Preliminary results from the COPE study using primary-care electronic health records and environmental modelling to examine COPD exacerbations

2018 ◽  
Vol 68 (suppl 1) ◽  
pp. bjgp18X696749 ◽  
Author(s):  
Maimoona Hashmi ◽  
Mark Wright ◽  
Kirin Sultana ◽  
Benjamin Barratt ◽  
Lia Chatzidiakou ◽  
...  
Keyword(s):  
Primary Care ◽  
Electronic Health Records ◽  
Health Management ◽  
Practice Research ◽  
Chronic Obstructive ◽  
Clinical Practice Research Datalink ◽  
Health Records ◽  
Preliminary Results ◽  
Copd Exacerbations ◽  
Electronic Health

BackgroundChronic Obstructive Airway Disease (COPD) is marked by often severely debilitating exacerbations. Efficient patient-centric research approaches are needed to better inform health management primary-care.AimThe ‘COPE study’ aims to develop a method of predicting COPD exacerbations utilising personal air quality sensors, environmental exposure modelling and electronic health records through the recruitment of patients from consenting GPs contributing to the Clinical Practice Research Datalink (CPRD).MethodThe study made use of Electronic Healthcare Records (EHR) from CPRD, an anonymised GP records database to screen and locate patients within GP practices in Central London. Personal air monitors were used to capture data on individual activities and environmental exposures. Output from the monitors were then linked with the EHR data to obtain information on COPD management, severity, comorbidities and exacerbations. Symptom changes not equating to full exacerbations were captured on diary cards. Linear regression was used to investigate the relationship between subject peak flow, symptoms, exacerbation events and exposure data.ResultsPreliminary results on the first 80 patients who have completed the study indicate variable susceptibility to environmental stressors in COPD patients. Some individuals appear highly susceptible to environmental stress and others appear to have unrelated triggers.ConclusionRecruiting patients through EHR for a study is feasible and allows easy collection of data for long term follow up. Portable environmental sensors could now be used to develop personalised models to predict risk of COPD exacerbations in susceptible individuals. Identification of direct links between participant health and activities would allow improved health management thus cost savings.

scholarly journals Childhood obesity trends from primary care electronic health records in England between 1994 and 2013: population-based cohort study

2015 ◽  
Vol 100 (3) ◽  
pp. 214-219 ◽  
Author(s):  
Cornelia H M van Jaarsveld ◽  
Martin C Gulliford
Keyword(s):  
Primary Care ◽  
Cohort Study ◽  
Electronic Health Records ◽  
Age Groups ◽  
Overweight And Obesity ◽  
Practice Research ◽  
Clinical Practice Research Datalink ◽  
Health Records ◽  
Obesity Trends ◽  
Electronic Health

ObjectiveThis study aimed to use primary care electronic health records to evaluate the prevalence of overweight and obesity in 2–15-year-old children in England and compare trends over the last two decades.DesignCohort study of primary care electronic health records.Setting375 general practices in England that contribute to the UK Clinical Practice Research Datalink.PatientsIndividual participants were sampled if they were aged between 2 and 15 years during the period 1994–2013 and had one or more records of body mass index (BMI).Main outcome measurePrevalence of overweight (including obesity) was defined as a BMI equal to or greater than the 85th centile of the 1990 UK reference population.ResultsData were analysed for 370 544 children with 507 483 BMI records. From 1994 to 2003, the odds of overweight and obesity increased by 8.1% per year (95% CI 7.2% to 8.9%) compared with 0.4% (−0.2% to 1.1%) from 2004 to 2013. Trends were similar for boys and girls, but differed by age groups, with prevalence stabilising in 2004 to 2013 in the younger (2–10 year) but not older (11–15 year) age group, where rates continued to increase.ConclusionsPrimary care electronic health records in England may provide a valuable resource for monitoring obesity trends. More than a third of UK children are overweight or obese, but the prevalence of overweight and obesity may have stabilised between 2004 and 2013.

scholarly journals Data-driven identification of ageing-related diseases from electronic health records

