Elevate your coding standards with a new automation
In New York state’s intricate health system, it’s crucial to implement effective healthcare data management that meets Statewide Planning and Research Cooperative System (SPARCS) deadlines. The SPARCS Program requires consistent data submission reports. With the wrong system, SPARCS formatting and submissions can waste precious time and resources for health information management (HIM) coders, SPARCS data analysts and healthcare professionals.
With DataGen's UDS (UIS Data System™) new trending failures feature, you can automate more aspects of your SPARCS data to keep up with the evolving healthcare industry. Continue reading to learn how this functionality allows SPARCS data analysts and administrators to see repeat issues with coded records immediately and save your team precious time.
The cost of correcting records
Submitting records to SPARCS has significant financial implications. Each time a coder touches a record for correction, there’s an associated cost. Consider this scenario:
Imagine it takes a coder 20 minutes to fix a single record and a SPARCS admin an additional 10-15 minutes to log errors in a spreadsheet. With a facility submitting 10,000 records monthly and a failure rate of 10%, approximately 1,000 records require correction. This translates to ~333 hours of coder time each month dedicated to fixing failed record — or nearly 4,000 hours annually.
By trending failures, healthcare facilities can identify opportunities to improve the process instantaneously, allowing more focus on improving coding practices and avoiding the extensive hours currently spent on corrections.
DataGen’s trending feature
Spreadsheets have been the go-to tool for capturing common submission problems. Coders reconciled these issues at the time of coding, often resulting in additional labor for SPARCS and HIM coders. However, DataGen’s new feature streamlines this process.
Methodology
When a coder revisits a record to correct errors, the organization loses time and money. But by recognizing these problems month-over-month (MOM), organizations can implement upstream corrections, reducing rework in the future.
This approach is part of DataGen’s innovative methodology. Unlike traditional methods where reports are generated from billing systems, DataGen analyzes submission processes to optimize healthcare billing and reduce time spent handling data. The ultimate goal is to decrease the need for repetitive record adjustments, enhancing efficiency and accuracy in SPARCS data submissions.
How it works
Trending failures is a unique software feature in DataGen’s UDS. This functionality identifies and analyzes recurring issues in SPARCS data submissions, eliminating the time SPARCS administrators would take to review and correct HIM coding errors.
Information is logged at the time of automated import, providing HIM managers and SPARCS managers with real-time insights into the status of last month’s submissions. This immediate feedback loop reduces manual legwork and facilitates a more efficient workflow by identifying and addressing issues before they become systemic.
Benefits
1. Reduce time expended on corrections
The primary advantage of trending failures is reduced time expended on record correction. By fixing coding processes proactively, healthcare organizations can significantly cut down on the time required for corrections. Instead of spending hundreds of hours monthly correcting records, staff can concentrate on refining current submissions and maintaining compliance with SPARCS deadlines.
For instance, facilities can channel efforts toward improving coding accuracy by making the error identification process instantaneous. This proactive approach helps mitigate the risk of errors and enhances the overall submission quality, saving valuable time that can be reallocated to other critical tasks. Learn more about the benefits of automated SPARCS submissions.
2. Meet SPARCS deadlines more effectively
Adhering to SPARCS deadlines is vital for healthcare organizations to avoid SPARCS compliance risks and penalties. With fewer records failing initial submissions, the rework associated with correction decreases significantly. Coders can focus on addressing current issues rather than revisiting old data, ensuring compliance is achieved sooner in the workflow.
Consider a scenario where organizations are working on March SPARCS data in June. Without trending failures, they may still be addressing March errors in July. However, with DataGen’s feature, March data can be finalized promptly, allowing efforts to shift seamlessly to April’s submissions.
How this tool can help
Example 1: High record failure rates
Imagine a mid-sized healthcare organization struggling to meet SPARCS deadlines due to high record failure rates. By implementing trending failures through DataGen, they reduced their correction time from 300 hours per month to just 50 hours. This not only improves their compliance rates but also allows staff to focus on patient care and other essential services.
Example 2: Quickly addressing and adjusting record submissions
In another example, an ambulatory surgery center saw a 25% decrease in submission errors after adopting the trending failures approach. By identifying patterns in their coding errors, they adjusted their training programs and coding guidelines, improving accuracy and efficiency in their record submissions.
Healthcare billing optimization
SPARCS data analysis plays a crucial role in optimizing healthcare billing processes. By leveraging comprehensive data insights healthcare facilities can pinpoint inefficiencies and areas for improvement leading to a more streamlined billing workflow.
This method is not only focused on reducing errors but also on enhancing the overall financial performance of the billing process. The use of SPARCS data analysis facilitates a deeper understanding of coding trends and practices, especially within HIM, ensuring that organizations can align their coding strategies with industry standards and regulatory requirements. As a result, healthcare billing optimization becomes attainable, driving better outcomes for providers and patients through improved operational efficiency and accuracy.
Join the 77+ New York state facilities using UDS
Trending failures offer a strategic advantage for healthcare organizations aiming to optimize their SPARCS data submissions. By identifying recurring issues and addressing them proactively, facilities can reduce correction time, enhance coding accuracy and more effectively meet SPARCS deadlines.
For those looking to explore this innovative approach further, DataGen’s new trending feature in UDS 7 provides a streamlined solution that integrates seamlessly into existing workflows. Accessible to all UDS 7 users, this tool empowers organizations to learn from past mistakes and drive continuous improvement in their data submission processes.
Contact us to start trending coding failures today, and experience the benefits of a more efficient, accurate and compliant SPARCS data submission process.
This content is for informational purposes only. It has been partially generated from an AI language model, which may not always be exhaustive or tailored to individual circumstances. We encourage you to contact one of our experts for more information. We assume no liability arising from any use of this content.
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