Using e-mail recruitment and an online questionnaire to establish effect size: A worked example

Background\ud Sample size calculations require effect size estimations. Sometimes, effect size estimations and standard deviation may not be readily available, particularly if efficacy is unknown because the intervention is new or developing, or the trial targets a new population. In such cases, one way to estimate the effect size is to gather expert opinion. This paper reports the use of a simple strategy to gather expert opinion to estimate a suitable effect size to use in a sample size calculation.\ud \ud Methods\ud Researchers involved in the design and analysis of clinical trials were identified at the University of Birmingham and via the MRC Hubs for Trials Methodology Research. An email invited them to participate.\ud \ud An online questionnaire was developed using the free online tool 'Survey Monkey©'. The questionnaire described an intervention, an electronic participant information sheet (e-PIS), which may increase recruitment rates to a trial. Respondents were asked how much they would need to see recruitment rates increased by, based on 90%. 70%, 50% and 30% baseline rates, (in a hypothetical study) before they would consider using an e-PIS in their research.\ud \ud Analyses comprised simple descriptive statistics.\ud \ud Results\ud The invitation to participate was sent to 122 people; 7 responded to say they were not involved in trial design and could not complete the questionnaire, 64 attempted it, 26 failed to complete it. Thirty-eight people completed the questionnaire and were included in the analysis (response rate 33%; 38/115). Of those who completed the questionnaire 44.7% (17/38) were at the academic grade of research fellow 26.3% (10/38) senior research fellow, and 28.9% (11/38) professor. Dependent upon the baseline recruitment rates presented in the questionnaire, participants wanted recruitment rate to increase from 6.9% to 28.9% before they would consider using the intervention.\ud \ud Conclusions\ud This paper has shown that in situations where effect size estimations cannot be collected from previous research, opinions from researchers and trialists can be quickly and easily collected by conducting a simple study using email recruitment and an online questionnaire. The results collected from the survey were successfully used in sample size calculations for a PhD research study protocol.\ud \u

Accuracy of the discharge destination field in administrative data for identifying transfer to a long-term acute care hospital

<p>Abstract</p> <p>Background</p> <p>Long-term acute care hospitals (LTACs) provide specialized care for patients recovering from severe acute illness. In order to facilitate research into LTAC utilization and outcomes, we studied whether or not the discharge destination field in administrative data accurately identifies patients transferred to an LTAC following acute care hospitalization.</p> <p>Findings</p> <p>We used the 2006 hospitalization claims for United States Medicare beneficiaries to examine the performance characteristics of the discharge destination field in the administrative record, compared to the reference standard of directly observing LTAC transfers in the claims. We found that the discharge destination field was highly specific (99.7%, 95 percent CI: 99.7% - 99.8%) but modestly sensitive (77.3%, 95 percent CI: 77.0% - 77.6%), with corresponding low positive predictive value (72.6%, 95 percent CI: 72.3% - 72.9%) and high negative predictive value (99.8%, 95 percent CI: 99.8% - 99.8%). Sensitivity and specificity were similar when limiting the analysis to only intensive care unit patients and mechanically ventilated patients, two groups with higher rates of LTAC utilization. Performance characteristics were slightly better when limiting the analysis to Pennsylvania, a state with relatively high LTAC penetration.</p> <p>Conclusions</p> <p>The discharge destination field in administrative data can result in misclassification when used to identify patients transferred to long-term acute care hospitals. Directly observing transfers in the claims is the preferable method, although this approach is only feasible in identified data.</p

An innovative telemedicine knowledge translation program to improve quality of care in intensive care units: protocol for a cluster randomized pragmatic trial

