.

Interpretation of trial-based economic evaluations of musculoskeletal physical therapy interventions

BACKGROUND

As resources for healthcare are scarce, decision-makers increasingly rely on economic evaluations when making reimbursement decisions about new health technologies, such as drugs, procedures, devices, and equipment. Economic evaluations compare the costs and effects of two or more interventions. Musculoskeletal disorders have a high prevalence and result in high levels of disability and high costs worldwide. Because physical therapy interventions are usually the first line of treatment for musculoskeletal disorders, economic evaluations of such interventions are becoming increasingly important for stakeholders in the field of physical therapy, including physical therapists, decision-makers, and reseachers. However, economic evaluations are relatively difficult to interpret for the majority of stakeholders.

OBJECTIVE

To support physical therapists, decision-makers, and researchers in the field of physical therapy interpreting trial-based economic evaluations and translating the results of such studies to clinical practice.

METHODS

The design, analysis, and interpretation of economic evaluations performed alongside randomized controlled trials are discussed. To further illustrate and explain these concepts, we use a case study assessing the cost-effectiveness of exercise therapy compared to standard advice in patients with musculoskeletal disorders.

CONCLUSIONS

Economic evaluations are increasingly being used in healthcare decision-making. Therefore, it is of utmost importance that their design, conduct, and analysis are state-of-the-art and that their interpretation is adequate. This masterclass will help physical therapists, decision-makers, and researchers in the field of physical therapy to critically appraise the quality and results of trial-based economic evaluations and to apply the results of such studies to their own clinical practice and setting.

The statistical approach in trial-based economic evaluations matters: get your statistics together!

Background

Baseline imbalances, skewed costs, the correlation between costs and effects, and missing data are statistical challenges that are often not adequately accounted for in the analysis of cost-effectiveness data. This study aims to illustrate the impact of accounting for these statistical challenges in trial-based economic evaluations.

Methods

Data from two trial-based economic evaluations, the REALISE and HypoAware studies, were used. In total, 14 full cost-effectiveness analyses were performed per study, in which the four statistical challenges in trial-based economic evaluations were taken into account step-by-step. Statistical approaches were compared in terms of the resulting cost and effect differences, ICERs, and probabilities of cost-effectiveness.

Results

In the REALISE study and HypoAware study, the ICER ranged from 636,744€/QALY and 90,989€/QALY when ignoring all statistical challenges to − 7502€/QALY and 46,592€/QALY when accounting for all statistical challenges, respectively. The probabilities of the intervention being cost-effective at 0€/ QALY gained were 0.67 and 0.59 when ignoring all statistical challenges, and 0.54 and 0.27 when all of the statistical challenges were taken into account for the REALISE study and HypoAware study, respectively.

Conclusions

Not accounting for baseline imbalances, skewed costs, correlated costs and effects, and missing data in trial-based economic evaluations may notably impact results. Therefore, when conducting trial-based economic evaluations, it is important to align the statistical approach with the identified statistical challenges in cost-effectiveness data. To facilitate researchers in handling statistical challenges in trial-based economic evaluations, software code is provided.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-06513-1.

Cost-Effectiveness of Dopamine Agonists and Monoamine Oxidase B Inhibitors in Early Parkinson's Disease

BACKGROUND

The PD MED study reported small but persistent benefits in patient-rated mobility scores and quality of life from initiating therapy with levodopa compared with levodopa-sparing therapies in early Parkinson's disease (PD).

OBJECTIVES

The objective was to estimate the cost-effectiveness of levodopa-sparing therapy (dopamine agonists or monoamine oxidase type B inhibitors compared with levodopa alone.

METHODS

PD MED is a pragmatic, open-label randomized, controlled trial in which patients newly diagnosed with PD were randomly assigned between levodopa-sparing therapy (dopamine agonists or monoamine oxidase type B inhibitors ) and levodopa alone. Mean quality-adjusted life-years and costs were calculated for each participant. Differences in mean quality-adjusted life-years and costs between levodopa and levodopa-sparing therapies and between dopamine agonists and monoamine oxidase type B inhibitors were estimated using linear regression.

RESULTS

Over a mean observation period of 4 years, levodopa was associated with significantly higher quality-adjusted life-years (difference, 0.18; 95% CI, 0.05-0.30; P < 0.01) and lower mean costs (£3390; £2671-£4109; P < 0.01) than levodopa-sparing therapies, the difference in costs driven by the higher costs of levodopa-sparing therapies. There were no significant differences in the costs of inpatient, social care, and institutional care between arms. There was no significant difference in quality-adjusted life-years between those allocated dopamine agonists and monoamine oxidase type B inhibitors (0.02; -0.17 to 0.13 in favor of dopamine agonists; P = 0.81); however costs were significantly lower for those allocated monoamine oxidase type B inhibitors (£2321; £1628-£3015; P < 0.01) because of the higher costs of dopamine agonists. There were no significant differences between arms for other costs.

CONCLUSIONS

Initial treatment with levodopa is highly cost-effective compared with levodopa-sparing therapies. Monoamine oxidase type B inhibitors, as initial levodopa-sparing therapy was more cost-effective, with similar quality-adjusted life-years but lower costs than dopamine agonists. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Joint Longitudinal Models for Dealing With Missing at Random Data in Trial-Based Economic Evaluations

OBJECTIVES

In trial-based economic evaluation, some individuals are typically associated with missing data at some time point, so that their corresponding aggregated outcomes (eg, quality-adjusted life-years) cannot be evaluated. Restricting the analysis to the complete cases is inefficient and can result in biased estimates, while imputation methods are often implemented under a missing at random (MAR) assumption. We propose the use of joint longitudinal models to extend standard approaches by taking into account the longitudinal structure to improve the estimation of the targeted quantities under MAR.

METHODS

We compare the results from methods that handle missingness at an aggregated (case deletion, baseline imputation, and joint aggregated models) and disaggregated (joint longitudinal models) level under MAR. The methods are compared using a simulation study and applied to data from 2 real case studies.

RESULTS

Simulations show that, according to which data affect the missingness process, aggregated methods may lead to biased results, while joint longitudinal models lead to valid inferences under MAR. The analysis of the 2 case studies support these results as both parameter estimates and cost-effectiveness results vary based on the amount of data incorporated into the model.

CONCLUSIONS

Our analyses suggest that methods implemented at the aggregated level are potentially biased under MAR as they ignore the information from the partially observed follow-up data. This limitation can be overcome by extending the analysis to a longitudinal framework using joint models, which can incorporate all the available evidence.

Is the whole larger than the sum of its parts? Impact of missing data imputation in economic evaluation conducted alongside randomized controlled trials

Outcomes in economic evaluations, such as health utilities and costs, are products of multiple variables, often requiring complete item responses to questionnaires. Therefore, missing data are very common in cost-effectiveness analyses. Multiple imputations (MI) are predominately recommended and could be made either for individual items or at the aggregate level. We, therefore, aimed to assess the precision of both MI approaches (the item imputation vs. aggregate imputation) on the cost-effectiveness results. The original data set came from a cluster-randomized, controlled trial and was used to describe the missing data pattern and compare the differences in the cost-effectiveness results between the two imputation approaches. A simulation study with different missing data scenarios generated based on a complete data set was used to assess the precision of both imputation approaches. For health utility and cost, patients more often had a partial (9% vs. 23%, respectively) rather than complete missing (4% vs. 0%). The imputation approaches differed in the cost-effectiveness results (the item imputation: - 61,079€/QALY vs. the aggregate imputation: 15,399€/QALY). Within the simulation study mean relative bias (< 5% vs. < 10%) and range of bias (< 38% vs. < 83%) to the true incremental cost and incremental QALYs were lower for the item imputation compared to the aggregate imputation. Even when 40% of data were missing, relative bias to true cost-effectiveness curves was less than 16% using the item imputation, but up to 39% for the aggregate imputation. Thus, the imputation strategies could have a significant impact on the cost-effectiveness conclusions when more than 20% of data are missing. The item imputation approach has better precision than the imputation at the aggregate level.

