Reflection 2: Cloud-Based Decision Support
Health care outcomes depend on the interventions providers use to deliver patient care. In the advancing practice, the role of technology is critical and support tools for optimizing efficiency continue to be developed and integrated into regular practice (Sutton et al., 2020). Clinical decision support tools dominate the current practice. For better outcomes, health practitioners should understand their background, application, and other critical elements. The purpose of this reflection is to explore cloud-based decision support and clinical decision support experience in clinical practice.
Cloud-Based Decision Support
Clinical Decision Support Consortium (CDSC) and Purpose
The Agency for Healthcare Research and Quality (AHRQ) plays an integral role in promoting information technology (IT) in health practice. To achieve this goal, AHRQ funds research and projects that demonstrate how health IT can improve health for all Americans. The CDSC was among the two projects that AHRQ funded in 2008 to explore how to create high-quality Clinical Decision Support (CDS) and deliver it on a large scale to the point of care around the United States (AHRQ Digital Healthcare Research, 2014). Through this project, CDSC demonstrated how its model could benefit health care providers of different sizes and types using different electronic health records (EHRs) in diverse locations in the nation. Overall, CDSC laid a strong foundation for the development and continuous absorption of CDS in the health care system.
CDSC Four-Stage Approach
Health care technologies need a strong background and effective guidelines to ensure they are efficient and free from risks. The CDSC used a four-stage approach to develop CDS that included a guideline, key rules, computer code, and a web service (AHRQ Digital Healthcare Research, 2014). The first step entailed identifying and developing a guideline that described specific clinical best practices. Such guidelines are crucial since a clinical decision support system’s primary role is to enhance medical decisions and utilize clinical knowledge for better health outcomes (Sutton et al., 2020). The second step was abstracting key rules and logical statements. The CDSC used the logical statements to develop computer code for CDS rules (third step), and the web service (final step) was created to deliver clinical decision support.
Biggest Challenge that CDSC Faced
Health technologies are challenging to design and implement. The biggest challenge that CDSC faced was delivering knowledge on a large scale across thousands of miles in the United States (AHRQ Digital Healthcare Research, 2014). In this case, it was challenging to deliver knowledge from Boston to the point of care across the country. Korte et al. (2020) observed a similar problem with technology absorption and noted that IT knowledge takes a long time to be delivered to the point of care. The implication is that the knowledge was not quickly available to practitioners despite being ready and validated for use.
Overcoming the Challenge and the Role of Collaboration
Innovation challenges require creative and practical interventions. The CDSC overcame the knowledge delivery challenge by partnering with EHR vendors and medical practitioners around the nation to implement cloud-based services (AHRQ Digital Healthcare Research, 2014). Collaboration was instrumental in the project’s success and in ensuring that the targeted users were involved in knowledge implementation. It ensured health care providers validated CDS through direct participation, testing, and providing views on what the consortium presented in the project.
How CDS Improves Patient Care
CDS plays an instrumental role in transforming patient care in the evolving practice. From a practice viewpoint, health care practitioners improve care quality and patient safety when they make sound decisions. CDS systems provide health care practitioners with real-time, procedural guidance through their clinical decision-making process (Røst et al., 2020). Such systems are the foundation of efficient and effective patient care, which is critically needed to reduce the escalating medical costs.
Clinical Decision Support Experience
Using Clinical Decision Support Systems (CDSS) in Practice
Health care practitioners who embrace information technologies recognize the value of clinical decision support systems in delivering efficient care. As a regular user of EHRs and other systems in health practice, I have used clinical decision support systems in practice to enhance decision-making and achieve other outcomes. These support systems include computerized alert systems, patient data reports, and clinical guidelines. EHRs users can also derive order sets using data from electronic records.
Improving Patient Safety and Outcomes Using Clinical Support Systems
Clinical decision support systems are a sophisticated health information technology component. Integrating them into patient care denotes a commitment to generate and utilize health information by combining knowledge and data (HealthIT. Gov, 2018). Similarly, the support systems I have used have been integral in supporting workflow, facilitating quick and informed decision-making, and reducing possible errors associated with information processing. As Bates and Singh (2018) noted, reducing medical errors enhances patient safety and optimizes health outcomes since it reduces health complications, injuries, and hospital-acquired infections. High patient safety increases patient satisfaction, among other outcomes, such as high patient satisfaction and patients’ trust in health care practitioners.
