Background: The generalisability of randomized controlled trials (RCTs) can be uncertain because the impact of exclusion criteria is rarely quantified. The aim of this study was to systematically review studies examining the percentage of clinical populations with a physical health condition who would be excluded by RCTs of treatments for that condition. Methods: Medline and Embase were searched from inception to Feb 11th 2018. Two reviewers independently completed screening, full-text review, data extraction and risk-of-bias assessment. The primary outcome was the percentage of patients in the clinical population who would have been excluded from each examined trial. Subgroup analyses examined exclusion by population setting, publication date and funding source. Results: Titles/abstracts (20,754) were screened, and 50 studies were included which reported exclusion rates from 305 trials of treatments in 31 physical conditions. Estimated rates of exclusion from trials varied from 0% to 100%, and the median exclusion rate was 77.1% of patients (interquartile range 55.5% to 89.0% exclusion). Median exclusion rates for trials in common chronic conditions were high, including hypertension 83.0%, type 2 diabetes 81.7%, chronic obstructive pulmonary disease 84.3%, and asthma 96.0%. The most commonly applied exclusion criteria related to age, co-morbidity and co-prescribing, whereas more implicit criteria relating to life expectancy or functional status were not typically examined. There was no evidence that exclusion varied by the nature of the clinical population in which exclusion was evaluated or trial funding source. There was no statistically significant change in exclusion rates in more recent compared with older trials. Conclusions: The majority of trials of treatments for physical conditions examined excluded the majority of patients with the condition being treated. Almost a quarter of the trials studied excluded over 90% of patients, more than half of trials excluded at least three quarters of patients, and four out of five trials excluded at least half of patients. A limitation is that most studies applied only a subset of eligibility criteria, so exclusion rates are likely underestimated. Exclusion from trials of older people and people with co-morbidity and co-prescribing is increasingly untenable given population aging and increasing multimorbidity. Trial registration: PROSPERO registration CRD42016042282.
The use of online interventions for diabetes care is increasing, alongside a political drive toward e-health initiatives, 1 despite limited robust evidence relating to clinical outcomes. E-health is a term coined in the late 1990s to encompass convergence of the Internet and health care. The definition is constantly changing but generally covers user interaction with health data through online systems, cross transfer of data (often between institutions or systems) and user to user communication. Traditional users of e-health are health institution staff, but a new wave of e-health initiatives directed at patients brings exciting possibilities. 2More cost-effective diabetes management is needed, and technology could be key to care delivery and diabetes prevention. Around 8-9% of the global population has diabetes. Health expenditure for diabetes is increasing dramatically. The total health care costs of a person with diabetes in the United States are 2 to 3 times those for people without the condition. 4 In the United Kingdom, annual spending on diabetes is expected to reach 17% of the entire NHS budget over the next 20 years. 5Around 40% of the world population is now Internetconnected 6 rising to around 84% in higher economic countries, like the United Kingdom (2015). 7 Mobile phone and tablet use in the United Kingdom has increased from 30% in 2013 to 41% in 2014 7 associated with increased use of apps, remote monitors, fitness devices, and environmental sensors. 8,9 Health care system data quantity is also increasing exponentially, although it often remains in silos and its true potential thus never realized. Good data linkage and timely data availability to frontline health staff have the potential to transform care delivery. [10][11][12] This vision is highlighted in key political reports 13,14 making data and technology use in diabetes care a key priority. As informatics systems mature in their ability to connect and transform data, their outputs can become increasingly personalized, driving individualized support, advice and real-time decision making.This will become more apparent with the advent of the "Internet of Things" 15 opening up further linkages to community devices containing sensors and electronics. This forthcoming tsunami of health related data will move into the realm of genuine "big data," requiring "data science" approaches to (MDMW) is an award-wining national electronic personal health record and self-management platform for diabetes patients in Scotland. This platform links multiple national institutional and patient-recorded data sources to provide a unique resource for patient care and self-management. This review considers the current evidence for online interventions in diabetes and discusses these in the context of current and ongoing developments for MDMW. Evaluation of MDMW through patient reported outcomes demonstrates a positive impact on self-management. User feedback has highlighted barriers to uptake and has guided platform evolution from an education resource website to an...
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