G1803044045

IOSR Journal of Computer Engineering (IOSR-JCE)
e-ISSN: 2278-0661,p-ISSN: 2278-8727, Volume 18, Issue 3, Ver. IV (May-Jun. 2016), PP 40-45
www.iosrjournals.org
DOI: 10.9790/0661-1803044045 www.iosrjournals.org 40 | Page
Electronic Health Records Information Security Dynamics for
EHR Projects
Ricardo Matos Chaim, Phd1
,Andre Amaro Toffanello, Msc 2
, Joao Gondim,
Msc3
,Ricardo Staciarini Puttini4
,
1,2,3,
Universidade De Brasília (Unb) Universidade De Brasiliabrasilia – Brazil Brasilia - Brazil
Universidade De Brasilia Phd
4
Brasilia - Brazil Universidade De Brasília (Unb)
Abstract: S ecuring information assets in National Electronic Health Record project is critical and complex.
This research examined the effect of investing in this kind of project using S ervice Oriented Architecture and a
system dynamics model that includes many concerns to analyze interdependencies between factors and explore
feedback effects that emerge from its inherent dynamics.
Keywords: S ervice Oriented Architecture; S ecurity policies; System Dynamics modeling; Electronic Health
Records S ecurity
I. Introduction
Managing risk security for Electronic Health Records information assets requires big data tools and
technologies in order to cope with the huge amount information that comes from hospitals, laboratories, clinics
and the other agents involved on a national scale project.
To get interoperability of many systems on distinct sites and environments, service oriented
architecture (SOA) solutions are essentially distributed computing solutions and the security aspects of these
solutions become complex and require a structured approach to design so as to prevent that different distributed
components adopt incomplete security mechanisms or even incompatible, causing degradation in the desired
security level for the environment.
SOA is a specialized architecture and makes direct reference to the Enterprise Architecture of the
health applications, in particular, issues related to high availability and resilience of the environment are main
concerns of the architecture.
Fig 1: Architecture Framework Source: Adapted from OASIS Reference Model for Service Oriented
Architecture Version 1.0 p. 5.
The IHE ATNA (Audit Trail and Node Authentication) profile describes a basic level of security
through (a) functional access controls, (b) security audit log and (c) secure network communications. This is a
standard member of the interoperability architecture CNS health and the National HER (Electronic Health
Records), (to be) implemented in the service bus.

Electronic Health Records Information Security Dynamics For EHR Projects
Fig 2: IHE Integration Profiles Infrastructure
Source: (IHE ITI_TF Volume 1)
The IHE Profile BPPC (Basic Patient Privacy Consent) establishes a method for creating patient
privacy consent form to be used to enforce a privacy level suitable for use information. Although this profile is
not directly related to technological issues of security, which are the focus of this assessment, it directly
influences the business issues that drive the Security Architecture.
Fig 3: Overall strategy to EHR´s project using SOA and Oracle
Source: Oracle
This researchs aims to adapt Forrester´s market growth model in order to get insights of policies to
guide decision making and to study a feedback loop structure that determines the growth and stability of EHR
(Electronic Health Records) projects . Forrester states that “the complexity of these systems usually precludes
intuitive determination of how a policy change will affect the total system”. The idea is to get a simulation
model of the feedback structure and policies to try policy changes to see how the
system reacts on different conditions and premises.
To place the issues into perspective, this paper has three sections. First, it discusses and overview of the model.
Next, discusses ways to model SOA security issues for EHR projects by the use of system dynamics method.
Finally, in the conclusion, there are considerations regarding the use of a multi-paradigm approach to address
SOA security typical problems.
II. Overview Of T He Model
Service Oriented Architecture and cloud computing provides the IT infrastructure, design patterns and
other artifacts to an IT company get intrinsic interoperability between software programs and achieve other
benefits like increase software federation, increase business and technology alignment, increase vendor
diversification options, increase return over investment, increase organizational agility and reduce IT burden.
Central in the model is the service bus that encompass agnostic and non-agnostic services that influence the
revenues that come from their commercialization or even by its utilization or reuse. [6]
The preceding concepts will be exemplified in order to show their utility and how it can be used by a
SOA security research once it may be considered an extension of IT governance or, in a broad sense, of
corporate governance as a whole and some key activities that were revealed by the diagnosis did on an
important Brazilian governmental IT organization as being part of it are:
 Managing the portfolio of services;
 Managing the service lifecycle;

 Using policies to restrict behavior;
 Monitoring performance of services;
 Managing how and by whom services are used;
The utilization of SD can add another way to see interactions within the company, within the market,
and between the two. In this paper, a model with no influences of the outside
can be made in order to represent their behavior, the social-economic and political environment to provide
deeper insights by simulation experiments and the flows of goods, services, money and information. Fig.1
shows the main relations on developing a secure information SOA based EHR Project implementation:
Delivery
delay +
B
3
Security Incidents
-
SOA Security + +
+ Research and
Development
+ R1 Credibili
ty
+
+
Quality
Organi
zationa
l
-
Maturit
y
+
Productivi
ty
+
+ Security
Contro
ls
Infrastructure
B1 +
+ C
os
ts
B
2
- R2
Risks
Fig 4: Cause and effects on factors for a SOA Security Site
The diagnosis revealed that the management of the demand, the quality, the credibility, the
organizational maturity framework and investments in the IT infrastructure are central on a good SOA security
program and that there is following reinforcing and balancing loops governing its dynamics:
R1: SOA security, organizational maturity, productivity, credibility. This loop focuses on productivity
as a consequence of the adoption of an organizational security framework and the consequent enhance on
productivity.
R2: SOA security, organizational maturity, quality. This loop is about the quality obtained as a consequence of
the adoption of an organizational security framework;

