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.

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 Do health checks improve risk factor detection in primary care? Matched cohort study using electronic health records

2015 ◽  
Vol 38 (3) ◽  
pp. 552-559 ◽  
Author(s):  
Alice S. Forster ◽  
Caroline Burgess ◽  
Hiten Dodhia ◽  
Frances Fuller ◽  
Jane Miller ◽  
...  
Keyword(s):  
Primary Care ◽  
Risk Factor ◽  
Cohort Study ◽  
Electronic Health Records ◽  
Matched Cohort ◽  
Health Records ◽  
Matched Cohort Study ◽  
Health Checks ◽  
Electronic Health

scholarly journals Provider Responses to Patients Controlling Access to their Electronic Health Records: A Prospective Cohort Study in Primary Care

2014 ◽  
Vol 30 (S1) ◽  
pp. 31-37 ◽  
Author(s):  
William M. Tierney ◽  
Sheri A. Alpert ◽  
Amy Byrket ◽  
Kelly Caine ◽  
Jeremy C. Leventhal ◽  
...  
Keyword(s):  
Primary Care ◽  
Cohort Study ◽  
Electronic Health Records ◽  
Prospective Cohort Study ◽  
Prospective Cohort ◽  
Health Records ◽  
Electronic Health

scholarly journals Documentation and Diagnosis of Overweight and Obesity in Electronic Health Records of Adult Primary Care Patients

2013 ◽  
Vol 173 (17) ◽  
pp. 1648 ◽  
Author(s):  
Heather J. Baer ◽  
Andrew S. Karson ◽  
Jane R. Soukup ◽  
Deborah H. Williams ◽  
David W. Bates
Keyword(s):  
Primary Care ◽  
Electronic Health Records ◽  
Overweight And Obesity ◽  
Health Records ◽  
Primary Care Patients ◽  
Electronic Health

scholarly journals Changing Epidemiology of Bariatric Surgery in the UK: Cohort Study Using Primary Care Electronic Health Records

2016 ◽  
Vol 26 (8) ◽  
pp. 1900-1905 ◽  
Author(s):  
Helen P. Booth ◽  
◽  
Omar Khan ◽  
Alison Fildes ◽  
A. Toby Prevost ◽  
...  
Keyword(s):  
Bariatric Surgery ◽  
Primary Care ◽  
Cohort Study ◽  
Electronic Health Records ◽  
Health Records ◽  
Electronic Health ◽  
The Uk

scholarly journals MORTALITY OF CARE HOME RESIDENTS AND COMMUNITY-DWELLING CONTROLS DURING THE COVID-19 PANDEMIC IN 2020: MATCHED COHORT STUDY

2021 ◽  
Author(s):  
Martin C Gulliford ◽  
Emma C Rezel-Potts
Keyword(s):  
Primary Care ◽  
Cohort Study ◽  
Electronic Health Records ◽  
Care Home ◽  
Community Dwelling ◽  
Matched Cohort ◽  
Long Term Conditions ◽  
Health Records ◽  
Matched Cohort Study ◽  
Electronic Health

Objective: To estimate mortality of care home residents during the Covid-19 pandemic from primary care electronic health records. Design: Matched cohort study Setting: 1,421 general practices contributing to the Clinical Practice Research Datalink Aurum Database in England. Participants: 217,987 patients aged 18 to 104 years with recorded care home residence in England in the period 2015 to 2020. There were 86,371 care home residents contributing data in 2020, with 29,662 deaths; 83,419 (97%) were matched on age, gender and general practice with 312,607 community-dwelling adults. Main outcome measures: All-cause mortality. Analysis was by Poisson regression adjusting for age, gender, long-term conditions, region, year and calendar week. Results: The highest first wave age-specific mortality rate was 6.02 (95% confidence interval 5.97 to 6.07) per 100 patients per week in men aged 95-104 years between 13th-19th April 2020. Compared with community-dwelling controls, the adjusted rate ratio for mortality of care home residents was 4.95 (4.62 to 5.32) in February 2020, increasing to 8.34 (7.95 to 8.74) in April 2020, declining to 3.93 (3.68 to 4.20) in December 2020. During the week of 13th to 19th April 2020, mortality of care home residents was 10.74 (9.72 to 11.85) times higher than for matched community-dwelling controls. Conclusions: Individual-patient data from primary care electronic health records may be used to estimate mortality in care home residents. Mortality is substantially higher than for community-dwelling comparators and showed a disproportionate increase in the first wave of the Covid-19 pandemic but not the second wave. This study provides evidence to support earlier, decisive action to protect these vulnerable populations in the event of further outbreaks. Prospective investigations of care home mortality are warranted.

scholarly journals Depression, depressive symptoms and treatments in women who have recently given birth: UK cohort study

BMJ Open ◽  
2018 ◽  
Vol 8 (10) ◽  
pp. e022152 ◽  
Author(s):  
Irene Petersen ◽  
Tomi Peltola ◽  
Samuel Kaski ◽  
Kate R Walters ◽  
Sarah Hardoon
Keyword(s):  
Primary Care ◽  
Cohort Study ◽  
Depressive Symptoms ◽  
Electronic Health Records ◽  
Postnatal Depression ◽  
Selective Serotonin Reuptake Inhibitors ◽  
Antidepressant Treatment ◽  
Health Records ◽  
Electronic Health ◽  
Ssri Treatment

ObjectivesTo investigate how depression is recognised in the year after child birth and treatment given in clinical practice.DesignCohort study based on UK primary care electronic health records.SettingPrimary care.ParticipantsWomen who have given live birth between 2000 and 2013.OutcomesPrevalence of postnatal depression, depression diagnoses, depressive symptoms, antidepressant and non-pharmacological treatment within a year after birth.ResultsOf 206 517 women, 23 623 (11%) had a record of depressive diagnosis or symptoms in the year after delivery and more than one in eight women received antidepressant treatment. Recording and treatment peaked 6–8 weeks after delivery. Initiation of selective serotonin reuptake inhibitors (SSRI) treatment has become earlier in the more recent years. Thus, the initiation rate of SSRI treatment per 100 pregnancies (95% CI) at 8 weeks were 2.6 (2.5 to 2.8) in 2000–2004, increasing to 3.0 (2.9 to 3.1) in 2005–2009 and 3.8 (3.6 to 3.9) in 2010–2013. The overall rate of initiation of SSRI within the year after delivery, however, has not changed noticeably. A third of the women had at least one record suggestive of depression at any time prior to delivery and of these one in four received SSRI treatment in the year after delivery.Younger women were most likely to have records of depression and depressive symptoms. (Relative risk for postnatal depression: age 15–19: 1.92 (1.76 to 2.10), age 20–24: 1.49 (1.39 to 1.59) versus age 30–34). The risk of depression, postnatal depression and depressive symptoms increased with increasing social deprivation.ConclusionsMore than 1 in 10 women had electronic health records indicating depression diagnoses or depressive symptoms within a year after delivery and more than one in eight women received antidepressant treatment in this period. Women aged below 30 and from the most deprived areas were at highest risk of depression and most likely to receive antidepressant treatment.

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.

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