Interactive System: Clinical Decision Support System in Healthcare

This document discusses the concept of an interactive system, specifically focusing on the clinical decision support system in healthcare. It explores the usability requirements, evaluation methodology, and findings of the system. The interactive system serves as a medium of communication between computers and humans in the healthcare sector.

INTERACTIVE SYSTEM
INTERACTIVE SYSTEM
Name of the Student
Name of the University
Author Note

1INTERACTIVE SYSTEM
Executive Summary
Clinical decision support system is one of the important tool in the health care sector. The
bedside nursing clinical decision support system is an example of user interactive system. It
helps the nurses in handing the critical situation of the patients. Accordingly, the nurses take
the decision of the further steps that is required. The design, the infrastructure and the
implementation of the support system helps the nurses clinical decision support system
mostly deals with the usability of the decision support system in the complex field of health
care. The system helps in the effective usability of the resources. The report discusses about
the interactive system and the way it serves as medium of communication between computer
and the human being.

2INTERACTIVE SYSTEM
Table of Contents
Interactive system and its users..................................................................................................3
The Use Cases............................................................................................................................4
The Usability Requirement........................................................................................................4
The Evaluation Methodology.....................................................................................................5
The evaluation............................................................................................................................6
The Findings of the Evaluation..................................................................................................9
References................................................................................................................................11

3INTERACTIVE SYSTEM
Interactive system and its users
Interactive system is an invention of the new technology, completely based on the
computer systems. Its features are that it helps in interaction between the computer-based
system and the humans. The most important that the interactive system need to consider is
about the human capabilities. Clinical decision support systems used in nursing is a type of
interactive system (Gephart, Carrington and Finley 2015). The clinical decision support
system serves as one of the important tools in the field of health care sector. The clinical
decision support system comprises of number of different tools that helps in health care
sector. It is mostly associated with improving the health of the patient. The clinical decision
support system comes with a diversity. It helps in maintaining the critical condition of the
patients. The nursing department present in the health care sector mostly uses it (Sockolow et
al., 2014). The main objective behind the designing and implementation of this system is to
help the nurses in managing the critical cases in a improve manner. The clinical decision
support system helps in preventing the worst cases. The main reason behind the success of
the clinical decision support system was the involvement of a user interface that is healthy in
nature (Sheehan et al., 2013).

4INTERACTIVE SYSTEM
The Use Cases
The use case helps in analysing and identifying the process that can help in
understanding the way the interactive system is operated. The entire system is computerized
and number of requirements are there that need to be fulfilled. With the help of the interactive
system, the doctor is able to access all the data related to the patient and is able to display the
data. On the other hand, the nurses are able to read, display and can make update in the
system regarding to the information of the patient. The interactive system helps the nurse in
analysing the data so that the frontline nurses is able to make the required report so that the
further steps can be taken properly. The patient is able to access the data in order to view,

5INTERACTIVE SYSTEM
change and check the status. The bedside clinical decision support system not only helps the
patients at the same time provides full assistance to the nurse and the doctor.
The Usability Requirement
The clinical decision support system comprises of several steps that are essential the
clinical decision support system follows the UFuRT framework. The framework helps in
keeping the record on track and easily detect the problems (Hum et al., 2014). The usability
requirement is mentioned based on the four vital steps. The first step is the user analysis,
which helps in the identification of the user, which is one of the requirement. The
requirement of the users is transferred into the requirement of the system design process. The
next requirement is related to the function analysis that aims in generating the required
description related to work (Fossum et al., 2013). This step requires the analysis of different
aspects related to the dimensions, relations and operations. The third requirement is based on
the representational analysis. The representational analysis is related with the process of
design and the method to identify and implement the system. This requirement helps in
giving users efficiency as well as the user productivity (Amland et al., 2015).The last
requirement is related to the task in which the requirement is to identify the step related
specifically to the users. The requirement helps in using the system more easily. The system
undergoes a very high level of functional analysis and the task analysis is not performed in
the same stage were design is done. To study the requirement of the software the UFuRT
framework is considered. The analysis requires the complete domain knowledge about the
flexibility of the clinical decision support system (Lau et al., 2017).
The Evaluation Methodology
The evaluation method is completely based on the framework. The framework guided
by the evaluation of the former usability. The framework comprises of the user, its function,

