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Enhancing health outcomes through advanced Medicaid solutions

Six ways analytics can improve outcomes and reshape public health  

Since its inception in 1965, state Medicaid agencies have focused on providing access to healthcare and ensuring prompt payment for services, prioritizing care delivery over health outcomes. Originally established to provide basic health coverage to people with limited resources, Medicaid has expanded to include individuals with permanent disabilities. Over time, state health services have evolved into primary, long-term coverage sources for vulnerable populations.

Today, advanced analytics, machine learning, and AI present state Medicaid agencies with unprecedented opportunities to enhance community health outcomes. By integrating technology with advanced data integrity, agencies can gain insights into costs, reduce waste, manage risks, and predict outcomes based on behavioral patterns in data. Implementing core data models for analytics that can be shared across agencies and state lines promises maximum value at minimal cost. 

But public health administrators and officials often don’t know where to turn to harness these technologies, especially considering limited funding, staffing and IT limitations.  

Building on data integrity 

Concerns about data integrity have been a primary barrier to adopting advanced analytics. Today, however, analytics built on nationally validated T-MSIS data provide measurable and proven reliability. States can create reliable analytics by combining T-MSIS data with other nationally available sources and state agency data, benefiting agencies beyond Medicaid and ultimately improving health outcomes. 

Machine learning and AI are powerful tools in predicting and preventing fraud, waste and abuse. CMS uses T-MSIS data for national Medicaid Program Integrity, signaling that states should follow suit. By adopting these technologies, states can ensure resources are directed to those who need them most, thereby enhancing the efficiency and effectiveness of healthcare delivery and improving overall community health. 

Innovations in healthcare analytics 

Data based on major diagnosis codes, incarceration history, veteran status, citizenship, gender, ethnicity, tribal affiliation, race and income can provide profound insights into healthcare needs and outcomes. Other ways advanced analytics can transform community health include:  

  1. Incarceration and healthcare 
    Analyzing the healthcare needs of beneficiaries recently released from incarceration can reveal critical issues affecting inmate health. These insights can help drive legislative changes to prison healthcare and aftercare programs, ensuring continuity of care and better health outcomes for this vulnerable population. 
  2. Tribal healthcare 
    Comparing health conditions specific to tribal health agencies with non-tribal populations can lead to innovative solutions that improve health while reducing federal costs. For example, Medicaid-funded mobile units can supplement tribal health clinics, addressing unique healthcare challenges faced by tribal communities. 
  3. Genetics and chronic illness 
    Agencies can leverage family-related healthcare information to detect potential genetic health issues. Early intervention in chronic illnesses like heart disease, diabetes, and high blood pressure can help prevent costly complications later. Proactive family treatment can significantly reduce the incidence of adult chronic conditions, leading to healthier communities and lower healthcare costs. 
  4. Veteran health 
    Military veterans face unique physical and mental health challenges. Behavioral health analytics can combine diagnosis information and services to predict and prevent incidents such as medication non-compliance, which can be an indicator of suicidal tendencies. Targeted interventions can support veterans in maintaining their health and well-being. 
  5. Law enforcement and at-risk populations 
    There is often a crossover between law enforcement incidents, child protective services, domestic abuse cases and Medicaid services. By coordinating and combining law enforcement data with Medicaid information, agencies can identify and support at-risk populations, leading to proactive interventions and long-term solutions that enhance community health. 
  6. Portability across states 
    Each state must conform to T-MSIS data format and content requirements, ensuring data is validated to national standards. This standardization makes T-MSIS data formats a versatile tool that can be used beyond their original purpose. Solutions based on T-MSIS data can be easily ported between states, shared with neighboring states or utilized by CMS to address cross-state patterns. This portability allows for the detection and sharing of solutions that improve health outcomes on a national scale. 

Conduent’s CMdS Federal Reporting Module 

At Conduent, our teams deploy our CMdS Medicaid Suite to facilitate the transition from legacy MMIS to modern Medicaid Enterprise Systems. CMdS supports both standardized data exchange and state-specific formats, ensuring integration across solutions, whether they originate from Conduent or other vendors. CMdS modules perform critical functions while unlocking modern, streamlined processes and capabilities. 

CMdS’s Federal Reporting module was designed with improving health outcomes in mind, starting with the modernization of legacy Medicaid Management Information Systems using Decision Support System/Business Intelligence (DSS/BI) tools more than 20 years ago.  

With tools like CMdS, state Medicaid leaders are provided a solid foundation to transition from providing a framework for basic healthcare needs as a payor of last resort, to developing strategies that improve health outcomes for their communities and ultimately better managing taxpayer contributions across multiple agencies, improving population health, and enacting positive change that transcends traditional agency obligations and roles. 

Ready to discover how Conduent can help your agency drive migration from legacy MMIS to a digital, interoperable enterprise that drives outcomes for your organization? Contact an expert now or visit us online.  

About the Author

Lori Erickson has nearly 40 years of experience in the Medicaid industry. She began her career as a Medicaid programmer for the State of Montana in 1985 and later joined Consultec/ACS, continuing through its acquisition by Optum. Lori spent over a decade with Optum before rejoining Conduent in 2019.

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