Healthcare Data Processing


Data Resources

Data Acquisition

Data Digitalization

Data Preprocessing

Data Modeling

Data Classification

Data Merging and Fusion

Data Management

Data Warehouse

Knowledge Discovery

Decision Support Systems

Data Visualization

Patient Data Security and Authorization

Data Regression

Electronic Patient Records

Hospital Patient Records


Healthcare Level Seven (HL7)

Integrating the Healthcare Enterprise (IHE)

Machine Learning

Data Modeling

Data Science and Engineering

Data Reporting and Presentation

Consulting Healthcare Data Analysis


MediX Computing LLC professionals provide outstanding consulting services to healthcare related data analysis. In our perspective, data analysis work contains couple phases as follows. We would like to provide our consulting services to these tasks.

A. Data Acquisition

This phase contains several efforts, such as data selection, data digitalization, data validation, data reformation, data type conversion, data trimming and preprocessing before formal analysis and reporting.

B. Data Aggregation

This phase allows healthcare data from various resources to be professionally combined with appropriate selection, merging and/or fusion, compatibility conversion, security transformation, authorization and authentication verification, selective filtering, and data restoration.

C. Data Modeling

This important phase focuses on establishing data model based on the observation of the obtained data set, defining analysis goals and criteria, checking with analysis methods or tools available, and preparation of suitable computing platform (desktop, workstation, centralized server, or high performance computing clustering)


D. Data Analysis


This is the core phase. It is very often a iterative process with Phase C. It mainly consists of several tasks:


1. Understanding data insights through data evaluation
2. Exploring data numerically using computing power
3. Discovering any meaningful oddities and trends
4. Interpreting each finding with relevant knowledge of healthcare domain
5. Presenting the analyzed data with a precise, consistent, consumable, simple way to public


E. Data Mining


Data mining can be viewed as an analysis process to classify and discover patterns in large data sets from which useful information can be extracted. It is a knowledge discovery processing and a foundational for decision supports being implemented in future intelligent healthcare systems. There are six major tasks in healthcare data mining:


1. Identify unusual healthcare data records interesting or errors
2. Searching for relationships between variables.
3. Clustering to find   "similarity" among data sets
4. Classify patterns of data
5. Estimating the model of relationships among data or data sets by regressing data with the least error
6. Providing a new representation of the data set and its structure, using data visualization and reports