Reference-based multiple imputation for missing data sensitivity analyses in trial-based cost-effectiveness analysis

Missing data are a common issue in cost-effectiveness analysis (CEA) alongside randomised trials and are often addressed assuming the data are 'missing at random'. However, this assumption is often questionable, and sensitivity analyses are required to assess the implications of departures from missing at random. Reference-based multiple imputation provides an attractive approach for conducting such sensitivity analyses, because missing data assumptions are framed in an intuitive way by making reference to other trial arms. For example, a plausible not at random mechanism in a placebo-controlled trial would be to assume that participants in the experimental arm who dropped out stop taking their treatment and have similar outcomes to those in the placebo arm. Drawing on the increasing use of this approach in other areas, this paper aims to extend and illustrate the reference-based multiple imputation approach in CEA. It introduces the principles of reference-based imputation and proposes an extension to the CEA context. The method is illustrated in the CEA of the CoBalT trial evaluating cognitive behavioural therapy for treatment-resistant depression. Stata code is provided. We find that reference-based multiple imputation provides a relevant and accessible framework for assessing the robustness of CEA conclusions to different missing data assumptions.

Cost-effectiveness of a patient-centred approach to managing multimorbidity in primary care: a pragmatic cluster randomised controlled trial

OBJECTIVE

Patients with multiple chronic health conditions are often managed in a disjointed fashion in primary care, with annual review clinic appointments offered separately for each condition. This study aimed to determine the cost-effectiveness of the 3D intervention, which was developed to improve the system of care.

DESIGN

Economic evaluation conducted alongside a pragmatic cluster-randomised trial.

SETTING

General practices in three centres in England and Scotland.

PARTICIPANTS

797 adults with three or more chronic conditions were randomised to the 3D intervention, while 749 participants were randomised to receive usual care.

INTERVENTION

The 3D approach: comprehensive 6-monthly general practitioner consultations, supported by medication reviews and nurse appointments.

PRIMARY AND SECONDARY OUTCOME MEASURES

The primary economic evaluation assessed the cost per quality-adjusted life year (QALY) gained from the perspective of the National Health Service (NHS) and personal social services (PSS). Costs were related to changes in a range of secondary outcomes (QALYs accrued by both participants and carers, and deaths) in a cost-consequences analysis from the perspectives of the NHS/PSS, patients/carers and productivity losses.

RESULTS

Very small increases were found in both QALYs (adjusted mean difference 0.007 (-0.009 to 0.023)) and costs (adjusted mean difference £126 (£-739 to £991)) in the intervention arm compared with usual care after 15 months. The incremental cost-effectiveness ratio was £18 499, with a 50.8% chance of being cost-effective at a willingness-to-pay threshold of £20 000 per QALY (55.8% at £30 000 per QALY).

CONCLUSIONS

The small differences in costs and outcomes were consistent with chance, and the uncertainty was substantial; therefore, the evidence for the cost-effectiveness of the 3D approach from the NHS/PSS perspective should be considered equivocal.

TRIAL REGISTRATION NUMBER

ISCRTN06180958.

Individual health trainers to support health and well-being for people under community supervision in the criminal justice system: the STRENGTHEN pilot RCT

Background

Little is known about the effectiveness or cost-effectiveness of interventions, such as health trainer support, to improve the health and well-being of people recently released from prison or serving a community sentence, because of the challenges in recruiting participants and following them up.

Objectives

This pilot trial aimed to assess the acceptability and feasibility of the trial methods and intervention (and associated costs) for a randomised trial to assess the effectiveness and cost-effectiveness of health trainer support versus usual care.

Design

This trial involved a pilot multicentre, parallel, two-group randomised controlled trial recruiting 120 participants with 1 : 1 individual allocation to receive support from a health trainer and usual care or usual care alone, with a mixed-methods process evaluation, in 2017–18.

Setting

Participants were identified, screened and recruited in Community Rehabilitation Companies in Plymouth and Manchester or the National Probation Service in Plymouth. The intervention was delivered in the community.

Participants

Those who had been out of prison for at least 2 months (to allow community stabilisation), with at least 7 months of a community sentence remaining, were invited to participate; those who may have posed an unacceptable risk to the researchers and health trainers and those who were not interested in the trial or intervention support were excluded.

Interventions

The intervention group received, in addition to usual care, our person-centred health trainer support in one-to-one sessions for up to 14 weeks, either in person or via telephone. Health trainers aimed to empower participants to make healthy lifestyle changes (particularly in alcohol use, smoking, diet and physical activity) and take on the Five Ways to Well-being [Foresight Projects. Mental Capital and Wellbeing: Final Project Report. 2008. URL: www.gov.uk/government/publications/mental-capital-and-wellbeing-making-the-most-of-ourselves-in-the-21st-century (accessed 24 January 2019).], and also signposted to other options for support. The control group received treatment as usual, defined by available community and public service options for improving health and well-being.

Main outcome measures

The main outcomes included the Warwick–Edinburgh Mental Well-being Scale scores, alcohol use, smoking behaviour, dietary behaviour, physical activity, substance use, resource use, quality of life, intervention costs, intervention engagement and feasibility and acceptability of trial methods and the intervention.

Results

A great deal about recruitment was learned and the target of 120 participants was achieved. The minimum trial retention target at 6 months (60%) was met. Among those offered health trainer support, 62% had at least two sessions. The mixed-methods process evaluation generally supported the trial methods and intervention acceptability and feasibility. The proposed primary outcome, the Warwick–Edinburgh Mental Well-being Scale scores, provided us with valuable data to estimate the sample size for a full trial in which to test the effectiveness and cost-effectiveness of the intervention.

Conclusions

Based on the findings from this pilot trial, a full trial (with some modifications) seems justified, with a sample size of around 900 participants to detect between-group differences in the Warwick-Edinburgh Mental Well-being Scale scores at a 6-month follow-up.

Future work

A number of recruitment, trial retention, intervention engagement and blinding issues were identified in this pilot and recommendations are made in preparation of and within a full trial.

Trial registration

Current Controlled Trials ISRCTN80475744.

Funding

This project was funded by the National Institute for Health Research Public Health Research programme and will be published in full in Public Health Research; Vol. 7, No. 20. See the National Institute for Health Research Journals Library website for further project information.

What do national pharmacoeconomic guidelines recommend regarding the statistical analysis of trial-based economic evaluations?

Introduction: The statistical quality of many trial-based economic evaluations is poor. When conducting trial-based economic evaluations, researchers often turn to national pharmacoeconomic guidelines for guidance. Therefore, this study reviewed which recommendations are currently given by national pharmacoeconomic guidelines on the statistical analysis of trial-based economic evaluations.Areas covered: 40 national pharmacoeconomic guidelines were identified. Data were extracted on the guidelines' recommendations on how to deal with baseline imbalances, skewed costs, correlated costs and effects, clustering of data, longitudinal data, and missing data in trial-based economic evaluations. Four guidelines (10%) were found to include recommendations on how to deal with baseline imbalances, five (13%) on how to deal with skewed costs, and seven (18%) on how to deal with missing data. Recommendations were very general in nature and recommendations on dealing with correlated costs and effects, clustering of data, and longitudinal data were lacking.Expert opinion: Current national pharmacoeconomic guidelines provide little to no guidance on how to deal with the statistical challenges to trial-based economic evaluations. Since the use of suboptimal statistical methods may lead to biased results, and, therefore, possibly to a waste of scarce resources, national agencies are advised to include more statistical guidance in their pharmacoeconomic guidelines.

