Using an electronic medical record (EMR) to conduct clinical trials: Salford Lung Study feasibility

A Sustainable Approach to Asthma Diagnosis: Classification with Data Augmentation, Feature Selection, and Boosting Algorithm

Asthma is a diverse disease that affects over 300 million individuals globally. The prevalence of asthma has increased by 50% every decade since the 1960s, making it a serious global health issue. In addition to its associated high mortality, asthma generates large economic losses due to the degradation of patients' quality of life and the impairment of their physical fitness. Asthma research has evolved in recent years to fully analyze why certain diseases develop based on a variety of data and observations of patients' performance. The advent of new techniques offers good opportunities and application prospects for the development of asthma diagnosis methods. Over the last few decades, techniques like data mining and machine learning have been utilized to diagnose asthma. Nevertheless, these traditional methods are unable to address all of the difficulties associated with improving a small dataset to increase its quantity, quality, and feature space complexity at the same time. In this study, we propose a sustainable approach to asthma diagnosis using advanced machine learning techniques. To be more specific, we use feature selection to find the most important features, data augmentation to improve the dataset's resilience, and the extreme gradient boosting algorithm for classification. Data augmentation in the proposed method involves generating synthetic samples to increase the size of the training dataset, which is then utilized to enhance the training data initially. This could lessen the phenomenon of imbalanced data related to asthma. Then, to improve diagnosis accuracy and prioritize significant features, the extreme gradient boosting technique is used. The outcomes indicate that the proposed approach performs better in terms of diagnostic accuracy than current techniques. Furthermore, five essential features are extracted to help physicians diagnose asthma.

An Observational Retrospective Matched Cohort Study of Healthcare Resource Utilisation and Costs in UK Patients with Moderate to Severe Osteoarthritis Pain

Introduction

Using data from patients residing in Salford, UK, we aimed to compare healthcare resource utilisation (HCRU) and direct healthcare costs between patients with moderate to severe (M-S) or severe osteoarthritis (OA) pain and those without OA.

Methods

Patients with a M-S OA pain event within a period of chronic pain were indexed from the Salford Integrated Record (SIR) between 2010 and 2017. Patients with a severe pain event formed an OA subcohort. Patients in each OA pain cohort were independently matched to patients without OA, forming two control cohorts. HCRU, prescribed analgesic drugs, and total direct costs per UK standardised tariffs were calculated for the year post-index. Multivariable models were used to identify drivers of healthcare cost.

Results

The M-S OA pain and control cohorts each comprised 3123 patients; the severe OA pain and control cohorts each comprised 1922 patients. Patients in both OA pain cohorts had a significantly higher mean number of general practitioner encounters, inpatient, outpatient, and accident and emergency visits, and were prescribed a broader range of analgesic drugs in the year post-index than respective controls. Mean healthcare costs of all types were significantly higher in the M-S and severe OA pain cohorts vs controls (total: M-S £2519 vs £1379; severe £3389 vs £1397). Paracetamol (M-S: 40% of patients had at least one prescription; severe: 50%) and strong opioids (34% and 59%) were the analgesics most prescribed to patients with OA pain. In all cohorts, multivariable models showed that a higher age at index, the presence of gout, osteoporosis, type 2 diabetes, or coronary artery disease, significantly contributed towards higher healthcare costs.

Conclusion

In the population of Salford, UK, patients with M-S OA pain had significantly higher annual HCRU and costs compared with matched controls without OA; generally, these were even higher in patients with severe OA pain.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40744-022-00431-2.

Primary care perspectives on implementation of clinical trial recruitment

Introduction:

Poor clinical trial (CT) recruitment is a significant barrier to translating basic science discoveries into medical practice. Improving support for primary care provider (PCP) referral of patients to CTs may be an important part of the solution. However, implementing CT referral support in primary care is not only technically challenging, but also presents challenges at the person and organization levels.

Methods:

The objectives of this study were (1) to characterize provider and clinical supervisor attitudes and perceptions regarding CT research, recruitment, and referrals in primary care and (2) to identify perceived workflow strategies and facilitators relevant to designing a technology-supported primary care CT referral program. Focus groups were conducted with PCPs, directors, and supervisors.