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Valerie Kuan ◽  
Helen C. Fraser ◽  
Melanie Hingorani ◽  
Spiros Denaxas ◽  
Arturo Gonzalez-Izquierdo ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
Clustering Algorithm ◽  
Age Of Onset ◽  
Disease Onset ◽  
Practice Research ◽  
Clinical Practice Research Datalink ◽  
Agglomerative Clustering ◽  
Health Records ◽  
Organ Systems ◽  
Electronic Health

AbstractReducing the burden of late-life morbidity requires an understanding of the mechanisms of ageing-related diseases (ARDs), defined as diseases that accumulate with increasing age. This has been hampered by the lack of formal criteria to identify ARDs. Here, we present a framework to identify ARDs using two complementary methods consisting of unsupervised machine learning and actuarial techniques, which we applied to electronic health records (EHRs) from 3,009,048 individuals in England using primary care data from the Clinical Practice Research Datalink (CPRD) linked to the Hospital Episode Statistics admitted patient care dataset between 1 April 2010 and 31 March 2015 (mean age 49.7 years (s.d. 18.6), 51% female, 70% white ethnicity). We grouped 278 high-burden diseases into nine main clusters according to their patterns of disease onset, using a hierarchical agglomerative clustering algorithm. Four of these clusters, encompassing 207 diseases spanning diverse organ systems and clinical specialties, had rates of disease onset that clearly increased with chronological age. However, the ages of onset for these four clusters were strikingly different, with median age of onset 82 years (IQR 82–83) for Cluster 1, 77 years (IQR 75–77) for Cluster 2, 69 years (IQR 66–71) for Cluster 3 and 57 years (IQR 54–59) for Cluster 4. Fitting to ageing-related actuarial models confirmed that the vast majority of these 207 diseases had a high probability of being ageing-related. Cardiovascular diseases and cancers were highly represented, while benign neoplastic, skin and psychiatric conditions were largely absent from the four ageing-related clusters. Our framework identifies and clusters ARDs and can form the basis for fundamental and translational research into ageing pathways.

scholarly journals Using electronic health records to inform trial feasibility in a rare autoimmune blistering skin disease in England

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
M. S. M. Persson ◽  
K. E. Harman ◽  
K. S. Thomas ◽  
J. R. Chalmers ◽  
Y. Vinogradova ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
Bullous Pemphigoid ◽  
Rare Diseases ◽  
Skin Disease ◽  
Practice Research ◽  
Clinical Practice Research Datalink ◽  
Care Hospital ◽  
Health Records ◽  
People With Dementia ◽  
Electronic Health

Abstract Background Trials of novel agents are required to improve the care of patients with rare diseases, but trial feasibility may be uncertain due to concerns over insufficient patient numbers. We aimed to determine the size of the pool of potential participants in England 2015–2017 for trials in the autoimmune blistering skin disease bullous pemphigoid. Methods The size of the pool of potential participants was estimated using routinely collected healthcare data from linked primary care (Clinical Practice Research Datalink; CPRD) and secondary care (Hospital Episode Statistics; HES) databases. Thirteen consultant dermatologists were surveyed to determine the likelihood that a patient would be eligible for a trial based on the presence of cautions or contra-indications to prednisolone use. These criteria were applied to determine how they influenced the potential pool of participants. Results Extrapolated to the population of England, we would expect approximately 10,800 (point estimate 10,747; 95% CI 7191 to 17,239) new cases of bullous pemphigoid to be identified in a three-year period. For a future trial involving oral prednisolone (standard care), the application of cautions to its use as exclusion criteria would result in approximately 365 potential participants unlikely to be recruited, a further 5332 could be recruited with caution, and 5104 in whom recruitment is still possible. 11–17% of potential participants may have pre-existing dementia and require an alternative consent process. Conclusions Routinely collected electronic health records can be used to inform the feasibility of clinical trials in rare diseases, such as whether recruitment is feasible nationally and how long recruitment might take to meet recruitment targets. Future trials of bullous pemphigoid in England may use the data presented to inform trial design, including eligibility criteria and consent processes for enrolling people with dementia.

scholarly journals Long-term impact of giving antibiotics before skin incision versus after cord clamping on children born by caesarean section: protocol for a longitudinal study based on UK electronic health records

