HealthCare

Clinical Decision Support Systems: Do They Enhance Care and Cut Costs?

The HealthCare industry is a high-stakes environment where making decisions is a tough process, which often treads the line between the life and death of other people. And, even when the stakes aren’t that high, everyday decisions may affect the further quality of patients’ lives and how successful their recovery from the illness is going to be. Most often, the success of decisions boils down to the experience of a medical professional who has to consider a ton of different factors and insights, which are often based on imperfect information, and deliver the best possible solution under tight time constraints and psychological pressure. One would agree that it’s not the best environment for making the most appropriate choices. Even the toughest individual with the nerves of steel will make some mistakes after hours of such a taxing process. This is where clinical decision support systems can help to mitigate the pressure that HealthCare employees experience, minimize the possibility of mistakes, and help deliver efficient care regardless of the current load on a medical establishment.

This article will explore clinical decision support systems, the benefits they provide, challenges of implementing CDSS.  

Content:

1. What is a clinical decision support system?
2. Benefits of a clinical decision support system
3. Challenges of Implementing CDSS
4. Conclusion
What Is a Clinical Decision Support System?

What Is a Clinical Decision Support System?

In essence, a clinical decision support system is a complex program that helps physicians and managers with decision-making processes. The functionality of such a system varies greatly. The more complex programs can help to identify a disease a patient suffers from and help choose a treatment plan, employing a power of specialized AI, which is equipped with appropriate rules and models. The other programs help to manage drug control, tests, inventory processing, etc. 

Clinical decision support systems come in different shapes and sizes. They can be a part of the bigger HRM systems, Electronic Health Record, or act as singular lightweight modules, which specialize in one particular task. In any case, there are types of clinical decision support systems for any taste, and if one doesn’t exist, it can be developed. Currently, the availability of powerful cloud technologies, well-sharpened approaches to the development process, and multi-purpose tools make the development of fairly complex CDSS a fairly inexpensive endeavor. 

Benefits of a clinical decision support system

How exactly do pharmacy / clinical decision support systems help HealthCare establishments? 

There’re plenty of applications for CDSS, and each one has a different effect on a medical organization. Here are some of them. 

Diagnostic CDSS

Diagnostic CDSS (DDSS) are some of the most complex, heavy-weight, and often AI-powered programs that help with diagnostics and can grant great results. Such systems help to determine the disease of a patient, comparing his or her symptoms with the data.

It’s important to mention though that the final decision is still after a physician, CDSS simply provides a list of possible diagnoses, which narrows a field of possible answers and helps the medic to make a well-informed decision. Besides, a Diagnostic System may help a doctor to determine rare conditions that didn’t occur to a physician because the more obvious options were ‘in the way.’ 

DDSS isn’t used as much as they could be used because of the prejudice regarding the effectiveness of AI, ethical concerns, and the unwillingness of HealthCare establishments to make ‘risky’ investments, with which their audience may not agree because they may lack knowledge about the program’s accuracy and the benefits it can grant. The situation is likely to change as people tend to trust AI more.

The main benefit of a diagnostic system is a higher number of accurate diagnoses, which positively affects the overall efficiency of a healthcare establishment. 

Drug Selection CDSS

Drug selection is unimaginably complex. The number of possible diseases, symptoms, other conditions that may affect treatment, allergies, an assortment of available drugs that should be considered before suggesting a treatment plan make it extremely difficult to be accurate all the time. Therefore, it’s not strange that in the US alone ‘7,000 to 9,000 people die as a result of a medication error.’ A human being cannot handle and process such a gargantuan amount of data with consistent effectiveness without making any hefty mistakes. 

A CDSS can help by decreasing the number of such mistakes by mitigating human factors, such as distraction, which adds up to 75% of medication errors. Drug selection CDSS can also help with dosages, which cause up to 60% of prescription mistakes, as well as help to determine how a chosen treatment interacts with other treatments with which a patient was prescribed. 

