What is an assisted living facility — and how does it differ from a nursing home?
Assisted living residences are nonmedical facilities that provide older adults with housing, meals, and support for daily activities like dressing, bathing, and medication. They promote independence while offering a safety net of care.
'[Assisted living] is often the next logical step in the continuum of care for adults who don't need complex medical treatment but would benefit from daily support in a setting that values independence, freedom of choice, and quality of life,' said Brian Doherty, president and CEO of Massachusetts Assisted Living. 'Assisted living also provides structure and support for individuals with cognitive impairment, memory loss, or Alzheimer's disease through specialized memory care units.'
Unlike nursing homes, which provide round-the-clock care for individuals with significant medical needs, assisted living residences offer a more homelike environment. Residents typically live in private or semiprivate apartments and receive help with activities of daily living — such as bathing, dressing, grooming, and mobility.
Advertisement
Nursing homes are licensed and inspected by the state Department of Public Health. Assisted living residences are certified by the Executive Office of Aging & Independence (AGE), which does not require the same level of clinical staffing or oversight.
Advertisement
'[Assisted living residences are] very loosely regulated,' said Malka Young, an aging consultant and director of Allies in Aging JFS Elder Care Solutions.
Young says each facility varies by the level of care that's needed. The care involves one wellness nurse, which can only provide first aid.
'The one nurse is responsible for the well being of each person in the community. They can't give injections, they can't take blood pressure, so there's not really any medical services,' she explained.
What are the different types of aging services?
Managed long-term care programs include:
Program of All-inclusive Care for the Elderly (
Senior Care Options (
Aside from aging at home, options for long-term care include:
Senior housing (includes public, privately-owned subsidized, and congregate and supportive housing)
Continuing Care Retirement Communities are sometimes known as a life plan community, where
independent living, assisted living, and skilled nursing care are offered.
Assisted living residences provide meals, housekeeping, and help with personal care, but charge separately for additional services like medication management or assistance with bathing and memory care.
Rest Homes / Residential Care Facilities are considered a healthcare facility, though they offer basic care, not skilled nursing, and are often included in MassHealth coverage.
Nursing/skilled-nursing and rehabilitation facilities operate under a medical model, offering care typically covered by Medicaid or long-term care insurance and could include memory care units.
How much does it cost — and who pays?
The average monthly cost for assisted living in Massachusetts is nearly $10,000, or $300 a day, depending on location, room type and level of care, according to
'Each person is given an individual care plan, and sometimes you have up to one hour of care and if you need help with your medications, then that's an additional fee,' Young said.
Nursing homes are more expensive, often exceeding $13,000 per month, but may be partially covered by Medicaid if the resident qualifies financially.
Health insurance only covers assisted living facilities if someone has long term care insurance.
'I'll have couples come to me and they'll have a million dollars, and they think they have a lot of money, but that's really not a lot of money if someone's in their late 70s or even early 80s,' Young said.
Related
:
Advertisement
Gabriel House served a high number of low-income seniors.
More than 75 percent of its residents are enrolled in Medicaid, state officials have said, and it charges significantly less than a typical assisted living facility does for private-paying patients. Built in 1964, Gabriel House had been the subject of several complaints from family members about living conditions, the Globe
Subsidies also depend on potential tax credits, the median income of the community and what they offer
.
'Gabriel House in Fall River was mainly for people who were on veterans benefits or MassHealth,' Young explained. 'But there's a subgroup of regular assisted livings that depended on how the building itself was financed, they're called tax credit units.'
Robin Lipson, secretary of AGE, raised the possibility that facilities that heavily dependent on government housing or Medicaid payments, 'should be regulated or supported in a different way' from those that rely on private payers.
Michelle Woodbrey, co-owner of 2Sisters Senior Living Advisors, serving families across New England, said assisted living facilities that support lower income seniors are rare to find and 'often don't provide high levels of care.'
'If you're on MassHealth and can't pay privately, a nursing home is typically your only option, and there are very few exceptions,' she said.
Each year, Woodbrey said, more people are falling into a growing gap: they don't meet the high medical threshold for nursing home care, but can't afford assisted living or home care services.
