Prolifics Guide to Data Privacy

Prolifics Guide to Data Privacy

Data Privacy

Data Management

Data Governance Framework

Enterprise Data Management

Big Data Integration Tools

Cloud Data Management Strategies

Data Governance in Healthcare

Government Data Privacy

Data Governance in Healthcare


Information about the health and medical history of individuals is critically important to keep private, which precipitates the need for effective data governance in healthcare. The American Health Information Management Association defines data governance in healthcare as "an organization-wide framework for managing health information throughout its lifecycle."

In this section, you'll learn about the unique lifecycle of healthcare data, the impacts of data governance in healthcare, and the current legislation that revolves around healthcare data.

As the world becomes more technology-driven and more industries are recognizing data as an asset, the importance of data governance becomes more evident. Data governance is relatively new as a discipline; however, healthcare information management has existed as an industry for nearly a century.

Data governance in healthcare is a means of using the data that is collected to create additional value from that data as well as outlining the process through which that data is collected and handled to ensure that it is secure.

Because of the way that data governance can change the entire landscape of the healthcare industry, there is an increasing demand for professionals that are knowledgeable not only in healthcare itself but also in information management and data security. Academic programs, regulatory agencies, and professional organizations have been established all over America to promote the growth of this area of the healthcare industry.

Professionals in this space have a handful of key responsibilities. These include:

  • Advance data governance in healthcare through the development of policies, procedures, and dedicated Data Governance Frameworks as they relate to the industry.
  • Implement training programs throughout healthcare organizations to promote education in data governance.
  • Analyze and apply key healthcare data to create and support organizational strategies.


Impacts Of Data Governance in Healthcare

The impacts of data governance in healthcare are what makes it so important. As you have read several times, data is an exceptionally valuable asset. Healthcare organizations can use the data that they collect in the same that any other business can; this data can be used to audit the quality of care that is being provided, create innovative strategies to increase efficiency, and streamline operations within a facility or company. Data is a great tool when it comes to making business decisions.

However, healthcare organizations are in a unique position. The data that they collect can also be used to help enhance the clinical decision-making process, which has a direct impact on individuals that rely on them for care. This is possible because of the lifecycle of healthcare data, which includes everything from treatment to research, government reporting, and beyond.

Having accurate data, which comes from a strong Data Governance Framework, helps improve the individual experiences of patients in a healthcare facility. It can help certain steps like triage and registration go more smoothly so that patients experience fewer delays in actually seeing a healthcare provider and getting treated.

Entire communities can benefit from strong data governance in healthcare. Data can demonstrate trends in certain populations that can inform intervention and inform public health policy. Robust data can also help improve research, innovate treatment avenues, and more.

Finally, cost reduction is one of the largest impacts of data governance in healthcare. Strong data management practices can increase the efficiency and cost-efficacy of an individual facility or throughout an organization of providers. These lower operating costs can help reduce costs for patients down the line.

Effective data governance in healthcare can ensure that the necessary information is easily accessible and properly integrated in order to inform the decisions made by individual providers and those in leadership roles, which can radiate out to create significant improvements throughout the entire healthcare industry.

Data Privacy

Data Management

Data Governance Framework

Enterprise Data Management

Big Data Integration Tools

Cloud Data Management Strategies

Data Governance in Healthcare

Government Data Privacy


Cloud Data Management Strategies


Cloud-based data management is becoming increasingly popular for a variety of reasons. It is more cost-effective, flexible, and can be much faster. In this section, you will read more about data management in the cloud, its challenges, and what to keep in mind when creating a strategy for cloud data.


What Are The Benefits of Cloud-Based Data Management?

Historically, data management involved purchasing on-premise storage resources. These resources would need to be managed and regular system maintenance is required for their upkeep. This is a very secure option but it is steadily becoming less efficient. Now that there is a cloud, cloud-based data management has materialized as a favorable alternative for a number of corporations.

When it comes to cloud-based data management, corporations are able to purchase the resources that they need as they are needed. This means that there is less of an investment when taking this approach to data management. Because of that, it is the perfect solution to the issue of scalability. When more resources become necessary, they can be expanded.

Technology is continuously altering the landscape of business as a whole and the cloud-based approach to data management offers flexibility that can become crucial as things change. Cloud-based options can also make it easier to share, integrate, and apply data over time.

Finally, having data that is stored and managed in the cloud can protect it from being lost or corrupted by user error. It can help reduce access to make sure that only necessary and authorized personnel can get to it. There are innumerable benefits to modernizing your data management strategy.


What Are The Challenges of Cloud-Based Data Management?

Even though there are a lot of benefits that come along with adopting a cloud data management strategy, there are some challenges. The primary concern of cloud data management is security. When storage resources are on-premise, there are a lot of protections in place for the data being stored.

When things are in the cloud, they do not exist behind a dedicated firewall. Transmitting data, especially sensitive data, is something that can be cause for concern in terms of data security. There are regulations that dictate how data can be transmitted and there is always the risk of unauthorized access or some kind of leak. These risks can be amplified by opting for cloud data management if there are not proper protocols in place.

The transition to a cloud-based data management solution can also be difficult. Existing users within a corporation, or applications that rely on the data in order to function, will need to be updated in order to maintain compatibility with the cloud.

Acknowledging the potential problems of cloud data management is an important thing to do; however, you shouldn't let this turn you off to the concept altogether. Instead, these issues just increase the importance of an airtight strategy for cloud data management to safeguard your data and your business.


Creating a Cloud-Based Strategy

Cloud data management is a great option for data management as a whole; technology in this space is always growing and capabilities expanding. When you choose cloud data management over on-premise options, you open up your business to faster, more advanced, and more efficient tools and processes. Using cloud data management as effectively as possible and doing everything you can to mitigate risk does not have to be difficult. The key to striking a balance between both of these things is creating a strong strategy for cloud-based data management.

There are four key things to consider when you are creating this strategy.

First, there is stored data. As we addressed before, data that is stored in the cloud is not protected by a firewall in the same way that on-premise data would be. The data that you are trying to manage is going to spend the majority of its life cycle in storage so you need to have a good strategy for protecting that data.

Best practice: Make sure that everything is encrypted.

Data accessibility is another important part of effectively managing data. There needs to be a balance here; employees need to be able to access the data necessary to get their jobs done but unfettered access poses significant security concerns. You need to have a strategy for making sure that data is both safe and accessible.

Best practice: Tailor access rights based on the needs of each employee, require authentication, and record all data transactions.

Next is the transmission of data. Whenever anyone accesses data that is stored in the cloud, it will have to travel from where it is stored to the point of access. This process is going to need to happen quickly and efficiently but you can't jeopardize the security of the data in question. You need to map out a way for data transmissions to happen both swiftly and securely.

Best practice: Ensure that all users are authenticated and that the pathways that data will be transferred through are also encrypted. Consider time-limiting access so that no data can remain on insecure devices after access.

Finally, backup and recovery methods are important. When data is stored locally, backups also exist locally. In the cloud, you will need cloud-based backup and recovery solutions. However, if all of this information is stored in the same place, it will all be lost at once. You need to have a strategy for backups that includes multiple storage locations.

Best practice: Have a separate cloud for storing all backup and recovery data; make sure that you test these periodically just as you would if you were using on-premise data management.