Results:

Analysis indicated widespread support for the intrinsic scientific value of CTs, while at the same time deep concerns regarding protecting patient well-being, perceived loss of control when patients participate in trials, concern about the impact of point-of-care referrals on clinic workflow, the need for standard processes, and the need for CT information that enables referring providers to quickly confirm that the burdens are justified by the benefits at both patient and provider levels. PCP suggestions pertinent to implementing a CT referral decision support system are reported.

Conclusion:

The results from this work contribute to developing an implementation approach to support increased referral of patients to CTs.

Working together to deliver stratified medicine research effectively

INTRODUCTION OR BACKGROUND

Stratified medicine is an important area of research across all clinical specialties, with far reaching impact in many spheres. Despite recently formulated global policy and research programmes, major challenges for delivering stratified medicine studies persist. Across the globe, clinical research infrastructures have been setup to facilitate high quality clinical research.

SOURCES OF DATA

This article reviews the literature and summarizes views collated from a workshop held by the UK Pharmacogenetics and Stratified Medicine Network and the NIHR Clinical Research Network in November 2016.

AREAS OF AGREEMENT

Stratified medicine is an important area of clinical research and health policy, benefitting from substantial international, cross-sector investment and has the potential to transform patient care. However there are significant challenges to the delivery of stratified medicine studies.

AREAS OF CONTROVERSY

Complex methodology and lack of consistency of definition and agreement on key approaches to the design, regulation and delivery of research contribute to these challenges and would benefit from greater focus.

GROWING POINTS

Effective partnership and development of consistent approaches to the key factors relating to stratified medicine research is required to help overcome these challenges.

AREAS TIMELY FOR DEVELOPING RESEARCH

This paper examines the critical contribution clinical research networks can make to the delivery of national (and international) initiatives in the field of stratified medicine. Importantly, it examines the position of clinical research in stratified medicine at a time when pressures on the clinical and social services are mounting.

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.

Accrual to Clinical Trials (ACT): A Clinical and Translational Science Award Consortium Network

The Accrual to Clinical Trials (ACT) network is a federated network of sites from the National Clinical and Translational Science Award (CTSA) Consortium that has been created to significantly increase participant accrual to multi-site clinical trials. The ACT network represents an unprecedented collaboration among diverse CTSA sites. The network has created governance and regulatory frameworks and a common data model to harmonize electronic health record (EHR) data, and deployed a set of Informatics for Integrating Biology and the Bedside (i2b2) data repositories that are linked by the Shared Health Research Information Network (SHRINE) platform. It provides investigators the ability to query the network in real time and to obtain aggregate counts of patients who meet clinical trial inclusion and exclusion criteria from sites across the United States. The ACT network infrastructure provides a basis for cohort discovery and for developing new informatics tools to identify and recruit participants for multi-site clinical trials.

Long term extension of a randomised controlled trial of probiotics using electronic health records

Most randomised controlled trials (RCTs) are relatively short term and, due to costs and available resources, have limited opportunity to be re-visited or extended. There is no guarantee that effects of treatments remain unchanged beyond the study. Here, we illustrate the feasibility, benefits and cost-effectiveness of enriching standard trial design with electronic follow up. We completed a 5-year electronic follow up of a RCT investigating the impact of probiotics on asthma and eczema in children born 2005–2007, with traditional fieldwork follow up to two years. Participants and trial outcomes were identified and analysed after five years using secure, routine, anonymised, person-based electronic health service databanks. At two years, we identified 93% of participants and compared fieldwork with electronic health records, highlighting areas of agreement and disagreement. Retention of children from lower socio-economic groups was improved, reducing volunteer bias. At 5 years we identified a reduced 82% of participants. These data allowed the trial’s first robust analysis of asthma endpoints. We found no indication that probiotic supplementation to pregnant mothers and infants protected against asthma or eczema at 5 years. Continued longer-term follow up is technically straightforward.

Big data from electronic health records for early and late translational cardiovascular research: challenges and potential

Aims

Cohorts of millions of people's health records, whole genome sequencing, imaging, sensor, societal and publicly available data present a rapidly expanding digital trace of health. We aimed to critically review, for the first time, the challenges and potential of big data across early and late stages of translational cardiovascular disease research.

