Electronic Health Records improve Understanding of Disease Heritability, say Studies

Electronic Health Records Improve Understanding of Disease Heritability, Say Studies

Recent studies say the mining data in EHRs can provide important information to understand heritability of medical conditions, which can streamline the efforts to mitigate disease risk.

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Diagnostic and therapeutic services provided during an evaluation and management (E/M) visit is based on the documentation of key components, such as history, physical examination and medical decision making. The history and physical (H&P) is the primary document that medical transcription service providers include in the medical record. As many health concerns are genetic, documenting details about the family members' health is an important part of a patient’s medical record.

According to recent studies, electronic health records (EHRs) improve understanding of disease heritability. This can help understand and lessen disease risk, especially for medical conditions with no known disease-associated genes, say researchers.

Genes and Medical Conditions Gene mutations cause genetic disorders. A gene mutation can be inherited from one or both parents or happen during a person’s lifetime. Diseases can be caused by a defect in a single gene or in a set of genes.

There are different types of genetic diseases: chromosomal abnormalities, single gene defects, multifactorial problems, and teratogenic problems. Common genetic disorders include autism, Crohn's disease; Parkinson's disease, breast and skin cancer, hemophilia and thalassemia. Genes are also linked to the occurrence of infectious diseases like tuberculosis and AIDS as well as certain non-communicable diseases like cancer and One of the central goals of genetic research is to understand the mechanisms of genetic diseases so that personalized treatment approaches and preventative measures can be devised.

EHR data used to estimate Disease Heritability from Familial Relationships Researchers at Columbia University Irving Medical Center and NewYork-Presbyterian analyzed data from millions of electronic health records to estimate the heritability of hundreds of different traits and conditions. According to the study published May 2018 in Cell, understanding how much of a condition’s variability can be attributed to genesis essential for identifying the biological causes of the disease and for precision medicine.

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The researchers analyzed data from 5.5 million electronic health records of patients and their emergency contacts at NewYork-Presbyterian/Columbia University Irving Medical Center, NewYork-Presbyterian/Weill Cornell Medical Center, and Mount Sinai Health System.

The study is unique in that it has been able to differentiate disease risk for patients of various ethnic groups in New York City.

Algorithms were used for inferring 7.4 million family relationships among patients and contacts. They generated heritability estimates by analyzing the incidence of about 500 different traits and conditions reported in the EHRs. The team’s heritability estimates were similar across all three medical centers and matched previously published estimates.

However, the researchers say that the results were quite unexpected for many conditions for which heritability had never been estimated. A Columbia University news report listed some of the “surprises” as follows:

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HDL cholesterol is notably more heritable than LDL cholesterol, even after accounting for the use of lipid-lowering statin medications

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Respiratory diseases in general seem more heritable among African-Americans

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Sinus infections are identified as highly heritable across all the populations studied

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Acne is highly heritable

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Anxiety is more strongly associated with environmental causes rather than genetics

By providing information about a condition’s heritability, the researchers say that such analysis of EHR data will help clinicians estimate disease risk, customize treatment, and tailor patient care.

EHR Data can identify Undiagnosed Genetic Diseases If a genetic condition cannot be identified, physicians term it undiagnosed rare or genetic condition. With genetic testing becoming more widespread, it is important to understand the impact of genetic variants. However, only fraction of the rare genetic variants found in human beings are known.

A new study by researchers at Vanderbilt University Medical Center used EHR data to identify undiagnosed genetic diseases in large populations. This will allow treatments to be

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customized to the actual cause of the illness, says the study which was published March 2018 in the journal Science.

The researchers’ theory was that many patients currently diagnosed with conditions like heart failure, stroke, infertility or kidney failure may actually have a rare genetic disease. If the underlying disease could be identified and if it had a specific treatment, it would be possible to prevent the symptoms from recurring or getting worse.

The researchers combined traditional resources and newer data mining techniques to develop a phenotype risk score and detect patterns of symptoms that may be caused by an underlying genetic variant. Scores were assigned to 21,701 individuals based on how well their list of symptoms fitted the clinical description of each of 1,204 different genetic diseases. The study found 18 associations between genetic variants and high phenotype risk scores. Some associations were well known, but many associations were for variants not previously described.

Studying outcomes in EHRs could therefore help determine if a variant might be diseaseassociated. The researchers say that phenotype risk scoring can easily be applied in any electronic medical record system that is linked to DNA. Documenting Patient Medical History in EHRs The American Medical Association stresses that properly collected family history can improve care by: •

Identifying whether a patient has a higher risk for a disease

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Helping providers recommend treatments or other options to reduce a patient’s risk of disease

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Providing early warning signs of disease

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Helping plan lifestyle changes to improve patient wellbeing

The Centers for Medicare and Medicaid Services (CMS) Documentation Guidelines for E/M Services have four history levels --problem focused, expanded problem focused, detailed, and comprehensive. Each of these history levels consists of four elements -- chief complaint, history of present illness, review of systems, and pertinent past, family and/or social history. Family medical history is crucial to identify health concerns that are genetic.

Many diseases that are genetic that may not show up in each generation, but as these

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studies show, identifying the presence of those genetic markers in EHRs can make it easier to understand an illness or set of symptoms.

Complete and accurate documentation in the medical record is essential to promote a culture of quality and continuity of patient care. Outsourcing medical transcription can ensure proper documentation of all elements in the EHR, including family history.

Comprehensive, error-free, timely EHR documentation can improve communication among providers and ultimately, treatment, planning and delivery of care.

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