Abstract Background There are challenges to timely adoption of, and ongoing adherence to, evidence-based practices known to improve patient care in the intensive care unit (ICU). Quality improvement initiatives using a collaborative network approach may increase the use of such practices. Our objective is to evaluate the effectiveness of a novel knowledge translation program for increasing the proportion of patients who appropriately receive the following six evidence-based care practices: venous thromboembolism prophylaxis; ventilator-associated pneumonia prevention; spontaneous breathing trials; catheter-related bloodstream infection prevention; decubitus ulcer prevention; and early enteral nutrition. Methods and design We will conduct a pragmatic cluster randomized active control trial in 15 community ICUs and one academic ICU in Ontario, Canada. The intervention is a multifaceted videoconferenced educational and problem-solving forum to organize knowledge translation strategies, including comparative audit and feedback, educational sessions from content experts, and dissemination of algorithms. Fifteen individual ICUs (clusters) will be randomized to receive quality improvement interventions targeting one of the best practices during each of six study phases. Each phase lasts four months during the first study year and three months during the second. At the end of each study phase, ICUs are assigned to an intervention for a best practice not yet received according to a random schedule. The primary analysis will use patient-level process-of-care data to measure the intervention's effect on rates of adoption and adherence of each best practice in the targeted ICU clusters versus controls. Discussion This study design evaluates a new system for knowledge translation and quality improvement across six common ICU problems. All participating ICUs receive quality improvement initiatives during every study phase, improving buy-in. This study design could be considered for other quality improvement interventions and in other care settings. Trial Registration This trial is registered with http://www.clinicaltrials.gov (ID #: NCT00332982

Evidence-based effect size estimation:An illustration using the case of acupuncture for cancer-related fatigue

<p>Abstract</p> <p>Background</p> <p>Estimating a realistic effect size is an important issue in the planning of clinical studies of complementary and alternative medicine therapies. When a minimally important difference is not available, researchers may estimate effect size using the published literature. This evidence-based effect size estimation may be used to produce a range of empirically-informed effect size and consequent sample size estimates. We provide an illustration of deriving plausible effect size ranges for a study of acupuncture in the relief of post-chemotherapy fatigue in breast cancer patients.</p> <p>Methods</p> <p>A PubMed search identified three uncontrolled studies reporting the effect of acupuncture in relieving fatigue. A separate search identified five randomized controlled trials (RCTs) with a wait-list control of breast cancer patients receiving standard care that reported data on fatigue. We use these published data to produce best, average, and worst-case effect size estimates and related sample size estimates for a trial of acupuncture in the relief of cancer-related fatigue relative to a wait-list control receiving standard care.</p> <p>Results</p> <p>Use of evidence-based effect size estimation to calculate sample size requirements for a study of acupuncture in relieving fatigue in breast cancer survivors relative to a wait-list control receiving standard care suggests that an adequately-powered phase III randomized controlled trial comprised of two arms would require at least 101 subjects (52 per arm) if a strong effect is assumed for acupuncture and 235 (118 per arm) if a moderate effect is assumed.</p> <p>Conclusion</p> <p>Evidence-based effect size estimation helps justify assumptions in light of empirical evidence and can lead to more realistic sample size calculations, an outcome that would be of great benefit for the field of complementary and alternative medicine.</p

A knowledge translation collaborative to improve the use of therapeutic hypothermia in post-cardiac arrest patients: protocol for a stepped wedge randomized trial

<p>Abstract</p> <p>Background</p> <p>Advances in resuscitation science have dramatically improved survival rates following cardiac arrest. However, about 60% of adults that regain spontaneous circulation die before leaving the hospital. Recently it has been shown that inducing hypothermia in cardiac arrest survivors immediately following their arrival in hospital can dramatically improve both overall survival and neurological outcomes. Despite the strong evidence for its efficacy and the apparent simplicity of this intervention, recent surveys show that therapeutic hypothermia is delivered inconsistently, incompletely, and often with delay.</p> <p>Methods and design</p> <p>This study will evaluate a multi-faceted knowledge translation strategy designed to increase the utilization rate of induced hypothermia in survivors of cardiac arrest across a network of 37 hospitals in Southwestern Ontario, Canada. The study is designed as a stepped wedge randomized trial lasting two years. Individual hospitals will be randomly assigned to four different wedges that will receive the active knowledge translation strategy according to a sequential rollout over a number of time periods. By the end of the study, all hospitals will have received the intervention. The primary aim is to measure the effectiveness of a multifaceted knowledge translation plan involving education, reminders, and audit-feedback for improving the use of induced hypothermia in survivors of cardiac arrest presenting to the emergency department. The primary outcome is the proportion of eligible OHCA patients that are cooled to a body temperature of 32 to 34°C within six hours of arrival in the hospital. Secondary outcomes will include process of care measures and clinical outcomes.</p> <p>Discussion</p> <p>Inducing hypothermia in cardiac arrest survivors immediately following their arrival to hospital has been shown to dramatically improve both overall survival and neurological outcomes. However, this lifesaving treatment is frequently not applied in practice. If this trial is positive, our results will have broad implications by showing that a knowledge translation strategy shared across a collaborative network of hospitals can increase the number of patients that receive this lifesaving intervention in a timely manner.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov Trial Identifier: <a href="http://www.clinicaltrials.gov/ct2/show/NCT00683683">NCT00683683</a></p

