Customer Story

Improving membership visibility, insights, and data quality

Total Health Care logo


members for a range of health plans for group, ACA exchange and Medicaid


enrollment transactions at more than 30 key data points in the process.


unique data points to reconcile the Medicaid population to the monthly Medicaid audit file

Total Health Care, a Michigan-based managed care organization, offers a range of health plans for group, ACA exchange and Medicaid to approximately 100,000 members. Each of these lines of business had its own membership process involving a variety of internal systems, external vendors and CMS. This disjointed structure of multiple systems and sources for membership data adversely impacted the company’s data management efforts by offering very limited visibility into the membership process and prevented leadership from seeing a complete and accurate understanding of key membership analytics. It also posed significant risks to the overall data quality of Total Health Care’s digital records. This combined lack of insights and quality control meant increased financial risk, inaccurate quality of care reporting and lost opportunity to improve the member experience.

Business challenge

The company’s chief information officer (CIO) Noah Monro and his team quickly recognized the numerous challenges presented by multiple membership sources and systems and began looking for a single platform to give the company complete visibility across disparate systems to better understand membership analytics to improve operations and make better business decisions. Members frequently hopped back and forth between exchange and Medicaid plans, resulting in duplicate membership files that gave an inaccurate view of gaps in care and other quality measures—lowering HEDIS scores and health plan reimbursement. To correct this inaccurate, inconsistent and duplicate data, Total Health Care needed a data reconciliation process that would reconcile data across multiple sources and use complex matching to detect any potential duplicates. This included summary and detail-level reporting on errors, reconciliations and membership data to consolidate duplicate files and resolve other quality issues.

Total Health Care was initially concerned that an automated solution wouldn’t yield sufficient ROI to justify the investment. But after careful review of the business case by every business segment they approved the initiative and selected Precisely to deliver an enterprise solution to improve process visibility and data quality.

The health plan’s objectives included:

  • Reconciliation of membership system data with daily 834 enrollment transactions
  • Reconciliation of the Medicaid population with the monthly Medicaid audit file
  • Identification of duplicates across every health plan business segment

Total Health Care logo


Total Health Care, a Midwest managed care organization offering group health, ACA exchange and Medicaid plans to approximately 100,000 members


Health insurance

The Challenge

  • Outsourced membership processes limited the plan’s end-to-end visibility into the quality of their key membership data
  • Lack of accurate membership analytics within and across business segments prevented the company from uncovering insights to improve operations and enhance the member experience
  • Inability to evaluate data quality metrics presented significant risk to the company

The Result

  • Real-time visibility into membership analytics
  • Proactive reconciliation of Medicaid and Exchange members to eliminate duplicates and prevent inaccurate reporting and costly re-work
  • Comprehensive data quality metrics around outsourced processes hold partners accountable for service level requirements

“The Precisely solution included real-time dashboards, and a reconciliation workflow to provide complete visibility of membership analytics and exceptions.”


The Precisely solution was deployed at Total Health Care to provide enterprise visibility and improve membership data quality. Automated membership data reconciliation identified any duplicates, discrepancies and other data issues between disparate systems, and featured real-time dashboards to view membership analytics, track enrollment files and report on exceptions. Its reconciliation workflow allowed users to easily view process statuses, obtain reports and resolve potential issues. As a cloud-based solution, it provided a financial advantage for the plan and enabled rapid implementation in a matter of months.

The Precisely solution provides the following functionality:

    • Provide end-to-end reconciliation of membership system extracts and daily 834 enrollment transactions at more than 30 key data points in the process

Graphic 1

    • Reconcile the Medicaid population to the monthly Medicaid audit file at more than 18 unique data points. An exception list, as well as a “Terminated by Absence” list is created and dispositioned appropriately

Graphic 2

  • Members are assigned unique identifiers enterprise-wide to reconcile between different business lines and systems. The solution includes a queued workflow where suspect matches are investigated to consolidate duplicates and properly identify unique members.



Total Health Care began to realize positive results even before the solution was in production. During user acceptance testing, the Precisely solution immediately began identifying files that were not properly updating between their membership system and the 834 transactions, as well as Medicaid files that were not updated.

Overall, Total Health Care has realized extensive value from their partnership with Precisely. First and foremost, the CIO and his team have greater visibility into membership accuracy and membership analytics. This was key to assuring member satisfaction and improving member satisfaction scores. Increased membership data integrity also ensured compliance with reports that are required for both health exchange and Medicaid lines of business.

Duplicate matching also resulted in a marked improvement to HEDIS data quality, as duplicate member records reflected inaccurate care gaps and other quality of care issues that mistakenly lowered HEDIS scores. By consolidating duplicates and improving data accuracy, the company’s HEDIS rose significantly, directly impacting Total Health Care’s financial reimbursement across multiple lines of business.
Additionally, greater operational efficiencies around highly manual processes were recognized in a number of areas, including proactive detection of incomplete or inaccurate membership records, automated enterprise-wide identification of duplicate members within and across business lines, and a standardized reconciliation workflow that guarantees detected errors or duplicates are resolved in an efficient and auditable process.

Lastly, complete visibility into data integrity metrics allows Total Health Care to better measure and monitor compliance around partner service level agreements.

Discussing situation

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