Being able to accurately capture data for patient care management and regulatory requirements reporting can be a daunting task. HSi has worked with two clients (Client A and Client B) who had identified unique EHR (electronic health record) hemodialysis report requirement needs. Client A desired a detailed report with columns for patient name, treatment start and stop dates, type of treatment, name of the nurse who administrated the treatment, and medication information. Client B sought a monthly summary report with over 2 dozen measures such as the number of treatments, whether an inpatient or outpatient, if an acute or chronic patient, and access types (tunneled or non-tunneled; and, external jugular, femoral, subclavian, trans lumbar, etc.) deaths during the month. The data for both reports was pulled from many areas within the EHR databases such as patient encounters, documentation flowsheets, and charges. Initial report development was based upon assumptions of how the clinical information was typically entered into the EHR by the caregivers. Further investigation into the data found gaps between what was thought to be entered and what was actually being entered. The challenge for both hospitals was quality of the information clinicians were actually documenting in the EHR. There were instances when it was not clear when a hemodialysis treatment started or ended, how many treatments a patient received on a given day, or the actual type of treatment. These issues highlighted the need for workflow improvements at both locations to correct data quality concerns.
Before the reports could be completed, a better understanding of the immensity of the gaps in question was needed. Therefore, audit reports were created to assist with resolving the data quality concerns. The reports, once implemented and analyzed, resulted in identifying the following key areas of adjustment to ensure the IT and clinical staff was now working in concert and all data points were being collected:
In both cases, HSi was able to deliver the client requested reports; furthermore, the request also spurred changes in workflow and system build hampering data quality and consistency. Correcting these issues directly contributed to both the development of the reports and meeting regulatory hemodialysis reporting requirements. More importantly, the modifications spurred long term changes ensuring data integrity while inspiring a mindset transformation that encouraged the locations to critically analyze data along with how it is being entered and utilized. Quality information with rock-solid integrity is a key to harnessing the power of any organization’s data.
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