Articles

Could AI Transform the Role of the Community-Based Care Manager? Leadership, Judgment and Accountability in US Services
Artificial intelligence could change how community-based care managers coordinate services, supervise teams, identify emerging risks and demonstrate quality. But the opportunity extends beyond administrative efficiency. This article examines how AI may reshape managerial responsibilities across US Medicaid HCBS, LTSS, IDD and behavioral health services, including human oversight, workforce capability, funding, participant rights, regulatory accountability and the evidence needed to establish whether technology genuinely improves care. Read more...
Digital Exclusion and the Future of Technology-Enabled Community Care
As digital systems become central to US community-based care, people without reliable connectivity, accessible devices, digital confidence or appropriate support risk losing access to services and meaningful choice. This flagship analysis examines digital exclusion across Medicaid HCBS, LTSS, disability services, behavioral health and aging, connecting federal and state responsibilities with provider operations, funding, workforce capability, participant rights and evidence-led approaches to inclusive technology adoption. Read more...
Technology-Enabled Care and the Future of Community-Based Service Delivery
Technology-enabled care is reshaping how community-based services can be organized, delivered and evaluated across the United States. This flagship analysis examines the opportunities and limitations of remote support, digital coordination, assistive technology and hybrid service models across Medicaid HCBS, LTSS, disability and behavioral health. It explores the funding, workforce, rights, governance and quality requirements needed to turn technological capability into sustainable improvements in everyday support. Read more...
What Happens When AI Becomes Part of Everyday Community-Based Care?
Artificial intelligence is moving beyond administrative experimentation toward everyday decisions in community-based care. This flagship analysis examines how AI could reshape Medicaid-funded HCBS, LTSS, disability and behavioral health services, from workforce scheduling and documentation to risk identification and care coordination. It explores the implications for participant rights, provider governance, privacy, payment, workforce competence and the evidence needed to distinguish useful innovation from unsafe automation. Read more...
Digital Accessibility in Health and Human Services: What the Revised Section 504 Timeline Means for Providers
HHS has extended the Section 504 web and mobile accessibility deadlines to May 2027 for recipients with 15 or more employees and May 2028 for smaller recipients. The additional time creates an important implementation window for health and human services providers to examine websites, portals, forms, mobile apps, digital communications, procurement and effective communication as connected disability-rights responsibilities rather than isolated technology projects. Read more...
The Digital Social Care Workforce of 2035
By 2035, the U.S. community-based care workforce is likely to combine human support, digital systems, AI-enabled decision support, remote care, automation and new specialist roles. This flagship analysis examines how Medicaid, state administration, provider economics, workforce redesign, governance and people’s rights will determine whether digital transformation strengthens HCBS and LTSS rather than simply adding technology to an already pressured workforce. Read more...
Could AI Identify Training Needs Before Workforce Performance Falls in U.S. Community-Based Care?
Artificial intelligence may help community-based providers recognize emerging training and competency needs before incidents, complaints or declining outcomes make them obvious. This article examines how U.S. HCBS, LTSS, IDD, behavioral health and aging-services organizations could use workforce, supervision and quality data responsibly—while preserving human judgment, worker trust, privacy, equity and accountability. Read more...
Can Digital Workforce Models Improve Continuity of Care Across U.S. Community-Based Services?
Digital workforce models can help community-based providers stabilize scheduling, preserve staff knowledge, strengthen supervision and respond earlier when continuity is at risk. This article examines how technology-enabled workforce design can support HCBS, LTSS, IDD, aging and behavioral health services without replacing relationships, weakening accountability or allowing efficiency goals to override people’s choices and rights. Read more...
The Future Operating Model for HCBS, LTSS and Community-Based Care Providers
Community-based care providers are operating across increasingly complex Medicaid, managed care, workforce, regulatory and cross-system environments. This article presents a practical future operating model for HCBS, LTSS, IDD, behavioral health and human services organizations, connecting governance, person-centered delivery, workforce intelligence, digital infrastructure, predictive quality assurance, financial resilience and continuous organizational learning. Read more...
How Data, Automation and Workforce Insight Are Reshaping Community-Based Care Organizations
Community-based care organizations are generating more operational information than ever before. This pillar article explores how data, automation and workforce insight can strengthen governance, improve decision-making, identify emerging risks and support more responsive, resilient and person-centered services across HCBS, LTSS, IDD, behavioral health and complex community care. Read more...
Digital Twins in Human Services: How Virtual Models Could Transform Risk, Capacity, Quality, and System Performance
Digital twins could become one of the most transformative technologies in human services, helping organizations move beyond retrospective reporting toward predictive planning, risk modeling, and system-wide decision support. By creating virtual representations of real-world care pathways, provider networks, workforce capacity, quality indicators, utilization patterns, and population needs, digital twins may enable leaders to test interventions before implementing them in practice. This article explores how digital twins could strengthen care coordination, crisis prevention, HCBS capacity planning, quality oversight, workforce management, interoperability, value-based care, and long-term system sustainability while highlighting the governance,... Read more...
Artificial Intelligence in U.S. Community-Based Care: Opportunities, Risks, Governance and What Providers Need to Do Next
Artificial intelligence is rapidly moving into U.S. community-based care. This pillar guide explains where AI can support quality, workforce planning, care documentation and governance, while highlighting the safeguards providers need around privacy, bias, human oversight and accountability. Read more...