Running Head: INFORMATION SYSTEM & DECISION SUPPORT SYSTEM
INFORMATION SYSTEM & DECISION SUPPORT SYSTEM
Paul Godfrey, MBA, BSN, RN, MSN Candidate
Rutgers University, Newark NJ
School of Nursing
NINF5210: Information System Principles
Faculty Advisor: LeAnthony Mathews, MSN, RN, CNML, CCRN-P Alumnus
November 20, 2014
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Abstract
Synthesized data yields information. Coronel et al. (2013) explained that “Information is
the result of processing raw data to reveal its meaning” (p6). One common concept between an
Information System (IS) and a Decision Support System (DSS) is the utilization of a system
methodology for a purpose or goal. Both IS and DSS utilize System Development Life Cycle
(SDLC) to accomplish the objective of the system in question. IS could be said to be a subset of
a DSS because information is embedded within DSS to obtain conclusive or suggestive opinions
towards making final decision. The instantiation of information is utilized by a system to offer
suggestions towards the solution of a problem in a DSS. Complex calculations or manipulations
of factual data are involved in a process before the suggestions of a DSS have meaningful
scientific conclusion. Complicated issues could be resolved with DSS while linear non-
complicated issues are solved using IS. DSS is invaluable in the application of medical science in
helping to obtain the best care for patients. Both DSS and IS are generally applicable in many
industries and follows a uniform concept although data and information obtained differs. Nursing
practice benefits tremendously from clinical DSS with respect to obtaining suggestions to
complex nursing processes.
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System Development Life Cycle (SDLC)
Satzinger et al (2012) stated “The System Development Life Cycle (SDLC) identifies all
the activities required to build, launch, and maintain an information system. Normally, the SDLC
includes all the activities that are part of systems analysis, systems design, programming, testing,
and maintaining the system as well as other project management processes that are required to
successfully launch and deploy the new information system” (p6). IS and DSS must follow the
process of the SDLC. All system must have input, user interface, and output. The logic
implemented to analyze input will depend on the objective of the system. The stakeholders of the
project usually identify the purpose or goal of the system. The project charter will define what
the system objective is identified as and defines the resources to be used to for the project. Time,
scope, and resources are the triple constraints of a project. These triple constraints must align as
each modification will affect the other.
To proceed in developing an IS or DSS, identifying the problem to be solved must be
performed. There must be an established need or problem for an IS or DSS system to solve. The
stakeholders must agree on what the problem is and present the problem to system developers.
The system developers will present the solution to the stakeholders. Once agreement of the
problem and possible solution is established, approval to proceed will be given by the
stakeholders. Once approval to proceed is obtained, project planning will be performed by the
project manager and then agreed upon by all stakeholders. As part of the details of the SDLC,
emphasis will detail monitoring the project and methods of communications between all
stakeholders. Performing discovery before development will include thoroughly understanding
the details of the problem. Subject matter experts will be interviewed and answers will be
verified to ensure that a clear understanding of the problem is established.
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The series of final processes in developing either the IS or DSS includes designing
system components. Designing the system components is done with the ultimate goal of solving
identified problems as the system’s success is tied to how the identified problems are solved.
After designing the system by establishing all the business requirements, verifying the functional
requirements, screens, user interfaces, and other activities within the design phase, the next step
proceeds to building the system. The system is built by using a selected programming language.
While using the selected programming language, the syntax and semantics of the selected
language must be adhered to. The final phases of the SDLC commonly performed for either an
IS or DSS including testing the systems, integrating system components, completing system
testing, and final deployment of the solution. (Satzinger et al, 2012, p6)
Characteristics of an Information System (IS)
Stair and Ralph (2012) explained that IS “is a set of interrelated elements or components
that collect (input), manipulate (process), store, and disseminate (output) data and information
and provide a corrective reaction (feedback mechanism) to meet an objective” (p8). The input in
an IS can be patient or business attribute. The industry determines the type of input required as
fields to hold values. The manipulation process will involve actions to be performed on input
before storage. Examples of these actions can be aggregation or comparison of data before
storage. Stored data will be retrieved as a display upon request in a report or simply displayed as
user viewable instant information. The hallmark of IS is the ability to be used to collect data,
synthesize data, and provide information. The application of IS is universal and the concept does
not change as it is applied to different industries for different purposes. Systems that require
known outcomes follow the concept of programmed decision. When a procedure involving set
rules and quantitative methods are used, it is referred to as a programmed decision (Stair and
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Ralph, 2012, p266). Decision of this sort will not require any further system analyses but simply
to relate what is known as information to the user. Two main examples of IS system which will
be further examined in this paper are Management Information Systems (MIS) and Health
Information Systems (HIS).
