HS 420 Unit 8 Decision Support Systems Discussion

HS 420 Unit 8 Decision Support Systems Discussion

HS 420 Unit 8 Decision Support Systems Discussion

Technology has played a critical role in healthcare, such as in improving patient care outcomes. Among the technological applications is the Clinical Decision Support System, which, since its inception, has substantially improved healthcare effectiveness, efficiency, safety, and quality. However, it also has drawbacks, as demonstrated in the comparison table below.

Pros of CDSS Cons of CDSS
It enhances the process of clinical decision-making.

Rationale: This CDSS operated by integrating a host of technologies and tools that foster the process of decision-making, hence improving patient outcomes (Sutton et al.,2020)

-A potential to cause fatigue in the healthcare professionals using it

Rationale: Sometimes, the use of CDSS comes with high rates of alerts, which may make the practitioners feel fatigued (Kouri et al.,2022)

It helps reduce medication errors by identifying potential adverse drug effects

Rationale: The systems also offer the right data on medications and how patients react to the medication. As such, the practitioner is in a better position to give the right prescriptions and avoid adverse drug events and occurrences.

-A potential of not being able to detect some medication errors.

Rationale: In some cases, the system may fail to detect errors, which may lead to the clinicians to provide the wrong medications, which can be harmful to patients’ health

Fosters communication between the patient and care providers and also improves patient awareness (Kwan et al.,2020)

Rationale: The communication and alert system technology, which forms part of the CDSS helps in improving communication between the providers and patients, which is a key factor for better treatments.

-Increased workload and Pressure:

Rationale: The increased usage of the system and workflow changes may lead to increased workload, hence burnout (Musen et al.,2021)


As shown in the pros and cons table, the CDSS supports decision-making in clinical settings. Therefore, the providers are in a position to make appropriate decisions that can help improve patient outcomes. Therefore, this section focuses on a scenario that illustrates an exemplary depiction of how CDSS might influence my decision as an APN. The case is a scenario that involves a patient presenting with multiple chronic problems, such as diabetes and hypertension, and showing symptoms of complications controlling the blood sugar, breath shortness, and fatigue. The patient uses various medications to manage his condition. The use of the CDSS can be important in this scenario. Integration of the electronic health records and the CDSS system plays a key role in flagging the patient’s case by showing that there is a potential interaction between the current symptoms and the medications the patient is using (Wasylewicz et al.,2019). The system also offers a chance to think about the current clinical guidelines that can be used to manage patients with comorbid chronic illnesses such as this patient.

As an APN, the CDSS can influence my clinical decisions regarding this case in various ways. For example, I would quickly review the patient’s medication list after getting a medication interaction alert from the system. Since the patient has comorbid conditions and is presenting with the current symptoms, there is a possibility of medication interactions. The CDSS, through the recommendations and guidelines it provides, will also lead to checking the guidelines, especially for blood pressure control within the acceptable range for his conditions (Wasylewicz et al.,2019). In addition, I would also be able to come up with an individualized care plan for the patient since the CDSS can recommend various adjustments to the patient’s management plan. For example, I would recommend a change in medications for better outcomes.



Kouri, A., Yamada, J., Lam Shin Cheung, J., Van de Velde, S., & Gupta, S. (2022). Do providers use computerized clinical decision support systems? A systematic review and meta-regression of clinical decision support uptake. Implementation Science17(1), 21. Doi: 10.1186/s13012-022-01199-3

Kwan, J. L., Lo, L., Ferguson, J., Goldberg, H., Diaz-Martinez, J. P., Tomlinson, G., … & Shojania, K. G. (2020). Computerized clinical decision support systems and absolute improvements in care: Meta-analysis of controlled clinical trials. Bmj370.

Musen, M. A., Middleton, B., & Greenes, R. A. (2021). Clinical decision-support systems. In Biomedical informatics: computer applications in health care and biomedicine (pp. 795-840). Cham: Springer International Publishing. Doi: 10.1007/978-3-030-58721-5_24

Sutton, R. T., Pincock, D., Baumgart, D. C., Sadowski, D. C., Fedorak, R. N., & Kroeker, K. I. (2020). An overview of clinical decision support systems: benefits, risks, and strategies for success. NPJ Digital Medicine3(1), 17.