Trial of healthy relationship initiatives for the very early years (THRIVE), evaluating Enhanced Triple P for Baby and Mellow Bumps additional social and care needs during pregnancy and their infants who are at higher risk of maltreatment: study protocol for a randomised controlled trial

BACKGROUND

Growing evidence suggests that experiences in the early years play a major role in children's development in terms of health, wellbeing and educational attainment. The Trial of healthy relationship initiatives for the very early years (THRIVE) aims to evaluate two antenatal group interventions, Enhanced Triple P for Baby and Mellow Bumps, designed for those with additional health or social care needs in pregnancy. As both interventions aim to improve maternal mental health and parenting skills, we hypothesise that in the longer term, participation may lead to an improvement in children's life trajectories.

METHODS

THRIVE is a three-arm, longitudinal, randomised controlled trial aiming to recruit 500 pregnant women with additional health or social care needs. Participants will be referred by health and social care professionals, predominately midwives. Consenting participants will be block randomised to one of the three arms: Enhanced Triple P for Baby plus care as usual, Mellow Bumps plus care as usual or care as usual. Groups will commence when participants are between 20 and 34 weeks pregnant.

DISCUSSION

The population we aim to recruit are traditionally referred to as "hard to reach", therefore we will monitor referrals received from maternity and social care pathways and will be open to innovation to boost referral rates. We will set geographically acceptable group locations for participants, to limit challenges we foresee for group participation and retention. We anticipate the results of the trial will help inform policy and practice in supporting women with additional health and social care needs during antenatal and early postnatal periods. This is currently a high priority for the Scottish and UK Governments.

TRIAL REGISTRATION

International Standard Randomised Controlled Trials Number (ISRCTN) Registry, ISRCTN:21656568 . Registered on 28 February 2014 (registered retrospectively (by 3 months)).

A patient-centred intervention to improve the management of multimorbidity in general practice: the 3D RCT

Background

People with multimorbidity experience impaired quality of life, poor health and a burden from treatment. Their care is often disease-focused rather than patient-centred and tailored to their individual needs.

Objective

To implement and evaluate a patient-centred intervention to improve the management of patients with multimorbidity in general practice.

Design

Pragmatic, cluster randomised controlled trial with parallel process and economic evaluations. Practices were centrally randomised by a statistician blind to practice identifiers, using a computer-generated algorithm.

Setting

Thirty-three general practices in three areas of England and Scotland.

Participants

Practices had at least 4500 patients and two general practitioners (GPs) and used the EMIS (Egton Medical Information Systems) computer system. Patients were aged ≥ 18 years with three or more long-term conditions.

Interventions

The 3D (Dimensions of health, Depression and Drugs) intervention was designed to offer patients continuity of care with a named GP, replacing separate reviews of each long-term condition with comprehensive reviews every 6 months. These focused on individualising care to address patients’ main problems, attention to quality of life, depression and polypharmacy and on disease control and agreeing treatment plans. Control practices provided usual care.

Outcome measures

Primary outcome – health-related quality of life (assessed using the EuroQol-5 Dimensions, five-level version) after 15 months. Secondary outcomes – measures of illness burden, treatment burden and patient-centred care. We assessed cost-effectiveness from a NHS and a social care perspective.

Results

Thirty-three practices (1546 patients) were randomised from May to December 2015 [16 practices (797 patients) to the 3D intervention, 17 practices (749 patients) to usual care]. All participants were included in the primary outcome analysis by imputing missing data. There was no evidence of difference between trial arms in health-related quality of life {adjusted difference in means 0.00 [95% confidence interval (CI) –0.02 to 0.02]; p = 0.93}, illness burden or treatment burden. However, patients reported significant benefits from the 3D intervention in all measures of patient-centred care. Qualitative data suggested that both patients and staff welcomed having more time, continuity of care and the patient-centred approach. The economic analysis found no meaningful differences between the intervention and usual care in either quality-adjusted life-years [(QALYs) adjusted mean QALY difference 0.007, 95% CI –0.009 to 0.023] or costs (adjusted mean difference £126, 95% CI –£739 to £991), with wide uncertainty around point estimates. The cost-effectiveness acceptability curve suggested that the intervention was unlikely to be either more or less cost-effective than usual care. Seventy-eight patients died (46 in the intervention arm and 32 in the usual-care arm), with no evidence of difference between trial arms; no deaths appeared to be associated with the intervention.

Limitations

In this pragmatic trial, the implementation of the intervention was incomplete: 49% of patients received two 3D reviews over 15 months, whereas 75% received at least one review.

Conclusions

The 3D approach reflected international consensus about how to improve care for multimorbidity. Although it achieved the aim of providing more patient-centred care, this was not associated with benefits in quality of life, illness burden or treatment burden. The intervention was no more or less cost-effective than usual care. Modifications to the 3D approach might improve its effectiveness. Evaluation is needed based on whole-system change over a longer period of time.

Trial registration

Current Controlled Trials ISRCTN06180958.

Funding

This project was funded by the National Institute for Health Research (NIHR) Health Services and Delivery Research programme and will be published in full in Health Services and Delivery Research; Vol. 7, No. 5. See the NIHR Journals Library website for further project information.

Self-reported and routinely collected electronic healthcare resource-use data for trial-based economic evaluations: the current state of play in England and considerations for the future

BACKGROUND

Randomised controlled trials (RCTs) are generally regarded as the "gold standard" for providing quantifiable evidence around the effectiveness and cost-effectiveness of new healthcare technologies. In order to perform the economic evaluations associated with RCTs, there is a need for accessible and good quality resource-use data; for the purpose of discussion here, data that best reflect the care received. Traditionally, researchers have developed questionnaires for resource-use data collection. However, the evolution of routinely collected electronic data within care services provides new opportunities for collecting data without burdening patients or caregivers (e.g. clinicians). This paper describes the potential strengths and limitations of each data collection method and then discusses aspects for consideration before choosing which method to use.

MAIN TEXT

We describe electronic data sources (large observational datasets, commissioning data, and raw data extraction) that may be suitable data sources for informing clinical trials and the current status of self-reported instruments for measuring resource-use. We assess the methodological risks and benefits, and compare the two methodologies. We focus on healthcare resource-use; however, many of the considerations have relevance to clinical questions. Patient self-report forms a pragmatic and cheap method that is largely under the control of the researcher. However, there are known issues with the validity of the data collected, loss to follow-up may be high, and questionnaires suffer from missing data. Routinely collected electronic data may be more accurate and more practical if large numbers of patients are involved. However, datasets often incur a cost and researchers are bound by the time for data approval and extraction by the data holders.

CONCLUSIONS

Owing to the issues associated with electronic datasets, self-reported methods may currently be the preferred option. However, electronic hospital data are relatively more accessible, informative, standardised, and reliable. Therefore in trials where secondary care constitutes a major driver of patient care, detailed electronic data may be considered superior to self-reported methods; with the caveat of requiring data sharing agreements with third party providers and potentially time-consuming extraction periods. Self-reported methods will still be required when a 'societal' perspective (e.g. quantifying informal care) is desirable for the intended analysis.

