AIMC Topic: Health Services Research
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Machine Learning, Natural Language Processing, and the Electronic Health Record: Innovations in Mental Health Services Research.
Psychiatric services (Washington, D.C.)
Feb 20, 2019
An unprecedented amount of clinical information is now available via electronic health records (EHRs). These massive data sets have stimulated opportunities to adapt computational approaches to track and identify target areas for quality improvement ...
Machine learning approaches for predicting high cost high need patient expenditures in health care.
Biomedical engineering online
Nov 20, 2018
BACKGROUND: This paper studies the temporal consistency of health care expenditures in a large state Medicaid program. Predictive machine learning models were used to forecast the expenditures, especially for the high-cost, high-need (HCHN) patients.
A Machine Learning Approach to Identify NIH-Funded Applied Prevention Research.
American journal of preventive medicine
Oct 25, 2018
INTRODUCTION: To fulfill its mission, the NIH Office of Disease Prevention systematically monitors NIH investments in applied prevention research. Specifically, the Office focuses on research in humans involving primary and secondary prevention, and ...
ProvCaRe Semantic Provenance Knowledgebase: Evaluating Scientific Reproducibility of Research Studies.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Apr 16, 2018
Scientific reproducibility is critical for biomedical research as it enables us to advance science by building on previous results, helps ensure the success of increasingly expensive drug trials, and allows funding agencies to make informed decisions...
[Position Paper of The AG Digital Health DNVF on Digital Health Applications: Framework Conditions For Use in Health Care, Structural Development and Science].
Gesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes (Germany))
Dec 29, 2017
The term "digital health" is currently the most comprehensive term that includes all information and communication technologies in healthcare, including e-health, mobile health, telemedicine, big data, health apps and others. Digital health can be se...
Development of a Natural Language Processing Engine to Generate Bladder Cancer Pathology Data for Health Services Research.
Urology
Sep 12, 2017
OBJECTIVE: To take the first step toward assembling population-based cohorts of patients with bladder cancer with longitudinal pathology data, we developed and validated a natural language processing (NLP) engine that abstracts pathology data from fu...
Healthcare in the 21st century.
European journal of internal medicine
Nov 12, 2016
Multilevel Weighted Support Vector Machine for Classification on Healthcare Data with Missing Values.
PloS one
May 19, 2016
This work is motivated by the needs of predictive analytics on healthcare data as represented by Electronic Medical Records. Such data is invariably problematic: noisy, with missing entries, with imbalance in classes of interests, leading to serious ...
How to build up the actionable knowledge base: the role of 'best fit' framework synthesis for studies of improvement in healthcare.
BMJ quality & safety
Aug 25, 2015
Increasing recognition of the role and value of theory in improvement work in healthcare offers the prospect of capitalising upon, and consolidating, actionable lessons from synthesis of improvement projects and initiatives. We propose that informed ...
Assessment of surveys for the management of hospital clinical pharmacy services.
Artificial intelligence in medicine
Apr 23, 2015
OBJECTIVE: Survey data sets are important sources of data, and their successful exploitation is of key importance for informed policy decision-making. We present how a survey analysis approach initially developed for customer satisfaction research in...
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