Also, the systems may suggest cheaper drug alternatives, which proved to save hundreds of thousands of dollars annually

Clinical decision support software guidance

Some CDSS can be used to check whether the processes and procedures go along with the guidelines established by a facility or other higher-standing institutions. The programs can help nurses to follow routines described in protocols as well as to help monitor how a patient’s treatment is going. It’s all about ensuring the smoothness of a healthcare establishment’s productivity. 

Appropriate Use Criteria Support

In July 2021, in the US, the Appropriate Use Criteria for advanced diagnostic imaging services, such as computer tomography, positron emission tomography, nuclear medicine, and magnetic resonance imaging, goes into full strength. The AUC helps to determine whether a patient requires a diagnostic medical service. Upon requesting a diagnostic service for a patient, a physician will need to consult a specified CDSS first to determine whether the order complies with AUC. 

Of course, there are plenty more CDSSs that handle various tasks, but the ones provided in this list are among the most prevalent, and they provide a general idea of how clinical decision support system software adoption helps medical establishments.

Challenges of Implementing CDSS

As the load on medical organization increases and the necessity to one-up productivity and efficiency become more apparent, more establishments turn their strategic vision to the integration of clinical decision support software to improve their standing. Even though the benefits of CDSS are apparent and desired, there are some challenges associated with the implementation of the systems. 

One of the most hard-hitting challenges is “to unite team members from disparate disciplines, organizations, and cultures so that they have a common understanding of the CDS system’s overall objectives and can perform and hand off tasks appropriately.” This issue of synchronization can significantly slow down the CDSS implementation. 

Another sticking point is a possible failure to align a clinical decision support system with the strategy of an establishment. In such a case, the results can be underwhelming, bringing low performance, wasting lots of resources, and leaving plenty of untapped opportunities. 

Software developed for medical establishments should follow the guidelines of the respective higher-standing governmental institutions. For instance, it’s the Food and Drug Administration in the US and Medicines & Healthcare Products Regulatory Agency in the UK. Whether it’s FDA regulation of clinical decision support software MHRA regulation, or regulations imposed by other countries, the painstaking process of ensuring that the developed software would be relevant to the legal environment is one of the most challenging aspects of CDSS development. 

Finally, transforming a medical establishment’s workflows and guidelines into code is a challenging process that requires specific skills, thorough analysis, and well-polished approaches. Clinical decision support software interface is also a nuanced and complicated matter because the intuitiveness of the system’s UX is responsible for the learning curve employees would have to deal with. 

Conclusion

A clinical decision support system that adheres to a strategic vision of a medical establishment and carefully translates its guidelines and workflows into executable code, which is encased in an intuitive interface, is huge money, time, and reputation saver. 

If you decide to implement a clinical and patient decision support system, you have two options: either choose a third-party provider from clinical decision support system vendors who can have a system that suits your needs; or roll with the development of a custom solution that will address all the requirements down to specific nuances of your company’s profile. If you aim for the second option seeking more independence and flexibility, we can help with all the heavy software development and business analysis work and develop for you a reliable HealthCare digital solution. Or, we can also lay the foundation for further development by conducting a Discovery Phase. 

With experience creating software for HealthCare establishments, we’re well-equipped to develop, consult, and research solutions for the industry.

Feel free to contact us, if you are interested.

Mykhailo Bogdan

Recent Posts

10 Fintech UX Design Trends

One design trend at a time, every digital finance interaction is becoming not just more…

1 month ago

What Is Personal Finance Management (PFM) and How Is It Used?

The abbreviation PFM stands for Personal Finance Management, and it usually refers to the ways…

2 months ago

How to Create a Money Transfer App: a Step-by-Step Guide

Fintech innovations have made it possible to turn money into digital assets, which can be…

4 months ago

How Customer Service Chatbots Can Improve Your Business

Integrating a customer service chatbot has proven to be a game-changer for businesses. It allows…

4 months ago

The Manifest Crowns Kindgeek as one of the Most-Reviewed App Developers in Lviv

With the popularity of mobile and web apps, companies and businesses are now fighting to…

5 months ago

Conversational AI in Banking: What You Need to Know

As traditional banking models face increasing pressure from digital disruption and changing consumer expectations, financial…

5 months ago