Ubiquitous Computing Synchronization for Efficient Error Detection in Electronic Medical Records (EMR)

Literature Review (Secondary Research)
Student Name& CSU
ID
Project Topic Title Ubiquitous computing synchronization for efficient error detection in Electronic Medical Records (EMR)
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Version 1.0 _ Week 1 (5 Journal Papers from CSU Library)
1
Reference in APA format that will be
in 'Reference List'
Jimenez-Molina, A., Gaete-Villegas, J., & Fuentes, J. (2018). ProFUSO: Business process and
ontology-based framework to develop ubiquitous computing support systems for chronic patients’
management. Journal of biomedical informatics, 82, 106-127.
Citation that will be in the content (Jimenez-Molina, et. al., 2018)
URL of the Reference Level of Journal (Q1, Q2, …Qn) Keywords in this Reference
https://ac-els-cdn-
com.ezproxy.csu.edu.au/
S1532046418300650/1-s2.0-
S1532046418300650-main.pdf?
_tid=647c0c20-0391-49b9-9393-
05718157ca3c&acdnat=1531463246_3
4f8ce01deb22d2a88396d3699f00fbd
Level of journal: Q1 Data architecture, Chronic disease management,
Ubiquitous health (u-health) services, Clinical decision
support systems (CDSS), Ubiquitous computing,
Interoperability
The Name of the Current Solution
(Technique/ Method/ Scheme/
Algorithm/ Model/ Tool/ Framework/
... etc )
The Goal (Objective) of this Solution &
What is the Problem that need to be
solved
What are the components of it?
Techniques:
ProFUSO(Process-oriented Framework
for Ubiquitous Systems based on
Ontologies)
Tools:
Business Process Modeling Notation
(BPMN)
Problem:
The problem is related to the issues of
integration between applications and
existing healthcare systems
Goal:
The research approach to manage all stages
 E-health (Electronic Health)
 Clinical decision support system
 Ubiquitous computing (Ubicomp)
 Computer Interpretable Guidelines (CIG)
 Message Queue Telemetry Transport (MQTT)
2

Applied Area:
Chronic patients
of the chronic patient diagnosis and
treatment.
The Process (Mechanism) of this Work; The process steps of the Technique/system
Process Steps Advantage (Purpose of this step) Disadvantage (Limitation/Challenge)
1 Data input
Data input to the system. It can be either bio
signal or medical information of patient.
Acceptance of patient’s data Requires pre-processed information of
data
2 Data storage
Storing the captured data of data gathering
layer.
Storage on different manager API’s Minimal functionalities for receiving
and storing data
3 Data extraction
Extraction of high-level context and the U-
health services selection
Output for data publication N/A
4 Data publishing
Publishing the collected data on third party
applications.
Making available the existing ontology
information and parsing the information to
fit specific formats for consumption.
Required interaction of third party
applications.
Validation Criteria (Measurement Criteria)
Dependent Variable Independent Variable
Computer system Network services
Gathering chronic patient data ProFUSO framework
3

