The adaptive designs CONSORT extension (ACE) statement: a checklist with explanation and elaboration guideline for reporting randomised trials that use an adaptive design.

Adaptive designs (ADs) allow pre-planned changes to an ongoing trial without compromising the validity of conclusions and it is essential to distinguish pre-planned from unplanned changes that may also occur. The reporting of ADs in randomised trials is inconsistent and needs improving. Incompletely reported AD randomised trials are difficult to reproduce and are hard to interpret and synthesise. This consequently hampers their ability to inform practice as well as future research and contributes to research waste. Better transparency and adequate reporting will enable the potential benefits of ADs to be realised.This extension to the Consolidated Standards Of Reporting Trials (CONSORT) 2010 statement was developed to enhance the reporting of randomised AD clinical trials. We developed an Adaptive designs CONSORT Extension (ACE) guideline through a two-stage Delphi process with input from multidisciplinary key stakeholders in clinical trials research in the public and private sectors from 21 countries, followed by a consensus meeting. Members of the CONSORT Group were involved during the development process.The paper presents the ACE checklists for AD randomised trial reports and abstracts, as well as an explanation with examples to aid the application of the guideline. The ACE checklist comprises seven new items, nine modified items, six unchanged items for which additional explanatory text clarifies further considerations for ADs, and 20 unchanged items not requiring further explanatory text. The ACE abstract checklist has one new item, one modified item, one unchanged item with additional explanatory text for ADs, and 15 unchanged items not requiring further explanatory text.The intention is to enhance transparency and improve reporting of AD randomised trials to improve the interpretability of their results and reproducibility of their methods, results and inference. We also hope indirectly to facilitate the much-needed knowledge transfer of innovative trial designs to maximise their potential benefits. In order to encourage its wide dissemination this article is freely accessible on the BMJ and Trials journal websites."To maximise the benefit to society, you need to not just do research but do it well" Douglas G Altman.

The Adaptive designs CONSORT Extension (ACE) statement: a checklist with explanation and elaboration guideline for reporting randomised trials that use an adaptive design.

Adaptive designs (ADs) allow pre-planned changes to an ongoing trial without compromising the validity of conclusions and it is essential to distinguish pre-planned from unplanned changes that may also occur. The reporting of ADs in randomised trials is inconsistent and needs improving. Incompletely reported AD randomised trials are difficult to reproduce and are hard to interpret and synthesise. This consequently hampers their ability to inform practice as well as future research and contributes to research waste. Better transparency and adequate reporting will enable the potential benefits of ADs to be realised.This extension to the Consolidated Standards Of Reporting Trials (CONSORT) 2010 statement was developed to enhance the reporting of randomised AD clinical trials. We developed an Adaptive designs CONSORT Extension (ACE) guideline through a two-stage Delphi process with input from multidisciplinary key stakeholders in clinical trials research in the public and private sectors from 21 countries, followed by a consensus meeting. Members of the CONSORT Group were involved during the development process.The paper presents the ACE checklists for AD randomised trial reports and abstracts, as well as an explanation with examples to aid the application of the guideline. The ACE checklist comprises seven new items, nine modified items, six unchanged items for which additional explanatory text clarifies further considerations for ADs, and 20 unchanged items not requiring further explanatory text. The ACE abstract checklist has one new item, one modified item, one unchanged item with additional explanatory text for ADs, and 15 unchanged items not requiring further explanatory text.The intention is to enhance transparency and improve reporting of AD randomised trials to improve the interpretability of their results and reproducibility of their methods, results and inference. We also hope indirectly to facilitate the much-needed knowledge transfer of innovative trial designs to maximise their potential benefits.

Perceptions of healthcare professionals and managers regarding the effectiveness of GP-led walk-in centres in the UK.

