Integration of Heterogeneous Data into Electronic Patient Records
Date Issued
2021-10-15
Author(s)
Savoska, Snezana
Ristevski, Blagoj
Blazheska-Tabakovska, Natasha
Jolevski, Ilija
Bocevska, Andrijana
Abstract
The deficiency of data for patients with chronic
diseases and other diseases and previous medical treatments
shows a significant weakness with many patients. Typically,
due to the healthcare system insufficiently, patients with
comorbidities might not survive the diseases, especially
when the disease is novel. The lack of information on genetic
disorders in patients they are not aware of also contributes
to increased patient deaths. This leads to the need to
integrate medical and health data with various biological
and other data, especially in pandemic circumstances and
the increasing number of patients with chronic diseases.
Patients' health data issues are evident, but they are stored
in various hospital and public health systems such as
electronic health records (EHRs), healthcare institutions,
and laboratories. Furthermore, biological data are often not
integrated and cannot be used by patients, physicians, and
specialists to treat particular diseases. Although the urgent
need for healthcare and medical data integration is
apparent, personal data protection laws are rigorous. They
do not allow much progress in the field without
implementing patient healthcare data security and privacy
standards. One solution for this issue is establishing a
personal health record (PHR) as an integrative system for
the patient. Many ontological frameworks have been
proposed to unify the record formats, but none of them is
accepted as healthcare standards. The efforts towards
approving the HL7 standards and the well-known medical
codding systems promise future data integrations. Also,
some attempts are made to associate particular diseases with
data obtained from external environmental sensors that
measure disease-related data. Using these data, called
exposure data or exposome, one can clarify the increasing
symptoms of particular diseases influenced by external
factors. This paper proposes a cloud-based model for
integrating healthcare and medical data from different
sources as EHR, health information systems, and
measurement sensors into PHR as the first stage towards
integrating patient health data. The medical data, PHR,
numerous biological and exposome data, and data obtained
from wearables are considered and stored on the cloud
following the required data security and privacy standards.
diseases and other diseases and previous medical treatments
shows a significant weakness with many patients. Typically,
due to the healthcare system insufficiently, patients with
comorbidities might not survive the diseases, especially
when the disease is novel. The lack of information on genetic
disorders in patients they are not aware of also contributes
to increased patient deaths. This leads to the need to
integrate medical and health data with various biological
and other data, especially in pandemic circumstances and
the increasing number of patients with chronic diseases.
Patients' health data issues are evident, but they are stored
in various hospital and public health systems such as
electronic health records (EHRs), healthcare institutions,
and laboratories. Furthermore, biological data are often not
integrated and cannot be used by patients, physicians, and
specialists to treat particular diseases. Although the urgent
need for healthcare and medical data integration is
apparent, personal data protection laws are rigorous. They
do not allow much progress in the field without
implementing patient healthcare data security and privacy
standards. One solution for this issue is establishing a
personal health record (PHR) as an integrative system for
the patient. Many ontological frameworks have been
proposed to unify the record formats, but none of them is
accepted as healthcare standards. The efforts towards
approving the HL7 standards and the well-known medical
codding systems promise future data integrations. Also,
some attempts are made to associate particular diseases with
data obtained from external environmental sensors that
measure disease-related data. Using these data, called
exposure data or exposome, one can clarify the increasing
symptoms of particular diseases influenced by external
factors. This paper proposes a cloud-based model for
integrating healthcare and medical data from different
sources as EHR, health information systems, and
measurement sensors into PHR as the first stage towards
integrating patient health data. The medical data, PHR,
numerous biological and exposome data, and data obtained
from wearables are considered and stored on the cloud
following the required data security and privacy standards.
Subjects
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