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Quality Assurance, Health Care

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Enabling Data-Driven Clinical Quality Assurance: Predicting Adverse Event Reporting in Clinical Trials Using Machine Learning.

Drug safety
INTRODUCTION: Adverse event (AE) under-reporting has been a recurrent issue raised during health authorities Good Clinical Practices (GCP) inspections and audits. Moreover, safety under-reporting poses a risk to patient safety and data integrity. The...

Ripe for Disruption? Adopting Nurse-Led Data Science and Artificial Intelligence to Predict and Reduce Hospital-Acquired Outcomes in the Learning Health System.

Nursing administration quarterly
Nurse leaders are dually responsible for resource stewardship and the delivery of high-quality care. However, methods to identify patient risk for hospital-acquired conditions are often outdated and crude. Although hospitals and health systems have b...

Automated Classification of Multi-Labeled Patient Safety Reports: A Shift from Quantity to Quality Measure.

Studies in health technology and informatics
Over the past two decades, there have seen an ever-increasing amount of patient safety reports yet the capacity of extracting useful information from the reports remains limited. Classification of patient safety reports is the first step of performin...

Improving Terminology Mapping in Clinical Text with Context-Sensitive Spelling Correction.

Studies in health technology and informatics
The mapping of unstructured clinical text to an ontology facilitates meaningful secondary use of health records but is non-trivial due to lexical variation and the abundance of misspellings in hurriedly produced notes. Here, we apply several spelling...

Technical Note: Unified imaging and robotic couch quality assurance.

Medical physics
PURPOSE: To introduce a simplified quality assurance (QA) procedure that integrates tests for the linac's imaging components and the robotic couch. Current QA procedures for evaluating the alignment of the imaging system and linac require careful pos...

A mathematical framework for virtual IMRT QA using machine learning.

Medical physics
PURPOSE: It is common practice to perform patient-specific pretreatment verifications to the clinical delivery of IMRT. This process can be time-consuming and not altogether instructive due to the myriad sources that may produce a failing result. The...

Assessment of quality outcomes for robotic pancreaticoduodenectomy: identification of the learning curve.

JAMA surgery
IMPORTANCE: Quality assessment is an important instrument to ensure optimal surgical outcomes, particularly during the adoption of new surgical technology. The use of the robotic platform for complex pancreatic resections, such as the pancreaticoduod...

Utility of Arden Syntax for Representation of Fuzzy Logic in Clinical Quality Measures.

Studies in health technology and informatics
BACKGROUND: Prior work has established that fuzzy logic is prevalent in clinical practice guidelines and that Arden Syntax is suitable for representing clinical quality measures (CQMs). Approved since then, Arden Syntax v2.9 (2012) has formal constru...

Assessment of an expert system for the automated validation of electrophoretic profiles.

Clinical laboratory
BACKGROUND: The Core-lab of the Greater Romagna Area Hub Laboratory carries out about 250,000 capillary electrophoresis assays/year. The huge workload demands the assessing of an Experimental Expert System (EES) capable to sort out the negative sampl...