Constructing data-derived family histories using electronic health records from a single healthcare delivery system

Abstract Background In order to examine the potential clinical value of integrating family history information directly from the electronic health records of patients’ family members, the electronic health records of individuals in Clalit Health Services, the largest payer/provider in Israel, were l...

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Bibliographic Details
Published in:European journal of public health Vol. 30; no. 2; pp. 212 - 218
Main Authors: Leventer-Roberts, Maya, Gofer, Ilan, Barak Corren, Yuval, Reis, Ben Y, Balicer, Ran
Format: Journal Article
Language:English
Published: England Oxford University Press 01.04.2020
Subjects:
Archives & records
Asthma
Cardiovascular diseases
Chronic asthma
Chronic illnesses
Clinical decision making
Computerized medical records
Data
Decision making
Diabetes
Diabetes mellitus
Diabetics
Diagnostic systems
Disease
Electronic health records
Electronic medical records
Families & family life
Family medical history
Genetics
Health care delivery
Health records
Health services
Health Services Research
Heart diseases
History
Medical decision making
Medical records
Patients
Public health
Relatives
ISSN:1101-1262, 1464-360X, 1464-360X
Online Access:Get full text
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Summary:Abstract Background In order to examine the potential clinical value of integrating family history information directly from the electronic health records of patients’ family members, the electronic health records of individuals in Clalit Health Services, the largest payer/provider in Israel, were linked with the records of their parents. Methods We describe the results of a novel approach for creating data-derived family history information for 2 599 575 individuals, focusing on three chronic diseases: asthma, cardiovascular disease (CVD) and diabetes. Results In our cohort, there were 256 598 patients with asthma, 55 309 patients with CVD and 66 324 patients with diabetes. Of the people with asthma, CVD or diabetes, the percentage that also had a family history of the same disease was 22.0%, 70.8% and 70.5%, respectively. Conclusions Linking individuals’ health records with their data-derived family history has untapped potential for supporting diagnostic and clinical decision-making.
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Ben Y. Reis andd Ran Balicer contributed equally to this work.
ISSN:1101-1262
1464-360X
1464-360X
DOI:10.1093/eurpub/ckz152