Randomized Controlled Trials of HIV/AIDS Prevention and Treatment in Africa: Results from the Cochrane HIV/AIDS Specialized Register

INTRODUCTION: To effectively address HIV/AIDS in Africa, evidence on preventing new infections and providing effective treatment is needed. Ideally, decisions on which interventions are effective should be based on evidence from randomized controlled trials (RCTs). Our previous research described African RCTs of HIV/AIDS reported between 1987 and 2003. This study updates that analysis with RCTs published between 2004 and 2008. OBJECTIVES: To describe RCTs of HIV/AIDS conducted in Africa and reported between 2004 and 2008. METHODS: We searched the Cochrane HIV/AIDS Specialized Register in September 2009. Two researchers independently evaluated studies for inclusion and extracted data using standardized forms. Details included location of trials, interventions, methodological quality, location of principal investigators and funders. RESULTS: Our search identified 834 RCTs, with 68 conducted in Africa. Forty-three assessed prevention-interventions and 25 treatment-interventions. Fifteen of the 43 prevention RCTs focused on preventing mother-to-child HIV transmission. Thirteen of the 25 treatment trials focused on opportunistic infections. Trials were conducted in 16 countries with most in South Africa (20), Zambia (12) and Zimbabwe (9). The median sample size was 628 (range 33-9645). Methods used for the generation of the allocation sequence and allocation concealment were adequate in 38 and 32 trials, respectively, and 58 reports included a CONSORT recommended flow diagram. Twenty-nine principal investigators resided in the United States of America (USA) and 18 were from African countries. Trials were co-funded by different agencies with most of the funding obtained from USA governmental and non-governmental agencies. Nineteen pharmaceutical companies provided partial funding to 15 RCTs and African agencies co-funded 17 RCTs. Ethical approval was reported in 65 trials and informed consent in 61 trials. CONCLUSION: Prevention trials dominate the trial landscape in Africa. Of note, few principal investigators and funders are from Africa. These findings mirror our previous work and continue to indicate a need for strengthening trial research capacity in Africa

Risk Factors for SARS Transmission from Patients Requiring Intubation: A Multicentre Investigation in Toronto, Canada

In the 2003 Toronto SARS outbreak, SARS-CoV was transmitted in hospitals despite adherence to infection control procedures. Considerable controversy resulted regarding which procedures and behaviours were associated with the greatest risk of SARS-CoV transmission.A retrospective cohort study was conducted to identify risk factors for transmission of SARS-CoV during intubation from laboratory confirmed SARS patients to HCWs involved in their care. All SARS patients requiring intubation during the Toronto outbreak were identified. All HCWs who provided care to intubated SARS patients during treatment or transportation and who entered a patient room or had direct patient contact from 24 hours before to 4 hours after intubation were eligible for this study. Data was collected on patients by chart review and on HCWs by interviewer-administered questionnaire. Generalized estimating equation (GEE) logistic regression models and classification and regression trees (CART) were used to identify risk factors for SARS transmission. ratio ≤59 (OR = 8.65, p = .001) were associated with increased risk of transmission of SARS-CoV. In CART analyses, the four covariates which explained the greatest amount of variation in SARS-CoV transmission were covariates representing individual patients.Close contact with the airway of severely ill patients and failure of infection control practices to prevent exposure to respiratory secretions were associated with transmission of SARS-CoV. Rates of transmission of SARS-CoV varied widely among patients