HIM-430: Data Governance course is a study of legal, ethical, and regulatory principles and frameworks that guide data governance within health care organizations. Students examine policy issues and current laws related to the uses of health information and determine processes and organizational policies to effectively and ethically manage data and personal health information.
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In recent years, data is becoming the core asset that can determine the success of an organization success. With the recent advancement in technology, it has also greatly impacted the healthcare sector. Health care facilities now use technology to make the provision of health care services to people more effective and efficient. Moreover, by the use of data analytics methods like prescriptive analytics, medical professionals are able to prepare for future health-related crises.
Table of Contents
What is data governance?
It is a set of principles and practices that ensure high quality through the complete lifecycle of your data.
Since data has become an asset that can determine whether an organization is going to succeed, the ability to govern and exploit your data assets in order to do successful digital transformation is important. Therefore, it is crucial for a healthcare organization to deploy a data governance framework that fits it and its future objectives and goals.
In short, data governance ensures that data is:
- Secured.
- Trustworthy.
- Documented.
- Managed and
- Audited.
Levels of organizations that will be supported by data governance.
Management.
It will ensure the oversight of the organization’s data assets, their value, and effect in changing business operations and market opportunities.
Finance.
In finance, it safeguards consistent and accurate reporting.
Sales.
It enables trustworthy insights into customer preferences and behavior.
Procurement.
For procurement, it fortifies cost production and operational efficiency initiatives based on exploiting data and business ecosystem collaboration.
Production.
For production, it is crucial in deploying automation.
Legal.
For legal and compliance, it enables achieving of increasing regulatory requirements.
Goals of establishing data governance.
It is mainly about establishing methods, and an organization with clear responsibilities and processes to standardize, integrate, protect and store corporate data. These are the other key goals of data governance:
- Minimizing risks.
- Establishing internal rules for data use.
- Implementing compliance requirements.
- Improving internal and external communication.
- The increasing value of data.
- Facilitating the administration of the above goals.
- Reducing costs.
- Helping by ensuring the continued existence of the company or organization through risk management and optimization.
What are the key elements for data governance success?
These are the key elements that ensure successful data governance:
- Commitment and ongoing support from all senior leadership.
- Having a plan that clearly clarifies responsibilities, accountability, and set expectations in line with the organization’s goals.
- Having clear and measurable metrics.
- Applying agile management methodology that ensures achievement of short-term goals.
- Constant communication to ensure tasks are completed on time, goals and objectives are met and stakeholders are informed of progress.
- Data quality with high integrity information thus improving data value and minimizing the compliance of risks of bad data. In addition, it also encourages data use.
Objectives of a strong data governance strategy.
Ensuring that data is used properly.
Having clear policies and effective procedures to monitor and enforce those policies helps to prevent data errors.
Complying with all regulatory requirements.
These regulatory requirements should not only be adhered to during data governance but also during all phases of development and implementation.
Improving data security.
This ensures that the data is secure and there is no unauthorized data access.
Creating and enforcing data distribution policies.
Creating policies that define how data should be distributed also ensures data security.
