The Community Personal Assistance Services (CPAS) program is a state plan program that provides in‐home personal assistance services, nurse monitoring, and supports planning to older adults and individuals who need assistance with at least one activity of daily living. This infographic presents information for fiscal year (FY) 2019 to FY 2021.

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The Community Supports Waiver (CSW) provides community-based services and supports to individuals of all ages with developmental or intellectual disabilities. This infographic presents information for fiscal year (FY) 2018 to FY 2021.

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The Community Pathways Waiver provides community‐based services and supports to individuals with developmental or intellectual disabilities. This infographic presents information for fiscal year (FY) 2017 to FY 2021.

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The Home and Community‐Based Options Waiver (CO Waiver) provides community‐based services and supports that enable older adults and those with physical disabilities to continue living in their own homes or in assisted living facilities. This infographic presents information for fiscal year (FY) 2019 to FY 2021.

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The Community First Choice Program (CFC) is a §1915(k) state plan program that provides home and community‐based services (HCBS) to older adults and individuals with disabilities who meet an institutional level of care. This infographic presents information for fiscal year (FY) 2019 to FY 2021.

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The Brain Injury (BI) Waiver provides services to individuals aged 22 or older with a brain injury diagnosis who require specialty hospital or nursing facility level of care to be supported in their own homes or community‐based settings. This infographic presents information for fiscal year (FY) 2017 to FY 2021.

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Due to the high demand for Autism Waiver services and a defined capacity, individuals wishing to receive waiver services must have their name placed on the Autism Waiver Registry. This infographic presents information for fiscal year (FY) 2019 to FY 2023.

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Autism Waiver services enable individuals who have Autism Spectrum Disorder and who meet an institutional level of care to be supported in their own homes or community‐based settings. This infographic presents information for fiscal years (FYs) 2017 through 2021.

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In 2014, the state of Maryland partnered with the Centers for Medicare and Medicaid Services (CMS) to modernize its unique all-payer rate-setting system for hospital services to improve the overall health of Maryland residents by increasing health care quality and reducing the cost of care. In service of providing better care at lower costs, The Hilltop Institute at UMBC, in partnership with the Maryland Department of Health, has developed predictive risk stratification models to identify patients at high risk for potentially preventable health care utilization that can be used to help target care resources to the patients who need them most.

This document strives to explain the intended use, technical implementation, and model performance of the Hilltop Pre- Models as of November 2022. The Pre- Models are a suite of prediction tools spanning the Pre-AH Model™, Pre-CH Model™, Pre-DC Model™, and Pre-HE Model™. This document will be updated as the models are updated or when new models become operational, and significant changes will be noted in the documentation edit history table and in the text when necessary. This first section of the codebook provides a short introduction; the second section provides a general overview of data sources, training methodology, and scoring methodology; the third section provides specific details on the performance and operations of each model within the Hilltop Pre- Models suite; and the fourth section presents limitations.

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In this article published in the Gerontologist, Hilltop Director of Aging & Disability Studies Christin Diehl and Policy Analyst Roberto Millar, PhD—along with Nancy Kusmaul, PhD, and Ian Stockwell, PhD, from UMBC—discuss their study, which aimed to compare two quality frameworks: one based on observational factors and one based on family satisfaction.

Read the article online.