Data Governance: Core Domains, EMR Program, and Future Directions

This essay provides an overview of data governance in healthcare, emphasizing its importance in balancing the need to collect and secure information while extracting value from it. It identifies core domains of data governance including data governance itself, data management, and data transparency, detailing their respective functions and requirements within healthcare organizations. The essay also examines the current status of data governance with the Electronic Medical Records (EMR) program in Canada, highlighting both its achievements and challenges, such as the potential for 'faster inaccurate data'. It concludes with suggestions for improving data governance, including government support, stakeholder participation, and public involvement in policy-making, to ensure data security, smooth data transfer, and enhanced healthcare services.

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Data Governance
Students Name
Institutional Affiliation

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Introduction
Data governance is a strategy of managing data that helps the organizations to balance
their needs. It is essential for any organization to have data governance where the information is
secure. The core domains of data include data governance, data management, and data
transparency. Electronic Medical Records program was developed in 2005 to help in securing
information digitally. However, the extent to which it has enhanced healthcare is still unknown.
Hence the government must also develop other approaches that will help in securing information
regarding healthcare.
Data governance refers to a way of managing the information which allows organizations
to balance two needs: the need to collect and keep the information safe while also getting value
from that data. In healthcare, data governance is explained as an organization-wide framework
for managing health data throughout its lifecycle from the time a patient’s information is entered
first into the system till well after they are discharged (Hripscak, George, and David, 2012). The
cycle encompasses things such as studies, payments, medication, outcomes enhancement and
government reporting. Having data governance regulations and practices assists facilities to
attain the institute for healthcare enhancement objectives improves the sufferer's experience of
care, enhance populations health and minimize per capita cost of healthcare.
Data governance ensures that there are continuity, reliability, and repeatability. Without
documented values around metrics, some decisions might be made using false assumptions; It is

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used to give organizations a means to link both business and clinical policy needs as part of the
data employed in automating the collection and reporting in conformance to those regulations
Core domains of data governance
Data Governance
This refers to how information controllers practice their control and compliance over
their data assets. This area is essential to make sure that compliance is maintained. In addition,
any information breaches an organization might experience should be communicated within
three days and to affected information subjects and the controllers of the information without
undue delay if the breach might get into a significant risk to rights and freedoms (Isaacs &Leigh,
2016 ). Furthermore, there is privacy by design under data governance where the business should
start to put in consideration the feature of data privacy at the onset of beginning a project as well
as throughout the whole data processing process. There is also vendor management where the
third parties and the vendors will go through the regulatory scrutiny. Any controller of data
should hold details records of any processing; all actions are done with the information. This will
enable the patients to trust the health organizations with their information
Data management
This is how information controllers and processors will handle the processing actions. In
addition, it is vital that data is maintained in the following areas: data erasure where people can
now request personal data to be deleted even if it is public.
Nevertheless, people might also request that individual information not be processed in
particular contexts that can be found there. There is also data processing where organizations
should maintain records internally of all data processing. The recorded information will require

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to encompass the name and the details of the organizations, data processing purposes, categories
description of people and individual data, personal data recipients, data transfer details and data
retention schedules. In addition, any data controller processing more than 5000 information
subject records in a year are needed to have a data protection officer ( Smallwood &Robert, 2014
). The officer will monitor and conduct a data protection evaluation and train the personnel on
overall regulations.
Data transparency
Data processing organizations should be able to show that a consent has been given from
the person whom the data associated with so that his or her data can be used. People also have a
right to withdraw their consent any time, and the organization should make it easy for them to
withdraw. Also, data must be able to move or transfer from one service giver to another without
hindering usability. Furthermore, organizations should give disclosures regarding data
processing to data subjects and the consumer's rights should not be explainable and easily
accessible. This creates an opportunity for the patients to release out the information that will be
important to them in the future.
Data Quality
Data quality is involved in all aspects of a framework. The main function of governance
is to enhance and maintain data quality. Hence, data quality must be measured endlessly for data
governance to be successful and the results fed back continuously into the governance procedure.
Data quality is a much more involved procedure that puts its focus on the resources of the
organization and addressing challenges of quality at the source. Data quality enables the
stakeholders to solve issues related at the source rather than relying on data cleansing and

