Data Management after EHR Implementation

EHR Implementation projects from the last decade have been costly and time-consuming projects for most healthcare systems in the country. Making an implementation successful often requires a ‘get live, then optimize’ mentality. When the organization is ready to optimize, discussions about data management are typically top of the priority list.

You can relate if you’ve ever heard these types of conversations:

  • “Who owns maintenance of ___? Where do those requests come from?”
  • “How do I know what is needed to request a new ____? Do we have a form for that?”
  • “I need a report on _____ visits at this department. I’m not sure how we define visits though – appointments or charges?”

Data management is a critical concept to regular business functions because it establishes processes, relationships, and shared facts for the entire organization. If it is unclear how to request a certain change or how to get a certain change implemented – money is lost in the time it takes to figure out the process for making those changes. If there is not a consistent way to display a key piece of data – most will be lost in the time it takes to figure out a new way to display the data. If there is not clear ownership for maintaining a specific piece of data – money will be lost in the time it takes to get the data updated and back to a useful state. Data management is focused on cost control by making it easier and cheaper for internal stakeholders to understand how the business operates.

Several examples of data management in action:Data Management Chart

  • A charge entry user is entering a nursing home charge for a physician. It seems that location is not built in the EHR yet, so she requests a new record be built because she knows exactly which form to fill out and she is prompted on how to fill out the form correctly.
  • A workgroup is working on a key initiative and puts in a request to see all the active patients with such and such criteria. A report writer gets the request and processes the request easily because the definition of an “active” patient is one already used consistently across the enterprise.
  • IT would like to automate maintenance of a few key fields in their master list of providers within the EHR. The Infrastructure / ETL team can support this request because they already have an automated reconciliation query to identify changes in the credentialing software that need to be now transferred to the EHR.

As healthcare IT systems continue to change and mature, there is an ever-expanding amount of data to pull from. ERP systems have payroll data and cost metrics, EHR systems have patient data and operational activity, CRM and VoIP solutions have customer data – getting this data to integrate with each other, stay in sync with each other, and create meaningful information requires conscious effort. Choosing the source of truth for identifying a single user within each system and syncing that user’s activity across systems requires implementing a plan to keep these concepts in sync.

A fast and profitable optimization of IT requires a strategy for data management across the organization. It requires input from multiple stakeholder groups and to be successful you need project managers who have experience with cross-department projects and the political negotiating they entail. It is often necessary to find partners with deep experience across multiple IT platforms and with a history of establishing successful data management protocols. When considering how to improve performance of your organization, consider data management as a top priority.

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EHR Implementation projects from the last decade have been costly and time-consuming projects for most healthcare systems in the country. Making an implementation successful often requires a ‘get live, then optimize’ mentality. When the organization is ready to optimize, discussions about data management are typically top of the priority list.

You can relate if you’ve ever heard these types of conversations:

  • “Who owns maintenance of ___? Where do those requests come from?”
  • “How do I know what is needed to request a new ____? Do we have a form for that?”
  • “I need a report on _____ visits at this department. I’m not sure how we define visits though – appointments or charges?”

Data management is a critical concept to regular business functions because it establishes processes, relationships, and shared facts for the entire organization. If it is unclear how to request a certain change or how to get a certain change implemented – money is lost in the time it takes to figure out the process for making those changes. If there is not a consistent way to display a key piece of data – most will be lost in the time it takes to figure out a new way to display the data. If there is not clear ownership for maintaining a specific piece of data – money will be lost in the time it takes to get the data updated and back to a useful state. Data management is focused on cost control by making it easier and cheaper for internal stakeholders to understand how the business operates.

Several examples of data management in action:Data Management Chart

  • A charge entry user is entering a nursing home charge for a physician. It seems that location is not built in the EHR yet, so she requests a new record be built because she knows exactly which form to fill out and she is prompted on how to fill out the form correctly.
  • A workgroup is working on a key initiative and puts in a request to see all the active patients with such and such criteria. A report writer gets the request and processes the request easily because the definition of an “active” patient is one already used consistently across the enterprise.
  • IT would like to automate maintenance of a few key fields in their master list of providers within the EHR. The Infrastructure / ETL team can support this request because they already have an automated reconciliation query to identify changes in the credentialing software that need to be now transferred to the EHR.

As healthcare IT systems continue to change and mature, there is an ever-expanding amount of data to pull from. ERP systems have payroll data and cost metrics, EHR systems have patient data and operational activity, CRM and VoIP solutions have customer data – getting this data to integrate with each other, stay in sync with each other, and create meaningful information requires conscious effort. Choosing the source of truth for identifying a single user within each system and syncing that user’s activity across systems requires implementing a plan to keep these concepts in sync.

A fast and profitable optimization of IT requires a strategy for data management across the organization. It requires input from multiple stakeholder groups and to be successful you need project managers who have experience with cross-department projects and the political negotiating they entail. It is often necessary to find partners with deep experience across multiple IT platforms and with a history of establishing successful data management protocols. When considering how to improve performance of your organization, consider data management as a top priority.