Methods and results

We sought exemplars based on literature reviews and expertise across the BigData@Heart Consortium. We identified formidable challenges including: data quality, knowing what data exist, the legal and ethical framework for their use, data sharing, building and maintaining public trust, developing standards for defining disease, developing tools for scalable, replicable science and equipping the clinical and scientific work force with new inter-disciplinary skills. Opportunities claimed for big health record data include: richer profiles of health and disease from birth to death and from the molecular to the societal scale; accelerated understanding of disease causation and progression, discovery of new mechanisms and treatment-relevant disease sub-phenotypes, understanding health and diseases in whole populations and whole health systems and returning actionable feedback loops to improve (and potentially disrupt) existing models of research and care, with greater efficiency. In early translational research we identified exemplars including: discovery of fundamental biological processes e.g. linking exome sequences to lifelong electronic health records (EHR) (e.g. human knockout experiments); drug development: genomic approaches to drug target validation; precision medicine: e.g. DNA integrated into hospital EHR for pre-emptive pharmacogenomics. In late translational research we identified exemplars including: learning health systems with outcome trials integrated into clinical care; citizen driven health with 24/7 multi-parameter patient monitoring to improve outcomes and population-based linkages of multiple EHR sources for higher resolution clinical epidemiology and public health.

Conclusion

High volumes of inherently diverse ('big') EHR data are beginning to disrupt the nature of cardiovascular research and care. Such big data have the potential to improve our understanding of disease causation and classification relevant for early translation and to contribute actionable analytics to improve health and healthcare.

A Novel Screening Method to Identify Late-Stage Dementia Patients for Palliative Care Research and Practice

CONTEXT

Investigators need novel methods for timely identification of patients with serious illness to test or implement new palliative care models.

OBJECTIVES

The study's aim was to develop an electronic health record (EHR) phenotype to identify patients with late-stage dementia for a clinical trial of palliative care consultation.

METHODS

We developed a computerized method to identify patients with dementia on hospital admission. Within a data warehouse derived from the hospital's EHR, we used search terms of age, admission date, and ICD-9 and ICD-10 diagnosis codes to create an EHR dementia phenotype, followed by brief medical record review to confirm late-stage dementia. We calculated positive predictive value, false discovery rate, and false negative rate of this novel screening method.

RESULTS

The EHR phenotype screening method had a positive predictive value of 76.3% for dementia patients and 24.5% for late-stage dementia patients; a false discovery rate of 23.7% for dementia patients and 75.5% for late-stage dementia patients compared to physician assessment. The sensitivity of this screening method was 59.7% to identify hospitalized patients with dementia. Daily screening-including confirmatory chart reviews-averaged 20 minutes and was more feasible, efficient, and more complete than manual screening.

CONCLUSION

A novel method using an EHR phenotype plus brief medical record review is effective to identify hospitalized patients with late-stage dementia. In health care systems with similar clinical data warehouses, this method may be applied to serious illness populations to improve enrollment in clinical trials of palliative care or to facilitate access to palliative care services.

Digital Care in Epilepsy: A Conceptual Framework for Technological Therapies

Epilepsy is associated with a significant increase in morbidity and mortality. The likelihood is significantly greater for those patients with specific risk factors. Identifying those at greatest risk of injury and providing expert management from the earliest opportunity is made more challenging by the circumstances in which many such patients present. Despite increasing recognition of the importance of earlier identification of those at risk, there is little or no improvement in outcomes over more than 30 years. Despite ever increasing sophistication of drug development and delivery, there has been no meaningful improvement in 1-year seizure freedom rates over this time. However, in the last few years, there has been an increase in patient-triggered interventions based on automated monitoring of indicators and risk factors facilitated by technological advances. The opportunities such approaches provide will only be realized if accompanied by current working practice changes. Replacing traditional follow-up appointments at arbitrary intervals with dynamic interventions, remotely and at the point and place of need provides a better chance of a substantial reduction in seizures for people with epilepsy. Properly implemented, electronic platforms can offer new opportunities to provide expert advice and management from first presentation thus improving outcomes. This perspective paper provides and proposes an informed critical opinion built on current evidence base of an outline techno-therapeutic approach to harnesses these technologies. This conceptual framework is generic, rather than tied to a specific product or solution, and the same generalized approach could be beneficially applied to other long-term conditions.

