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Home Financial Markets

ProPublica Adds Ownership Information to Nursing Home Database

It can be hard to determine who is responsible for the quality of care in a nursing home.

Ruth Talbot by Ruth Talbot
January 5, 2024
in Financial Markets
0
ProPublica Adds Ownership Information to Nursing Home Database

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This story was originally published by ProPublica. ProPublica is a Pulitzer Prize-winning investigative newsroom. Sign up for The Big Story newsletter to receive stories like this one in your inbox.

The quality of care that residents receive in a nursing home can be profoundly affected by who owns it, studies have shown. It’s not always clear who should be held accountable, though: Many nursing homes are owned by companies that are owned by other companies, obscuring who has the ultimate decision-making power. As more nursing homes are sold, information about an incoming owner’s performance in other homes becomes more relevant, as it may provide insight into how their latest acquisitions will fare.

To help navigate the confusing world of nursing home ownership, ProPublica’s Nursing Home Inspect now publishes detailed ownership information for facilities and an upgraded search to help you sift through the information.

The data comes from the Centers for Medicare & Medicaid Services, which publishes “affiliated entities” for nursing homes — lists of people or companies that have an ownership stake in or operational control over multiple nursing homes. CMS’ goal is to provide a better understanding of an owner or operator’s performance across all the nursing homes they are associated with. Some entities are affiliated with only a handful of homes, while others, like Genesis HealthCare or The Ensign Group, are affiliated with hundreds of homes across multiple states. Because CMS does not provide this data in a way that’s easy for most people to use, we’ve added it to our Nursing Home Inspect tool.

Our new affiliated entity pages allow users to easily explore data on each company or person who is responsible for nursing homes, listing all homes associated with that entity and showing recent serious deficiencies — failure to meet care requirements — found at those homes. You can even view a list of all affiliated entities nationwide.

We also added detailed ownership information to individual nursing home pages, allowing users to see who has an ownership stake in the home, as well as who has managerial control over the facility and how long they have held that position.

To go along with these additions, we’ve also expanded the database’s advanced search capabilities so journalists and others can quickly identify affiliated entities that have a history of serious deficiencies or other problems. For instance, users can search for all serious deficiencies associated with Life Care Centers of America.

Separately, users can also now filter searches by F-tags, which are a system for specifying the types of compliance issues that may be found during a CMS inspection. These tags allow users to narrow their search beyond broad categories such as “infection control deficiencies” to more targeted queries such as deficiencies associated with reporting COVID-19 data to residents and families or ensuring staff are vaccinated against COVID-19.

ProPublica plans to continue enhancing Nursing Home Inspect with new data and features in the coming months. If you write a story using this new information, come across bugs or issues, or have ideas for improvements, please let us know!

Source: ProPublica
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Ruth Talbot

Ruth Talbot

Ruth Talbot is a news applications developer at ProPublica.

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Videos

In this episode, the host discusses the significance of large language models (LLMs) in healthcare, their applications, and the challenges they face. The conversation highlights the importance of simplicity in model design and the necessity of integrating patient feedback to enhance the effectiveness of LLMs in clinical settings.

Takeaways
LLMs are becoming integral in healthcare.
They can help determine costs and service options.
Hallucination in LLMs can lead to misinformation.
LLMs can produce inconsistent answers based on input.
Simplicity in LLMs is often more effective than complexity.
Patient behavior should guide LLM development.
Integrating patient feedback is crucial for accuracy.
Pre-training models with patient input enhances relevance.
Healthcare providers must understand LLM limitations.
The best LLMs will focus on patient-centered care.

Chapters

00:00 Introduction to LLMs in Healthcare
05:16 The Importance of Simplicity in LLMs
The Future of LLMs in HealthcareDaily Remedy
YouTube Video U1u-IYdpeEk
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AI Regulation and Deployment Is Now a Core Healthcare Issue

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Ambient Artificial Intelligence Clinical Documentation: Workflow Support with Emerging Governance Risk

Ambient Artificial Intelligence Clinical Documentation: Workflow Support with Emerging Governance Risk

by Daily Remedy
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Health systems are increasingly deploying ambient artificial intelligence tools that listen to clinical encounters and automatically generate draft visit notes. These systems are intended to reduce documentation burden and allow clinicians to focus more directly on patient interaction. At the same time, they raise unresolved questions about patient consent, data handling, factual accuracy, and legal responsibility for machine‑generated records. Recent policy discussions and legal actions suggest that adoption is moving faster than formal oversight frameworks. The practical clinical question is...

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