PGodfrey_IS &_DSS_Term_Paper

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

INFORMATION SYSTEM & DECISION SUPPORT SYSTEM GODFREY, P1

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.


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.


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


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.


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


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

http://www.healthit.gov/


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.


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


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


(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

http://www.zeomega.com/

http://www.zeomega.com/

http://www.zeomage.com/


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


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


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:


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


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.


References

Bright, T. J., Wong, A., Dhurjati, R., Bristow, E., Bastian, L., Coeytaux, R. R., & Lobach, D.

(2012). Effect of Clinical Decision-Support Systems. Annals Of Internal

Medicine, 157(1), 29-43

Coronel, C., Morris, S., Rob, P., (2013). Database Systems: Design, Implementation,

and Management, Tenth Edition, Course Technology, Boston, MA

Friedman, D. J., Parrish, R. G., & Ross, D. A. (2013). Electronic Health Records and US Public

Health: Current Realities and Future Promise. American Journal Of Public

Health, 103(9), 1560-1567. doi:10.2105/AJPH.2013.301220

http://www.healthit.gov/providers-professionals/benefits-electronic-health-records-ehrs,

retrieved 10/15/2014

http://www.zeomega.com/what-we-provide/jiva/, retrieved 11/1/2014

Jones, D., Shipman, J., Plaut, D., & Selden, C. (2010). Characteristics of personal health records:

findings of the Medical Library Association/National Library of Medicine Joint

Electronic Personal Health Record Task Force. Journal Of The Medical Library

Association, 98(3), 243-249. doi:10.3163/1536-5050.98.3.013

Kaparthi, S., & Woodlief, N. F. (2005). Information Systems and Health Care-

VI: Medical Nomograms with Decision Support Systems: A Case Study and an Enhanced

Architecture. Communications Of The Association For Information Systems, 16435-456

Krist, A. H., Woolf, S. H., Bello, G. A., Sabo, R. T., Longo, D. R., Kashiri, P., & ... Cohn, J.

(2014). Engaging Primary Care Patients to Use a Patient-Centered Personal Health

Record. Annals Of Family Medicine, 12(5), 418-426. doi:10.1370/afm.1691

Kuziemsky, C. E., & Jahnke, J. H. (2005). Information Systems and Health Care

http://www.healthit.gov/providers-professionals/benefits-electronic-health-records-ehrs

http://www.zeomega.com/what-we-provide/jiva/


V - A Multi-Modal Approach to Health Care Decision Support

Systems. Communications Of The Association For Information Systems, 16, 407-420.

Robbins, G. K., Lester, W., Johnson, K. L., Yuchiao, C., Estey, G., Surrao, D., & ... Freedberg,

K. A. (2012). Efficacy of a Clinical Decision-Support System in an HIV Practice. Annals

Of Internal Medicine, 157(11), 757-766.

Satzinger, J.W., Jackson, R.B., Burd, S.D. (2012). System Analysis and Design in a

Changing World, Sixth Edition, Course Technology, Boston, MA

Sookyung, H., Hodorowski, J. K., Nirenberg, A., Perocchia, R. S., Staats, J. A., Velez, O., &

Bakken, S. (2013). Mobile Health-Based Approaches for Smoking Cessation

Resources. Oncology Nursing Forum, 40E312-E319. doi:10.1188/13.ONF.E312-E319

Stair, R. & Reynolds, G. (2012). Fundamentals of Information Systems, Sixth Edition,

Course Technology, Boston, MA

Weber, S. (2007). Critical care nurse practitioners and clinical nurse specialists interface patterns

with computer-based decision support systems. Journal Of The American Academy Of

Nurse Practitioners, 19(11), 580-590. doi:10.1111/j.1745-7599.2007.00262.x

Wills, M. J., Sarnikar, S., El-Gayar, O. F., & Deokar, A. V. (2010). Information Systems and

Healthcare XXXIV: Clinical Knowledge Management Systems--Literature Review and

Research Issues for Information Systems. Communications Of The Association For

Information Systems, 26(26), 565-597.

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PGodfrey_IS &_DSS_Term_Paper