Nowhere is the potential for better, faster healthcare offered by wireless devices more welcome than in critical care environments. As hospital information technology departments start taking advantage of the speed, mobility, and flexibility of
Nowhere is the potential for better, faster healthcare offered by wireless devices more welcome than in critical care environments.
As hospital information technology departments start taking advantage of the speed, mobility, and flexibility of handheld wireless computing technologies, caregivers have begun using computer information obtained at bedside to make more accurate and efficient treatment decisions.
Handheld devices are superior to manual data collection and entry for quality improvement projects in medical intensive care units, according to a study presented at CHEST 2001, this week's meeting of the American College of Chest Physicians in Philadelphia.
Researchers found the use of a handheld device simplifies data collection, eliminates manual data entry, and provides prompt availability of information -- on ICU practice patterns, protocol compliance, drug utilization, and ventilator days -- that facilitates process improvement.
"This study demonstrates that use of a handheld device, or PDA (personal data assistant), is a superior alternative to manual data collection and entry in a medical intensive care unit, especially in hospitals that lack sophisticated information systems," said Dr. Barry Fuchs, medical director of the medical ICU at the University of Pennsylvania Medical Center in Philadelphia.
In cases in which data entry requires professional judgment, use of a handheld device or PDA allows the clinician to input data while participating in routine patient-care duties, such as rounds, he said.
"Measuring the effectiveness of quality initiatives for process improvement in critical care units is difficult," Fuchs said.
Typically, this process involves retrospective medical record review and/or hospital database queries unless an electronic medical record or sophisticated ICU information system is available, he said. This approach has several limitations:
According to the Fuchs study, data collection using wireless devices offers several potential improvements:
Can AI Enhance PET/MRI Assessment for Extraprostatic Tumor Extension in Patients with PCa?
December 17th 2024The use of an adjunctive machine learning model led to 17 and 21 percent improvements in the AUC and sensitivity rate, respectively, for PET/MRI in diagnosing extraprostatic tumor extension in patients with primary prostate cancer.
Can Radiomics Bolster Low-Dose CT Prognostic Assessment for High-Risk Lung Adenocarcinoma?
December 16th 2024A CT-based radiomic model offered over 10 percent higher specificity and positive predictive value for high-risk lung adenocarcinoma in comparison to a radiographic model, according to external validation testing in a recent study.