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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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