Immersive’s ClarityDG Framework and Maturity Model for data governance promotes discipline driven by standards, definitions, workflows and workforce enablement to validate and ensure data consistency across your organization. We make data governance achievable by taking you through a step-by-step implementation process that is sensitive to resource, culture change and integration with your organization’s strategic plan.
Connectivity & Integration
Access to data where and when it is needed, with transaction transparency and accountability, is the goal. Creative and effective connectivity solutions are our forte – we are all things enterprise application integration and medical device connectivity.
Application Information Lifecycle Management
Immersive helps you establish a practical, end-to-end information management program to cost-effectively manage data growth, thoughtfully retire systems and dispose of unneeded information, formally classify information assets and create a culture of information stewardship. Your growing data footprint introduces more challenges than ever before. Ensuring that the right information is accessible at the right time to only the right people is a tougher proposition when you don’t have a good handle on your information universe in the first place. And we have not even started to talk about risk…
Data Quality & Integrity
Immersive’s portfolio of data quality and integrity solutions assist you in understanding your current level of data quality, how to analyze and enhance data quality, and how to maintain an ongoing data quality program. From data profiling to data definition harmonization, data normalization to de-duplication, we aim to increase data usability and trustworthiness.
Master Data Management
By creating a single, timely, relevant, and trusted view of your business, Immersive’s approach to multi-domain MDM enables IT to be a strategic and tactical partner in the initiatives that drive clinical and operational value. We assess the current state, develop an action plan, identify tools and implement in a scalable fashion that allows you to start small and establish repeatable process, so you can being seeing results quickly.
Data Management Office
For most healthcare organizations, data is siloed, is poorly managed and there is limited visibility to data that enables the workforce to make better decisions and be more productive. Immersive helps you implement a Data Management Office (DMO) where the primary goal is to achieve benefits from standardizing, implementing and following data management policies, processes and methods. The DMO serves as the epicenter for all data-related activity to accelerate the appropriate and productive use of data that aligns with your organization’s strategy.
ePHI Data Inventory
- Locate and classify ePHI and other electronic sensitive information (ESI) on file shares, in databases, SharePoint, CMS, MS Exchange
- Locate and classify ePHI and other electronic sensitive information (ESI) on endpoints, laptops and desktops
- Gain visibility into file and device activity on endpoints
- Evaluate risk
Data Quality Assessment
- Determine and quantify data quality issues and business impacts
- Assess people, processes, rules, and technology that create, use and/or manage the targeted data set, both quantitatively and qualitatively
- Identify root causes of deficiencies discovered and recommend remediation options
- Define a continuous monitoring approach to assess data quality performance
Data Profiling Study
- Discover and assess of a domain or subset of data without extensive evaluation and judgments of its quality
- Perform an algorithmic analysis on a defined data set
- Provide a statistical representation of each scoped data element without any further evaluation of its quality
- Measure key data elements against applicable contextual dimensions
- Understand business impacts
Data Definition Harmonization
- Describe “current state” of information use/context for the data set under study
- Document “current” formal data element names and definitions
- Identify of one or more data elements from which the information is derived
- Define scope of information use and consumption of the data from which the information is derived
- Examine defined or implied business rules (technical, operational or administrative) for the information
- Perform data quality assessments that validate the usability of the data as intended