Management Information System (MIS)
In the world of business, management needs to know how successful the business venture
is becoming or how close it could be to insolvency. The ability to use IS to store business data
and retrieve meaningful information to help in making certain business decisions is invaluable.
MIS is defined to be “an integrated collection of people, procedures, databases, and devices that
provides managers and decision makers with information to help achieve organizational goals”
(Stair and ralph, 2012, p269). The procedure within the MIS involves a process and a workflow
which varies with respect to business type or component of the same business. Different
components of an organization might have MIS to support their functions. Examples of
applications of MIS include the following areas: financial, manufacturing, marketing, human
resources, sales, etc. In a hospital or other health related organizations, MIS is widely used for
management and non-clinical purposes. Most hospitals and health organizations have the
following departments: Human Resources, Marketing, financial department, and other support
departments. Solvency is a requirement of every organization and health organizations are not
exempt from this. It is the goal of all health care organization to utilize effective MIS to make
decisions that will inevitably help the organization to sustainably enable growth. An organization
that cannot effectively utilize dependable well-articulated MIS runs the risk of ineffective
management, closure and possible bankruptcy.
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Health Information Systems (HIS)
The application of IS in the area of HIS involves electronic health records (EHR), patient
health records (PHR), electronic medical record (EMR), and various other ways of electronically
storing and retrieving health related information. HIS is the ability to utilize IS to save health
related data and retrieve information at the request of the user. There are standalone systems
developed with various programming languages being utilized for HIS. Most of standalone
applications use local area networking to share information between users and systems. The
standalone applications offer limited accessibility because of lack of availability beyond the
reach of the local networking environment. Despite the accessibility issue of standalone
applications, it is however a great improvement from the traditional paper documentation which
is tedious and not automated in any form. The ability to establish a relationship between patient
health data and make it available to many care givers is invaluable towards providing best care
outcome. The spread of internet application has given a new dimension to HIS.
EHR relates to individual health information that could be accessible by other
organizations. There has to be a portal that will enable access on demand to authorized users
from different organizations. “EHRs can contribute to public health population-based programs
through improving the reporting and investigation of diseases and conditions that are mandated
for reporting to state and local public health agencies; identifying sentinel diseases, injuries, and
events that can be used to assess the stability or change in the health levels of a population; and
providing data for population and disease registries, such as registries of newly diagnosed
cancers” (Friedman et al., 2013, p1561). The health of the population can greatly be improved if
meaningful use of health information is made available at the point of care. Cost of care will also
be greatly influenced by eliminating or minimizing redundancy in procedures and tests. Ability
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to view all recently completed tests and procedure will help the next point of care clinician to
have access to such information. The Affordable Care Act has a great emphasis on the
meaningful use of health information. Sharing information can be crucial in emergency
situations where health history can be used to make decisions. It is expected that care
organization will agree to participate in using HL7 standard communication protocol to share
health information between each other. Interoperability is an issue of importance and having a
standard of communication helps to breach the gap created by different vendor applications.
Some of the benefits of EHR are improving the quality of care, advancing convenience of patient
care, positively increasing the level of patient participation in their care, positively affecting the
accuracy of diagnoses and health outcomes, instrumental to improving care coordination, and
inevitably bringing about cost saving in care process and increasing efficiencies of practice
(www.healthit.gov).
PHR is the ability of individuals to be proactive in securing their health information and
have the ability to share such information with authorized parties. “The focus group discussions
indicated that a PHR can be seen not simply as a record of care but also as an educational tool
with three functions: to engage the patient with their care and information about that care, to
promote interaction with the healthcare team (doctors, optometrists, pharmacists, nurses, etc.)
and to educate both parties in the therapeutic relationship by providing both with better
information.” (Sommer et al., 2013, p630). Institutional support of PHR will help to address the
issue of standardization of information. Jones et al. (2010) explained that the issue of
standardization has to be addressed for both EHRs and PHRs. Finding standardization solution
will enable the movement of patient medical record from one facility to another. “MyChart,
developed by Epic, is one of the most widely used PHRs by health systems such as Kaiser
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Permanente” (Jones et al., 2010, p246). Many private vendors provide PHR to users and
accessibility is usually through the internet which allows authorized users to have access to
patient record with a click of a mouse from any location where internet access is available.