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scrubbing completely (Mastrian & Mcgonigle,2018). The accountability and the ownership of
the information quality must be within the organizations of the systems of the source.
Data Integrity
This refers to the assurance and maintenance of the continuity and the authentic of the
information over its whole cycle. This ensures that data is recorded correctly and as intended and
when it is retrieved it remains the same as it was recorded originally. Its objective is to avert
changes to data that are unintentional.
Data Access
This is the capability of accessing data within a database. The users who have access to
data can store, regain or manipulate information. The organizations have ways of accessing data
which includes sequential way that needs data to be moved within the disk by using a seek
operation till information is found. The other way is reading randomly until the data is found.
Data Security
This is the behavior of keeping information protected from corruption and unaccredited
access. It makes sure that there is privacy when individual or corporate information is protected.
Research has indicated that data security has been emphasized because of the internet. This
ensures that data is secured in healthcare organizations.
Data Analysis
Refers to a procedure of inspection, cleansing and modelling information with the
objective of creating information that is useful, supportive and used in making decisions. It has

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various approaches that include methods under different names and is used in various
organizations, social science domains and science. It helps the organizations to work more
effectively.
Current status of data governance
Electronic Medical Records (EMR) adoption programme began in 2005, Canadian
governments have been pushing for the execution of the EMR among the physicians to improve
the quality of care while minimizing costs. Research has indicated that 7 out of 10 primary care
physicians are using the software in their practice. Additionally, over 80% of data regarding
healthcare are in digital form (Ontario Medical Association, 2014). This has enabled health
professionals to transfer data faster. However, the degree to which EMR enhances healthcare
services is still unclear despite remarkable accomplishments. It has also been argued that
healthcare organizations might be facing "faster inaccurate data" as various organizations have
executed their applications of technology, that uses inconsistent metrics and create information
in multiple ways hence making faulty information that may lead to medical mistakes
(Smallwood &Robert, 2014 ). Health information is an essential aspect of a healthcare system.
They act as a foundation to create best practice and make crucial clinical decisions. It is observed
that the quality information support high-quality care, appropriate study, positive outcomes of
the patient, cost-effective risk assessment and strategic decision making. Information governance
has gained more attention in healthcare ( Dong & Keshavjee, 2016). Canada Infoway has argued

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that there is a need to create a data governance framework to govern the flow of information in
the interoperable.
Suggestions
The government must ensure that they develop a model that will enable them to secure
information for the patients to ensure that there is smooth transfer of data from one organization
to the other ( Reeves, Mary, and Rita, 2013 ). Therefore, the necessary stakeholders must review
the regulations that are existing about data governance and clearly explain the main data
processes, rules, and procedures. Also, there must be training, and support provided to ensure
buy-in. The regulations that legitimize data governance and assisting data governance execution
are important to make sure that data governance is successful (Scardilli &Brandi, 2014). The
organization should also enable the public to participate in the making of policies by giving their
views regarding healthcare. This will enable everyone to live in a harmonious environment and
respect each other’s opinion. In addition, the government must offer financial assistance in the
implementation of these regulations of data governance so that healthcare services can be
improved. Relevant stakeholders must always participate in every meeting that involves data
governance and creates awareness about the advantages of securing data.

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Conclusion
Data governance makes sure that factual information is collected within the organization.
It is Important since it preserves information for future use. Data governance ensures that there
are consistency and reliability to make sure that the data is always secure. There are core
domains of data which include data governance, data management, and data transparency. These
domains ensure that healthcare organizations are responsible for data collection and their
security.
References
Dong, L., & Keshavjee, K. (2016). Why is information governance important for electronic
healthcare systems? A Canadian experience
Hripscak, George, and David J. Albers. 2012. Next generation phenotyping of electronic health
records. Journal of the American Medical Informatics Association 20, no. 1: 117-121
Isaacs, Leigh. 2016. Information governance strategy isn't a project. Computer Weekly, 11-15.

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Mastrian, K., & Mcgonigle, D. (2018). Cognitive informatics: An essential component of nursing
technology design. Nursing Outlook,56(6), 332-333. doi:10.1016/j.outlook.2018.09.01
Ontario Medical Association. 2014. Insights 4 care program: Strategic context and program
overview. URL: goo.gl/uaSvDu (accessed April 18,2019)
Reeves, Mary G., and Rita Bowen. 2013. Developing a data governance model in healthcare.
Health Care Financial Management. URL: goo.gl/GyJYQH (accessed April 18, 2019).
Scardilli &Brandi. 2014. Celebrating information governance. Information Today 31, no. 4: 33-
36.
Smallwood &Robert. 2014. Deϔining the differences between information governance, IT
governance, & data governance. URL: goo.gl/OxZaXX (accessed April 18, 2019).