BMJ Open ◽  
2019 ◽  
Vol 9 (9) ◽  
pp. e033013 ◽  
Author(s):  
Dana Šumilo ◽  
Krishnarajah Nirantharakumar ◽  
Brian H Willis ◽  
Gavin Rudge ◽  
James Martin ◽  
...  
Keyword(s):  
Caesarean Section ◽  
Electronic Health Records ◽  
Skin Incision ◽  
Practice Research ◽  
Health Improvement ◽  
Clinical Practice Research Datalink ◽  
Care Hospital ◽  
Health Records ◽  
Cord Clamping ◽  
Electronic Health

IntroductionIn the UK, about a quarter of women give birth by caesarean section (CS) and are offered prophylactic broad-spectrum antibiotics to reduce the risk of maternal postpartum infection. In 2011, national guidance was changed from recommending antibiotics after the umbilical cord was cut to giving antibiotics prior to skin incision based on evidence that earlier administration reduces maternal infectious morbidity. Although antibiotics cross the placenta, there are no known short-term harms to the baby. This study aims to address the research gap on longer term impact of these antibiotics on child health.Methods and analysisA controlled interrupted time series study will use anonymised mother-baby linked routine electronic health records for children born during 2006–2018 recorded in UK primary care (The Health Improvement Network, THIN and Clinical Practice Research Datalink, CPRD) and secondary care (Hospital Episode Statistics, HES) databases. The primary outcomes of interest are asthma and eczema, two common allergy-related diseases in childhood. In-utero exposure to antibiotics immediately prior to CS will be compared with no exposure when given after cord clamping. The risk of outcomes in children delivered by CS will also be compared with a control cohort delivered vaginally to account for time effects. We will use all available data from THIN, CPRD and HES with estimated power of 80% and 90% to detect relative increase in risk of asthma of 16% and 18%, respectively at the 5% significance level.Ethics and disseminationEthical approval has been obtained from the University of Birmingham Ethical Review Committee with scientific approvals obtained from the independent scientific advisory committees from the Medicines and Healthcare products Regulatory Agency for CPRD and the data provider, IQVIA for THIN. The results will be published in peer-reviewed journals, presented at national and international conferences and disseminated to stakeholders.

scholarly journals Transforming and evaluating electronic health record disease phenotyping algorithms using the OMOP common data model: a case study in heart failure

JAMIA Open ◽  
2021 ◽  
Author(s):  
Vaclav Papez ◽  
Maxim Moinat ◽  
Stefan Payralbe ◽  
Folkert W Asselbergs ◽  
R Thomas Lumbers ◽  
...  
Keyword(s):  
Heart Failure ◽  
Primary Care ◽  
Data Model ◽  
Observational Research ◽  
Practice Research ◽  
Chronic Obstructive ◽  
Common Data Model ◽  
Clinical Practice Research Datalink ◽  
Clinical Biomarkers ◽  
Electronic Health

Abstract Objective The aim of the study was to transform a resource of linked electronic health records (EHR) to the OMOP common data model (CDM) and evaluate the process in terms of syntactic and semantic consistency and quality when implementing disease and risk factor phenotyping algorithms. Materials and Methods Using heart failure (HF) as an exemplar, we represented three national EHR sources (Clinical Practice Research Datalink, Hospital Episode Statistics Admitted Patient Care, Office for National Statistics) into the OMOP CDM 5.2. We compared the original and CDM HF patient population by calculating and presenting descriptive statistics of demographics, related comorbidities, and relevant clinical biomarkers. Results We identified a cohort of 502 536 patients with the incident and prevalent HF and converted 1 099 195 384 rows of data from 216 581 914 encounters across three EHR sources to the OMOP CDM. The largest percentage (65%) of unmapped events was related to medication prescriptions in primary care. The average coverage of source vocabularies was >98% with the exception of laboratory tests recorded in primary care. The raw and transformed data were similar in terms of demographics and comorbidities with the largest difference observed being 3.78% in the prevalence of chronic obstructive pulmonary disease (COPD). Conclusion Our study demonstrated that the OMOP CDM can successfully be applied to convert EHR linked across multiple healthcare settings and represent phenotyping algorithms spanning multiple sources. Similar to previous research, challenges mapping primary care prescriptions and laboratory measurements still persist and require further work. The use of OMOP CDM in national UK EHR is a valuable research tool that can enable large-scale reproducible observational research.

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