' . . . someone can't just move into a nursing home because they're out of money. There's this group of people who fall between the cracks. Gabriel House served many of those people.'
Advertisement
How do you know that the one you've selected is high quality?
Young suggests people consider how long staff has been there in a high-turnover job market, if there's an on-site chef , and what types of activities and length of stays are offered.
'Ask about the staff's education,' she advises. Also,some programs, will highlight they have a resident committee and they vote on what they want. Well, that means they don't have any staff or professional input.'
Sarah Rahal can be reached at
Hashtags
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
Yahoo
2 hours ago
- Yahoo
Wells Fargo Cuts Elevance (ELV) Price Target on Margin Uncertainty
Elevance Health, Inc. (NYSE:ELV) ranks among the . Wells Fargo kept its Overweight rating on Elevance Health, Inc. (NYSE:ELV) on July 15, but lowered its price target on the health insurer from $478 to $400. Wells Fargo applied a lower multiple of 10.5x to its 2026 earnings per share projection of $38.05, which is less than the previous multiple of 11.5x. designer491/ Wells Fargo stated that the primary driver of the reduced value multiple was uncertainty regarding margins in the Medicaid, Medicare Advantage (MA), and Health Insurance Exchange (HIX) segments for 2025. The firm also pointed out that there was 'relatively low visibility to improvement in 2026,' especially in the Medicaid and Health Insurance Exchange segments. However, it insisted that Elevance's valuation 'remains compelling once dust settles on estimates.' Elevance Health, Inc. (NYSE:ELV), previously Anthem, Inc., is a leading health-benefits provider in the United States. The company offers medical, pharmaceutical, dental, long-term care, disability, and behavioral health insurance under numerous brands, including Anthem Blue Cross, Blue Shield, Wellpoint, and Carelon. While we acknowledge the potential of ELV as an investment, we believe certain AI stocks offer greater upside potential and carry less downside risk. If you're looking for an extremely undervalued AI stock that also stands to benefit significantly from Trump-era tariffs and the onshoring trend, see our free report on the best short-term AI stock. Read More: and Disclosure: None. Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
3 hours ago
As ADA turns 35, groups fighting for disability rights could see funds slashed
TOPEKA, Kan. -- Nancy Jensen believes she'd still be living in an abusive group home if it wasn't shut down in 2004 with the help of the Disability Rights Center of Kansas, which for decades has received federal money to look out for Americans with disabilities. But the flow of funding under the Trump administration is now in question, disability rights groups nationwide say, dampening their mood as Saturday marks the 35th anniversary of the landmark Americans with Disabilities Act. Federal dollars pay for much of their work, including helping people who seek government-funded services and lawsuits now pushing Iowa and Texas toward better community services. Documents outlining President Donald Trump's budget proposals show they would zero out funds earmarked for three grants to disability rights centers and slash funding for a fourth. Congress' first discussion of them, by the Senate Appropriations Committee, is set for Thursday, but the centers fear losing more than 60% of their federal dollars. The threat of cuts comes as the groups expect more demand for help after Republicans' tax and budget law complicated Medicaid health coverage with a new work-reporting requirement. There's also the sting of the timing: this year is the 50th anniversary of another federal law that created the network of state groups to protect people with disabilities, and Trump's proposals represent the largest potential cuts in that half-century, advocates said. The groups are authorized to make unannounced visits to group homes and interview residents alone. 'You're going to have lots of people with disabilities lost,' said Jensen, now president of Colorado's advisory council for federal funding of efforts to protect people with mental illnesses. She worries people with disabilities will have 'no backstop' for fighting housing discrimination or seeking services at school or accommodations at work. The potential budget savings are a shaving of copper from each federal tax penny. The groups receive not quite $180 million a year — versus $1.8 trillion in discretionary spending. The president's Office of Management and Budget didn't respond to an email seeking a response to the disability rights groups' criticism. But in budget documents, the administration argued its proposals would give states needed flexibility. The U.S. Department of Education said earmarking funds for disability rights centers created an unnecessary administrative burden for states. Trump's top budget adviser, Russell Vought, told senators in a letter that a review of 2025 spending showed too much went to 'niche' groups outside government. 