Citation :

Justin Pathrose James, "DataOps Strategies for Automating HEDIS Compliance," International Journal of Computer Trends and Technology (IJCTT), vol. 73, no. 10, pp. 10-14, 2025. Crossref, https://doi.org/10.14445/22312803/IJCTT-V73I10P102

Abstract

This paper talks about how Data Ops concepts can be utilized in creating survey questions like HEDIS. The Data Ops principles, like Structured Data Pipeline, Automation, and Governance, are applied with the clinical rigor of HEDIS measures. Since DataOps can be applied to any business process or analytic solution that involves extracting, a time-consuming process like creating and collecting HEDIS data will have much scope for automation. 

Keywords

DataOps, Artificial Intelligence (AI), HealthCare, HEDIS, Data Analytics, NCQA.  

References

[1] NCQA, Improving HEDIS Data Quality in a Digital World, 2025. [Online]. Available: https://www.ncqa.org/blog/improving-hedis-data quality-in-a-digital-world/
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[3] NCQA, The Path to Digital HEDIS. [Online]. Available: https://github.com/databricks-industry-solutions/apollomed-ncqa-hedis
[4] NCQA, Health Plan Performance. [Online]. Available: https://www.ncqa.org/report-cards/health-plans/ 13 Justin Pathrose James / IJCTT, 73(10), 10-14, 2025
[5] AHRQ, Examples of Health Plan Quality Measures for Consumers. [Online]. Available: https://www.ahrq.gov/talkingquality/measures/setting/health-plan/examples.html
[6] Center for Care Innovations, Case Study: Sharing and Celebrating HEDIS Bright Spots at Community Health Center Network, 2019. [Online]. Available: https://www.careinnovations.org/resources/case-study-hedis-bright-spots-community-health-center-network/
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