Wasylewicz, A. T. M., & Scheepers-Hoeks, A. M. J. W. (2019). Clinical decision support systems. Fundamentals of clinical data science, 153-169.

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topic: Decision Support Systems (DSSs)

Compare and contrast the benefits and the limitations of using Decision Support Systems (DSSs). What does provider bias mean in using DSSs?

What Is a Decision Support System (DSS)?
A decision support system (DSS) is a computerized program used to support determinations, judgments, and courses of action in an organization or a business. A DSS sifts through and analyzes massive amounts of data, compiling comprehensive information that can be used to solve problems and in decision-making.

Typical information used by a DSS includes target or projected revenue, sales figures or past ones from different time periods, and other inventory- or operations-related data.

A decision support system (DSS) is a computerized system that gathers and analyzes data, synthesizing it to produce comprehensive information reports.
A decision support system differs from an ordinary operations application, whose function is just to collect data.
Decision support systems allow for more informed decision-making, timely problem-solving, and improved efficiency in dealing with issues or operations, planning, and even management.
Understanding a Decision Support System (DSS)
A decision support system gathers and analyzes data, synthesizing it to produce comprehensive information reports. In this way, as an informational application, a DSS differs from an ordinary operations application, whose function is just to collect data.

The DSS can either be completely computerized or powered by humans. In some cases, it may combine both. The ideal systems analyze information and actually make decisions for the user. At the very least, they allow human users to make more informed decisions at a quicker pace.

Using a DSS
The DSS can be employed by operations management and other planning departments in an organization to compile information and data and synthesize it into actionable intelligence. In fact, these systems are primarily used by mid- to upper-level management.

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For example, a DSS may be used to project a company’s revenue over the upcoming six months based on new assumptions about product sales. Due to a large number of factors that surround projected revenue figures, this is not a straightforward calculation that can be done manually. However, a DSS can integrate all the multiple variables and generate an outcome and alternate outcomes, all based on the company’s past product sales data and current variables.

A DSS can be tailored for any industry, profession, or domain including the medical field, government agencies, agricultural concerns, and corporate operations.
Characteristics of a DSS
The primary purpose of using a DSS is to present information to the customer in an easy-to-understand way. A DSS system is beneficial because it can be programmed to generate many types of reports, all based on user specifications. For example, the DSS can generate information and output its information graphically, as in a bar chart that represents projected revenue or as a written report.

As technology continues to advance, data analysis is no longer limited to large, bulky mainframe computers. Since a DSS is essentially an application, it can be loaded on most computer systems, whether on desktops or laptops. Certain DSS applications are also available through mobile devices.

The flexibility of the DSS is extremely beneficial for users who travel frequently. This gives them the opportunity to be well-informed at all times, providing them the ability to make the best decisions for their company and customers on the go or even on the spot.

What Is a Decision Support System Used for?
In organizations, a decision support system (DSS) analyzes and synthesizes vast amounts of data to assist in decision-making. With this information, it produces reports that may project revenue, sales, or manage inventory. Through the integration of multiple variables, a DSS can produce a number of different outcomes based on the company’s previous data and current inputs.

What Is an Example of a Decision Support System?
Many different industries, from medicine to agriculture, use decision support systems. To help diagnose a patient, a medical clinician may use a computerized decision support system for diagnostics and prescriptions. Combining clinician inputs and previous electronic health records, a decision support system may assist a doctor in diagnosing a patient.1

What Are the Benefits of a Decision Support System?
Broadly speaking, decision support systems help in making more informed decisions. Often used by upper and mid-level management, decision support systems are used to make actionable decisions, or produce multiple possible outcomes based on current and historical company data. At the same time, decision support systems can be used to produce reports for customers that are easily digestible and can be adjusted based on user specifications.