Validation of an algorithm that determines stroke diagnostic code accuracy in a Japanese hospital-based cancer registry using electronic medical records

BACKGROUND

This study aimed to validate an algorithm that determines stroke diagnostic code accuracy, in a hospital-based cancer registry, using electronic medical records (EMRs) in Japan.

METHODS

The subjects were 27,932 patients enrolled in the hospital-based cancer registry of Osaka University Hospital, between January 1, 2007 and December 31, 2015. The ICD-10 (international classification of diseases, 10th revision) diagnostic codes for stroke were extracted from the EMR database. Specifically, subarachnoid hemorrhage (I60); intracerebral hemorrhage (I61); cerebral infarction (I63); and other transient cerebral ischemic attacks and related syndromes and transient cerebral ischemic attack (unspecified) (G458 and G459), respectively. Diagnostic codes, both "definite" and "suspected," and brain imaging information were extracted from the database. We set the algorithm with the combination of the diagnostic code and/or the brain imaging information, and manually reviewed the presence or absence of the acute cerebrovascular disease with medical charts.

RESULTS

A total of 2654 diagnostic codes, 1991 "definite" and 663 "suspected," were identified. After excluding duplicates, the numbers of "definite" and "suspected" diagnostic codes were 912 and 228, respectively. The proportion of the presence of the disease in the "definite" diagnostic code was 22%; this raised 51% with the combination of the diagnostic code and the use of brain imaging information. When adding the interval of when brain imaging was performed (within 30 days and within 1 day) to the diagnostic code, the proportion increased to 84% and 90%, respectively. In the algorithm of "definite" diagnostic code, history of stroke was the most common in the diagnostic code, but in the algorithm of "definite" diagnostic code and the use of brain imaging within 1 day, stroke mimics was the most frequent.

CONCLUSIONS

Combining the diagnostic code and clinical examination improved the proportion of the presence of disease in the diagnostic code and achieved appropriate accuracy for research. Clinical research using EMRs require outcome validation prior to conducting a study.

Factors influencing the development of primary care data collection projects from electronic health records: a systematic review of the literature

BACKGROUND

Primary care data gathered from Electronic Health Records are of the utmost interest considering the essential role of general practitioners (GPs) as coordinators of patient care. These data represent the synthesis of the patient history and also give a comprehensive picture of the population health status. Nevertheless, discrepancies between countries exist concerning routine data collection projects. Therefore, we wanted to identify elements that influence the development and durability of such projects.

METHODS

A systematic review was conducted using the PubMed database to identify worldwide current primary care data collection projects. The gray literature was also searched via official project websites and their contact person was emailed to obtain information on the project managers. Data were retrieved from the included studies using a standardized form, screening four aspects: projects features, technological infrastructure, GPs' roles, data collection network organization.

RESULTS

The literature search allowed identifying 36 routine data collection networks, mostly in English-speaking countries: CPRD and THIN in the United Kingdom, the Veterans Health Administration project in the United States, EMRALD and CPCSSN in Canada. These projects had in common the use of technical facilities that range from extraction tools to comprehensive computing platforms. Moreover, GPs initiated the extraction process and benefited from incentives for their participation. Finally, analysis of the literature data highlighted that governmental services, academic institutions, including departments of general practice, and software companies, are pivotal for the promotion and durability of primary care data collection projects.

CONCLUSION

Solid technical facilities and strong academic and governmental support are required for promoting and supporting long-term and wide-range primary care data collection projects.

The Salford Lung Study: a pioneering comparative effectiveness approach to COPD and asthma in clinical trials

The Salford Lung Study (SLS) of patients with asthma and chronic obstructive pulmonary disease (COPD) is a practical, community-based, randomized, open-label pragmatic study on the efficacy and safety of the once-daily dry powder inhaler that combines the inhaled corticosteroid fluticasone furoate (FF) with the long-acting beta₂ agonist vilanterol (VI). The asthma component of the SLS is not yet reported but the COPD component, done over a 12-month period, found a statistically significant 8.4% reduction in COPD exacerbations when compared to usual care. No differences in adverse events, including serious adverse events and pneumonia, were noted. The importance of real-world findings, such as those found in the SLS COPD trial with inhaled FF/VI, is discussed in comparison to classical randomized controlled trials (RCTs) with inhaled FF/VI in COPD patients. The real-world, community-based pragmatic RCT like the SLS provides additional generalizable data with direct clinical applicability and potential usefulness in the development of practice guidelines. The results from the SLS, along with those of large and small RCTs, are supportive of the use of once-daily FF/VI in COPD maintenance therapy.