'We also considered, for each program, whether the governmental service provided could be provided better by State or local governments (if provided at all),' Vought wrote. Disability rights advocates doubt that state protection and advocacy groups — known as P&As — would see any dollar not specifically earmarked for them. They sue states, so the advocates don't want states deciding whether their work gets funded. The 1975 federal law setting up P&As declared them independent of the states, and newer laws reinforced that. 'We do need an independent system that can hold them and other wrongdoers accountable,' said Rocky Nichols, the Kansas center's executive director. Nichols' center has helped Matthew Hull for years with getting the state to cover services, and Hull hopes to find a job. He uses a wheelchair; a Medicaid-provided nurse helps him run errands. 'I need to be able to do that so I can keep my strength up,' he said, adding that activity preserves his health. Medicaid applicants often had a difficult time working through its rules even before the tax and budget law's recent changes, said Sean Jackson, Disability Rights Texas' executive director. With fewer dollars, he said, 'As cases are coming into us, we're going to have to take less cases.' The Texas group receives money from a legal aid foundation and other sources, but federal funds still are 68% of its dollars. The Kansas center and Disability Rights Iowa rely entirely on federal funds. 'For the majority it would probably be 85% or higher,' said Marlene Sallo, executive director of the National Disability Rights Network, which represents P&As. The Trump administration's proposals suggest it wants to shut down P&As, said Steven Schwartz, who founded the Center for Public Representation, a Massachusetts-based organization that works with them on lawsuits. Federal funding meant a call in 2009 to Disability Rights Iowa launched an immediate investigation of a program employing men with developmental disabilities in a turkey processing plant. Authorities said they lived in a dangerous, bug-infested bunkhouse and were financially exploited. Without the dollars, executive director Catherine Johnson said, 'That's maybe not something we could have done.' The Kansas center's private interview in 2004 with one of Jensen's fellow residents eventually led to long federal prison sentences for the couple operating the Kaufman House, a home for people with mental illnesses about 25 miles (40 kilometers) north of Wichita. And it wasn't until Disability Rights Iowa filed a federal lawsuit in 2023 that the state agreed to draft a plan to provide community services for children with severe mental and behavioral needs. For 15 years, Schwartz's group and Disability Rights Texas have pursued a federal lawsuit alleging Texas warehouses several thousand people with intellectual and developmental disabilities in nursing homes without adequate services. Texas put at least three men in homes after they'd worked in the Iowa turkey plant. Last month, a federal judge ordered work to start on a plan to end the 'severe and ongoing' problems. Schwartz said Disability Rights Texas did interviews and gathered documents crucial to the case. 'There are no better eyes or ears,' he said.
Time Business News
4 hours ago
- Time Business News
Artificial Intelligence Transforming Healthcare and Improving Lives
Artificial intelligence (AI) has emerged as a groundbreaking force reshaping the healthcare landscape. Its rapid advancement over the past decade has led to improved diagnostics, personalized treatment, efficient management of health services, and the democratization of medical knowledge and care. In this comprehensive analysis, we will explore how AI is elevating health outcomes, the mechanisms behind these advancements, its impact on patients and practitioners, challenges faced, and the future outlook of AI-driven healthcare. AI refers to computer systems capable of performing tasks that typically require human intelligence, such as learning, reasoning, pattern recognition, and decision-making. Within healthcare, AI draws upon vast medical datasets—ranging from electronic health records and genetic data to real-time wearable device streams—and applies sophisticated algorithms to uncover patterns, predict outcomes, and recommend optimal interventions. The goal is not to replace clinicians and caregivers but to amplify their abilities, reduce diagnostic errors, and enable personalized, efficient, and timely care. One of the most transformative applications of AI in healthcare is in disease diagnosis, particularly using medical imaging. AI-powered tools can analyze X-rays, CT scans, MRIs, and retinal scans at incredible speeds and with accuracy levels that often match or surpass human experts. Advanced algorithms are trained on millions of medical images, allowing them to detect subtle changes in tissue and anatomical structures that indicate diseases such as: Cancer (breast, lung, skin, and prostate): AI can spot early tumor growths that radiologists might miss, aiding in earlier detection and better