Electronics health records and business analytics a cloud based approach

1. Proceedings of the International Conference on Emerging Trends in Engineering and Management (ICETEM14)
30 – 31, December 2014, Ernakulam, India
173
ELECTRONICS HEALTH RECORDS AND BUSINESS
ANALYTICS: A CLOUD BASED APPROACH
Syed Thouheed Ahmed
M.Tech Scholar, Dept. of Computer Science and Engineering REVA Institute of Technology and Management,
Bangalore - 64
ABSTRACT
Scientific computing in the field on medical requires high computing facility to solve any complex problem.
Cloud Technology has emerged to solve the complex problems with higher computing powers; Since Cloud Technology
is comprised of huge data. Maintaining and using the data in most appropriate way is the current IT’s challenge. In this
paper we investigate a systematic approach of scrutinising the Electronic Health Records in a cloud based environment
using the approach of pattern recognition algorithm. As pattern recognition algorithms belong to larger class of
evolutionary algorithms. The paper proposes intelligent agent based on Pattern recognition algorithm to achieve better
resource utilization in cloud (Big-data) environment and thereby tested with different sizes of EHR requests and analytics
of results has shown better resource utilization and time optimization.
I. INTRODUCTION
Trivial system of treatment practised by a physician is based on paper documents and telephone conversation.
On changing the location or a physician, there is an exchange of previous treatment summary reports in a paper file
format which provides a limited understanding to the physician leading to improper decisions under treatment. Hence to
overcome the drawbacks of trivial approach, EHR (Electronic Health Records) were proposed. In this paper we
investigate the case study on enhancing electronic health records EHR under a cloud based environment developing
business analytics.
EHR can contribute greatly in managing and increasing the cost performance in a developing country like India.
As the healthcare industry is concentrated on developing high-end healthcare facility and deploying maximum
automation in the treatment process leading to the origin and introduction of EHR [1]. EHR is now a grooming up
business concern, attracting the entrepreneurs for the investment by developing itself into a business analytic model. A
business model and a margin of profit could be seen in installation and processing of EHR-cloud and eHospitals
(Electronic Hospitals) by collaborating with the hospital management for sourcing the data in a cloud environment (Third
party trusting)
The rest of the paper is organised as follows, Related Work in EHR and cloud together formulating a business
model is discussed in Session II and Session III discusses the Business scopes and trends related to EHR Investments,
followed by a proposed architectural model in Session IV and the paper is concluded in Session V.
II. RELATED WORK
Many new and advanced approaches have been proposed in the field of EHR and trivial record migration
towards cloud based environment, in this session we have discussed some approaches and they introduction with a case
study[3][4].
INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING &
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Volume 5, Issue 12, December (2014), pp. 173-176
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2. Proceedings of the International Conference on Emerging Trends in Engineering and Management (ICETEM14)
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174
A. Electronic Health Records (EHR)
Electronic Health Records is the new twist in the E-Health system. The trivial records of the patients are now
converted digital, generally it is defined as “An electronic health record (EHR) is a digital collection of patient health
information compiled at one or more meetings at any care delivery point” [2]. A patient's record typically includes
patient demographics, progress notes, problem and side effects, and medications, vital signs, past medical history,
laboratory report information and radiology/diagnosis reports.
Generating and collecting records related to patient from various sources later a migrating the EHR to cloud for
further analysis is challenging. To make the EHR universally acceptable, a defined standards is been proposed by Aden,
Riesmeier, Dogac,.Laleci, G.B [5]
The growing critical mass of clinical data accumulating in Electronic Health Record(EHR) systems is secondary
use (or re-use) of the data for other purposes, such as quality improvementand clinical research. The growth of such data
has increased dramatically in recent years due to incentives for EHR adoption in the US funded by the Health
Information Technology for Economic and Clinical Health (HITECH) Act. The analysis of this data is usually called
analytics (or data analytics).
B. Business analytics
Business analytics and big data (cloud Computing) are being discussed everywhere in today’s IT and hence
some of the teaching methodologies and analytics have been bought forward by Sharda, Asamoah, D.A and Ponna in
Business analytics: Research and teaching perspectives [6]. Technically we can define “Business analytics (BA)”, as a
benchmark to all the methods and techniques, used by an organization to measure the performance and the growth
estimation. It is used to evaluate an entire production, or simply it is performed to identify weaknesses in existing
processes and thereby focusing on meaningful data that will help an organization prepare for future growth and
challenges.
Internally Business analytics is made up of statistical methods that can be applied to a specific project, process
or product. There is very important need for good business analytics to spur the creation of business analytics software’s
and development of an enterprise platform that can mine an organization’s data, measures and pick out meaningful
insights from the outcome. For the insightful mining of data, IT industry has adopted a new trend of cloud computing
which shall be the next identity element in the industry. With the introduction of Cloud, it is possible to erase the
boundaries between technical analytics and commercial tactics used in business productivity.
C. Cloud
A Cloud computing fulfills the long-held dream of computing as a utility and thus represents geography free
computation and IT services delivery at the doorstep. It is a style of computing in which dynamically scalable and often
virtualized resources are provided as service over there. The origin of the term cloud computing is yet unclear. But the
expression cloud is commonly used in science to describe alarge floating and air suspended objects that visually appear
from a distance as a cloud and describes any set of things whose details are not inspected further in a given context.
Cloud Computing is the result of evolution and adoption of existing technologies and paradigms. The goal of
cloud computing is to allow users to take benefit from all of these technologies, without the need for deep knowledge of
Understanding about or expertise with any service.
III. BUSINESS ANALYTICS WITH CLOUD MODELS
Today every company irrespective of being small or big are looking towards the cloud Migration for various
reasons as follows:
• Fast timeline for deployment and aggressive growth plan
• Data Mobility
• Global collaborations
• Optimized IT resource utilization
E-Health and Business Analytics in Cloud
Business analytics handles a particular set of data which is structured. Unstructured data is to be converted to
the structural form for processing in cloud based BA model.
A core methodology in Business analytics is machine learning, which is the area of computer science that aims
to build systems and algorithms that learn fromdata. One of the major techniques of machine learning is data mining,
which is defined as the processingand modeling of large amounts of data to discover previously unknown patterns or
relationships. Asubarea of data mining is text mining, which applies data mining techniques to mostly unstructuredtextual
data. Another close but more recent term in the vernacular is big data, which describes large andever-increasing volumes
of data that adhere to the following attributes:

3. Proceedings of the International Conference on Emerging Trends in Engineering and Management (ICETEM14)
30 – 31, December 2014, Ernakulam, India
175
• Volume – ever-increasing amounts
• Velocity – quickly generated
• Variety – many different types
• Veracity – from trustable sources
With the digitization of clinical data, hospitals and other healthcare organizations are generating an ever
increasing amount of data. In all healthcare organizations, clinical data takes a variety of forms, from structured (e.g.,
images, lab results, etc.) to unstructured (e.g., textual notes including clinical narratives, reports, and other types of
documents)
The growing quantity of data requires that its users have a good understanding of its provenance, which is where
the data originated and how trustworthy it is for large-scale processing and analysis.
Generally the BA is applied on the cloud data for improving the access speed of the EHR, reliable pattern
matching for a searched or given pattern, appropriate data summary result generation on miss match, this entire task
should be performed in a smooth and zeal manner such that the end-user is beneficent.
Fig 1.1: E-Health and Business Analytics in Cloud
Studies using EHR data for clinical prediction have been proliferating. One common area of focus has been the
use of data analytics to identify patients at risk for hospital readmission within 30 days of discharge.
A number of other critical clinical situations have been amenable to detection by analytics applied to EHR and other
clinical data:
• Predicting 30-day risk of readmission and death among HIV-infected inpatients
• Identification of children with asthma
• Risk-adjusting hospital mortality rates
• Detecting postoperative complications
• Detecting potential delays in cancer diagnosis
• Identifying patients with cirrhosis at high risk for readmission
• Predicting out of intensive care unit cardiopulmonary arrest or death

4. Proceedings of the International Conference on Emerging Trends in Engineering and Management (ICETEM14)
30 – 31, December 2014, Ernakulam, India
176
Cast Study: A summary report of patient A in Indian hospital suffering from cancer includes the entire case details such
as age, sex and stage of cancer with current medical treatment status along with recent diagnosed images such as CT or
mammographic (in case of Breast Cancer), which could be now made available in the cloud environment. This cloud is
created on mutual understanding of two or more distinct hospitals from one or more geographical areas. At some
instance, similar sickness case is encountered in New York but the pattern for solving is complicated and it’s a waste of
time and money to start the process of diagnosis from the beginning and prescribe a medical period of observation which
increases the time and thus reflects on the Deeping of cancer .
Hence we make use of cloud model as described in fig 1.1, through which symptoms of Patient B can be
uploaded and the cloud based data analyser tool in cloud environment finds the similar pattern by making use of already
stored data and making use of machine learning algorithms in an efficient manner.
The discussed protocol model is developed and available for public regarding Breast cancer at url: www.tms-
india.org named as Telemammography Services for Rural Indian Women (TMS-India) for remote location data sharing
and demonstrating telemedicine terminology by targeting to the rural Indian population. This site also contains preloaded
health calculator for self-health monitoring and also features breast cancer awareness with detailed informatics and is
supported by a Novel Breast Cancer Detection Technique Algorithm, deigned to detect breast cancer lumps and further
generate an instance summarised report of patient cancer status reviling its level of complexity and pre-medical treatment
to be followed and remote doctor-patient consultation. On majority goal concerned, the cost is reduced with the
migration to cloud.
VI. CONCLUSION
Clearly there is great promise ahead for healthcare driven by data analytics leading in evolvement of business
models. The growing quantity of clinical and research data, along with methods to analyze and put it to use, can lead to
improve personal health system, healthcare delivery and biomedical research and its quality of work. Cloud Based E-
health business analytics will help in predicting, analyzing various health disorders remotely and hence provide effective
health care services with increasing the reality of using existing data by extracting meaningful information for human
benefiter.
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