Clinical Research Informatics: Supporting the Research Study Lifecycle

Objectives: The primary goal of this review is to summarize significant developments in the field of Clinical Research Informatics (CRI) over the years 2015-2016. The secondary goal is to contribute to a deeper understanding of CRI as a field, through the development of a strategy for searching and classifying CRI publications. Methods: A search strategy was developed to query the PubMed database, using medical subject headings to both select and exclude articles, and filtering publications by date and other characteristics. A manual review classified publications using stages in the "research study lifecycle", with key stages that include study definition, participant enrollment, data management, data analysis, and results dissemination. Results: The search strategy generated 510 publications. The manual classification identified 125 publications as relevant to CRI, which were classified into seven different stages of the research lifecycle, and one additional class that pertained to multiple stages, referring to general infrastructure or standards. Important cross-cutting themes included new applications of electronic media (Internet, social media, mobile devices), standardization of data and procedures, and increased automation through the use of data mining and big data methods. Conclusions: The review revealed increased interest and support for CRI in large-scale projects across institutions, regionally, nationally, and internationally. A search strategy based on medical subject headings can find many relevant papers, but a large number of non-relevant papers need to be detected using text words which pertain to closely related fields such as computational statistics and clinical informatics. The research lifecycle was useful as a classification scheme by highlighting the relevance to the users of clinical research informatics solutions.

Monitoring safety in a phase III real-world effectiveness trial: use of novel methodology in the Salford Lung Study

Background

The Salford Lung Study (SLS) programme, encompassing two phase III pragmatic randomised controlled trials, was designed to generate evidence on the effectiveness of a once‐daily treatment for asthma and chronic obstructive pulmonary disease in routine primary care using electronic health records.

Objective

The objective of this study was to describe and discuss the safety monitoring methodology and the challenges associated with ensuring patient safety in the SLS. Refinements to safety monitoring processes and infrastructure are also discussed. The study results are outside the remit of this paper. The results of the COPD study were published recently and a more in‐depth exploration of the safety results will be the subject of future publications.

Achievements

The SLS used a linked database system to capture relevant data from primary care practices in Salford and South Manchester, two university hospitals and other national databases. Patient data were collated and analysed to create daily summaries that were used to alert a specialist safety team to potential safety events. Clinical research teams at participating general practitioner sites and pharmacies also captured safety events during routine consultations. Confidence in the safety monitoring processes over time allowed the methodology to be refined and streamlined without compromising patient safety or the timely collection of data. The information technology infrastructure also allowed additional details of safety information to be collected.

Conclusion

Integration of multiple data sources in the SLS may provide more comprehensive safety information than usually collected in standard randomised controlled trials. Application of the principles of safety monitoring methodology from the SLS could facilitate safety monitoring processes for future pragmatic randomised controlled trials and yield important complementary safety and effectiveness data. © 2016 The Authors Pharmacoepidemiology and Drug Safety Published by John Wiley & Sons Ltd.

Effectiveness of Fluticasone Furoate-Vilanterol for COPD in Clinical Practice

BACKGROUND

Evidence for the management of chronic obstructive pulmonary disease (COPD) comes from closely monitored efficacy trials involving groups of patients who were selected on the basis of restricted entry criteria. There is a need for randomized trials to be conducted in conditions that are closer to usual clinical practice.

METHODS

In a controlled effectiveness trial conducted in 75 general practices, we randomly assigned 2799 patients with COPD to a once-daily inhaled combination of fluticasone furoate at a dose of 100 μg and vilanterol at a dose of 25 μg (the fluticasone furoate-vilanterol group) or to usual care (the usual-care group). The primary outcome was the rate of moderate or severe exacerbations among patients who had had an exacerbation within 1 year before the trial. Secondary outcomes were the rates of primary care contact (contact with a general practitioner, nurse, or other health care professional) and secondary care contact (inpatient admission, outpatient visit with a specialist, or visit to the emergency department), modification of the initial trial treatment for COPD, and the rate of exacerbations among patients who had had an exacerbation within 3 years before the trial, as assessed in a time-to-event analysis.