Challenges to Implementing and Using a Clinical Support System
Challenges associated with implementing and using clinical support systems are multifaceted since the systems are diverse and health care practitioners perceive them differently. As earlier noted, health IT knowledge takes a long time to be delivered to the points of care (Korte et al., 2020). The slow adoption is a huge barrier to implementation since quick adoption is necessary to ensure technologies are utilized when they are most relevant. The other challenge is fragmented workflows in clinical practice. Sutton et al. (2022) observed that clinical support systems have the potential to disrupt clinician workflow, particularly when designed without considering human information processing and behaviors. The other significant barrier is technology know-how among health care practitioners. CDSS’ effectiveness depends on health care professionals’ literacy, which varies across ages and health care facilities’ types and sizes. Above all, CDSS requires system and content maintenance. As a result, health care organizations require substantial financial resources to sustain decision support systems besides a robust technology infrastructure and providers’ literacy.
Advocating for the Adoption of a Clinical Support System
Clinical decision support systems are the spine of health care transformation. Their benefits include optimizing care quality and enhancing health outcomes, reducing medical errors and adverse events, and promoting efficient, cost-effective care (HealthIT.gov, 2018). As health informatics continues dominating health practice, practitioners should continue embracing support systems that allow them to combine knowledge and data. Due to such benefits, I would advocate for my organization to adopt a clinical support system. Increased care quality ensures that an organization meets the threshold for accreditation (Jha, 2018). It also improves an organization’s reputation and competitiveness, which my organization should strive to attain. Importantly, avoiding errors and adverse events should be a leading objective for all organizations seeking to provide cost-effective care. I would like my organization to benefit from such outcomes; hence, it should embrace clinical decision support systems and promote their use among health care staff.
Conclusion
Health care professionals are mandated to provide the best care to patients. The role of clinical decision support systems in facilitating such care is critical in the evolving practice. However, implementation challenges such as computer literacy and the lack of robust infrastructure to support health IT continues to hamper CDS adoption. As a result, health care organizations should continue improving their IT infrastructure and ensure their staff has adequate IT literacy to use CDS appropriately.
References
AHRQ Digital Healthcare Research. (2014). CDSC: Cloud-based decision support. YouTube. https://www.youtube.com/watch?v=aL1rkmoLPno
Bates, D. W., & Singh, H. (2018). Two decades since to err is human: an assessment of progress and emerging priorities in patient safety. Health Affairs, 37(11), 1736-1743. doi: 10.1377/hlthaff.2018.0738
HealthIT.gov. (2018). Clinical decision support. https://www.healthit.gov/topic/safety/clinical-decision-support
Jha, A. K. (2018). Accreditation, quality, and making hospital care better. Jama, 320(23), 2410-2411. doi:10.1001/jama.2018.18810
Korte, B. J., Rompalo, A., Manabe, Y. C., & Gaydos, C. A. (2020). Overcoming challenges with the adoption of point-of-care testing: from technology push and clinical needs to value propositions. Point of Care, 19(3), 77–83. https://doi.org/10.1097/POC.0000000000000209
Røst, T. B., Clausen, C., Nytrø, Ø., Koposov, R., Leventhal, B., Westbye, O. S., … & Skokauskas, N. (2020). Local, early, and precise: Designing a clinical decision support system for child and adolescent mental health services. Frontiers in Psychiatry, 11, 564205. https://doi.org/10.3389%2Ffpsyt.2020.564205
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), 1-10. https://doi.org/10.1038%2Fs41746-020-0221-y
Hsncb 376 reflection 2 instructions
CDSC: Cloud-Based Decision Support | Digital Healthcare Research (ahrq.gov)
students will describe how clinical decision support systems are used to improve patient safety and care.
Reflection
Reflect on the following in a minimum of 500 words each.
This reflection is comprised of two sections highlighting cloud-based decision support and clinical decision support experience. This activity is meant to help you solidify your knowledge in preparation for the competency assessment.
Complete your reflection by responding to all prompts.
1) Cloud-Based Decision Support
The Clinical Decision Support Consortium project is funded by the Agency for Healthcare Research and Quality and illustrates how clinical decision support is scalable from one population to another.
Watch Cloud-Based Decision Support to see how a clinical decision support tool built and housed in Boston benefited a small rural community far from the city. CDSC: Cloud-Based Decision Support | Digital Healthcare Research (ahrq.gov)
Answer the following questions:
What is the Clinical Decision Support Consortium (CDSC), and what is its purpose?
What is the four-stage approach the CDSC used to develop clinical decision support?
What was the biggest challenge the CDSC faced?
How did the CDSC overcome that challenge?
What role did collaboration play in improving the care for patients at the point of care?
How does clinical decision support improve patient care?
2) Clinical Decision Support Experience
Answer the following questions:
How have you used clinical decision support systems in practice?
How have your clinical support systems improved patient safety and outcomes?
What are some of the biggest challenges to implementing and using a clinical support system?
If you have not had an opportunity to use a clinical support system, what do you see as some of the benefits and challenges with these types of systems?
After researching these clinical support systems, would you advocate for your organization to adopt a clinical support system? Why or why not?
Submit your reflection.