Privacy and protection of health record is an issue but the benefits are truly immeasurable. In a
situation like a natural disaster where patient record is permanently destroyed, it will be a great
idea to have backup copies of the same record accessible through the internet. In an emergency
situation where distance is an issue, it will be lifesaving to have access to patient data at the point
of care.
EMR is another example of HIS. It is patient health information accessible within the
same facility. This is a replacement of the paper documentation within the clinical activities of
patient care. EMR should contain medication prescriptions, diagnoses, nurse’s notes, doctor’s
documentations, pharmacy documentations, and other interdisciplinary team (IDT) member’s
documentations. Most of the information contained within the EMR may not be easily shared
with outside facilities. Inter facility sharing of EMR is usually not available. Most information
within EMR could be printed or exported as formatted data to be shared when asked by other
facility if the treating facility policy allows for such sharing. HIPAA regulations will always be
observed in all cases involving sharing any health related information of a patient. EMR is
always available for all the IDT to review while providing care to patients. Patients can ask to
see what’s contained within their EMR while in the facility or designate a representative to ask
for the content and the facility will be obligated to share such information. If there is a need for
legal review of care received while in a facility, the EMR is trusted information that should
reveal the details of care provided.
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The alteration of EMR could result in legal implication as it is a trusted record of
activities. As with other IS, users will have interface to enter data and save data. Information can
be retrieved through display or report request. Some EMR contains task functionality which
enables users to distribute tasks within a workflow. Nurses can share a workbasket to document
or perform tasks which should be attributed to the EMR. Sharing work list or work queue
enables user groups to coordinate all necessary tasks associated with providing care to patients
and data from the patients response or other related care activities will in turn serve as input into
the EMR.
Characteristic of Decision Support System (DSS)
Stair and Ralph (2012) explained that DSS “is an organized collection of people,
procedures, software, databases, and devices used to help make decisions that solve problems”
(p288). The general understanding of a system connotes using a procedure by using logic and
algorithm, providing software by utilizing syntax and semantics of a programming language,
developing a database to be used for data entity definition and storage, and finally utilizing
devices for architecture and entry/retrieval of data as information according to the manipulations
of the procedure. DSS utilizes all the attributes of the system nomenclature but primarily
effectively helps with decisions relating to unstructured or semi-structured business problems.
DSS has to have a repository of information which will be manipulated to offer opinions or
possible solutions to a problem to the user. There has to be a learning period for a DSS which
could be the period of entering into the DSS known facts that will help the system when asked or
inquired to offer suggestion. In patient care, certain diseases have established signs and
symptoms, and when stored in a system, suggestion could be offered to the user when similar
signs and symptom are manifested and presented. DSS does not make the decision but offers
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support to the user in issues that are complex. Certain calculations are complex in nature and
when proper procedure is established in DSS, the system can make faster calculation and offer
supportive decision to the user.
Applications of DSS in Nursing Practice
Nursing process includes assessment, nursing diagnoses, planning, implementation, and
evaluation. Evidenced based practice is the pillar upon which the nursing process is built. A DSS
cannot implement the nursing care plan but will offer a suggestion based on known process.
Weber (2007) estimated that the first computer based DSS was developed in the 1980’s. In
different practices of nursing, there are established workflows when certain attributes of care
process is identified. These established workflows can be automated and presented as a DSS to
help the nurse in making decisions relating to patient care effectively. Knowledge acquisition
and repository of such knowledge will be essential to establishing procedure for a DSS to
function effectively. Wills et al. (2010) explained that “a variety of systems and technologies
support knowledge creation in the clinical environment, including neural networks, data mining
techniques, Bayesian methods, and many others. These technologies make it possible for
knowledge to be created from disparate data sources and used to support the clinical processes of
diagnosis, treatment, monitoring and prognosis” (p569). Nurses use varieties of DSS in different
areas of practice to help support and make effective decision regarding care for patients.
