martes, 6 de diciembre de 2016

blog.aids.gov − CMS, CDC & HRSA Host State Medicaid & Public Health HIV Health Improvement Affinity Group

blog.aids.gov − CMS, CDC & HRSA Host State Medicaid & Public Health HIV Health Improvement Affinity Group
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CMS, CDC & HRSA HOST STATE MEDICAID & PUBLIC HEALTH HIV HEALTH IMPROVEMENT AFFINITY GROUP

Rich Wolitski - headshot - March 2016
Richard J. Wolitski, Ph.D., Director, Office of HIV/AIDS and Infectious Disease Policy, U.S. Department of Health and Human Services
On December 6-7, the 19 state teams that form the HIV Health Improvement Affinity Group* (HHIAG) will meet in Washington, DC, to develop new approaches for achieving better outcomes along the HIV care continuum for their Medicaid/Children’s Health Insurance Program (CHIP) beneficiaries who are living with HIV.
These teams will be comprised of a cross-section of staff from state public health and Medicaid/CHIP agencies, who will be grouped into three learning communities:
  • Data linkage and outcomes
  • Data analysis and utilization for delivery system improvement and provider engagement
  • Quality improvement
The communities will give participants opportunities to learn from one another and to receive technical assistance at the meeting and throughout the year, as they develop and refine plans to improve viral suppression in their states.
Data Linkage and Outcome Learning Community
The improvement plans for the six states in this learning community (California, Georgia, Iowa, Maryland, North Carolina, and Wisconsin) will focus on instituting or expanding currently limited data-sharing activities, as well as analyzing these data to identify targets for performance improvement.
All the members of this learning community have some foundation on which to build broader data-sharing agreements, including some history of exchanging data. In addition, many of these states indicated that they will use shared data to evaluate outcomes along the care continuum for HIV-positive Medicaid/CHIP beneficiaries, as well as to report results for the viral load suppression (VLS) measure included in the CMS Adult Medicaid core set. These states also intend to use their newly improved capacity to evaluate system effectiveness at multiple levels and along multiple dimensions (e.g., specific beneficiary subpopulations, service providers, and care delivery models) for continuous quality improvement and public health actions.
health-affinity-group-image-dec-2016Data Analysis and Utilization for Delivery System Improvement Learning Community
All six states participating in this learning community (Illinois, Louisiana, Maryland, New York, Rhode Island, and Washington) have elected to expand Medicaid coverage under the Affordable Care Act. As the majority of Medicaid/CHIP beneficiaries living with HIV in these states receive their health care through a managed care organization (MCO), increasing collaboration and engagement with Medicaid MCOs is crucial for accomplishing these states’ goals. This group’s focus is on using data to identify quality-improvement opportunities. Some states hope to use aggregate or state-level data analyses to identify areas where they can make delivery-system improvements. In their preliminary plans, these states propose several mechanisms to create change in delivery systems, including: using existing Medicaid authorities to make new evidence-based services available to people living with HIV/AIDS; promoting integration of services funded by Medicaid and the Ryan White HIV/AIDS Program; encouraging systems that focus on interdisciplinary care teams; and accelerating value-based purchasing through accountable care organizations.
While data analysis at program and state levels is useful for improving delivery systems and health policies, it is necessary to integrate and analyze client-level data across federally funded HIV programs to improve care coordination and avoid duplication or misalignment of services. While these states have made great strides in overcoming barriers to sharing data and information, more work can be done to reduce the administrative burden of data-sharing and to include MCO care-management and quality-improvement projects focused on HIV care, especially those aimed at measuring, reporting, and reducing HIV viral load among those enrolled in Medicaid.
Provider Engagement and Quality Improvement Learning Community
Members of this learning community (Alaska, Connecticut, Michigan, Mississippi, Nevada, New Hampshire, and Virginia) plan to improve clinical outcomes and achieve greater VLS rates through increased efforts to engage providers and improve quality of care. Because engagement and retention in care are critical to help PLWH achieve and maintain VLS, the improvement plans in this group focus on developing mechanisms to better share data between their state’s public health and Medicaid organizations. These improved information-sharing mechanisms will help states to identify people who may have been unable to access care or who have fallen out of care and get them into treatment.
Each state already has a unique system for collecting clinical and diagnostic information on its clients. While these states have made great strides in increasing their VLS rates, the teams will be doing more work to determine the unmet needs of PLWH and help to navigate them into care. Specific plans focus on collaborations between the public health and Medicaid teams to improve screening and testing, identify gaps in care, increase engagement in care, and improve surveillance techniques to identify quality-improvement opportunities.
*The HHIAG is a joint, 12-month initiative between the Centers for Medicare and Medicaid Services (CMS), the Centers for Disease Control and Prevention (CDC), and the Health Resources and Services Administration (HRSA), in collaboration with the HHS Office of HIV/AIDS and Infectious Disease Policy, and in partnership with the National Academy for State Health Policy, to support state collaborations to improve rates of sustained viral suppression among Medicaid/CHIP enrollees who are living with HIV.

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