6INTERACTIVE SYSTEM
representation and the analysis of the task. The overall aim of the entire decision system is to
look after the patient safety issues during the critical stages of change (Moss and Berner
2015).The nurse first identifies the patient symptoms and then comes to an evaluation. Based
on the evaluation the next steps that are required for the patients is decided. With the help of
the clinical decision support system tools, the error in the diagnostic can be prevented. The
nurse those are working in the frontline do not have sufficient training related to medical. The
system is developed with high specification features related to the product and the
implementation is flexible. The method include the process of interviewing users in order to
identify the clinical decision support system. The method identify the requirements and the
functions that are listed and the operation of the system in which it is performed (Gephart,
Carrington and Finley 2015). The method is used to improve the method of the symptom
recognition and its evaluation. The nurse are the first person who helps in diagnosing the
symptoms. After the nurses, diagnoses the symptoms based on that the further steps are
decided. The framework and the tools of the clinical decision support system helps in
reducing the errors caused during the diagnosis. The CDSS need to provide two important
function. The nurses working in the frontline are not much experienced about the medicine so
the CDSS need to provide them with the instruction about what need to be done in the next
step (Umscheid et al., 2015). The system does not interrupt the human decision it improves
the steps involved in the diagnosis. After that, the visual design and the workflow is
represented. After that the evaluation of the performance of the end user is done. After the
evaluation of the performance the heuristic evaluation is performed. The evaluators of the
first prototype were expertise with deep domain knowledge. The outcomes of the heuristic
evaluation was incorporated with the product before the evaluation of the end user part. After
the prototype, an interview was conducted. However, the methods analysis is related to user,
function, representation and task related (Lee 2013).

7INTERACTIVE SYSTEM
The evaluation
The interface involving the users and the design related to the workflow of the
system is evaluated with the help of the heuristic evaluation. The evaluation is completely
based upon the performance of the system and the evaluation made by the end users. The
term heuristic evaluation is used for user interface system. The methods is designed in such a
way that it is able to recognize the hidden potential of any products (Piscotty et al., 2013).
The heuristic method is mainly conducted on a small numbers of expert who are professional
in the field of user interface system. It is seen that in the health care sector the heuristic
evaluation is used in defining the various products. In clinical decision support system it is
seen that the evaluation is used for the designing and development purpose. The main
requirement of the system is to provide assistance without disturbing the clinical workflow.
The second type of the evaluation is based on the performance. As soon as the first designing
of the system is done few nurses formed a panel (Honour 2013). The interview report
highlighted many key points and the feedback of the interview conducted. The study or rather
the interview continued and followed certain steps. The nurse first entered the patient room to
monitor the health. The monitor showed some symptoms. The nurse went back to bring the
tablet device and while doing that the nurse selected one of the trigger. The nurse received
enough data and decided to do the diagnostic and then announces the results of the diagnostic
report. It was then observed that whether all the task was done individually and completed by
all the nurses. The first attempt by all the nurses was just for training purpose so that the
nurses were familiar with the systems. The main aim for the evaluation was to make the nurse
work with the system without any help. The entire time was recorded so that an estimation
can be made about the time requirement. The time calculated the amount of time that was
required by the system. It was important to see that the system did not consume much time.
The requirement that the tool was supposed to meet was that it should consume less than 5

8INTERACTIVE SYSTEM
minutes (Beeler, Bates and Hug 2014). The clinical workflow continued with its own flow.
After every session the nurses had the opportunities to do self-evaluation .The evaluation
decided that which system was suitable and what conditions where required for multi-tasking.
The evaluation is completely based on the evaluation. The criteria for the system was that the
task in the system must be minimum. The system status was received and the visibility status
stated that when the system was started it was not known that how much time it is going to
consume. It was not known that the system will consume 15 seconds or it will take 10
minutes at the end of the evaluation it was seen that the system took near about 1 minute. The
evaluation also stated and compared the difference between the system and the world’s
reality (Yılmaz and Ozdemir 2017). The main element of the clinical decision support system
is the need of professional expertise. Clinical decision support system used in bedside nursing
comprises of many actions, knowledge and various types of activities involving planning.
The models contains of certain models the models are related to the knowledge, the data
required the planning that is required in the future. The evaluation used is heuristic evaluation
is the study of engineering, methods that is used to find the problems that are related with the
usability. It involves the requirement of lots of expertise who can analyse the entire interface
and give the resultant outcomes in many ways. The study conducted with the help of different
experts (Spat et al., 2013). The clinical decision support system completion time is an
estimate of the time required by the system. Another type of evaluation that is involved with
clinical decision support system is the NASA method of task loading index. In this method,
the nurses are asked to make the self-assessment. In the assessment, they require to assess the
burden and the problem they faced while handling the system. The outcomes of the
assessment applied in the health care sectors and the product that related with the health field.
The violation of the heuristic evaluation caused issue related to the tracking system related to
the engineering team. The data extraction involves all sorts of study, design and the collection

