Commentary
Is AI Threatening Health Care Jobs? Or Just Changing Them?
Sep 16, 2024
Delivery Improvements
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Innovations in health care delivery aim to make health care more accessible, more effective, and more efficient. Health information technology (IT) has held great promise for helping providers and health systems manage the care they deliver, and though its use is ubiquitous, health IT has not always lived up to its potential. Different organizational approaches to care integration, such as the medical home model, accountable care organizations (ACOs) model, or bringing behavioral health into the primary care setting have all tried in different ways to put patients’ needs at the center of care. Yet because health care delivery is so complex, the hunt continues for delivery improvements that can catalyze systemic improvements in access, effectiveness, and efficiency.
RAND Health Care researchers with expertise spanning medicine, statistics, systems approaches, and health policy disciplines, among others, explore a range of innovations to sort hype from promise. Our teams are uniquely capable of detecting unintended consequences of new approaches and technologies, allowing us to provide robust, nonpartisan analysis to help decisionmakers weigh the benefits and risks of a range of difficult policy choices, including artificial intelligence (AI), telehealth in the wake of the COVID-19 public health emergency, and efforts to address attrition, burnout, and shortages within the health care workforce.
Highlights
Examining the Use of AI in Clinical Care
The application of AI across global sectors, including health care, has garnered significant attention and speculation. For over a decade, RAND researchers have investigated the impact of new health technologies, such as the use of health IT in hospitals and safety-net clinics, while addressing risks of bias and errors. Leveraging this expertise, RAND has systematically studied AI's role in clinical care and the COVID-19 response, providing policymakers with accessible evidence mapping. Given the ongoing complexities policymakers face in this area, RAND partnered with the Carnegie Endowment for International Peace in July 2023 to host workshops focused on security guardrails for AI systems, encouraging industry and government to consider and collaborate on these issues.
Evaluating the Effects of Telehealth
Telehealth existed before the COVID-19 pandemic, but its role transformed significantly when contactless health care became essential. The use of telehealth surged during the early months of the pandemic, and although its use has ebbed, patients and providers continue to use virtual care more frequently than before the pandemic, often in tandem with in-person care. Drawing on a wide array of expertise across various fields of health care, RAND researchers examined changes and impacts in telehealth use across numerous studies. A research brief summarizes key findings from dozens of investigations into telehealth’s role in adapting to emergencies, enabling treatment for behavioral health, lowering barriers to care, and addressing health care inequities.
Modeling the Health Care Workforce
Matching the supply of clinicians in the U.S. health care workforce with the demand for care in each of the many—and varied—health care markets across the country has been a long-standing problem. The Commonwealth of Virginia collaborated with RAND to build a model that predicted the availability of provider types through 2038 and then explored a variety of workforce enhancement interventions to identify policies that will boost the retention, recruitment, and efficiency of the workforce, including changes to Medicaid reimbursement for primary care and behavioral health, increasing the number of residency slots, supporting team-based care through regulatory and reimbursement reform, and expanding incentives such as tuition support and loan forgiveness.
RAND has also used modeling to estimate geographic variation in the capacity of the health care system to provide Alzheimer’s disease-modifying therapies, now that such treatments are becoming available. The simulation model, which assessed patient demand for these therapies and the supply of providers who can deliver them, found substantial variation in capacity by state and estimated that average wait times to see a provider could be three times longer in rural areas. An interactive tool allows users to modify assumptions about patient demand, provider supply, and other relevant factors to illustrate the effects of potential alternative actions to improve care delivery.
Another model that has been built, and will be continuously refined, uses a system dynamics approach to estimate the health care workforce as a whole, throughout the United States. The model considers not only the supply of clinicians and demand from patients, but also the need for care, and then calculates utilization. Sign up for updates about this project to learn when more information becomes available.
