Data Specification Management Process (DSMP)

What is Data Specification Management Process (DSMP)?

Standardised uniform process that facilitates new and existing dataset specification
Quality assurance process for new and existing dataset specifications
Opportunity for early input from downstream functions to enhance service planning, analytics and reporting
Reduction in re-work and costs due to errors and omissions in dataset specifications

The DSMP follows a set of Enterprise Architecture Principles that are integral in the development of datasets not only for here and now but future proofing for interoperability and ensuring that the data standards are set to support the delivery of integrated healthcare.

These principles are:

Data is an asset that has value to the enterprise and is managed accordingly.
Users have access to data necessary to perform their duties; therefore, data is shared across enterprise functions and organisations in accordance with legislation.
Data should be accessible for all users to perform their work. Users should have access to local and core national records relevant to their role and within legislative parameters.
Data is defined consistently throughout the enterprise, and the definitions are understandable and available to all users.
Each data element has a trustee accountable for data quality.
Semantic interoperability is achieved through the use of SNOMED CT in all clinical information systems.

Benefits of the DSMP

The Dataset Specification Management Process brings Subject Matter Experts from core areas, within and external to the HSE, together to ensure a consistent approach to dataset specification management. Subject Matter Experts were identified by process mapping the role of all stakeholders and their role in managing datasets.

This process and group were developed to provide a forum and process to enable stakeholders who have a role in the management and analysis of data, to:

Champion their data requirements,
Contribute to an enterprise view of data
Give feedback and advice to dataset owners
Manage dataset specifications to provide foundational information governance.

The aim of the Dataset Specification Management Process:

A standardised uniform process that facilitates new and existing dataset specification
A quality assurance process for new and existing dataset specifications
The opportunity for early input from downstream functions to enhance service planning, analytics and reporting
A reduction in re-work and costs due to errors and omissions in dataset specifications.

Overview of Dataset Management Process

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What is Data?

Data is defined as facts or figures, or information that's stored in or used by a computer. An example of data is information collected for a research paper.
Data sources include patient medical records, hospital records, medical exam results and information collected by healthcare testing machines.
Health data is any data "related to health conditions, reproductive outcomes, causes of death, and quality of life" for an individual or population. Health data includes clinical metrics along with environmental, socioeconomic, and behavioural information pertinent to health and wellness.