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Clinical Decision Support Associated with Improved Patient Outcomes

Researchers found that the use of clinical decision support resulted in a 38 percent reduction in mortality among pneumonia patients, improving patient outcomes.

Clinical decision support tools were associated with better patient outcomes as the tools assisted clinicians in providing better care with lower mortality rates for emergency departments with pneumonia, according to a recent study.

Before the COVID-19 pandemic, pneumonia was the leading cause of death from infectious diseases.

“Treating pneumonia in emergency departments is challenging, especially in community hospitals that don’t see severe pneumonia as often as urban academic medical centers,” said Nathan Dean, MD, section chief of pulmonary and critical care medicine at Intermountain Medical Center.

The study published in the American Journal of Respiratory and Critical Care Medicine examined the effects clinical decision support had on unnecessary variation and healthcare quality.

Between December 2017 and June 2019, researchers at Intermountain Healthcare embedded an open loop, real-time clinical decision (ePNa) support system within 16 community hospital EHRs.

The clinical decision support tool offers clinicians vital patient indicators such as age, fever, oxygen saturation, chest imaging results, and vital signs to make care suggestions, including appropriate antibiotic therapy and microbiology studies.

In addition, the Intermountain decision support tool provided care setting recommendations, informing clinicians of whether a patient should be sent to the ICU, admitted to the hospital, or discharged.

Over the three-year study period, the hospitals received more than 6,800 pneumonia patients, and clinicians utilized ePNa in 67 percent of patients.

Clinician use of the tool resulted in a range of positive outcomes for patients. Patient mortality rates after being diagnosed with pneumonia decreased by 38 percent upon using the clinical decision support tool. Mortality in patients admitted directly from the emergency department into the ICU was also reduced.

In addition, outpatient disposition increased by 30 percent.

The findings showed that with the use of the clinical support tool, clinicians were also able to decrease intensive care unit admissions.

Researchers found that the use of the clinical support tool resulted in more appropriate antibiotic use, lowering the average time between emergency department admission and the start of antibiotics.

“In giving clinicians a real-time assessment tool that pulls together over 50 factors that can determine how a patient will do with pneumonia, our study found that clinicians were able to make better treatment decisions with this resource,” stated Dean, who is also a principal investigator of the study.

“Some of our community hospitals have as little as 20 beds. We wanted to validate the effectiveness of ePNa in very different healthcare settings.”

The clinical decision support system, ePNa, not only streamlined patient information to aid clinicians in making patient recommendations, but it also enabled clinicians to be more structured and consistent in decision making, Dean noted.

“Even if they don’t follow the recommendation, decision-making is more consistent with best practices,” Dean said.

In a similar study, the use of clinical decision support also achieved better results regarding the reversible risk of cardiovascular disease. Researchers associated the implementation of a clinical decision support system with a 4.4 percent decrease of reversible risk among high-risk patients at clinics with access to the tool.

Despite risk reduction being relatively small, it could contribute to a population-level reduction in cardiovascular events if maintained over time.

In some cases, clinical decision support can also mitigate clinician burnout. A study found that the use of these tools significantly lowered clinician cognitive workload and decreased the time clinicians spent searching for information. That said, most experts also advise against alert fatigue, which can drive burnout among clinicians using clinical decision support tools.

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