9INTERACTIVE SYSTEM
of the different type of required. The data collection is done with the help of data collection
method. The studies suggested that 80-90% of the total problems that are not covered and
related to usability, which are solved with the help of three experts (Richardson et al., 2016).
The heuristic evaluation helps in the successful evaluation of the product related with user
interface products that range from the EMRs to all the medical related devices. The method
of heuristic evaluation help in the method of designing the product and the process related to
the development. The evaluators are the people who helped in evaluation. The evaluators
goes through number of elements, which are related to the user interface. The system is
designed in such a way so that the tools used requires minimum time. The main criteria for
the new released product evaluation is that the load of the task that is introduced should be
minimum. The performance-based evaluation was done repeatedly so that the outcome can be
evaluated based on the average performance. The system also uses a tablet device that helps
in the working of the system. The evaluation criteria was for the nurses, the tools used by the
system and for the entire system. The National Aeronautics and Space Administration helped
the nurses in doing the evaluation for the bedside nursing clinical decision support system.
The system helps in the cases where the application needs to perform multi task. The entire
multi task is performed parallel in the system.
The Findings of the Evaluation
After the evaluation, certain important issues related to the heuristic evaluation was
identified. The evaluators identified the issues. All the issues where differentiated and each
issues where accordingly categorized. There was almost ten issues related to the software
applications. The issues related with the software products were identified with the ratings
that were given by the evaluators. The total count of the heuristic violations was 82 according
to the study that was done by the evaluators (Sousa et al., 2015). The evaluation helped in
identification of the issues and then helped in improving the usability quality of the product.

10INTERACTIVE SYSTEM
The nurses involved in the evaluation process completed the process successfully. After the
completion of the process, all the nurses who were involved in the evaluation process were
able to use the system properly after a single session of training. There was total of 3 sessions
that were performed after that the median was done and then the calculation was based on the
mean method and the standard deviation was conducted across all the nurses involved. It was
seen that the average taken by the nurses was 111 seconds to complete the entire task of
simulation (Lichtner, Dowding and Closs 2015). Based on that the evaluators concluded that
the overhead time goal was 5 minutes. The evaluation performed by the National Aeronautics
and Space Administration stated that work overhead was low on the nurses. The nurses as
such did not face any problems and most of the burden was seen to have zero rate. The only
burden noticed were temporary demand, which was usual with the use of the basic tools
required by the system. The tools were designed keeping in mind that it will help the nurses
in identifying the symptoms and accordingly further process is carried out. The process
creates a natural temporary burden on the users. The evaluation also concluded that the
system design functions properly and met the entire requirement. All the factors related to the
characteristics, advantages, implementation of the system, its uses, the barrier involved and
the implementation of the clinical decision support system in the field of nursing were
recognized and each having its own contribution and its uses (Chlan et al., 2013). The clinical
decision support system design and its implementation are complicated consisting of different
variables that includes different function, number of users, setting and expected outcomes.
The user interface and the implementation were the difficult factors however, it contributed to
the successful development of all the clinical decision support system tools. Certain solution
were made to evaluate the outcomes of the system, to overcome the barriers, and to improve
the overall efficiency. The frontline nurses will use the systems to evaluate the health of the
patience on a regular basis. The system helps in automatically identifying the probable

11INTERACTIVE SYSTEM
diagnosis required by the patience. However, the nurses need to focus on the workflow and
examine the planning and the decision made by the clinical decision support system. It is
expected that with the growing use of the clinical decision support system the future of the
health care field will be more intuitive and will involve less of intrusive.

12INTERACTIVE SYSTEM
References
Amland, R.C., Lyons, J.J., Greene, T.L. and Haley, J.M., 2015. A two-stage clinical decision
support system for early recognition and stratification of patients with sepsis: an
observational cohort study. JRSM open, 6(10), p.2054270415609004.
Beeler, P.E., Bates, D.W. and Hug, B.L., 2014. Clinical decision support systems. Swiss
medical weekly, 144(5152).
Chlan, L.L., Weinert, C.R., Heiderscheit, A., Tracy, M.F., Skaar, D.J., Guttormson, J.L. and
Savik, K., 2013. Effects of patient-directed music intervention on anxiety and sedative
exposure in critically ill patients receiving mechanical ventilatory support: a randomized
clinical trial. Jama, 309(22), pp.2335-2344.
Fossum, M., Ehnfors, M., Svensson, E., Hansen, L.M. and Ehrenberg, A., 2013. Effects of a
computerized decision support system on care planning for pressure ulcers and malnutrition
in nursing homes: an intervention study. International journal of medical informatics, 82(10),
pp.911-921.
Gephart, S., Carrington, J.M. and Finley, B., 2015. A systematic review of nurses'
experiences with unintended consequences when using the electronic health record. Nursing
administration quarterly, 39(4), pp.345-356.
Gephart, S., Carrington, J.M. and Finley, B., 2015. A systematic review of nurses'
experiences with unintended consequences when using the electronic health record. Nursing
administration quarterly, 39(4), pp.345-356.
Honour, M., 2013. Elevating nursing leadership at the bedside. Newborn and Infant Nursing
Reviews, 13(3), pp.127-130.