B1: SOA security, organizational maturity, controls, costs, credibility. This loops considers the enhance on costs
because the growth of controls on the adoption of the organizational security framework; B2: SOA security,
organizational maturity, controls, costs, risks, Security infrastructure, quality. This loop considers that security
infrastructure investments cause the growth on quality; B3: SOA security, organizational maturity, controls,
costs, risks, Security infrastructure, quality, Security incidents, delivery delay. This loop considers that security
infrastructure investments causes enhance on demand that may cause delivery delays if it exceeds the capacity
available.
III. Modeling Soa Security Issues
Planning under uncertainty and considering operational risks inherent of IT enterprises requires reliable
tools to do better analysis and to manage IT assets in order to set policies that assure good performance and
credibility to such organization.
Thus, a decision making simulation model based on an adaption of Forrester’s’ Market
Growth model[15][11][12] and on the system dynamics method were considered in order to represent
interactions of intended rational policies in the study of dynamics that can arise of the complex combinations of
SOA Architecture, Secure Infrastructure and resources available factors, principles and structures.
In Fig. 5, the model represents a governmental IT agency with functions and structures that share
controls and together have an organizational security program that can produce an acceptable level of
productivity and credibility that gives better governance if the costs are maintained on appropriate levels.
Though revenues were previously budgeted, in the model they are used to express how many investments on IT
infrastructure are permanently required in order to assure good levels of quality and thus, assure better security
results. The focus is on those resources to be leveraged for SOA to deliver value to the business.
Fig 5: A System Dynamics Model of SOA security information adoption
Modeling is based on abstraction, simplification, quantification, and analysis [1]. The modeling process
is an iterative learning process that encompass many steps like getting information about the real world or the
problem articulation, structure a dynamic hypothesis, formulation or transformation of the dynamic hypothesis
in many diagrams, testing and the policy formulation and evaluation [12] to assure that “the model’s structure is
sound and that it is capable of reproducing the dynamic symptoms of the original problem” [11]
For system dynamicists, once a decision is based on the observed state of the system, there are a
structure of interacting feedback loops and it implies a circularity of cause and effect, where the system
produces the decision which produces the action which produces change in the system [7]. Within the feedback
loop there are level variables that mean accumulations within the system and mathematically are integrations.
Rates variables that are system condition at any point of time represent the system activity and are the policy
statements in the system which defines how the existing conditions of the system produce a decision stream
controlling action.
To Forrester, “speak of systems implies a structure of interacting functions. Both the separate functions
and the interrelationships as defined by the structure contribute to the system behavior”[15]. Rates are not
instantaneously observable once they depend only on the values of the level. Rate equation defining a rate
variable is a statement of system policy that describes how and why decisions are made. “A policy statement
incorporates four components - the goal of the decision point, the observed conditions as a basis for decision,
the discrepancy between goal and observed conditions, and the desired action based on the discrepancy” [7].