Input and Output Critical Thinking: Feature of this work, and
Why (Justify)
Critical Thinking: Limitations of the
research current solution, and Why
(Justify)
Input Output
The input is to
develop a
framework which
helps chronicle
patient to get
treatment and help
hospital to keep
patient’s data
capture in secure
system using bio
signal or medical
information.
The output of the
system to enhance
the patient data
gathering system so
that chronic patient
and hospital can
continue the
treatment with safe
and secured patient
data.
Clinical pathways have been redesigned using
Business Process Modeling Notion (BPMN).
It provides the technological support in
healthcare organizational process
This research has proposed ProFUSO(Process-
oriented Framework for Ubiquitous Systems
based on Ontologies) framework for managing
all stages of chronically ill patient.
Spontaneous composition of process has not
been sufficiently solved. Hence, complexion
of processes would be a limitation of proposed
framework.
(Describe the research/current solution) Evaluation Criteria How this research/current solution is
valuable for your project
What is the Future work that set by the
author in Conclusion and Future work
section
Jimenez-Molina, et. al. (2018), proposed
framework, bio-signals or medical
information of chronic patients can be
gathered using four-layer process and further,
it can be accessed by both patient and
This research has introduced a ProFUSO
(Process-oriented Framework for Ubiquitous
Systems based on Ontologies) system that is
use to provide treatment schedule and security
The proposed framework for chronically ill
patients will help to enhance the process of in-
hospital and out-hospital data to get vaulted
and get the access through third party
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hospital. to chronically ill patients. applications.
Diagram/Flowchart
Figure 1: Layered architecture of the ProFUSO framework using ubiquitous computing
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2
Reference in APA format that will be
in 'Reference List'
Liu, L., Liu, L., Fu, X., Huang, Q., Zhang, X., & Zhang, Y. (2018). A cloud-based framework for
large-scale traditional Chinese medical record retrieval. Journal of biomedical informatics, 77, 21-33.
Citation that will be in the content (Lui, et. al., 2018)
URL of the Reference Level of Journal (Q1, Q2, …Qn) Keywords in this Reference
https://ac-els-cdn-
com.ezproxy.csu.edu.au/
S1532046417302587/1-s2.0-
S1532046417302587-main.pdf?
_tid=cd9ad67e-a495-48c3-b47f-
bf6f6f242cb6&acdnat=1531396934_1a
9bcfd16fe8d01cfb3df6230c38a902
Level of Journal:Q1  Electronic medical records
 HL7-CDA
 Real-time indexing
 Information retrieval
 Semantic expansion
 Cloud-computing
The Name of the Current Solution
(Technique/ Method/ Scheme/
Algorithm/ Model/ Tool/ Framework/
... etc )
The Goal (Objective) of this Solution &
What is the Problem that need to be
solved
What are the components of it?
Techniques:
CDA engine, WADO service, TCMLs
Tools:
Parallel index building method
Applied Area:
Medical area
Problem:
The retrieval of medical data of patient is a
big challenge in medical sector. The main
difficulty is that there is a huge amount of
medical data available. The retrieval of
relevant data from the voluminous medical
records is very time consuming. This
makes it difficult to find the few record of
the patient from a large pile of data which
is relevant to patient current condition.
 Report visualization
 Distributed retrieval
 Multi-index model
 Parallel indexing
 HDFS API
 Lucene API
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Goal:
The goal is to develop a parallel indexing
method and building a distributed search
centre. This will make the searching the
patients file more efficiently and in less
time.
The Process (Mechanism) of this Work; The process steps of the Technique/system
Process Steps Advantage (Purpose of this step) Disadvantage (Limitation/Challenge)
1 Retrieval
Cloud based framework is used for
implementing the large scale TCMRs
retrieval system
It gives efficient and robust framework N/A
2 Cluster based processing
Parallel indexing and distributed search
cluster
It will be improve the performance of
indexing and will give high online retrieval
rate
N/A
3 Indexing
Multi indexing model is to be used
Help indexing the latest TCMRs and
retrieve them in real-time
It may not give the idea of actual utility
of returned document.
4 Expansion
Semantic expansion is used
It will enhance the quality of retrieved data N/A
5 Visualization
Template based visualization method is used
for increasing the ability of data.
It will enhance the usability and general
ability of the data
Designing and management of large
number of templates is difficult.
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Validation Criteria (Measurement Criteria)
Dependent Variable Independent Variable
Merging and writing patient data CAD engine
Real time indexing of patient data WADO service
Input and Output Critical Thinking: Feature of this work, and
Why (Justify)
Critical Thinking: Limitations of the
research current solution, and Why
(Justify)
Input Output
The input in this
process is to
develop a model
that will make the
retrieval of medical
data of patients easy
and less time-
consuming. This
will provide the
required details of
the patient's current
condition out of all
un-necessary data.
The output in this
process is to
develop a
distributed TCMRs
retrieval system to
improve the use of
large scale of
TCMRs in cloud
computing. The
details of a patient
at the current
condition can be
fetched at higher
efficiency and in
very less time using
 C-MRRS is implemented on a cloud
environment and medical records are
represent as
 The technique uses template based
visualisation method which helps users to
display their content of medical report via
a friendly web interface.
 In this role based and grade based mixed
security policies are used.
 It is easily integrated with the exiting
clinical systems.
The main limitation in this model is that it
can only work on TCMRs only. It is very
difficult for this model to work on non-TCM
settings. Secondly, CDA templates are
designed and managed in a large number
which becomes very difficult. Third, This
model can give the idea of small term
matching but may not give the idea of actual
utility out of the returned documents. Lastly,
the effective feedback system is not present in
the model which makes it difficult to
understand user's intentions with the retrieved
data.
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