13INTERACTIVE SYSTEM
Hum, R.S., Cato, K., Sheehan, B., Patel, S., Duchon, J., DeLaMora, P., Ferng, Y.H., Graham,
P., Vawdrey, D.K., Perlman, J. and Larson, E., 2014. Developing clinical decision support
within a commercial electronic health record system to improve antimicrobial prescribing in
the neonatal ICU. Applied clinical informatics, 5(02), pp.368-387.
Lau, B.D., Shaffer, D.L., Hobson, D.B., Yenokyan, G., Wang, J., Sugar, E.A., Canner, J.K.,
Bongiovanni, D., Kraus, P.S., Popoola, V.O. and Shihab, H.M., 2017. Effectiveness of two
distinct web-based education tools for bedside nurses on medication administration practice
for venous thromboembolism prevention: A randomized clinical trial. PloS one, 12(8),
p.e0181664.
Lee, S., 2013. Features of computerized clinical decision support systems supportive of
nursing practice: a literature review. CIN: Computers, Informatics, Nursing, 31(10), pp.477-
495.
Lichtner, V., Dowding, D. and Closs, S.J., 2015. The relative meaning of absolute numbers:
the case of pain intensity scores as decision support systems for pain management of patients
with dementia. BMC medical informatics and decision-making, 15(1), p.111.
Moss, J. and Berner, E.S., 2015. Evaluating clinical decision support tools for medication
administration safety in a simulated environment. International journal of medical
informatics, 84(5), pp.308-318.
Piscotty, R.J., Kalisch, B., Gracey-Thomas, A. and Yarandi, H., 2015. Electronic nursing care
reminders: implications for nursing leaders. Journal of Nursing Administration, 45(5),
pp.239-242.
Richardson, K.J., Sengstack, P., Doucette, J.N., Hammond, W.E., Schertz, M., Thompson, J.
and Johnson, C., 2016. Evaluation of nursing documentation completion of stroke patients in

14INTERACTIVE SYSTEM
the emergency department: a pre-post analysis using flowsheet templates and clinical
decision support. CIN: Computers, Informatics, Nursing, 34(2), pp.62-70.
Sheehan, B., Nigrovic, L.E., Dayan, P.S., Kuppermann, N., Ballard, D.W., Alessandrini, E.,
Bajaj, L., Goldberg, H., Hoffman, J., Offerman, S.R. and Mark, D.G., 2013. Informing the
design of clinical decision support services for evaluation of children with minor blunt head
trauma in the emergency department: a sociotechnical analysis. Journal of biomedical
informatics, 46(5), pp.905-913.
Sockolow, P.S., Rogers, M., Bowles, K.H., Hand, K.E. and George, J., 2014. Challenges and
facilitators to nurse use of a guideline-based nursing information system: Recommendations
for nurse executives. Applied Nursing Research, 27(1), pp.25-32.
Sousa, V.E., Lopez, K.D., Febretti, A., Stifter, J., Yao, Y., Johnson, A., Wilkie, D.J. and
Keenan, G.M., 2015. Use of Simulation to Study Nurses Acceptance and Non-Acceptance of
Clinical Decision Support Suggestions. Computers, informatics, nursing: CIN, 33(10), p.465.
Spat, S., Höll, B., Petritsch, G., Schaupp, L., Beck, P. and Pieber, T.R., 2013, April.
Automatic system testing of a decision support system for insulin dosing using Google
Android. In EFMI-STC (pp. 187-191).
Umscheid, C.A., Betesh, J., VanZandbergen, C., Hanish, A., Tait, G., Mikkelsen, M.E.,
French, B. and Fuchs, B.D., 2015. Development, implementation, and impact of an
automated early warning and response system for sepsis. Journal of hospital medicine, 10(1),
pp.26-31.
Yılmaz, A.A. and Ozdemir, L., 2017. Development and implementation of the clinical
decision support system for patients with cancer and nurses' experiences regarding the
system. International journal of nursing knowledge, 28(1), pp.4-12.