Clinical Decision Support Assignment
A clinical decision support system (CDSS) refers to healthcare technologies utilized to improve medical decision-making by healthcare providers. The systems combine different information sources from clinical information, patient data, and other sources to ensure patient-centered and evidence-based decisions. Therefore, this paper examines CDSS. It focuses on topics such as the types of CDSS, CDSS that could be used in a healthcare setting, and their triggers and differences.
Types of Clinical Decision Support
CDSS can be classified into two types. They include the knowledge and non-knowledge-based CDSS. Knowledge-based CDSS uses rules to evaluate patient data and displays results for use in making clinical decisions. The systems have an inference engine, data repository, and a method of communicating results. They operate under the if-then rules. Non-knowledge-based CDSS utilizes artificial intelligence, statistical pattern recognition, or machine learning to analyze and present information. The systems do not follow logic to produce treatment recommendations for healthcare providers (Sutton et al., 2020). Non-knowledge-based systems analyze patterns in data and use them to provide clinical recommendations that inform providers’ decisions.
Types of Clinical Decision Support that could be used in a Health Care Setting and Their Triggers
Several types of CDSS could be used in healthcare settings. One of them is knowledge-based systems. As noted above, knowledge-based systems use rules to provide clinical alerts or recommendations. The systems have information obtained from different sources such as clinical protocols, guidelines, and evidence-based practices. Information entered into the system such as a prescribed drug for a disorder acts as a trigger for the knowledge-based systems. The system compares the drug with the diagnosis and the available data to make decisions such as the safety or an increased risk of drug interactions, hence, giving alerts to healthcare providers (Fernandes et al., 2020). The alerts inform the decisions that healthcare providers make.
The other type of CDSS is diagnostic support CDSS. Diagnostic support CDSS helps healthcare providers diagnose the client’s problems. The systems have information about different diagnoses that should be considered based on the patient’s presenting complaints. Healthcare providers can access differential diagnoses for their patients and the appropriate laboratory tests and diagnostics that should be ordered to rule them out or in. The triggers for the diagnostic support system are data such as the presenting complaints of a patient, which activate the knowledge and non-knowledge-based systems. Predictive analytics is the other CDSS that can be used in healthcare settings. Predictive analytics are non-knowledge CDSS that extract data from different databases and use it to predict the outcomes of an adopted decision. Healthcare providers use predictive analytics to determine the soundness of their decisions and their alignment with the identified patient needs (Fitriyani et al., 2020; Olakotan & Yusof, 2020). The trigger for predictive analytics CDSS would be the decisions that healthcare providers make such as the primary diagnosis and treatments, diagnostic, or laboratory investigations.
Differentiating
Clinical decision support refers to technologies designed to help healthcare providers to make their clinical decisions. They incorporate information from different sources to optimize healthcare provider’s decision-making. Clinical workflow analysis entails the study of the approaches to task undertaking in an organization to identify inefficiencies and strategies to improve the workflows. Modeling entails simulating system functionalities to gain insights into their efficiency and ability to improve organizational performance. Reducing data entry errors entails the adoption of strategies that would reduce or prevent errors that healthcare providers make when entering data into healthcare systems (Musen et al., 2021). Usability testing is a process where organizations use a system to identify potential issues or challenges that end users might experience with an adopted technology.
Conclusion
In summary, CDS systems help healthcare providers make informed decisions about their patients’ needs. Healthcare settings can use different CDS systems. CDDS rely on different triggers. An organization’s needs determine the CDSS for use by healthcare providers.
References
Fernandes, M., Vieira, S. M., Leite, F., Palos, C., Finkelstein, S., & Sousa, J. M. C. (2020). Clinical Decision Support Systems for Triage in the Emergency Department using Intelligent Systems: A Review. Artificial Intelligence in Medicine, 102, 101762. https://doi.org/10.1016/j.artmed.2019.101762
Fitriyani, N. L., Syafrudin, M., Alfian, G., & Rhee, J. (2020). HDPM: An Effective Heart Disease Prediction Model for a Clinical Decision Support System. IEEE Access, 8, 133034–133050. https://doi.org/10.1109/ACCESS.2020.3010511
Musen, M. A., Middleton, B., & Greenes, R. A. (2021). Clinical Decision-Support Systems. In E. H. Shortliffe & J. J. Cimino (Eds.), Biomedical Informatics: Computer Applications in Health Care and Biomedicine (pp. 795–840). Springer International Publishing. https://doi.org/10.1007/978-3-030-58721-5_24
Olakotan, O. O., & Yusof, M. Mohd. (2020). Evaluating the alert appropriateness of clinical decision support systems in supporting clinical workflow. Journal of Biomedical Informatics, 106, 103453. https://doi.org/10.1016/j.jbi.2020.103453
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 Medicine, 3(1), Article 1. https://doi.org/10.1038/s41746-020-0221-y
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Clinical decision support is about using the right trigger, to the right person, with the right instructions, with the intent to ensure that the person is making the right decision. The purpose of this assignment is to describe the different types of clinical decision support and determine the outcomes of applied clinical decision support.
Write a paper addressing the following:
- What are the different types of clinical decision support?
- Describe at least three different types of clinical decision support that could be used in a health care setting or provide a personal workplace example.
- Using the examples you have provided (above), identify the triggers that would initiate the criteria for clinical decision support.
- Differentiate clinical decision support and clinical workflow analysis, modeling, reducing data entry errors, and usability testing for improving end-user experience.