Economic evaluation of telephone-based weight loss support for patients with knee osteoarthritis: a randomised controlled trial

Background

The prevalence of knee osteoarthritis is increasing worldwide. Obesity is an important modifiable risk factor for both the incidence and progression of knee osteoarthritis. Consequently, international guidelines recommend all patients with knee osteoarthritis who are overweight receive support to lose weight. However, few overweight patients with this condition receive care to support weight loss. Telephone-based interventions are one potential solution to provide scalable care to the many patients with knee osteoarthritis. The objective of this study is to evaluate, from a societal perspective, the cost-utility and cost-effectiveness of a telephone-based weight management and healthy lifestyle service for patients with knee osteoarthritis, who are overweight or obese.

Methods

An economic evaluation was undertaken alongside a pragmatic randomised controlled trial. Between May 19 and June 30, 2015, 120 patients with knee osteoarthritis were randomly assigned to an intervention or usual care control group in a 1:1 ratio. Participants in the intervention group received a referral to an existing non-disease specific 6-month telephone-based weight management and healthy lifestyle service. Quality-adjusted life years (QALYs) was the utility measure and knee pain intensity, disability, weight, and body mass index (BMI) were the clinical measures of effect. Costs included intervention costs, healthcare utilisation costs (healthcare services and medication use) and absenteeism costs due to knee pain. Data was collected at baseline, 6 weeks and 26 weeks. The primary cost-effectiveness analysis was performed from the societal perspective.

Results

Mean cost differences between groups (intervention minus control) were $493 (95%CI: -3513 to 5363) for healthcare costs, $-32 (95%CI: -73 to 13) for medication costs, and $125 (95%CI: -151 to 486) for absenteeism costs. The total mean difference in societal costs was $1197 (95%CI: -2887 to 6106). For QALYs and all clinical measures of effect, the probability of the intervention being cost-effective compared with usual care was less than 0.36 at all willingness-to-pay values.

Conclusions

From a societal perspective, telephone-based weight loss support, provided using an existing non-disease specific 6-month weight management and healthy lifestyle service was not cost-effective in comparison with usual care for overweight and obese patients with knee osteoarthritis.

Trial registration number

ACTRN12615000490572, registered 18th May 2015

Electronic supplementary material

The online version of this article (10.1186/s12889-018-6300-1) contains supplementary material, which is available to authorized users.

Economic evaluation of a healthy lifestyle intervention for chronic low back pain: A randomized controlled trial

BACKGROUND

Economic evaluations which estimate cost-effectiveness of potential treatments can guide decisions about real-world healthcare services. We performed an economic evaluation of a healthy lifestyle intervention targeting weight loss, physical activity and diet for patients with chronic low back pain, who are overweight or obese.

METHODS

Eligible patients with chronic low back pain (n = 160) were randomized to an intervention or usual care control group. The intervention included brief advice, a clinical consultation and referral to a 6-month telephone-based healthy lifestyle coaching service. The primary outcome was quality-adjusted life years (QALYs). Secondary outcomes were pain intensity, disability, weight and body mass index. Costs included intervention costs, healthcare utilization costs and work absenteeism costs. An economic analysis was performed from the societal perspective.

RESULTS

Mean total costs were lower in the intervention group than the control group (-$614; 95%CI: -3133 to 255). The intervention group had significantly lower healthcare costs (-$292; 95%CI: -872 to -33), medication costs (-$30; 95%CI: -65 to -4) and absenteeism costs (-$1,000; 95%CI: -3573 to -210). For all outcomes, the intervention was on average less expensive and more effective than usual care, and the probability of the intervention being cost-effective compared to usual care was relatively high (i.e., 0.81) at a willingness-to-pay of $0/unit of effect. However, the probability of cost-effectiveness was not as favourable among sensitivity analyses.

CONCLUSIONS

The healthy lifestyle intervention seems to be cost-effective from the societal perspective. However, variability in the sensitivity analyses indicates caution is needed when interpreting these findings.

SIGNIFICANCE

This is an economic evaluation of a randomized controlled trial of a healthy lifestyle intervention for chronic low back pain. The findings suggest that a healthy lifestyle intervention may be cost-effective relative to usual care.

A full Bayesian model to handle structural ones and missingness in economic evaluations from individual-level data

Economic evaluations from individual-level data are an important component of the process of technology appraisal, with a view to informing resource allocation decisions. A critical problem in these analyses is that both effectiveness and cost data typically present some complexity (eg, nonnormality, spikes, and missingness) that should be addressed using appropriate methods. However, in routine analyses, standardised approaches are typically used, possibly leading to biassed inferences. We present a general Bayesian framework that can handle the complexity. We show the benefits of using our approach with a motivating example, the MenSS trial, for which there are spikes at one in the effectiveness and missingness in both outcomes. We contrast a set of increasingly complex models and perform sensitivity analysis to assess the robustness of the conclusions to a range of plausible missingness assumptions. We demonstrate the flexibility of our approach with a second example, the PBS trial, and extend the framework to accommodate the characteristics of the data in this study. This paper highlights the importance of adopting a comprehensive modelling approach to economic evaluations and the strategic advantages of building these complex models within a Bayesian framework.

A Bayesian framework for health economic evaluation in studies with missing data

Health economics studies with missing data are increasingly using approaches such as multiple imputation that assume that the data are "missing at random." This assumption is often questionable, as-even given the observed data-the probability that data are missing may reflect the true, unobserved outcomes, such as the patients' true health status. In these cases, methodological guidelines recommend sensitivity analyses to recognise data may be "missing not at random" (MNAR), and call for the development of practical, accessible approaches for exploring the robustness of conclusions to MNAR assumptions. Little attention has been paid to the problem that data may be MNAR in health economics in general and in cost-effectiveness analyses (CEA) in particular. In this paper, we propose a Bayesian framework for CEA where outcome or cost data are missing. Our framework includes a practical, accessible approach to sensitivity analysis that allows the analyst to draw on expert opinion. We illustrate the framework in a CEA comparing an endovascular strategy with open repair for patients with ruptured abdominal aortic aneurysm, and provide software tools to implement this approach.

Sensitivity Analysis for Not-at-Random Missing Data in Trial-Based Cost-Effectiveness Analysis: A Tutorial

Cost-effectiveness analyses (CEA) of randomised controlled trials are a key source of information for health care decision makers. Missing data are, however, a common issue that can seriously undermine their validity. A major concern is that the chance of data being missing may be directly linked to the unobserved value itself [missing not at random (MNAR)]. For example, patients with poorer health may be less likely to complete quality-of-life questionnaires. However, the extent to which this occurs cannot be ascertained from the data at hand. Guidelines recommend conducting sensitivity analyses to assess the robustness of conclusions to plausible MNAR assumptions, but this is rarely done in practice, possibly because of a lack of practical guidance. This tutorial aims to address this by presenting an accessible framework and practical guidance for conducting sensitivity analysis for MNAR data in trial-based CEA. We review some of the methods for conducting sensitivity analysis, but focus on one particularly accessible approach, where the data are multiply-imputed and then modified to reflect plausible MNAR scenarios. We illustrate the implementation of this approach on a weight-loss trial, providing the software code. We then explore further issues around its use in practice.