patient outcomes. (breast, lung, skin, and prostate): AI can spot early tumor growths that radiologists might miss, aiding in earlier detection and better patient outcomes. Eye diseases : Diabetic retinopathy and age-related macular degeneration can be detected using AI analysis of retinal imagery, helping prevent blindness. : Diabetic retinopathy and age-related macular degeneration can be detected using AI analysis of retinal imagery, helping prevent blindness. Neurological disorders: AI models detect anomalies in brain scans indicating conditions like epilepsy, stroke, and Alzheimer's far more quickly than standard methods. Medical errors are a leading cause of preventable harm. By double-checking, highlighting anomalies, and flagging uncertain cases for further review, AI minimizes oversight. For example, a study showed that AI could detect breast cancer on mammograms with higher sensitivity and specificity than radiologists. No two people are biologically identical. The same disease may progress differently among patients due to genetic, lifestyle, and environmental variations. AI plays a vital role in making precision medicine a reality—treatments are customized based on individual molecular profiles. By analyzing genomic data, AI predicts how a patient will respond to specific drugs, identifies genetic risks, and helps design gene therapies. Continuous glucose monitoring systems empowered by AI adjust diabetes management in real time, analyzing dietary intake, exercise, and blood sugar trends to optimize insulin delivery. Similarly, wearable devices combined with AI alert heart failure patients before their condition worsens, enabling early intervention and reduction in hospitalizations. Conventional drug discovery is costly and time-consuming. AI revolutionizes this process by: Screening millions of compounds for drug candidates at unprecedented speeds. Predicting drug efficacy, optimal dosages, and potential side effects. Personalizing drug combinations for individuals based on genetic makeup and disease behavior. This accelerates the arrival of novel treatments and reduces costs, making medicine more accessible. AI helps predict who is at risk of developing certain conditions (like diabetes, cardiovascular disease, or sepsis) by analyzing medical records, social determinants, and lifestyle data. Early identification allows for proactive interventions—ranging from lifestyle modifications to preemptive medication—which can delay or even prevent disease onset. Hospital readmission within 30 days is costly for both patients and systems. Several health systems use AI algorithms to flag patients at high risk of readmission so care teams can intervene with additional monitoring, support, home visits, or telemedicine follow-ups. AI can detect patterns in public health data, travel patterns, social media signals, and genomic sequencing of pathogens. This helps forecast infectious disease outbreaks (such as influenza, COVID-19, or Ebola), allowing leaders to pre-position resources and enforce public health policies quickly. AI-driven chatbots and voice assistants operate around the clock, answering patient questions, managing appointments, providing medication reminders, and offering first-line triage advice. For individuals with chronic diseases, these tools check on symptoms daily, record vitals, and escalate issues to care teams when necessary. Digital therapeutics use AI-powered mobile apps to deliver behavioral interventions, manage pain, encourage activity, and support mental health. For example, apps can coach users through exercises to relieve chronic pain, offer personalized cognitive behavioral therapy for anxiety and depression, or gamify medication adherence for children. Wearables and home-based sensors collect data on heart rate, blood pressure, oxygen saturation, movement, and even sleep patterns. AI interprets this data, highlighting trends, and alerting caregivers early when intervention is needed, thus enabling proactive care outside the traditional clinic setting. Healthcare systems face immense pressure to improve efficiency while maintaining quality. AI optimizes scheduling, resource allocation, and administrative workflows: Triage : AI-powered systems assist paramedics in determining the severity of ambulance cases and the most appropriate hospital destination, saving time and lives. : AI-powered systems assist paramedics in determining the severity of ambulance cases and the most appropriate hospital destination, saving time and lives. Clinical documentation : Automated transcription and smart note-taking free up doctors from paperwork, allowing more focus on patient care. : Automated transcription and smart note-taking free up doctors from paperwork, allowing more focus on patient care. Billing and claims: AI reviews insurance claims, identifying fraud, reducing errors, and speeding up reimbursement. Clinical trials are expensive and often delayed due to challenges in site selection and patient recruitment. AI helps to: Identify optimal trial sites based on real-world data. Match eligible and diverse participants, ensuring