Clinical Decision Support Systems in Healthcare

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Clinical Decision Support Systems in Healthcare

With the increased data in telehealth, there is also an increased demand for ways to manage it. With overworked medical providers, a medical institution’s operations need to quickly take care of non-health-related administrative tasks and improve patient safety and diagnostic options. While there are many tools that clinicians can now rely on, such as artificial intelligence in healthcare, there is also the option of using a clinical decision support system.

While some dread using technology in healthcare, its benefits are hard to deny. Machine learning in telehealth cannot yet replace clinicians and remove human error altogether – but it does have the capacity to assist clinicians in their decision-making. These algorithms can help doctors with X-rays or MRI scans and can be used for drug development and prevent mistakes that could have been avoided.

What is Clinical Decision Support

A clinical decision support system is any tool developed to assist care providers, medical professionals, administrative staff, or patients. They encompass but are not limited to data set analysis, pop-ups or notifications, and alerts that can better guide those within the healthcare system. They can also suggest treatments, present information the doctor may have missed, or alert to potentially dangerous medication interactions.

While clinical decision support systems have an apparent use, they shouldn’t be taken for granted or left unchecked. This means those who fear technology will eventually take over their jobs have nothing to fear for now. IBM reported that Watson, a supercomputer developed to assist medical experts, made unsafe and incorrect treatment recommendations. In other words, human errors still exist, and can be reduced by technology. But there is such a thing as technical errors as well.

How Does Clinical Decision Support System Work

CDS is usually integrated with an organization’s electronic health record. According to CMS (Centers for Medicare and Medicaid Services), CDS is defined as:

a key functionality of health information technology. When CDS is applied effectively, it increases the quality of care, enhances health outcomes, helps avoid errors and adverse events, improves efficiency, reduces costs, and boosts provider and patient satisfaction.”

A considerable part of utilizing a clinical decision support software comes from its implementation within an organization’s EHR. This is especially important to note when we take into consideration that CDS can lead to burnout and create unnecessary workloads for healthcare professionals. Many have complained about too many notifications, which ultimately takes away from focusing on what is truly important: utilizing health IT to increase patient care.

Types of Clinical Decision Support Systems

CDSSs can usually be classified as either knowledge-based or non-knowledge-based. In the knowledge-based, rules (if-then) statements are created.

Knowledge based single system cdss, clinical decision support system - clinical decision support systems in healthcare

In the non-knowledge-based CDSSs, some form of the AI mentioned above is utilized to devise a solution on its own, based on the inputted data. Naturally, any such algorithm is only as good as the data used.

 

Non-knowldege based single system cdss, clinical decision support system - clinical decision support systems in healthcare

 

Clinical Decision Support Tools

We have already briefly mentioned that there are downfalls of utilizing this technology. Now we can take a closer look at the real-life cases where implementing CDSSs can significantly influence an organization’s operations.

  • For cardiovascular diseases: evidence shows that implementation of CDS can lead to improved preventive care services, clinical tests, and treatments.
  • For breast cancer: usage of a clinical decision support system in the most common cancer type diagnosed with women shows that there is improvement in the following areas: saving time (CDSSs give immediate feedback), cost reduction, better use of resources, reduction in the variation of quality of care, among others.
  • For allergies: knowledge of allergic conditions in primary care is suboptimal. Due to the care provider’s inexperience, lack of resources or expertise, or inability to analyze large data sets – patient care for allergic diseases is lacking. To that end, clinical decision making through the usage of CDSSs is greatly improved by targeted patient information, guidelines and evidence-based clinical knowledge, and prospectively collected data.

While more research is still needed when it comes to complete diagnostic benefits of the utilization of this technology, it is essential to note that usage of telehealth tools is rapidly rising, as can be seen below:

 

Currently using, clinical decision support system - clinical decision support systems in healthcare

Benefits of Clinical Decision Support Systems

Although touched upon above, there are also direct benefits from the implementation of this technology in the operations of your practice:

  • Dosing calculations: prescribing the correct medication dose can be a hassle, especially in cases involving children or infants. Varying amounts or emergency situations: CDSS can accurately determine the correct dose in real-time, allowing professionals to focus on the job at hand.
  • Easy access to the totality of information: as it was already mentioned since a clinical decision support system is integrated into an organization’s electronic health records, and all the health data is readily available to be put to good use.
  • Help with diagnosis: one of the main benefits, a correctly inputted CDSS can help with treatment guidelines and offer the following steps to ensure that the patient gets the highest possible level of care.