Missing data in trial-based cost-effectiveness analysis: An incomplete journey

Cost-effectiveness analyses (CEA) conducted alongside randomised trials provide key evidence for informing healthcare decision making, but missing data pose substantive challenges. Recently, there have been a number of developments in methods and guidelines addressing missing data in trials. However, it is unclear whether these developments have permeated CEA practice. This paper critically reviews the extent of and methods used to address missing data in recently published trial-based CEA. Issues of the Health Technology Assessment journal from 2013 to 2015 were searched. Fifty-two eligible studies were identified. Missing data were very common; the median proportion of trial participants with complete cost-effectiveness data was 63% (interquartile range: 47%-81%). The most common approach for the primary analysis was to restrict analysis to those with complete data (43%), followed by multiple imputation (30%). Half of the studies conducted some sort of sensitivity analyses, but only 2 (4%) considered possible departures from the missing-at-random assumption. Further improvements are needed to address missing data in cost-effectiveness analyses conducted alongside randomised trials. These should focus on limiting the extent of missing data, choosing an appropriate method for the primary analysis that is valid under contextually plausible assumptions, and conducting sensitivity analyses to departures from the missing-at-random assumption.

Utility and quality-adjusted life-years in coronary artery disease: Five-year follow-up of the MASS II trial

OBJECTIVES

This study evaluated the utility and quality-of-life year measurements for patients with coronary artery disease who underwent any of 3 therapeutic strategies with a 5-year follow-up.

METHODS

Quality-of-life data were obtained from the Medicine, Angioplasty, or Surgery Study II trial. To obtain utilities, the 36-Item Short-Form questionnaire was converted to a 6-Dimensional Health State Classification System.

RESULTS

Of the 611 initial patients, 579 completed the questionnaire. In all, 188 patients received the surgical treatment-194 the percutaneous, and the remaining 197 the medical. The median utility scores for the 5 years analyzed were 0.809 (95% confidence interval [CI] 0.794-0.842) for patients assigned to percutaneous coronary intervention, 0.755 (95% CI 0.723-0.774) for medical treatment, and 0.780 (95% CI 0.761-0.809) for coronary artery bypass graft surgery. The difference between percutaneous coronary intervention and medical treatment was statistically significant (P < .05, Dunn test). The median cumulative quality-of-life years across the 5 years were 3.802 (95% CI 3.668-3.936) for percutaneous, 3.540 (95% CI 3.399-3.681) for medical, and 3.764 (95% CI 3.638-3.890) for surgery. Additionally, the median quality-of-life years between percutaneous and medical treatment was 0.262 (95% CI 0.068-0.456), between surgery and medical treatment it was 0.224 (95% CI 0.036-0.413), and between surgery and percutaneous coronary intervention it was -0.038 (95% CI -0.221 to -0.146).

CONCLUSION

Coronary artery bypass surgery and percutaneous coronary intervention were similar regarding cumulative quality-of-life years; however, they were both superior to that of medical treatment. The results presented are valuable data for further cost-utility studies.

Subcutaneous Injection of Adalimumab Trial compared with Control (SCIATiC): a randomised controlled trial of adalimumab injection compared with placebo for patients receiving physiotherapy treatment for sciatica

BACKGROUND

Biological treatments such as adalimumab (Humira^®; AbbVie Ltd, Maidenhead, UK) are antibodies targeting tumour necrosis factor alpha, released from ruptured intervertebral discs, which might be useful in sciatica. Recent systematic reviews concluded that they might be effective, but that a definitive randomised controlled trial was needed. Usual care in the NHS typically includes a physiotherapy intervention.

OBJECTIVES

To test whether or not injections of adalimumab plus physiotherapy are more clinically effective and cost-effective than injections of saline plus physiotherapy for patients with sciatica.

DESIGN

Pragmatic, parallel-group, randomised controlled trial with blinded participants and clinicians, and an outcome assessment and statistical analysis with concurrent economic evaluation and internal pilot.

SETTING

Participants were referred from primary care and musculoskeletal services to outpatient physiotherapy clinics.

PARTICIPANTS

Adults with persistent symptoms of sciatica of 1-6 months' duration and with moderate to high levels of disability. Eligibility was assessed by research physiotherapists according to clinical criteria for diagnosing sciatica.

INTERVENTIONS

After a second eligibility check, trial participants were randomised to receive two doses of adalimumab (80 mg and then 40 mg 2 weeks later) or saline injections. Both groups were referred for a course of physiotherapy.

MAIN OUTCOME MEASURES

Outcomes were measured at the start, and after 6 weeks' and 6 months' follow-up. The main outcome measure was the Oswestry Disability Index (ODI). Other outcomes: leg pain version of the Roland-Morris Disability Questionnaire, Sciatica Bothersomeness Index, EuroQol-5 Dimensions, 5-level version, Hospital Anxiety and Depression Scale, resource use, risk of persistent disabling pain, pain trajectory based on a single question, Pain Self-Efficacy Questionnaire, Tampa Scale of Kinesiophobia and adverse effects.

SAMPLE SIZE

To detect an effect size of 0.4 with 90% power, a 5% significance level for a two-tailed t-test and 80% retention rate, 332 participants would have needed to be recruited.

ANALYSIS PLAN

The primary effectiveness analysis would have been linear mixed models for repeated measures to measure the effects of time and group allocation. An internal pilot study would have involved the first 50 participants recruited across all centres. The primary economic analysis would have been a cost-utility analysis.

RESULTS

The internal pilot study was discontinued as a result of low recruitment after eight participants were recruited from two out of six sites. One site withdrew from the study before recruitment started, one site did not complete contract negotiations and two sites signed contracts shortly before trial closure. In the two sites that did recruit participants, recruitment was slow. This was partly because of operational issues, but also because of a low rate of uptake from potential participants.

LIMITATIONS

Although large numbers of invitations were sent to potential participants, identified by retrospective searches of general practitioner (GP) records, there was a low rate of uptake. Two sites planned to recruit participants during GP consultations but opened too late to recruit any participants.

CONCLUSION

The main failure was attributable to problems with contracts. Because of this we were not able to complete the internal pilot or to test all of the different methods for primary care recruitment we had planned. A trial of biological therapy in patients with sciatica still needs to be done, but would require a clearer contracting process, qualitative research to ensure that patients would be willing to participate, and simpler recruitment methods.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN14569274.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 21, No. 60. See the NIHR Journals Library website for further project information.

Study protocol for the 'HelpMeDoIt!' randomised controlled feasibility trial: an app, web and social support-based weight loss intervention for adults with obesity

INTRODUCTION

HelpMeDoIt! will test the feasibility of an innovative weight loss intervention using a smartphone app and website. Goal setting, self-monitoring and social support are three key facilitators of behaviour change. HelpMeDoIt! incorporates these features and encourages participants to invite 'helpers' from their social circle to help them achieve their goal(s).

AIM

To test the feasibility of the intervention in supporting adults with obesity to achieve weight loss goals.

METHODS AND ANALYSIS

12-month feasibility randomised controlled trial and accompanying process evaluation. Participants (n=120) will be adults interested in losing weight, body mass index (BMI)> 30 kg/m2 and smartphone users. The intervention group will use the app/website for 12 months. Participants will nominate one or more helpers to support them. Helpers have access to the app/website. The control group will receive a leaflet on healthy lifestyle and will have access to HelpMeDoIt! after follow-up. The key outcome of the study is whether prespecified progression criteria have been met in order to progress to a larger randomised controlled effectiveness trial. Data will be collected at baseline, 6 and 12 months. Outcomes focus on exploring the feasibility of delivering the intervention and include: (i) assessing three primary outcomes (BMI, physical activity and diet); (ii) secondary outcomes of waist/hip circumference, health-related quality of life, social support, self-efficacy, motivation and mental health; (iii) recruitment and retention; (iv) National Health Service (NHS) resource use and participant borne costs; (v) usability and acceptability of the app/website; and (vi) qualitative interviews with up to 50 participants and 20 helpers on their experiences of the intervention. Statistical analyses will focus on feasibility outcomes and provide initial estimates of intervention effects. Thematic analysis of qualitative interviews will assess implementation, acceptability, mechanisms of effect and contextual factors influencing the intervention.

