In fact, without a pre-project plan and data migration checklist, your entire project could get derailed or cause security, privacy, compliance, or regulatory problems down the line. There’s also a lot of data to consider. The healthcare industry generates approximately 30% of the world’s data volume. By 2025, the compound annual growth rate of data for healthcare will reach 36%. That’s 6% faster than manufacturing, 10% faster than financial services, and 11% faster than media and entertainment.
Justifying the time and cost investment of a data migration project can require answering several critical operational questions and getting ahead of potential risks. Consider these six questions before meeting with leadership or setting a budget:
You’ll need to determine whether it makes sense to migrate all or only a subset of your data. As you consider the healthcare data life cycle, archiving data should be an important part of this conversation. Your conclusions will drive the cost and timeline of the entire data migration project, but there are other factors as well. With a full migration, you’re better able to meet regulatory compliance standards and will maintain complete access to patient information and historical clinical data – supporting care continuity, research, and data analysis and reporting. You also have to consider the importance of data integrity, however, and whether older information may be incomplete or in the wrong format, necessitating extra steps in the process. Migrating some data may be more efficient and allow for prioritization of the most high-value data and information, but you also lose the benefits of a full-system migration.
While a hybrid approach to clinical data management may feel more familiar, the reality is that today’s cloud services are safe, secure, scalable, and affordable. Migration to the cloud enables you to convert massive amounts of complex data automatically, and it eliminates the need to pay maintenance fees for expensive in-house hardware. In addition, many cloud storage service vendors even provide backup options to give you an additional layer of security. So, it’s not surprising that 78% of healthcare organizations have either completed a cloud-based migration or are in the process of migrating their data to the cloud, according to a 2023 HIMSS Analytics Report.
There is no right answer, and that answer may depend on business needs, like resource management and minimization of operational disruption, or concerns about mitigation of errors and the flexibility to adjust to shifting priorities. While an all-at-once transfer typically involves taking systems down for a longer period, the advantage is that it’s a “one and done” proposition. With a phased approach, the data migration process is completed in pieces by running both systems in parallel, thus eliminating downtime.
The individuals on the clinical data migration team each should bring distinct skills, knowledge, and experience that make the overall project successful. For this team, you’ll need data owners and stewards (e.g., health information management [HIM] teams, researchers, and clinicians) who understand the importance of data integrity and have a vested interest in ensuring the data is migrated successfully. Clinicians use this data to provide patient care, researchers use it for clinical research projects, and HIM teams use it for critical business functions. All these individuals can provide essential information about potential gaps or problems during the data migration process.
The clinical data migration team should also include a group of functional experts who can validate the data and ensure it transfers accurately and maps correctly. Finally, the team needs professionals skilled in software development and data transfer who can resolve potential technical issues quickly and effectively. If your organization doesn’t have the right clinical data management expertise to manage the project, consider partnering with a third-party vendor that can help you achieve the results you seek.
One challenge of any data migration project is poor-quality data. Migrating and archiving data doesn’t negate existing data errors and omissions, and it may even exacerbate them. To combat this, perform data cleanup before starting the migration process. Identify records with mistakes, duplicates, or unnecessary details, then leverage data cleansing tools to get rid of inaccurate or damaged data. Implement data quality checks, validation rules, and data cleansing workflows at every stage of the migration project.
A second challenge is inconsistent data formats. Clinical data comes in a wide variety of formats, and there may also be special considerations for migrating images, multi-level patient records, and diagnostics. Converting the data to a consistent, interoperable structure—especially older data in legacy systems—becomes paramount.
There are three major risks that we’ve identified:
The best way to mitigate these clinical data management risks is to stick to the data migration checklist and roadmap for completion that includes a clearly defined project scope, budget, specific data migration solutions and transfer methods you’ll use, and steps you’ll take to promote the importance of data integrity (e.g., ongoing and proactive validation and monitoring).
Anticipating and addressing clinical data management challenges ahead of time can make your data migration project, including archiving data, go smoothly. So can the right technology.
See Olah’s simple, fast, and complete solution to data archiving in action.