AIMC Topic: Quality Indicators, Health Care
Clear Filters Showing 21 to 30 of 31 articles
Assessing Hospital Performance After Percutaneous Coronary Intervention Using Big Data.
Circulation. Cardiovascular quality and outcomes
Nov 8, 2016
BACKGROUND: Although risk adjustment remains a cornerstone for comparing outcomes across hospitals, optimal strategies continue to evolve in the presence of many confounders. We compared conventional regression-based model to approaches particularly ...
Percutaneous Coronary Intervention
Databases, Factual
Data Mining
Female
Aged, 80 and over
Process Assessment, Health Care
Hospitals
Humans
Risk Factors
Quality Indicators, Health Care
Time Factors
Male
Machine Learning
Multivariate Analysis
Aged
Propensity Score
Hospital Mortality
Treatment Outcome
Algorithms
Middle Aged
Logistic Models
Likelihood Functions
Cause of Death
Massachusetts
Registries
Natural language processing as an alternative to manual reporting of colonoscopy quality metrics.
Gastrointestinal endoscopy
Apr 22, 2015
BACKGROUND AND AIMS: The adenoma detection rate (ADR) is a quality metric tied to interval colon cancer occurrence. However, manual extraction of data to calculate and track the ADR in clinical practice is labor-intensive. To overcome this difficulty...
Estimating the incubated river water quality indicator based on machine learning and deep learning paradigms: BOD5 Prediction.
Mathematical biosciences and engineering : MBE
Sep 1, 2022
As an indicator measured by incubating organic material from water samples in rivers, the most typical characteristic of water quality items is biochemical oxygen demand (BOD) concentration, which is a stream pollutant with an extreme circumstance of...
Follow-Up on the Use of Machine Learning in Clinical Quality Assurance: Can We Detect Adverse Event Under-Reporting in Oncology Trials?
Drug safety
Mar 1, 2020
Machine Learning for Health Services Researchers.
Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
Jul 1, 2019
BACKGROUND: Machine learning is increasingly used to predict healthcare outcomes, including cost, utilization, and quality.
Usability evaluation of communication service robot for the elderly.
Journal of back and musculoskeletal rehabilitation
Jan 1, 2019
BACKGROUND: The Republic of Korea has become the most rapidly aging society and is anticipated to enter the post-aged society in 2026. As the population ages, demand for senior-friendly products has gradually increased. Under the demands for these ci...
Measuring the quality of colonoscopy: Where are we now and where are we going?
Gastrointestinal endoscopy
Sep 1, 2015
Measuring physician adherence with gout quality indicators: a role for natural language processing.
Arthritis care & research
Feb 1, 2015
OBJECTIVE: To evaluate physician adherence with gout quality indicators (QIs) for medication use and monitoring, and behavioral modification (BM).
A Pilot Ontology for Healthcare Quality Indicators.
Studies in health technology and informatics
Jan 1, 2015
Computerisation of quality indicators for the English National Health Service currently relies primarily on queries and clinical coding, with little use of ontologies. We created a searchable ontology for a diverse set of healthcare quality indicator...
Utility of Arden Syntax for Representation of Fuzzy Logic in Clinical Quality Measures.
Studies in health technology and informatics
Jan 1, 2015
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...
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