To get the most out of your NextGen EHR, you must pay attention to clinical data management. The clinical data stored in your EHR system is a critical asset for patient care. Clinical data management includes the processes and procedures to generate, consolidate, and validate that data.

Here are four best practices for clinical data management.

Clinical Data Management Best Practice 1: Consolidate Your Data

Health care mergers and acquisitions slowed during the COVID-19 pandemic, but experts expect them to surge again in 2021. Also, the 21st Century CURES Act requires increased data sharing between health care systems and ambulatory practices. Changes in ownership, referral networks, and health IT requirements can lead to clinical and financial data being spread across multiple systems. Clinical data conversions can help you consolidate this data in your NextGen EHR and EPM.

Clinical data conversions are a key part of clinical data management. If you switch EHR systems, a clinical data conversion allows you to port all data into your new system. This prevents data loss and ensures continuity of care for your patients. You can also use clinical data conversion to incorporate outside data into your NextGen EHR. For example, you can convert data shared by providers using other EHR systems or consolidate data from legacy systems.

Clinical data conversion is a complex process. If you map data from outside your NextGen EHR incorrectly, you risk creating errors in patient records. This can create confusion among your providers and staff or even harm patient care. Most practices will need help from expert NextGen developers, like those at TempDev, to complete a clinical data conversion effectively.

Clinical Data Management Best Practice 2: Reduce Duplication

Streamlining your data and avoiding duplication is a critical task for clinical data management. When data is duplicated across multiple systems, it is more difficult to keep up to date. Duplicative data within your NextGen EHR system also causes confusion for providers and staff. Over time, this data can create conflicts and errors, such as if you update a data element but that update does not capture duplicate data elements. Navigating duplicate data wastes time and can reduce satisfaction with your EHR system.

Data conversions can cause duplicate data by incorporating information from multiple legacy and external systems. A strong data conversion process will include strategies to reduce data duplication. This helps you keep your patient records as streamlined as possible.

Undertaking a data conversion or developing processes to reduce data duplication can feel like an insurmountable challenge for your practice. Partners like TempDev will help you identify duplicative data, develop a strategy for de-duplication, and monitor results for errors and other issues.

Clinical Data Management Best Practice 3: Monitor Data Quality

Your EHR system is a powerful tool. Taking advantage of it requires accurate, up-to-date data. That is why your clinical data management processes should include procedures to monitor data quality. This helps with data quality checks and processes to reconcile conflicting data during data conversions.

Data quality checks can include automated processes built into your NextGen EHR system. For example, NextGen can automatically flag potential dosage issues in prescriptions, patient allergies, or medication interactions. Data quality checks also ensure that EHR users enter data as expected in each EHR field. For example, data quality procedures can identify errors in diagnosis and procedure codes. By monitoring the quality of clinical data, you can reduce claims denials and save time and money.

If your practice is planning a clinical data conversion, build in time for data quality testing. This includes ensuring that imported data has mapped correctly to your NextGen system. Your project plan for your clinical data conversion should also include processes for reconciling conflicting or duplicated data. For example, patient demographic or diagnostic information may vary between data sources because of data entry errors. Before beginning a clinical data conversion, your team will need to decide which data source to trust in such situations.

Clinical Data Management Best Practice 4: Establish Data Governance

Data governance is the practices and procedures your organization uses to make critical decisions about your clinical data. Data governance is a collaborative process. Establishing a consistent data governance structure will help you ensure you receive input from across your organization when making data management decisions.

A strong data governance structure will help you respond to regulatory changes with ease. Federal health IT requirements change over time, as do requirements from other health systems and payers. Bringing together a data governance team to review such changes and develop an agreed-upon plan of action will save your practice time. It will also increase the satisfaction with your EHR system, as the staff who use the system daily will have a voice in upgrades, changes, and clinical data conversion processes.

How TempDev Can Help with Clinical Data Management

TempDev’s NextGen consultants and developers can help you implement clinical data management best practices. TempDev has guided many ambulatory practices and clinics through clinical data conversions. As NextGen experts, we can help your practice manage your clinical data to ensure patient records are accurate, complete, and easy to use.

Call us at 888.TEMP.DEV or contact us here to get help on improving your clinical data management.