Use of SNOMED CT® and LOINC® to standardize terminology for primary care asthma electronic health records

2017 ◽  
Vol 55 (6) ◽  
pp. 629-639 ◽  
Author(s):  
M. Diane Lougheed ◽  
Nicola. J. Thomas ◽  
Nastasia. V. Wasilewski ◽  
Alison. H. Morra ◽  
Janice. P. Minard
Keyword(s):  
Primary Care ◽  
Electronic Health Records ◽  
Snomed Ct ◽  
Health Records ◽  
Electronic Health ◽  
Standardize Terminology

scholarly journals UK phenomics platform for developing and validating EHR phenotypes: CALIBER

2019 ◽  
Author(s):  
Spiros Denaxas ◽  
Arturo Gonzalez-Izquierdo ◽  
Kenan Direk ◽  
Natalie Fitzpatrick ◽  
Amitava Banerjee ◽  
...  
Keyword(s):  
Primary Care ◽  
Electronic Health Records ◽  
Population Based ◽  
Source Population ◽  
Snomed Ct ◽  
Health Records ◽  
Lifestyle Risk Factors ◽  
Electronic Health ◽  
Lifestyle Risk ◽  
The Uk

ABSTRACTObjectiveElectronic health records are a rich source of information on human diseases, but the information is variably structured, fragmented, curated using different coding systems and collected for purposes other than medical research. We describe an approach for developing, validating and sharing reproducible phenotypes from national structured Electronic Health Records (EHR) in the UK with applications for translational research.Materials and MethodsWe implemented a rule-based phenotyping framework, with up to six approaches of validation. We applied our framework to a sample of 15 million individuals in a national EHR data source (population based primary care, all ages) linked to hospitalization and death records in England. Data comprised continuous measurements such as blood pressure, medication information and coded diagnoses, symptoms, procedures and referrals, recorded using five controlled clinical terminologies: a) Read (primary care, subset of SNOMED-CT), b) ICD-9, ICD-10 (secondary care diagnoses and cause of mortality), c) OPCS-4 (hospital surgical procedures) and d) Gemscript Drug Codes.ResultsThe open-access CALIBER Portal (https://www.caliberresearch.org/portal) demonstrates phenotyping algorithms for 50 diseases, syndromes, biomarkers and lifestyle risk factors and provides up to six validation layers. These phenotyping algorithms have been used by 40 national/international research groups in 60 peer-reviewed publications.ConclusionHerein, we describe the UK EHR phenomics approach, CALIBER, with initial evidence of validity and use, as an important step towards international use of UK EHR data for health research.

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

Rheumatology ◽  
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.

The relationship between usage intention and adoption of electronic health records at primary care clinics

2013 ◽  
Vol 112 (3) ◽  
pp. 731-737 ◽  
Author(s):  
Usman Iqbal ◽  
Cheng-Hsun Ho ◽  
Yu-Chuan(Jack) Li ◽  
Phung-Anh Nguyen ◽  
Wen-Shan Jian ◽  
...  
Keyword(s):  
Primary Care ◽  
Electronic Health Records ◽  
Health Records ◽  
Primary Care Clinics ◽  
Electronic Health ◽  
The Relationship

scholarly journals An exploration of the properties of the CORE problem list subset and how it facilitates the implementation of SNOMED CT

2015 ◽  
Vol 22 (3) ◽  
pp. 649-658 ◽  
Author(s):  
Kin Wah Fung ◽  
Julia Xu
Keyword(s):  
Electronic Health Records ◽  
Growth Pattern ◽  
Problem List ◽  
Snomed Ct ◽  
Health Records ◽  
The Core ◽  
Core Subset ◽  
Electronic Health ◽  
Systematized Nomenclature Of Medicine ◽  
Core Problem

Abstract Objective Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) is the emergent international health terminology standard for encoding clinical information in electronic health records. The CORE Problem List Subset was created to facilitate the terminology’s implementation. This study evaluates the CORE Subset’s coverage and examines its growth pattern as source datasets are being incorporated. Methods Coverage of frequently used terms and the corresponding usage of the covered terms were assessed by “leave-one-out” analysis of the eight datasets constituting the current CORE Subset. The growth pattern was studied using a retrospective experiment, growing the Subset one dataset at a time and examining the relationship between the size of the starting subset and the coverage of frequently used terms in the incoming dataset. Linear regression was used to model that relationship. Results On average, the CORE Subset covered 80.3% of the frequently used terms of the left-out dataset, and the covered terms accounted for 83.7% of term usage. There was a significant positive correlation between the CORE Subset’s size and the coverage of the frequently used terms in an incoming dataset. This implies that the CORE Subset will grow at a progressively slower pace as it gets bigger. Conclusion The CORE Problem List Subset is a useful resource for the implementation of Systematized Nomenclature of Medicine Clinical Terms in electronic health records. It offers good coverage of frequently used terms, which account for a high proportion of term usage. If future datasets are incorporated into the CORE Subset, it is likely that its size will remain small and manageable.

scholarly journals Epidemiology of dementia: prevalence and incidence estimates using validated electronic health records from primary care

2019 ◽  
Vol Volume 11 ◽  
pp. 217-228 ◽  
Author(s):  
Anna Ponjoan ◽  
Josep Garre-Olmo ◽  
Jordi Blanch ◽  
Ester Fages ◽  
Lia Alves-Cabratosa ◽  
...  
Keyword(s):  
Primary Care ◽  
Electronic Health Records ◽  
Health Records ◽  
Dementia Prevalence ◽  
Epidemiology Of Dementia ◽  
Electronic Health
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