Feasibility of Algorithm-Based Clinical Decision Support for Suspected Urinary Tract Infections in Nursing Home Residents.
Garrett P NewArif NazirPenny LoganChristine E KistlerPublished in: Antibiotics (Basel, Switzerland) (2022)
Urinary tract infections (UTIs) are commonly suspected in nursing home (NH) residents, commonly resulting in antimicrobial prescriptions, even when symptoms are non-specific. To improve the diagnosis and management of suspected UTIs in NH residents, we conducted a pilot test of a paper-based clinical algorithm across NHs in the southern U.S. with ten advanced practice providers (APPs). The paper-based algorithm was modified based on the clinical care needs of our APPs and included antimicrobial treatment recommendations. The APPs found the UTI antimicrobial stewardship and clinical decision support acceptable. The educational sessions and algorithm improved baseline confidence toward UTI diagnosing and treatment. The APPs thought the algorithm was useful and did not negatively impact workload. Feedback from the pilot study will be used to improve the next iteration of the algorithm as we assess its impact on prescribing outcomes.
Keyphrases
- urinary tract infection
- clinical decision support
- machine learning
- deep learning
- neural network
- primary care
- healthcare
- pulmonary embolism
- staphylococcus aureus
- electronic health record
- emergency department
- patient safety
- randomized controlled trial
- clinical practice
- combination therapy
- skeletal muscle
- smoking cessation
- drug induced