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Data Tips and Tricks to Improve Outcomes Management and Quality Reporting

Data Tips and Tricks to Improve Outcomes Management and Quality Reporting
Get the most from your EHR Technology

Utilizing your Electronic Health Record (EHR) to its fullest capacity is an integral part of improving quality reporting and performance as well as outcomes management and analytics. Familiarity with the breadth of your EHR’s capabilities is critical but must also be paired with a sound workflow for maximum EHR usability. Capitalizing on the EHR’s usability and building clear workflows will not only create efficiencies within your organization but can also help with data extraction when it comes time for quality reporting and pay-for-performance incentives. 

When using multiple disparate systems, data can quickly turn from friend to enemy. Having detached and separate data across various systems essentially makes that data unusable for the purposes of outcomes management and quality reporting. For example, organizations that have a radiology department using PACs (Picture Archiving and Communications system), which is separate and disparate from the larger organization’s main EHR, will face great challenges when attempting to run analytics for internal measurement and/or quality reporting. For this example, information, in the form of discrete data fields needed for running analytics and for reporting to CMS and other payers, may not transfer over completely. Setting up workflows that can isolate certain text strings and then utilize .phrases in the EHR  is a great way to streamline data collection processes. The result is discrete data from all systems available for running analytics or ensuring better performance on quality measures reported to payers.

Diving deeper into one example, when reporting for a measure like measure #364 ‘Optimizing Patient Exposure to Ionizing Radiation: Appropriateness: Follow-up CT Imaging for Incidentally Detected Pulmonary Nodules According to Recommended Guidelines‘, final reports that have follow-up recommendations need to clearly state the source of the recommendation. In this scenario, a simple .phrase could be created for all final radiology reports of patients that had an incidental pulmonary nodule found to state “according to [name of guideline creating society] Society… and the remaining recommendation including the time frame for the follow up.  This .phrase could be utilized by your radiology team for reporting and better documentation. 

Another useful tool is an automatic recall system, which can be generated for a multitude of scenarios. Based on specific diagnosis codes, patient can be set up for a recall, which can help to ensure the patient knows they need to return to the clinic for needed follow-ups. A recall system can help when data extraction occurs for measures that require follow-up reporting.

Creating custom workflows that utilize various systems in your organization is a great way to improve documentation. However, especially when operating with multiple disparate systems, workflows are not the only answer. Standardized processes, which make best use of the exchange and management of discrete data in the EHR, are also critical. The combination of standardized workflows and better use of EHRs to facilitate better reporting will help promote better overall performance and patient care.