ETHICS AND DISSEMINATION

The protocol has been approved by the West of Scotland NHS Research Ethics Committee (Ref: 15/WS/0288) and the University of Glasgow MVLS College Ethics Committee (Ref: 200140108). Findings will be disseminated widely through peer-reviewed publication and conference presentations.

TRIAL REGISTRATION NUMBER

ISRCTN85615983.

Economic Evaluation of Complete Revascularization for Patients with Multivessel Disease Undergoing Primary Percutaneous Coronary Intervention

OBJECTIVES

To determine the cost-effectiveness of complete revascularization at index admission compared with infarct-related artery (IRA) treatment only, in patients with multivessel disease undergoing primary percutaneous coronary intervention (P-PCI) for ST-segment elevation myocardial infarction.

METHODS

An economic evaluation of a multicenter randomized trial was conducted, comparing complete revascularization at index admission to IRA-only P-PCI in patients with multivessel disease (12-month follow-up). Overall hospital costs (costs for P-PCI procedure(s), hospital length of stay, and any subsequent re-admissions) were estimated. Outcomes were major adverse cardiac events (MACEs, a composite of all-cause death, recurrent myocardial infarction, heart failure, and ischemia-driven revascularization) and quality-adjusted life-years (QALYs) derived from the three-level EuroQol five-dimensional questionnaire. Multiple imputation was undertaken. The mean incremental cost and effect, with associated 95% confidence intervals, the incremental cost-effectiveness ratio, and the cost-effectiveness acceptability curve were estimated.

RESULTS

On the basis of 296 patients, the mean incremental overall hospital cost for complete revascularization was estimated to be -£215.96 (-£1390.20 to £958.29), compared with IRA-only, with a per-patient mean reduction in MACEs of 0.170 (0.044 to 0.296) and a QALY gain of 0.011 (-0.019 to 0.041). According to the cost-effectiveness acceptability curve, the probability of complete revascularization being cost-effective was estimated to be 72.0% at a willingness-to-pay threshold value of £20,000 per QALY.

CONCLUSIONS

Complete revascularization at index admission was estimated to be more effective (in terms of MACEs and QALYs) and cost-effective (overall costs were estimated to be lower and complete revascularization thereby dominated IRA-only). There was, however, some uncertainty associated with this decision.

Handling Missing Data in Within-Trial Cost-Effectiveness Analysis: A Review with Future Recommendations

Cost-effectiveness analyses (CEAs) alongside randomised controlled trials (RCTs) are increasingly designed to collect resource use and preference-based health status data for the purpose of healthcare technology assessment. However, because of the way these measures are collected, they are prone to missing data, which can ultimately affect the decision of whether an intervention is good value for money. We examine how missing cost and effect outcome data are handled in RCT-based CEAs, complementing a previous review (covering 2003-2009, 88 articles) with a new systematic review (2009-2015, 81 articles) focussing on two different perspectives. First, we provide guidelines on how the information about missingness and related methods should be presented to improve the reporting and handling of missing data. We propose to address this issue by means of a quality evaluation scheme, providing a structured approach that can be used to guide the collection of information, elicitation of the assumptions, choice of methods and considerations of possible limitations of the given missingness problem. Second, we review the description of the missing data, the statistical methods used to deal with them and the quality of the judgement underpinning the choice of these methods. Our review shows that missing data in within-RCT CEAs are still often inadequately handled and the overall level of information provided to support the chosen methods is rarely satisfactory.

Wordless intervention for people with epilepsy and learning disabilities (WIELD): a randomised controlled feasibility trial

OBJECTIVE

To investigate the feasibility of a full-scale randomised controlled trial of a picture booklet to improve quality of life for people with epilepsy and learning disabilities.

TRIAL DESIGN

A randomised controlled feasibility trial. Randomisation was not blinded and was conducted using a centralised secure database and a blocked 1:1 allocation ratio.

SETTING

Epilepsy clinics in 1 English National Health Service (NHS) Trust.

PARTICIPANTS

Patients with learning disabilities and epilepsy who had: a seizure within the past 12 months, meaningful communication and a carer with sufficient proficiency in English.

INTERVENTION

Participants in the intervention group used a picture booklet with a trained researcher, and a carer present. These participants kept the booklet, and were asked to use it at least twice more over 20 weeks. The control group received treatment as usual, and were provided with a booklet at the end of the study.

OUTCOME MEASURES

7 feasibility criteria were used relating to recruitment, data collection, attrition, potential effect on epilepsy-related quality of life (Epilepsy and Learning Disabilities Quality of Life Scale, ELDQOL) at 4-week, 12-week and 20-week follow-ups, feasibility of methodology, acceptability of the intervention and potential to calculate cost-effectiveness.

OUTCOME

The recruitment rate of eligible patients was 34% and the target of 40 participants was reached. There was minimal missing data and attrition. An intention-to-treat analysis was performed; data from the outcome measures suggest a benefit from the intervention on the ELDQOL behaviour and mood subscales at 4 and 20 weeks follow-up. The booklet and study methods were positively received, and no adverse events were reported. There was a positive indication of the potential for a cost-effectiveness analysis.

CONCLUSIONS

All feasibility criteria were fully or partially met, therefore confirming feasibility of a definitive trial.

TRIAL REGISTRATION NUMBER

ISRCTN80067039.

Conducting Economic Evaluations Alongside Randomised Trials: Current Methodological Issues and Novel Approaches

Trial-based economic evaluations are an important aspect of health technology assessment. The availability of patient-level data coupled with unbiased estimates of clinical outcomes means that randomised controlled trials are effective vehicles for the generation of economic data. However there are methodological challenges to trial-based evaluations, including the collection of reliable data on resource use and cost, choice of health outcome measure, calculating minimally important differences, dealing with missing data, extrapolating outcomes and costs over time and the analysis of multinational trials. This review focuses on the state of the art of selective elements regarding the design, conduct, analysis and reporting of trial-based economic evaluations. The limitations of existing approaches are detailed and novel methods introduced. The review is internationally relevant but with a focus towards practice in the UK.

Effectiveness and economic evaluation of self-help educational materials for the prevention of smoking relapse: randomised controlled trial

BACKGROUND

Most people who quit smoking successfully for a short period will return to smoking again in 12 months. A previous exploratory meta-analysis indicated that self-help booklets may be effective for smoking relapse prevention in unaided quitters.

OBJECTIVES

This study aimed to evaluate the effectiveness of a set of self-help educational booklets to prevent smoking relapse in people who had stopped smoking with the aid of behavioural support.

DESIGN

This is an open, randomised controlled trial and qualitative process evaluation. Trial participants were randomly allocated to one of two groups, using a simple randomisation process without attempts to stratify by participant characteristics. The participant allocation was 'concealed' because the recruitment of quitters occurred before the random allocation.

SETTING

Short-term quitters were recruited from NHS Stop Smoking Clinics, and self-help educational materials were posted to study participants at home.

PARTICIPANTS

A total of 1407 carbon monoxide (CO)-validated quitters at 4 weeks after quit date in NHS Stop Smoking Clinics. The trial excluded pregnant women and quitters who were not able to read the educational materials in English.

INTERVENTIONS

Participants in the experimental group (n = 703) received a set of eight revised Forever Free booklets, and participants in the control group (n = 704) received a single leaflet that is currently given to NHS patients.

