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.

scholarly journals UK phenomics platform for developing and validating electronic health record phenotypes: CALIBER

2019 ◽  
Vol 26 (12) ◽  
pp. 1545-1559 ◽  
Author(s):  
Spiros Denaxas ◽  
Arturo Gonzalez-Izquierdo ◽  
Kenan Direk ◽  
Natalie K Fitzpatrick ◽  
Ghazaleh Fatemifar ◽  
...  
Keyword(s):  
Primary Care ◽  
International Classification Of Diseases ◽  
Population Based ◽  
Source Population ◽  
Snomed Ct ◽  
Lifestyle Risk Factors ◽  
Classification Of Diseases ◽  
Electronic Health ◽  
Lifestyle Risk

AbstractObjectiveElectronic health records (EHRs) 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 EHR in the United Kingdom with applications for translational research.Materials and MethodsWe implemented a rule-based phenotyping framework, with up to 6 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 (for example, blood pressure; medication information; coded diagnoses, symptoms, procedures, and referrals), recorded using 5 controlled clinical terminologies: (1) read (primary care, subset of SNOMED-CT [Systematized Nomenclature of Medicine Clinical Terms]), (2) International Classification of Diseases–Ninth Revision and Tenth Revision (secondary care diagnoses and cause of mortality), (3) Office of Population Censuses and Surveys Classification of Surgical Operations and Procedures, Fourth Revision (hospital surgical procedures), and (4) DM+D prescription codes.ResultsUsing the CALIBER phenotyping framework, we created algorithms for 51 diseases, syndromes, biomarkers, and lifestyle risk factors and provide up to 6 validation approaches. The EHR phenotypes are curated in the open-access CALIBER Portal (https://www.caliberresearch.org/portal) and have been used by 40 national and international research groups in 60 peer-reviewed publications.ConclusionsWe describe a UK EHR phenomics approach within the CALIBER EHR data platform with initial evidence of validity and use, as an important step toward international use of UK EHR data for health research.

scholarly journals Imported malaria in the UK, 2005 to 2016: Estimates from primary care electronic health records

PLoS ONE ◽  
2018 ◽  
Vol 13 (12) ◽  
pp. e0210040
Author(s):  
Hamad Bastaki ◽  
Louise Marston ◽  
Jackie Cassell ◽  
Greta Rait
Keyword(s):  
Primary Care ◽  
Electronic Health Records ◽  
Imported Malaria ◽  
Health Records ◽  
Electronic Health ◽  
The Uk

scholarly journals Health-related welfare prioritisation of canine disorders using electronic health records in primary care practice in the UK

2019 ◽  
Vol 15 (1) ◽  
Author(s):  
Jennifer F. Summers ◽  
Dan G. O’Neill ◽  
David Church ◽  
Lisa Collins ◽  
David Sargan ◽  
...  
Keyword(s):  
Primary Care ◽  
Electronic Health Records ◽  
Primary Care Practice ◽  
Care Practice ◽  
Health Records ◽  
Health Related ◽  
Electronic Health ◽  
The Uk

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

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 Validity of UK electronic health records to study migrant health: a population-based cohort study

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
N Pathak ◽  
P Patel ◽  
R Mathur ◽  
R Burns ◽  
A Gonzalez-Izquierdo ◽  
...  
Keyword(s):  
Primary Care ◽  
Cohort Study ◽  
Electronic Health Records ◽  
Barriers To Care ◽  
Population Based ◽  
Health Records ◽  
Migration Status ◽  
English Speaking ◽  
International Migrants ◽  
The Uk

Abstract Background An estimated 14.3% (9.4 million people) of people living in the UK in 2019 were international migrants. Despite this, little is known about how migrants access and use healthcare services. To use electronic healthcare records (EHRs) to study migration health, a valid migration phenotype is necessary: a transparent reproducible algorithm using clinical terminology codes to determine migration status. We have previously described the validity of a migration phenotype in CALIBER data using the Clinical Practice Research Datalink (CPRD), the largest UK primary care EHR. This study further evaluates the phenotype by examining certainty of migration status. Methods This is a population-based cohort study of individuals in CPRD Gold (1997-2018) with a Read term indicating migration to the UK. We describe completeness of recording of migration over time: percentage of individuals recorded as migrants. We also describe cohort size based on certainty of migration status: “definite” (country of birth or visa status terms), “probable” (non-English first/main language terms), and “possible” (non-UK origin terms). Results Overall, 2.5% (403,768/16,071,111) of CPRD had ≥1 of 434 terms indicating migration to the UK. The percentage of recorded migrants per year increased from 0.2% (4,417/2,210,551) in 1997 to 3.64% (100,626/2,761,397) in 2018, following a similar trend to national migration data. 44.27% (178,749/403,768) were “definite” migrants and 53.68% (216,731/403,768) were “probable” migrants. Only 2.05%(8,288/16,071,111) were “possible” migrants. Conclusions We have created a large cohort of international migrants in the UK and certainty of migration status is high. This cohort can be used to study migration health in UK primary care EHR. The large contribution of language terms make this phenotype particularly suitable for understanding healthcare access and use by non-English speaking migrants who may face additional barriers to care. Key messages We have developed a way to study migration health in UK primary care electronic health records. Our method is particularly useful to study healthcare for non-English speaking migrants who may face additional barriers to care.

scholarly journals Diagnostic code agreement for electronic health records and claims data for tuberculosis

2020 ◽  
Vol 24 (7) ◽  
pp. 706-711
Author(s):  
S. A. Iqbal ◽  
C. J. Isenhour ◽  
G. Mazurek ◽  
B. I. Truman
Keyword(s):  
Electronic Health Records ◽  
Latent Tuberculosis ◽  
Population Based ◽  
Positive Tuberculin Skin Test ◽  
Diagnostic Code ◽  
Snomed Ct ◽  
Health Records ◽  
Classification Of Diseases ◽  
International Statistical Classification ◽  
Electronic Health

OBJECTIVE: To measure the frequency of diseases related to latent tuberculosis infection (LTBI) and tuberculosis (TB), we assessed the agreement between diagnosis codes for TB or LTBI in electronic health records (EHRs) and insurance claims for the same person.METHODS: In a US population-based, retrospective cohort study, we matched TB-related Systematized Nomenclature of Medicine–Clinical Terms (SNOMED CT) EHR codes and International Statistical Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) claims codes. Furthermore, LTBI was identified using a published ICD-based algorithm and all LTBI- and TB-related SNOMED CT codes.RESULTS: Of people with the 10 most frequent TB-related claim codes, 50% did not have an exact-matched EHR code. Positive tuberculin skin test was the most frequent unmatched EHR code and people with the 10 most frequent TB EHR codes, 40% did not have an exact-matched claim code. The most frequent unmatched claim code was TB screening encounter. EHR codes for LTBI matched to claims codes for TB testing; pulmonary TB; and nonspecific, positive or adverse tuberculin reaction.CONCLUSION: TB-related EHR codes and claims diagnostic codes often disagree, and people with claims codes for LTBI have unexpected EHR codes, indicating the need to reconcile these coding systems.

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