Search results
May 27, 2024 · Data modeling is the process of creating a visual representation of either a whole information system or parts of it to communicate connections between data points and structures. This blog post will guide you through the basics of data modeling, its importance, types, and best practices, using a healthcare-focused example for better understanding.
Nov 28, 2022 · 1. Cross-Industry Enterprise Data Management (EDM) and Analytics Technology. EDM platforms frequently offer data models as a feature of analytical and data management tools. 2. Industry Clouds. Healthcare software-as-a-service (SaaS) clouds have begun providing pre-modeled content in their services. 3.
- HT Management
- Analytical Model: Grouping Patients Into Overlapping Clusters
- Quantifying Contributions of Changes in Modifiable Clinical Factors
- Visualisation of HT Trajectories
- Health Trajectory Example
- Dataset
- Investigated Lifestyle Factors
Working with a large amount of patient data in the form of EHRs (all the information collected and archived in hospital or outpatient electronic databases, including registries for particular treatments) and using automated processing and analysis methods based on machine learning or, generally, on artificial intelligence should result in CDMTs tha...
FCA and the concept lattice are used to illustrate our approach (see Additional file 1: Tables S1 and S2 and Figure S1). First, patient groups are formed into a concept lattice using FCA [23,24,25] applied to a selected set of binary factors. In this real-world example, there were five preoperative lifestyle factors. The formal concepts are cluster...
If the investigated factors are modifiable, then a sequence of concepts could be identified in which (i) the factors in the preceding concept are also contained in the succeeding concept of the sequence, (ii) patients in the succeeding concept are contained in the preceding concept of the sequence and (iii) the likelihood of risk in the succeeding ...
Concepts for each patient subgroup and the relationships between them can be visualised as a weighted-directed network. The vertices (circles) of the network represent individual concepts. The directed edges (arrows) represent whether the risk of reoperation increased or decreased after adding a factor. The groups of concepts connected in a sequenc...
Our approach was applied to a real-world cohort of patients with TKA, and the contribution of modifiable lifestyle factors to the risk of reoperation was evaluated. Our methodology of HT management consists of three components: (i) context, leading to the definition of a medical problem and risk event, acquisition and evaluation of patient data, (i...
To present our model, an unselected real-world cohort of 1885 patients (695 men and 1190 women) who underwent TKA surgery between September 2010 and April 2017 at a single tertiary orthopaedic centre was analysed. For all patients, the lifestyle and clinical factors before TKA surgery, as well as information regarding early reoperation (defined as ...
To demonstrate the capabilities of our model, the following preoperative factors were included: physical activity, sports activity, smoking, body mass index (BMI) and the ability to walk long distance (1000 m). Physical activity was evaluated using the University of California Los Angeles (UCLA) activity scale . In terms of UCLA, an inactive patien...
- Eva Kriegova, Milos Kudelka, Martin Radvansky, Jiri Gallo
- 2021
Jun 21, 2024 · The Benefits of Better Healthcare Data Management. Improved healthcare data management offers significant benefits, including enhanced patient care, more accurate diagnoses, and increased efficiency in the healthcare system. Health Data Analytics: The data can predict patient health, leading to early treatments and more focused healthcare.
May 15, 2023 · Implementing data models in healthcare IT systems has many practical use cases and benefits for organizations navigating these complex transitions. 1. Improved Data Quality. Well-designed data models improve healthcare data accuracy, completeness, and consistency, enabling the extraction of master data for use in combined systems and healthcare ...
Nov 23, 2022 · DMs are created by a process called data modeling. Data modeling is a step often performed during the software application design and development or whenever changes are to be made to the data elements within a database to support the real-world operational environment or research questions (PopMedNet n.d.). It occurs at three levels—(i ...
People also ask
What is a data model in healthcare?
What is health data management?
How do data models affect patient care and operational costs?
What is the role of a data model in clinical research?
What is health data management (HDM)?
How can healthcare data management improve patient care?
Jun 24, 2019 · Background Most healthcare data sources store information within their own unique schemas, making reliable and reproducible research challenging. Consequently, researchers have adopted various data models to improve the efficiency of research. Transforming and loading data into these models is a labor-intensive process that can alter the semantics of the original data. Therefore, we created a ...