MAIN OUTCOME MEASURES

Follow-up telephone interviews were conducted 3 and 12 months after quit date. The primary outcome was prolonged, CO-verified abstinence from months 4 to 12 during which time no more than five cigarettes were smoked. The secondary outcomes included self-reported abstinence during the previous 7 days at 3 and 12 months, CO-verified abstinence at 12 months, costs (NHS and NHS and participant medication costs perspectives) and quality-adjusted life-years. Logistic regression analyses were conducted to investigate effect-modifying variables. A simultaneous qualitative process evaluation was conducted to help interpret the trial results.

RESULTS

Data from 1404 participants were used for the final analysis, after excluding three participants who died before the 12-month follow-up. The proportion with prolonged abstinence from months 4 to 12 after quit date was 36.9% in the intervention group and 38.6% in the control group. There was no statistically significant difference between the groups (odds ratio 0.93, 95% confidence interval 0.75 to 1.15; p = 0.509). There were no statistically significant differences between the groups in secondary smoking outcomes. People who reported knowing risky situations for relapse and using strategies to handle urges to smoke were less likely to relapse. However, there were no differences between the groups in the proportion of participants who reported that they knew any more about coping skills, and no differences in reported use of strategies to cope with urges to smoke between the trial groups. The qualitative study found that some quitters considered self-help booklets unhelpful for smoking relapse prevention, although positive feedback by participants was common.

CONCLUSIONS

Among quitters who had stopped smoking with the aid of intensive behavioural support, there was no significant difference in the likelihood of smoking relapse between those who subsequently received a set of eight revised Forever Free booklets and those who received a single leaflet. Although many people had suboptimal strategies to prevent relapse and most relapsed, the Forever Free booklets proved an ineffective medium for teaching them the skills to prevent relapse. Further research should focus on interventions that may increase the use of coping skills when required.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN36980856.

Multiple imputation methods for bivariate outcomes in cluster randomised trials

Missing observations are common in cluster randomised trials. The problem is exacerbated when modelling bivariate outcomes jointly, as the proportion of complete cases is often considerably smaller than the proportion having either of the outcomes fully observed. Approaches taken to handling such missing data include the following: complete case analysis, single‐level multiple imputation that ignores the clustering, multiple imputation with a fixed effect for each cluster and multilevel multiple imputation.

We contrasted the alternative approaches to handling missing data in a cost‐effectiveness analysis that uses data from a cluster randomised trial to evaluate an exercise intervention for care home residents.

We then conducted a simulation study to assess the performance of these approaches on bivariate continuous outcomes, in terms of confidence interval coverage and empirical bias in the estimated treatment effects. Missing‐at‐random clustered data scenarios were simulated following a full‐factorial design.

Across all the missing data mechanisms considered, the multiple imputation methods provided estimators with negligible bias, while complete case analysis resulted in biased treatment effect estimates in scenarios where the randomised treatment arm was associated with missingness. Confidence interval coverage was generally in excess of nominal levels (up to 99.8%) following fixed‐effects multiple imputation and too low following single‐level multiple imputation. Multilevel multiple imputation led to coverage levels of approximately 95% throughout. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

The current practice of handling and reporting missing outcome data in eight widely used PROMs in RCT publications: a review of the current literature

Purpose

Patient-reported outcome measures (PROMs) are designed to assess patients’ perceived health states or health-related quality of life. However, PROMs are susceptible to missing data, which can affect the validity of conclusions from randomised controlled trials (RCTs). This review aims to assess current practice in the handling, analysis and reporting of missing PROMs outcome data in RCTs compared to contemporary methodology and guidance.

Methods

This structured review of the literature includes RCTs with a minimum of 50 participants per arm. Studies using the EQ-5D-3L, EORTC QLQ-C30, SF-12 and SF-36 were included if published in 2013; those using the less commonly implemented HUI, OHS, OKS and PDQ were included if published between 2009 and 2013.

Results

The review included 237 records (4–76 per relevant PROM). Complete case analysis and single imputation were commonly used in 33 and 15 % of publications, respectively. Multiple imputation was reported for 9 % of the PROMs reviewed. The majority of publications (93 %) failed to describe the assumed missing data mechanism, while low numbers of papers reported methods to minimise missing data (23 %), performed sensitivity analyses (22 %) or discussed the potential influence of missing data on results (16 %).

Conclusions

Considerable discrepancy exists between approved methodology and current practice in handling, analysis and reporting of missing PROMs outcome data in RCTs. Greater awareness is needed for the potential biases introduced by inappropriate handling of missing data, as well as the importance of sensitivity analysis and clear reporting to enable appropriate assessments of treatment effects and conclusions from RCTs.

Electronic supplementary material

The online version of this article (doi:10.1007/s11136-015-1206-1) contains supplementary material, which is available to authorized users.

Multiple imputation of multiple multi-item scales when a full imputation model is infeasible

Background

Missing data in a large scale survey presents major challenges. We focus on performing multiple imputation by chained equations when data contain multiple incomplete multi-item scales. Recent authors have proposed imputing such data at the level of the individual item, but this can lead to infeasibly large imputation models.

Methods

We use data gathered from a large multinational survey, where analysis uses separate logistic regression models in each of nine country-specific data sets. In these data, applying multiple imputation by chained equations to the individual scale items is computationally infeasible. We propose an adaptation of multiple imputation by chained equations which imputes the individual scale items but reduces the number of variables in the imputation models by replacing most scale items with scale summary scores. We evaluate the feasibility of the proposed approach and compare it with a complete case analysis. We perform a simulation study to compare the proposed method with alternative approaches: we do this in a simplified setting to allow comparison with the full imputation model.

Results

For the case study, the proposed approach reduces the size of the prediction models from 134 predictors to a maximum of 72 and makes multiple imputation by chained equations computationally feasible. Distributions of imputed data are seen to be consistent with observed data. Results from the regression analysis with multiple imputation are similar to, but more precise than, results for complete case analysis; for the same regression models a 39 % reduction in the standard error is observed. The simulation shows that our proposed method can perform comparably against the alternatives.

Conclusions

By substantially reducing imputation model sizes, our adaptation makes multiple imputation feasible for large scale survey data with multiple multi-item scales. For the data considered, analysis of the multiply imputed data shows greater power and efficiency than complete case analysis. The adaptation of multiple imputation makes better use of available data and can yield substantively different results from simpler techniques.

Electronic supplementary material

The online version of this article (doi:10.1186/s13104-016-1853-5) contains supplementary material, which is available to authorized users.

The four or more medicines (FOMM) support service: results from an evaluation of a new community pharmacy service aimed at over-65s

OBJECTIVE

Inappropriate prescribing and nonadherence have a significant impact on hospital admissions and patient quality of life. The English government has identified that community pharmacy could make a significant contribution to reducing nonadherence and improving the quality of prescribing, reducing both hospital admissions and medicines wastage. The objective of this study is to evaluate a community pharmacy service aimed at patients over the age of 65 years prescribed four or more medicines.

METHODS

Patients were invited to participate in the service by the community pharmacy team. The pharmacist held regular consultations with the patient and discussed risk of falls, pain management, adherence and general health. They also reviewed the patient's medication using STOPP/START criteria. Data were analysed for the first 6 months of participation in the service.

KEY FINDINGS

Six hundred twenty patients were recruited with 441 (71.1%) completing the 6-month study period. Pharmacists made 142 recommendations to prescribers in 110 patients largely centred on potentially inappropriate prescribing of NSAIDs, PPIs or duplication of therapy. At follow-up, there was a significant decrease in the total number of falls (mean -0.116 (-0.217--0.014)) experienced and a significant increase in medicine adherence (mean difference in Morisky Measure of Adherence Scale-8: 0.513 (0.337-0.689)) and quality of life. Cost per quality-adjusted life year estimates ranged from £11 885 to £32 466 depending on the assumptions made.