Fig 5 shows for addition of development capacity. The adition of capacity is contingent and can benefit
from Services reusability once it can be commercialized and assure a way to supply the demand for services on
an EHR context. Once it is a software component, it can be delivered immediately so the adequate expansion of
development capacity is to assure timing on the development of new services and to reduce pressure for
expanding capacity.The idea is to relate usability of services and the income that it can generate to assure
investments on infrastructure. Once high availability and resilience of the environment are main concerns of the
architecture.
IV. Conclusions And Future Research
A core objective of service-oriented computing is to achieve a state of intrinsic interoperability among
software programs delivered as services[6]. On a SOA security management problem, SD aid to comprehend the
complexity involved on EHR projects (different information, different decision rules, and different situations)
with the macro behavior of the system [9], [4].
The agents have several interaction rules and, by simulation, it is possible to explore the emergent
behavior along the time and the space [2], [3]. This modeling technique does not assume a unique component
that takes decisions for the system as a whole. Agents are independent entities that establish their own goals and
have rules for the decision making process and for the interactions with other agents.
As in Forrester’s “market growth model, this model encompass bounded and intended rationality in its
decision making. The SOA security decision making process is intended rational if “it would produce
reasonable and sensible results if the actual environment were as simple as the decision maker presumes it to be,
that is, if the premises accepted by the subject were true” [12] creating feedbacks or other complexities.
In order to reduce the complexity of decision making and to cope with bounded rationality because the
incapability of processing much information and complexity, Sterman argues that “s ince optimal decision
making with perfect models is impossible, people and organizations have developed a number of ways to
simplify the task of decision making” [12] like:
(a) stablishing routines that “may be informal or highly codified protocols”,
(b) using rules of thumb`(decision making heuristics) that “are based on simplified, incomplete models of
the problem situation” and “tend to rely on relatively certain information readily available to the decision
maker”;
(c) managing attention by “directing the attention of its members toward some cues and away from others” and
can include “formal reporting relationships, agenda setting, the geographical structure of the organization and
physical layout of its facilities, and accounting and information systems”;
(d) goal setting by setting “goals and adjust their behavior in an attempt to meet them” instead of ”making
decisions by explicitly solving optimization problems”. Sterman also refers to the “behavior effort is reduced
once a satisfactory solution to a problem is found or a satisfactory level of performance is attained”; and,
(e) problem decomposition when
“limited information processing capability forces people to divide the total task of making a decision into
smaller units.
Sterman considered that “cognitive limitations and the other bounds on rationality mean decisions are
often made as if there were no time delays, side effects, feedbacks, or nonlinearities” to conclude that “since real
systems often involve considerable dynamic complexity, decisions made in this fashion often cause policy
resistance, instability, and dysfunction”[14].
Setting specific goals provides decision makers with a concrete target against which they can compare
the actual performance of the system and initiate corrective action when there is a discrepancy. The more
concrete and specific the goal, the easier it is for people to determine which information cues are important and
which can be ignored and to decide which actions to take to reach the goal.[12].
References
[1]. Anylogic. Available at: < http://www.anylogic.com/>. Acessed in: January, 08th
, 2013.
[2]. Chaim, Ricardo Matos; STREIT, Rosalvo Ermes. IT organizations governance: combining SD, Agent based Modelling and fuzzy
logic to adress Dynamic Asset and Liability Management. In: 26th International Conference of the System Dynamics Society, 2008,
Athens, Greece. Proceedings of the 26th International Conference of the System Dynamics Society. Hoboken, NJ, Estados Unidos :
Wiley Blackwell, 2008. p. 42-42.
[3]. Chaim, Ricardo Matos. Combining ALM and System Dynamics in IT organizations. In: 24th International Conference of System
Dynamics Society, 2006a. Proceedings of the 24th International Conference The Netherlands: Wiley Inter Science, 2006. Available
at: <http://www.systemdynamics.org/conferences/2 006/ proceed/papers/ CHAIM315.pdf>. Acessed in: 30 de setembro de 2006.
[4]. Chaim, Ricardo Matos. 2007. Gestão das informações sobre riscos de ativos e passivos previdenciários em fundos de pensão:
associação entre a Dinâmica de Sistemas e o Asset and Liability Management (ALM). PhD dissertation, Information Science
School, University of Brasilia, Brazil.
[5]. Edmonds, Bruce. Simulation and complexity: How they can relate. Centre for Policy Modelling Discussion Papers, CPM Report
No.: CPM-03-118, 2003.
[6]. ERL, Thomas; Bennett, Stephen G; Carlyle, Benjamin ;Gee, Clive ; Laird, Robert ; Manes, Anne Thomas; Moores, Robert;

Schneider, Robert; ,Shuster, Leo; Tost, Andre ;Venable,
[7]. Chris; Santas, Filippos. SOA Governance: Governing Shared Services On-Premise and in the Cloud. Boston, Pearson
Education,Inc. 2011.
[8]. Forrester, Jay W. Market growth as influenced by capital investment. Boston, Industrial Managament Review, MIT Sloan School,
vol. 9, no 2, 1968.
[9]. Gilbert, Nigel. Simulation: An emergent perspective. Draft Paper, Department of Sociology, University of Surrey, 1995.
[10]. Lempert, Robert. Agent-based modeling as organizational and public policy simulators.
[11]. Proceedings of the National Academy of Sciences of the United States of America (PNAS), vol. 99, suppl. 3, p. 7195 – 7196, 2002.
[12]. Linthicum, David S. Cloud computing and SOA convergence in you enterprise. Boston, Pearson Education, 2011.
[13]. Morecroft, John. Strategic Modelling and Business Dynamics. NJ-USA, Wiley,2007.
[14]. Sterman, John D. Business Dynamics: Systems Thinking and Modeling for a Complex World. Boston, Irwin McGraw-Hill, 2000.
[15]. Streit, Rosalvo E. Um modelo baseado em agentes para a análise da governança regulamentar do sistema financeiro. PhD
dissertation, Management School, Federal
[16]. University of Rio Grande do Sul, Brazil, 2006.
[17]. Sterman, John D. Learning from Evidence in a Complex World. March 2006, Vol 96, No. 3. American Journal of Public Health.
[18]. Forrester, Jay W. Market Growth as Influenced by Capital Investment Originally published in the Indus trial Management Review,
MIT Sloan School, Vol. 9, No. 2, 1968. Reprinted in: Forrester, Jay W, 1975. Collected Papers of Jay W. Forrester. Waltham, MA:
Pegasus Communications. 284 pp. Available at, Acessed on 11.10.2015.

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