broader and more relevant trial results. Predict and mitigate obstacles—such as withdrawals or protocol violations—by adapting recruitment and retention strategies in real time. By shortening time-to-diagnosis, minimizing preventable admissions, and improving treatment efficacy, AI helps control rising healthcare expenditures. It also contributes to value-based care models by improving outcomes while using fewer resources. AI-powered systems synthesize large volumes of medical literature, guidelines, and individual patient data to provide clinicians with evidence-based recommendations—helping them select the most effective therapies, avoid harmful drug interactions, and keep up with the ever-growing body of medical knowledge. Virtual patients and intelligent simulation platforms powered by AI enhance medical training, allowing clinicians and students to practice complex scenarios and receive tailored feedback. AI also helps identify gaps in knowledge, guiding continuous professional development. A significant proportion of the world's population lacks ready access to quality healthcare, often due to provider shortages, geographic barriers, or cost. AI is helping bridge this gap: Remote diagnostics : AI tools enable health workers in low-resource settings to screen for diseases with smartphone-based imaging and cloud analytics. : AI tools enable health workers in low-resource settings to screen for diseases with smartphone-based imaging and cloud analytics. Automated translation : Multilingual AI models facilitate communication between patients and providers, breaking down language barriers. : Multilingual AI models facilitate communication between patients and providers, breaking down language barriers. Telemedicine platforms: AI-driven services connect patients anywhere with specialists, extending high-level care to underserved areas. The transformative promise of AI comes with substantial challenges: AI depends on sensitive medical data. Ensuring this data is secure, anonymized, and used ethically is paramount. Health organizations must comply with strict privacy regulations and remain vigilant to cyber threats. AI models can perpetuate existing health disparities if trained on unrepresentative data. Biases in algorithms may lead to worse outcomes for minority or marginalized populations. Ongoing efforts focus on transparent data collection, bias detection, and inclusive model development. Clinicians might distrust or resist AI recommendations, especially if the system's reasoning is opaque ('black box' problem). To foster adoption, AI outputs must be explainable and integrated into clinical workflows. AI-enabled devices and software require rigorous regulatory approval to ensure effectiveness and safety. Standards are still evolving, and regulatory bodies worldwide are updating frameworks to keep pace with AI innovation. Google Health's AI model trained on mammograms achieved higher accuracy than radiologists in identifying breast tumors, reducing both false negatives and false positives. This has led to earlier interventions and potentially saved lives. In India, AI-based retinal screening allows technicians to identify diabetic retinopathy in local clinics, referring only urgent cases to distant specialists. This has improved outcomes for thousands who previously lacked access to eye care. AI-powered robots and digital companions provide reminders, monitor mood and safety, and offer social interaction for older adults. These systems, already in use in parts of Europe and Asia, reduce loneliness and delay the need for institutional care. During the pandemic, AI helped accelerate vaccine development, optimize supply chains for personal protective equipment, track outbreaks, and inform public health decision-making by modeling possible scenarios. The journey of AI in healthcare is just beginning. In the coming years, we can expect: Further integration of multi-modal data (genomic, clinical, imaging, behavioral, and social determinants) to enhance predictive power and personalize interventions. Growing democratization of diagnostic and monitoring tools via smartphones and low-cost devices. Real-time adaptive clinical guidelines—algorithms that continuously learn from new data, clinical outcomes, and real-world evidence. Expansion of AI's reach into mental health, voice analysis for neurological and psychiatric disorders, and advanced prosthetics. Closer collaboration between AI developers, clinicians, regulatory bodies, and patients to ensure AI tools are transparent, ethical, and trusted. Artificial intelligence is not a panacea, but it is a catalyst—empowering clinicians, engaging patients, and optimizing the use of resources with the ultimate goal of better health for all. Responsible adoption and ongoing vigilance regarding ethics, equity, and privacy are essential to harness the benefits and minimize risks. As AI continues to evolve, its positive impact on the healthcare ecosystem will become ever more profound, bringing us closer to a future where health is more predictive, personalized, preventive, and accessible TIME BUSINESS NEWS