CONCLUSION

By focussing on patients over the age of 65 years with four or more medicines, community pharmacists can improve medicine adherence and patient quality of life.

A multi-centre, randomised controlled trial of the effectiveness of PDSAFE to prevent falls among people with Parkinson's: study protocol

Background

Falls amongst people with Parkinson’s (PwP) result in significant disability and reduced quality of life. There is emerging evidence that exercise-based and physiotherapeutic interventions are of benefit for improving fall risk factors, such as balance. However, the benefit, in terms of preventing falls, is mixed. The development of effective interventions has been identified as the highest research priority for this population.

The aim of this trial is to establish the effectiveness and cost-effectiveness of a novel, home-based physiotherapy programme, compared with usual care, on falls amongst PwP.

Methods/Design

A UK multi-centre, community-based, single blind, randomised controlled trial with twelve month follow-up, and nested economic evaluation and qualitative studies will be undertaken. Six hundred PwP who live in their own home, have had one or more falls in the previous year and an MMSE score of ≥24 will be recruited. Those living in care homes and those needing assistance from another person to walk indoors will not be eligible.

The intervention is a physiotherapist delivered, individually tailored and progressive, home-based programme (PDSAFE) comprising task orientated movement strategy training, functional lower limb strengthening and balance training, of six months duration. Unsupervised daily home exercises and strategies will be practised and supported using technology. Control participants will receive usual care.

Data collection will include falls, cognitive state, balance and mobility, fear of falling, freezing of gait, mood, quality of life, carer quality of life and resource use. Data will be collected at baseline, three, six and twelve months. Longitudinal semi-structured interviews will be undertaken with forty participants to explore the expectations and experiences of participants.

The primary outcome is risk of repeat falling at six months post-randomisation.

Discussion

The aims of this trial are to establish the effectiveness and cost-effectiveness of a novel, home-delivered physiotherapy intervention (PDSAFE) compared with usual care on risk of falling for PwP who have a history of falling. PDSAFE is a novel intervention that builds upon the existing literature and targeting known risk factors, being the first study that uses a novel delivery modus (technology) in conjunction with traditional physiotherapeutic approaches.

Trial registration

Current Controlled Trials ISRCTN48152791

Endovascular strategy or open repair for ruptured abdominal aortic aneurysm: one-year outcomes from the IMPROVE randomized trial

Aims

To report the longer term outcomes following either a strategy of endovascular repair first or open repair of ruptured abdominal aortic aneurysm, which are necessary for both patient and clinical decision-making.

Methods and results

This pragmatic multicentre (29 UK and 1 Canada) trial randomized 613 patients with a clinical diagnosis of ruptured aneurysm; 316 to an endovascular first strategy (if aortic morphology is suitable, open repair if not) and 297 to open repair. The principal 1-year outcome was mortality; secondary outcomes were re-interventions, hospital discharge, health-related quality-of-life (QoL) (EQ-5D), costs, Quality-Adjusted-Life-Years (QALYs), and cost-effectiveness [incremental net benefit (INB)]. At 1 year, all-cause mortality was 41.1% for the endovascular strategy group and 45.1% for the open repair group, odds ratio 0.85 [95% confidence interval (CI) 0.62, 1.17], P = 0.325, with similar re-intervention rates in each group. The endovascular strategy group and open repair groups had average total hospital stays of 17 and 26 days, respectively, P < 0.001. Patients surviving rupture had higher average EQ-5D utility scores in the endovascular strategy vs. open repair groups, mean differences 0.087 (95% CI 0.017, 0.158), 0.068 (95% CI −0.004, 0.140) at 3 and 12 months, respectively. There were indications that QALYs were higher and costs lower for the endovascular first strategy, combining to give an INB of £3877 (95% CI £253, £7408) or €4356 (95% CI €284, €8323).

Conclusion

An endovascular first strategy for management of ruptured aneurysms does not offer a survival benefit over 1 year but offers patients faster discharge with better QoL and is cost-effective.

Clinical trial registration

ISRCTN 48334791.

An educational review of the statistical issues in analysing utility data for cost-utility analysis

The aim of cost-utility analysis is to support decision making in healthcare by providing a standardised mechanism for comparing resource use and health outcomes across programmes of work. The focus of this paper is the denominator of the cost-utility analysis, specifically the methodology and statistical challenges associated with calculating QALYs from patient-level data collected as part of a trial. We provide a brief description of the most common questionnaire used to calculate patient level utility scores, the EQ-5D, followed by a discussion of other ways to calculate patient level utility scores alongside a trial including other generic measures of health-related quality of life and condition- and population-specific questionnaires. Detail is provided on how to calculate the mean QALYs per patient, including discounting, adjusting for baseline differences in utility scores and a discussion of the implications of different methods for handling missing data. The methods are demonstrated using data from a trial. As the methods chosen can systematically change the results of the analysis, it is important that standardised methods such as patient-level analysis are adhered to as best as possible. Regardless, researchers need to ensure that they are sufficiently transparent about the methods they use so as to provide the best possible information to aid in healthcare decision making.

Trial-based economic evaluations in occupational health: principles, methods, and recommendations

To allocate available resources as efficiently as possible, decision makers need information on the relative economic merits of occupational health and safety (OHS) interventions. Economic evaluations can provide this information by comparing the costs and consequences of alternatives. Nevertheless, only a few of the studies that consider the effectiveness of OHS interventions take the extra step of considering their resource implications. Moreover, the methodological quality of those that do is generally poor. Therefore, this study aims to help occupational health researchers conduct high-quality trial-based economic evaluations by discussing the theory and methodology that underlie them, and by providing recommendations for good practice regarding their design, analysis, and reporting. This study also helps consumers of this literature with understanding and critically appraising trial-based economic evaluations of OHS interventions.

Multiple imputation to deal with missing EQ-5D-3L data: Should we impute individual domains or the actual index?

PURPOSE

Missing data are a well-known and widely documented problem in cost-effectiveness analyses alongside clinical trials using individual patient-level data. Current methodological research recommends multiple imputation (MI) to deal with missing health outcome data, but there is little guidance on whether MI for multi-attribute questionnaires, such as the EQ-5D-3L, should be carried out at domain or at summary score level. In this paper, we evaluated the impact of imputing individual domains versus imputing index values to deal with missing EQ-5D-3L data using a simulation study and developed recommendations for future practice.

METHODS

We simulated missing data in a patient-level dataset with complete EQ-5D-3L data at one point in time from a large multinational clinical trial (n = 1,814). Different proportions of missing data were generated using a missing at random (MAR) mechanism and three different scenarios were studied. The performance of using each method was evaluated using root mean squared error and mean absolute error of the actual versus predicted EQ-5D-3L indices.

RESULTS

In large sample sizes (n > 500) and a missing data pattern that follows mainly unit non-response, imputing domains or the index produced similar results. However, domain imputation became more accurate than index imputation with pattern of missingness following an item non-response. For smaller sample sizes (n < 100), index imputation was more accurate. When MI models were misspecified, both domain and index imputations were inaccurate for any proportion of missing data.

CONCLUSIONS

The decision between imputing the domains or the EQ-5D-3L index scores depends on the observed missing data pattern and the sample size available for analysis. Analysts conducting this type of exercises should also evaluate the sensitivity of the analysis to the MAR assumption and whether the imputation model is correctly specified.