4 Ways Clinical Decision Support System for Nurses Is Transforming Care

Key Takeaways

• Nurses can leverage clinical decision support systems to monitor patients who are recovering from surgery and to observe if there’s any reaction to a medication. Nurses also receive alerts if a patient is at high risk for hospital readmission due to clinical or non-clinical aspects.
• Clinical decision support systems stores all data in one place, so nurses can interpret it easily. It doesn’t matter where a file may be, nurses can find it in half the time.
• Clinical decision support system for nurses is designed to reduce medication errors. Almost 44 percent of the studies show that clinical decision-making systems, when integrated with CPOE have resulted in a reduction in medication errors.

Clinical decision support system (CDSS) offers medical personnel with person-specific information to enhance care. Clinical decision support system for nurses makes use of tools and technologies to improve the quality of care and outcome. These include reminders and alerts sent to patients and doctors, diagnostic reports, data summaries, condition-specific order sets, etc.

According to a study, CDSS has positively impacted outcomes and care processes were better for those who adopted CDSS measures. Examples, of where care was better, are nurses’ adherence to hand disinfection, on-time blood sampling, insulin dosing, and documenting care.

How Clinical Decision Support System is Useful for Nurses

1. Improved Patient Outcomes and Care

Nurses can leverage clinical decision support systems to monitor patients who are recovering from surgery and to observe if there’s any reaction to the medication. Nurses also receive alerts if a patient is at high risk for hospital readmission due to clinical or non-clinical aspects. According to a study, CDSS is used for prescription drugs and for treating diseases such as hypertension, cardiovascular diseases, diabetes, respiratory diseases, AIDS, gastrointestinal and more.

The study stated that in some cases CDSS has shown positive patient outcomes due to facets such as compliance, patient and physician cooperation, and user-friendliness. In a nutshell, a clinical decision support system helps nurses track their vitals, monitor their health (even at home), and get real-time alerts, thus improving care and outcome.

CDSS plays a vital role in intensive care units. The system is set up to identify changes in heartbeats and breathing, and a sudden change can alert the nurse on duty. Moreover, for at-home care, CDSS provides instant alerts based on data on medication and vital signs collected from remote patient monitoring systems.

2. Access to Information in One Place

Clinical decision support systems stores all data in one place, so nurses can interpret it easily. It doesn’t matter where a file may be, nurses can find it in half the time. Also, all the data is updated and validated, leaving little or no room for outdated or duplicate data. The process of data backup and recovery is easy if there are no duplicate copies.

Updated health data helps nurses and physicians to stay on par with their patient’s health and wellness. With health data in one place, it is quite convenient for CDSS development companies to secure it with all possible means. HIPAA compliance is one of the ways to ensure the privacy and security of ePHI (Protected Health Information). Other means of security could be firewalls, physical safeguards, data encryption, etc.

Apart from this, having all health data in one place can be risky in terms of breaches, leakages, frauds, and scams, so it has to be stored in multiple places in the form of both soft and hard copies. Three copies are recommended for data storage.

3. Reduction in Medication Errors

A clinical decision support system for nurses is designed to reduce medication errors. Almost 44 percent of the studies show that clinical decision-making systems, when integrated with CPOE (Computerized Provider Order Entry) have resulted in a reduction of medication errors. Further, a decrease in medication errors has helped to increase patient satisfaction rates and outcomes. Incorrect medication is one of the leading causes of death in the USA.

As per the U.S. Food and Drug Administration, more than 100,000 reports of suspected medication errors are put forth. These reports arrive from healthcare professionals, patients, and drug manufacturers. Apart from death, harmful results of medication errors are disability, birth defects, brain damage, or hospitalization. Clinical decision support systems help nurses and physicians to decrease these errors. Thus, assuring safe medicines and dosages for patients, and a faster recovery.

4. Better Efficiency

According to the Institute of Medicine, around $17 to $29 billion is spent annually on inaccurate patient care which caused due to misdiagnosis and poor clinical decision-making.

Nurses and physicians can rapidly determine the right dosage, and diagnosis if they have accurate and relevant lab test results. This saves them appropriate referrals, saves time, and eliminates unwanted costs such as emergency room admissions. With the patient data available on CDSS, clinical staff can effectively diagnose patients, leaving no room for misdiagnosis.

Challenges of Clinical Decision Support System for Nurses

No doubt clinical decision support systems can reduce medication errors and improve care. But it can contribute to nurse and clinician burnout and frustration. As per a study published by researchers at the Stanford University School of Medicine, 35 to 60 percent of clinicians experience burnout. Burnout affects the health of nurses and is associated with the risk of depression, occupational injury, and substance abuse. So, to avoid this situation, end-users can be involved in the design and implementation phase of CDSS. They can contribute by leaving feedback and comments on the CDSS working process.

User feedback can help to overcome gaps that are a cause for burnout. Furthermore, integrating artificial intelligence with clinical decision support systems introduces challenges for nurses in terms of ‘how to operate it.’ The system can become complex after integrating AI. The end goal is to have a user-friendly clinical decision support system for nurses.

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