Ask anyone who’s been part of a new system implementation – and it doesn’t matter if it’s a new EMR, ERP or patient finance system – you’ll quickly learn that those are really significant endeavors for any healthcare organization.
Now, not to diminish the role “systems” play in system transitions (it’s IN the name, after all), I am about to make a bold statement:
During these projects, which require hefty investments of both time and money, the asset we should be most concerned with is not the software. It’s the data. We want it to be formatted appropriately and mapped correctly for the new systems. We want it to be accurate. We don’t want anything to get lost in the shuffle. We want to still be able to provide our end users access to any legacy data they may need that doesn’t move into the new systems.
Data fuels clinical care decisions. It drives processes. Quite frankly, it’s the foundation for every health system. And, as healthcare organizations continue to reach deeper into the communities they serve by way of ambulatory partnerships and acquisitions, there will be a need to address duplicate systems if they’re to achieve economies of scale.
But how do you prioritize data transfer from acquired entities — like ambulatory clinics — for conversion* or migration? How do you make it accessible for use? And what are the constraints that create friction, and maybe even prevent, organizations from liberating their data?
Think beyond “committee formation” to nurture trust
Yes, identifying and recruiting a multi-disciplinary team is a necessary part of any data transfer project. But, liberating your data is as much an exercise in nurturing trust among stakeholders as it is a technical project. Earning and nurturing trust among the people involved is often overlooked as a priority for data transfer projects. It’s understandable. We’re all busy and have competing priorities and most of the time none of them fit together all that easily. That’s why it’s important to acknowledge and invest in nurturing trust within that multi-disciplinary team.
Make your first exercise as a team an opportunity for each individual to openly share what’s going on in their world and how this project impacts/fits into that. This dialogue – and the act of both being heard and listening to others – helps set the stage for trust-building. Including an executive sponsor on the team who demonstrates a willingness to support success as an accountability partner for the work plan lends credibility and instills confidence and a sense of empowerment. Come to an agreement on communication. It must be consistent, reliable, concise, and clear. Set a cadence – communication must also be ongoing.
Define your requirements
It’s important that each individual recognizes and appreciates the reasons why the organization is taking on this significant of a project – i.e., why it’s moving its data to a new system. This shared mission builds trust among the team, but it will also help you and your stakeholders know where to focus your energies. Some reasons why you may need to transfer data include the need to:
Comply with state regulations. Some states want patient records to be retained for upwards of 27 years. Check your state regulations for the requirements for your type of healthcare organization. What data you’ll need to keep and how often it’s accessed will help you determine what type of archive solution you’ll need.
Support efficient, effective care decisions. When patients come in for their appointments or treatments, your clinicians need instant access to their medical history, past diagnoses, medications, allergies and other vital information.
Quickly transition to a new system. Say, for example, because your legacy system is sunsetting and you’ve got a window before you lose it and the data it contains.
Accelerate coding tasks. Before you can adopt new coding systems, which have more efficient data codes and identifiers for medication, insurance providers and patient data, you’ll need to convert old patient records.
Agree on standards
While APIs and the cloud are all the rage in newer software, they are not representative of the way many legacy systems live in today’s healthcare environment. Most of the data in many of these systems are simply not standardized. Many vendors and developers use disparate data formats and codes to store patient data. Apart from the CPT codes, standard ICD-10 codes, and billing information that follows HIPAA standards, a lot of data is stored in vendor-specified codes.
This is the time to set your standards for the input and retrieval of data on medical exams, history, treatment plans and complaints. Take time to find out how your current system stores data and decide how to improve on this for more efficient retrieval in the new system.
Use optimized data extraction methods
Ask your current vendor how you can access and extract data stored in your system. This includes data stored in the database as well as in the forms of audio, images and text files. Some EMR systems offer you mass export options in the form of clinical document architecture (CDA), while others provide CSV files. You can also export data in the form of PDF files from some EMR databases.
Evaluate your resource constraints
Resource constraints are defined as time, people with relevant expertise (experience + knowledge), budget and location. While they depend on multiple variables and manifest in ways unique to each organization, resource constraints impact every project and every priority.
With respect to budget, if your new EMR system allows you to export data successfully from your old system, your in-house IT team can explore this low-cost option. On the other hand, you may need to handle conflicts with data coding, incompatible identifiers and empty fields. This means you need to pay vendors who have the expertise and experience to help you handle all conflicts, data errors and data duplication that may occur during migration.
The total cost of a complete migration process should include cleaning the data and resolving any errors that occur after conversion. To reduce the cost of data migration, you can negotiate with your EHR vendor and ask your in-house IT team to handle the migration in stages.
Other than budget, a resource constraint that often stands out is the lack of ‘people with relevant expertise’. The growing demand for the right expertise in transferring data, for whatever reason to whatever system, requires outside help. It’s not about your organization not knowing its operational and clinical requirements. It’s about knowing how to meet them by using the technical discipline of transferring data.
Get an independent assessment of your situation. And, to keep things objective, get an assessment from more than one source. Comparison often creates a clearer perspective.
*Note: migration is defined as a transfer of data, in context, as-is, most often to an archive. Conversion is a transfer of data in the form of an import where specific fields are mapped and data are imported into a new enterprise system.
Daniel Alex VP of Conversion Services