OBJECTIVES: This study aimed to identify the perceptions of healthcare professionals regarding the effectiveness and the impact of a new general practitioner-led (GP-led) walk-in centre in the UK. SETTING: This qualitative study was conducted in a large city in the North of England. In the past few years, there has been particular concern about an increase in the use of emergency department (ED) services provided by the National Health Service and part of the rationale for introducing the new GP-led walk-in centres has been to stem this increase. The five institutes included in the study were EDs, a minor injuries unit, a primary care trust, a GP-led walk-in centre and GP surgeries. PARTICIPANTS: Semistructured interviews were conducted with healthcare providers at an adult ED, an ED at a children's hospital, a minor injuries unit, a GP-led walk-in centre, GPs from surrounding surgeries and GPs. RESULTS: 11 healthcare professionals and managers were interviewed. Seven key themes were identified within the data: the clinical model of the GP-led walk-in centre; public awareness of the services; appropriate use of the centre; the impact of the centre on other services; demand for healthcare services; choice and confusion and mixed views (positive and negative) of the walk-in services. There were discrepancies between the managers and healthcare professionals regarding the usefulness of the GP-led walk-in centre in the current urgent care system. CONCLUSIONS: Participants did not notice declines in the demand for EDs after the GP-led walk-in centre. Most of the healthcare professionals believed that the GP-led walk-in centre duplicated existing healthcare services. There is a need to have a better communication system between the GP-led walk-in centres and other healthcare providers to have an integrated system of urgent care delivery.

Health utility after emergency medical admission: a cross-sectional survey.

OBJECTIVES: Health utility combines health related quality of life and mortality to produce a generic outcome measure reflecting both morbidity and mortality. It has not been widely used as an outcome measure in evaluations of emergency care and little is known about the feasibility of measurement, typical values obtained or baseline factors that predict health utility. We aimed to measure health utility after emergency medical admission, to compare health utility to age, gender and regional population norms, and identify independent predictors of health utility. METHODS: We selected 5760 patients across three hospitals who were admitted to hospital by ambulance as a medical emergency. The EQ-5D questionnaire was mailed to all who were still alive 30 days after admission. Health utility was estimated by applying tariff values to the EQ-5D responses or imputing a value of zero for those who had died. Multivariable analysis was used to identify independent predictors of health utility at 30 days. RESULTS: Responses were received from 2488 (47.7%) patients, while 541 (9.4%) had died. Most respondents reported some or severe problems with each aspect of health. Mean health utility was 0.49 (standard deviation 0.35) in survivors and 0.45 (0.36) including non-survivors. Some 75% had health utility below their expected value (mean loss 0.32, 95% confidence interval 0.31 to 0.33) and 11% had health utility below zero (worse than death). On multivariable modelling, reduced health utility was associated with increased age and lower GCS, varied according to ICD10 code and was lower among females, patients with recent hospital admission, steroid therapy, or history of chronic respiratory disease, malignancy, diabetes or epilepsy. CONCLUSIONS: Health utility can be measured after emergency medical admission, although responder bias may be significant. Health utility after emergency medical admission is poor compared to population norms. We have identified independent predictors or health utility that need to be measured and taken into account in non-randomized evaluations of emergency care.

Cost effectiveness of a community based exercise programme in over 65 year olds: cluster randomised trial.

OBJECTIVE: To assess the cost effectiveness of a community based exercise programme as a population wide public health intervention for older adults. DESIGN: Pragmatic, cluster randomised community intervention trial. SETTING: 12 general practices in Sheffield; four randomly selected as intervention populations, and eight as control populations. PARTICIPANTS: All those aged 65 and over in the least active four fifths of the population responding to a baseline survey. There were 2283 eligible participants from intervention practices and 4137 from control practices. INTERVENTION: Eligible subjects were invited to free locally held exercise classes, made available for two years. MAIN OUTCOME MEASURES: All cause and exercise related cause specific mortality and hospital service use at two years, and health status assessed at baseline, one, and two years using the SF-36. A cost utility analysis was also undertaken. RESULTS: Twenty six per cent of the eligible intervention practice population attended one or more exercise sessions. There were no significant differences in mortality rates, survival times, or admissions. After adjusting for baseline characteristics, patients in intervention practices had a lower decline in health status, although this reached significance only for the energy dimension and two composite scores (p<0.05). The incremental average QALY gain of 0.011 per person in the intervention population resulted in an incremental cost per QALY ratio of 17 174 (95% CI = 8300 to 87 120). CONCLUSIONS: Despite a low level of adherence to the exercise programme, there were significant gains in health related quality of life. The programme was more cost effective than many existing medical interventions, and would be practical for primary care commissioning agencies to implement.

