AIMC Topic: Quality Indicators, Health Care
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Agility assessment using fuzzy logic approach: a case of healthcare dispensary.
BMC health services research
Jun 9, 2017
BACKGROUND: Agile concepts are not only beneficial for manufacturing sector but also for service sector such as healthcare. However, assessment of agility has been predominantly done in manufacturing enterprises. This study demonstrates a means to me...
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 ...
Registries
Percutaneous Coronary Intervention
Aged
Data Mining
Aged, 80 and over
Quality Indicators, Health Care
Male
Logistic Models
Time Factors
Treatment Outcome
Hospital Mortality
Massachusetts
Cause of Death
Middle Aged
Process Assessment, Health Care
Hospitals
Databases, Factual
Multivariate Analysis
Female
Humans
Propensity Score
Risk Factors
Machine Learning
Likelihood Functions
Algorithms
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...
Semantic Convergence with LLMs for Head and Neck Cancer Quality Indicators.
Studies in health technology and informatics
Aug 7, 2025
We developed a novel method for leveraging large language models (LLM) to systematically filter and categorize large numbers of clinical quality indicators (CQI) for head and neck cancer. This was used to transform a tedious, human-resource intensive...
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).
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