E-Health - Data incorporations through Technology

Delivery of healthcare is critically dependent on access to data, however much of this data resides across many data repositories and organizations, and is often highly protected and private.

The Environmental Drivers

Restructuring of the Health System (world wide) to meet the demands of ageing populations (major economic impact)

Funding agencies driving multi-disciplinary research initiatives and solutions to healthcare priorities and data sharing needs

Increasing pace of growth of the scientific knowledge base (e.g. genomics data) increased need for linking data across disciplines

Development and application of high-cost medical technologies and need for Cost/benefit analyses (global benchmarking)

Declining availability of specialist skills and thus improving productivity through advanced systems becomes a priority

Private-sector healthcare providers taking over more routine procedures from Public providers and data access issues

How do we answer a Health Query?

Identification of the real question

Design of the study

Collection of the data

Analysis of the data

How Easy is Health Data Incorporation into various Modules?

There are a hell lot of issues, like:

Patient Data is usually spread across several databases like:

• Hospital administration and clinical databases

Pathology and Pharmaceuticals databases

Absence of a common person identifier

• New identifying number or ID per institution or service provider

Privacy and Security

• Patient concerns

• Legislative requirements

• Data ownership concerns

No way to easily manage access to data in multiple databases

• Involves significant time and manual handling of data between computer systems

Data quality and consistency

• Data entry errors

• Non-standard coding and formats

Current Efforts and Practices

Data Linkage Units

National Data Network (NDN)

Various software solutions

Electronic Health Records

Clinical Information Systems

Current Technological Breakthroughs and Advances

Web Services

Easy federation of data and services

XML

Mechanism for text based exchange of data

Ontology

Relating concepts using semantic descriptions

Discipline based

Need domain expertise to define the ontology of data sources and fields

Removes ambiguity and provides base line agreement on terms

Integration of heterogeneous data sources

Wrapper technology allows any data or service to be incorporated

Query optimizer

Targeted at life sciences

SRS

Integrates data sources and analysis tools

Flat File, XML and relational data base

Any command line analysis tool

Integrates over 1000 data sources and 250 analysis tools

Wide usage in biotech and pharmaceutical industries

Meta data driven approach

Web service based with powerful web service API and web interface

Use Meta data to describe

The data source

How data elements interact with the system

The behavior of data

Relationship between data

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Data Revolution in Healthcare and Lifesciences Industry

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