A randomised, controlled, triple-blind trial of the efficacy of homeopathic treatment for chronic fatigue syndrome.

OBJECTIVE: There is no management regime for chronic fatigue syndrome (CFS) that has been found to be universally beneficial and no treatment can be considered a "cure". Patients with CFS may use complementary and alternative medicine (CAM). Our aim was to evaluate homeopathic treatment in reducing subjective symptoms of CFS. METHOD: Using a triple-blind design (patient and homeopath blind to group assignment and data analyst blind to group until after initial analyses to reduce the possibility of bias due to data analyst), we randomly assigned patients to homeopathic medicine or identical placebo. One hundred and three patients meeting the Oxford criteria for CFS were recruited from two specialist hospital out patient departments. Patients had monthly consultations with a professional homeopath for 6 months. Main outcome measures were scores on the subscales of the Multidimensional Fatigue Inventory (MFI) and proportions of each group attaining clinically significant improvements on each subscale. Secondary outcome measures were the Fatigue Impact Scale (FIS) and the Functional Limitations Profile (FLP). Ninety-two patients completed treatment in the trial (47 homeopathic treatment, 45 placebo). Eighty-six patients returned fully or partially completed posttreatment outcome measures (41 homeopathic treatment group who completed treatment, 2 homeopathic treatment group who did not complete treatment, 38 placebo group who completed treatment, and 5 placebo group who did not complete treatment). RESULTS: Seventeen of 103 patients withdrew from treatment or were lost to follow-up. Patients in the homeopathic medicine group showed significantly more improvement on the MFI general fatigue subscale (one of the primary outcome measures) and the FLP physical subscale but not on other subscales. Although group differences were not statistically significant on four out of the five MFI subscales (the primary outcome measures), more people in the homeopathic medicine group showed clinically significant improvement. More people in the homeopathic medicine group showed clinical improvement on all primary outcomes (relative risk=2.75, P=.09). CONCLUSIONS: There is weak but equivocal evidence that the effects of homeopathic medicine are superior to placebo. Results also suggest that there may be nonspecific benefits from the homeopathic consultation. Further studies are needed to determine whether these differences hold in larger samples.

Nurses' views of using computerized decision support software in NHS Direct.

BACKGROUND: Nurses working in NHS Direct, the 24-hour telephone advice line in England, use computerized decision support software to recommend to callers the most appropriate service to contact, or to advise on self-care. AIMS: To explore nurses' views of their roles and the computerized decision support software in NHS Direct. METHODS: Qualitative analysis of semi-structured interviews with 24 NHS Direct nurses in 12 sites. FINDINGS: Nurses described both the software and themselves as essential to the clinical decision-making process. The software acted as safety net, provider of consistency, and provider of script, and was relied upon more when nurses did not have clinical knowledge relevant to the call. The nurse handled problems not covered by the software, probed patients for the appropriate information to enter into the software, and interpreted software recommendations in the light of contextual information which the software was unable to use. Nurses described a dual process of decision-making, with the nurse as active decision maker looking for consensus with the software recommendation and ready to override recommendations made by the software if necessary. However, nurses' accounts of the software as a guide, prompt or support did not fully acknowledge the power of the software, which they are required to use, and the recommendation of which they are required to follow under some management policies. Over time, the influence of nurse and software merges as nurses internalize the software script as their own knowledge, and navigate the software to produce recommendations that they feel are most appropriate. CONCLUSIONS: The nurse and the software have distinct roles in NHS Direct, although the effect of each on the clinical decision-making process may be difficult to determine in practice.