Application of DSS in Nursing Practice Related to Non-Traditional In-Patient Care
Care coordination outside traditional inpatient facility connotes high task activities. Many
care organizations are focused on caring for populations within the community. Zeomega is a
health information provider corporation based in Texas and stipulated that they have provided a
DSS to help organizations involved in care management and care coordination
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(www.zeomega.com). Zeomega is offering an application called Jiva which has embedded task
management and a personalized plan of care process. Jiva qualifies as a DSS because part of the
functionality is to offer a set of goals and interventions for a member when the user through the
user interface enters the problems being presented by a member. Jiva offers configuration of a
plan of care which will create a relationship between problem, goals, and intervention. This
information is stored as a repository of knowledge and upon request by the user; the system will
in turn suggest goals and interventions to a problem. The clinician will either accept all the
suggested interventions or select what is applicable to a member. Zeomage explained that “Jiva
revolutionizes care management” (www.zeomega.com).
Some of the functionalities of Jiva is stated by ZeOmega to include “integrated real
time rules-driven workflow application that promotes transparency between utilization
management, care management and disease management functions; embedded clinical
analytics to stratify the population risk, identify gaps in care and deliver personalized care plans;
integrated workflow for health, wellness and lifestyle support programs complemented by
content from health risk assessments and clinical protocols and business rules; capabilities
for multi-channel communications that can deliver personal health records, patient decision aids,
health management tools, clinical content for health education and decision support tools at the
point of care; and the ability to exchange data with external systems, consolidate information
across disparate data sources and present this information through web services to physicians,
individuals and care managers” (www.zeomage.com).
Applications of DSS in Nursing Practice Related to Smoking Cessation
Sookyung et al. (2013) presented a research that involved the School of Nursing at
Columbia University, which was conducted in 2002. In this research, it was stipulated that
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Advanced Practice Nurse (APN) students will keep a clinical log which will contain patient
encounter data documentation, patient diagnoses information relating to nursing and medical
diagnosis, and then documentation of nursing interventions using mHealth platform. This
information was utilized “as a guideline-based decision support system (DSS) for smoking
cessation and was integrated into the mHealth clinical log and a randomized, controlled trial was
conducted to compare adherence to guideline-based care between those randomized to mHealth
DSS versus no DSS for smoking cessation” (Sookyung et al., 2013). As part of the personalized
plan of care consisting of diagnostics, medication, procedure, patient teaching, and referrals, the
mHealth DSS was used to guide RNs and APN in all phases of decision making. (Sookyung et
al., 2013). It was concluded that by incorporating evidence based practice into the workflow
within mHealth DSS, it can invariably assist nurses in managing a smoking cessation plan of
care and potentially expand the nurses’ roles in making referrals and providing helpful
information to smokers with the ultimate goal of encouraging smoking cessation (Sookyung et
al., 2013).
Applications of DSS in Nursing Practice Related to Critical Care
In the area of critical care, Weber (2007) explained that “the two factors inherent to
decision making in critical care settings that have received the most study are the elements of
uncertainty and the risk” (p582). For DSS to be effective in the area of critical care for nursing
practice, attributed factors which include a daily score of acuity and mortality rate and detailed
predictive equations with links to repository of patient database must be available. (Weber,
2007). There has to be an established relationship between the attributed factors. The
aforementioned factors will further draw inference from patient disease condition, severity of
disease, and chronic health problems (Weber, 2007). The integration of these factors will be
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statistically analyzed to come up with chances of occurrence as a probability related to patient
outcome. “Consideration of these common patient features allows the system to anticipate a
patient’s response to treatment and predict the probability of specific patient outcomes” (Weber,
2007). The effectiveness of the DSS is based on the reliability of the stored information and how
widely applicable the decision could be to all patients (Weber, 2007).
Implications of DSS for Nursing Related to Administration, Education, and Research
Clinicians were able to manage chronic disease like HIV by utilizing the functionalities
of a DSS called FastTrack (Robbins et al., 2012). “With informatics expected to play a crucial
role in improving efficiency and lowering the cost of health care in the United States, it is critical
to demonstrate meaningful use of the EMR” (Robbins et al., 2012, p 765). Research into the
applications of DSS in patient care with major emphasis on helping nurses to make informed
decision is growing and fruitful. Kaparthi and Woodlief (2005) explained that DSS related to
health care administration primarily focuses on the managerial issues of cost and efficiency of
operation. Medical DSS are geared towards identification and treatment of diseases. Some of the
applications of medical DSS are in the areas of medical diagnoses, therapeutic or intervention
suggestions, prognosis suggestions, and medical surgical solutions (Kaparthi & Woodlief, 2005).