RESULTS

The rate of moderate or severe exacerbations was significantly lower, by 8.4% (95% confidence interval, 1.1 to 15.2), with fluticasone furoate-vilanterol therapy than with usual care (P=0.02). There was no significant difference in the annual rate of COPD-related contacts to primary or secondary care. There were no significant between-group differences in the rates of the first moderate or severe exacerbation and the first severe exacerbation in the time-to-event analyses. There were no excess serious adverse events of pneumonia in the fluticasone furoate-vilanterol group. The numbers of other serious adverse events were similar in the two groups.

CONCLUSIONS

In patients with COPD and a history of exacerbations, a once-daily treatment regimen of combined fluticasone furoate and vilanterol was associated with a lower rate of exacerbations than usual care, without a greater risk of serious adverse events. (Funded by GlaxoSmithKline; Salford Lung Study ClinicalTrials.gov number, NCT01551758 .).

Abstracting ICU Nursing Care Quality Data From the Electronic Health Record

The electronic health record is a potentially rich source of data for clinical research in the intensive care unit setting. We describe the iterative, multi-step process used to develop and test a data abstraction tool, used for collection of nursing care quality indicators from the electronic health record, for a pragmatic trial. We computed Cohen's kappa coefficient (κ) to assess interrater agreement or reliability of data abstracted using preliminary and finalized tools. In assessing the reliability of study data ( n = 1,440 cases) using the finalized tool, 108 randomly selected cases (10% of first half sample; 5% of last half sample) were independently abstracted by a second rater. We demonstrated mean κ values ranging from 0.61 to 0.99 for all indicators. Nursing care quality data can be accurately and reliably abstracted from the electronic health records of intensive care unit patients using a well-developed data collection tool and detailed training.

Smart Technology in Lung Disease Clinical Trials

This article describes the use of smart technology by investigators and patients to facilitate lung disease clinical trials and make them less costly and more efficient. By "smart technology" we include various electronic media, such as computer databases, the Internet, and mobile devices. We first describe the use of electronic health records for identifying potential subjects and then discuss electronic informed consent. We give several examples of using the Internet and mobile technology in clinical trials. Interventions have been delivered via the World Wide Web or via mobile devices, and both have been used to collect outcome data. We discuss examples of new electronic devices that recently have been introduced to collect health data. While use of smart technology in clinical trials is an exciting development, comparison with similar interventions applied in a conventional manner is still in its infancy. We discuss advantages and disadvantages of using this omnipresent, powerful tool in clinical trials, as well as directions for future research.

Designing and incorporating a real world data approach to international drug development and use: what the UK offers

Assessments of the safety, efficacy and appropriate use of new medicines lie at the heart of treatment development and subsequent adoption in clinical practice. Highly controlled randomised clinical trials routinely inform decisions on the approval, coverage and use of a medicine. Researchers and decision makers have become increasingly aware that these experimental data alone are insufficient to address those decisions fully. Real world data recorded from routine healthcare delivery by healthcare professionals and patients help provide a more complete picture of care. The UK, with its connectivity and rich longitudinal patient records, accumulated research and informatics experience and National Health Service, provides an exemplar of how real world data address a wide range of challenges across drug development.

The Salford Lung Study protocol: a pragmatic, randomised phase III real-world effectiveness trial in chronic obstructive pulmonary disease

Background

New treatments need to be evaluated in real-world clinical practice to account for co-morbidities, adherence and polypharmacy.

Methods

Patients with chronic obstructive pulmonary disease (COPD), ≥40 years old, with exacerbation in the previous 3 years are randomised 1:1 to once-daily fluticasone furoate 100 μg/vilanterol 25 μg in a novel dry-powder inhaler versus continuing their existing therapy. The primary endpoint is the mean annual rate of COPD exacerbations; an electronic medical record allows real-time collection and monitoring of endpoint and safety data.

Conclusions

The Salford Lung Study is the world’s first pragmatic randomised controlled trial of a pre-licensed medication in COPD.

Trial registration

Clinicaltrials.gov identifier NCT01551758.