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

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.

Download Full-text

Identifying primary care patients at risk for future diabetes and cardiovascular disease using electronic health records

BMC Health Services Research ◽

10.1186/1472-6963-9-170 ◽

2009 ◽

Vol 9 (1) ◽

Cited By ~ 47

Author(s):

Marie-France Hivert ◽

Richard W Grant ◽

Peter Shrader ◽

James B Meigs

Keyword(s):

Cardiovascular Disease ◽

Primary Care ◽

At Risk ◽

Electronic Health Records ◽

Health Records ◽

Patients At Risk ◽

Primary Care Patients ◽

Electronic Health ◽

Future Diabetes

Download Full-text

Prevalence of Medical Cannabis Use and Associated Health Conditions Documented in Electronic Health Records Among Primary Care Patients in Washington State

JAMA Network Open ◽

10.1001/jamanetworkopen.2021.9375 ◽

2021 ◽

Vol 4 (5) ◽

pp. e219375

Author(s):

Theresa E. Matson ◽

David S. Carrell ◽

Jennifer F. Bobb ◽

David J. Cronkite ◽

Malia M. Oliver ◽

...

Keyword(s):

Primary Care ◽

Electronic Health Records ◽

Washington State ◽

Cannabis Use ◽

Health Conditions ◽

Medical Cannabis ◽

Health Records ◽

Primary Care Patients ◽

Electronic Health

Download Full-text

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

British Journal of General Practice ◽

10.3399/bjgp18x696749 ◽

2018 ◽

Vol 68 (suppl 1) ◽

pp. bjgp18X696749 ◽

Cited By ~ 2

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.

Download Full-text

Estimating the population health burden of musculoskeletal conditions using primary care electronic health records

Rheumatology ◽

10.1093/rheumatology/keab109 ◽

2021 ◽

Author(s):

Dahai Yu ◽

George Peat ◽

Kelvin P Jordan ◽

James Bailey ◽

Daniel Prieto-Alhambra ◽

...

Keyword(s):

Primary Care ◽

Chronic Pain ◽

Low Back Pain ◽

Back Pain ◽

Electronic Health Records ◽

High Impact ◽

Low Back ◽

Musculoskeletal Health ◽

Health Records ◽

Electronic Health

Abstract Objectives Better indicators from affordable, sustainable data sources are needed to monitor population burden of musculoskeletal conditions. We propose five indicators of musculoskeletal health and assessed if routinely available primary care electronic health records (EHR) can estimate population levels in musculoskeletal consulters. Methods We collected validated patient-reported measures of pain experience, function and health status through a local survey of adults (≥35 years) presenting to English general practices over 12 months for low back pain, shoulder pain, osteoarthritis and other regional musculoskeletal disorders. Using EHR data we derived and validated models for estimating population levels of five self-reported indicators: prevalence of high impact chronic pain, overall musculoskeletal health (based on Musculoskeletal Health Questionnaire), quality of life (based on EuroQoL health utility measure), and prevalence of moderate-to-severe low back pain and moderate-to-severe shoulder pain. We applied models to a national EHR database (Clinical Practice Research Datalink) to obtain national estimates of each indicator for three successive years. Results The optimal models included recorded demographics, deprivation, consultation frequency, analgesic and antidepressant prescriptions, and multimorbidity. Applying models to national EHR, we estimated that 31.9% of adults (≥35 years) presenting with non-inflammatory musculoskeletal disorders in England in 2016/17 experienced high impact chronic pain. Estimated population health levels were worse in women, older aged and those in the most deprived neighbourhoods, and changed little over 3 years. Conclusion National and subnational estimates for a range of subjective indicators of non-inflammatory musculoskeletal health conditions can be obtained using information from routine electronic health records.

Download Full-text