Education is the ability to learn and implement better and proven ways of performing a
task or reaching a set goal. Nursing practice is intertwined within the concept of evidence based
practice. DSS offers a learning process and gives the nurse the ability to learn from a repository
of proven solution. It could be a DSS highlighting proven nursing assessment methodology, it
might be a DSS offering nursing diagnoses based on established assessment analysis and results,
it might be a DSS related to nursing interventions based on known nursing diagnoses. DSS will
help the nurse to develop a personalized plan of care plan which is invaluable in helping the
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patient to obtain the best and optimal care. Nursing administration relies on DSS to provide a
benchmark or standardized workflow with respect to complex nursing process. Ongoing research
helps to equip the DSS with up to date information in the required area of expertise. Evidenced
based practice relies on research to ascertain and verify best practice. Good research
methodology will invariably yield reliable input into DSS.
Advantages and Disadvantages of DSS in Nursing Practice
The hallmark of DSS is the inherent advantage of offering solutions to complicated non-
structured problems. Some nurses have argued that DSS seems to suggest one solution fits all
problem approach. Bright et al. (2012) explained that a clinical DSS is “any electronic system
designed to aid directly in clinical decision making, in which characteristics of individual
patients are used to generate patient specific assessments or recommendations that are then
presented to clinicians for consideration” (p29 ) . DSS has favorable effect on articulating
treatment interventions, offering preventive care services, and propagating clinical studies within
diverse systems (Bright et al., 2012).
The perception that clinical DSS is suggesting solutions to the clinician is a view held by
some nurses. This view leads to push back when the idea of implementing a clinical DSS is
introduced. As part of the nursing informatics team in my organization, I witnessed this push
back when a new DSS was being introduced. Many clinicians view this as an intrusion and
reduction of their clinical expertise. They argue that a DSS is making clinical decisions. This
argument is not grounded on the true proven functionalities of clinical DSS.
Kuziemsky et al. (2005, p410) identified the following DSS theoretical models along
with their advantages and disadvantages:
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DSS Theoretical Model Advantages Disadvantages
Hypothetico-Deductive
Approach
Identifies differential
diagnosis and cyclical pattern
of clinical reasoning
Does not consider decision
making in different contexts
nor different expertise levels
Argumentative Approach Different types of reasoning
take place in different
contexts; decision deriving
and decision justification
require different evidence
Theory is presented as
conceptual and not validated
through research; does not
address evaluation of
decisions made
Making managerial health
care decisions in complex,
high velocity environments
Recognizes adaptation of
knowledge for integration into
new situation; considers
impact of work practices
No evaluation framework or
recommendations of how to
incorporate the multiple
decision making influences
Legal and Ethical Implications of DSS and IS
Legal implications of IS could be ignited when the system performance and ability to
yield intended result is lacking. Poor system performance and non-reliability could lead to legal
ramifications especially when such system affects patients care outcome. An IS used as a
repository to steal PHR, EMR, and EHR and then sold for business profitable purposes is good
example of unethical application of IS. Patient information cannot be shared with any
unauthorized party which is in violation of the HIPAA regulation. “In the United States,
regulations developed by the Office of the National Coordinator and the Centers for Medicare
and Medicaid Services to strengthen the functionality of electronic health record systems
(meaningful use regulations) encourage practices to engage patients in care through information
technology, such as personal health records. Although patients appear interested, practices
cannot meet this need without infrastructure, workflow, and cultural changes” (Krist et al., 2014,
p418).
Legal and ethical implications of DSS are rooted into the reliability of the solutions
suggested by DSS, safety of the application of the solution, flexibility of the system to allow for
corrections when necessary, unambiguity of the suggested solution, implication of erroneous
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solution to patient health, etc. “The decision to withhold or withdraw care is complex, and
ethical values are inherent in decision making because there is often no single correct decision”
(Weber, 2007, p583). If a DSS is used to withhold intervention and the result yields become
unintended negative health outcome, legal ramification may ensue. Health is on a continuum and
evidence based practice is a continuum as well. A DSS has to adapt to new research and trial
findings and avoid conclusive suggestions while maintaining the ability to analyze complex
processes and provide meaningful output to users.
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