Taking opioids at home after surgery: More harms than benefits

 A new study conducted at the RI-MUHC concludes that prescribing opioid analgesics at discharge after surgery does not reduce postoperative pain and increases the risk of adverse events.

Widespread opioid prescribing at discharge after surgery has contributed to an unprecedented crisis of addiction and overdose in North America. Considering the risks associated with this practice and the lack of evidence to support it, a team of researchers from the Research Institute of the McGill University Health Centre (RI-MUHC) conducted a study to estimate the impact of post-discharge opioids use on self-reported pain intensity and adverse events, in comparison with an opioid-free analgesic treatment. The study results indicate that prescribing opioids to manage postoperative pain after discharge is not only unnecessary, but harmful in many surgical settings. These findings, published in The Lancet, fill a critical gap in knowledge about how pain should be managed at home after surgery.

In this study, the researchers combined the results of 47 randomized clinical trials comparing opioid versus opioid-free analgesia in patients discharged after undergoing a surgical procedure. Of these, 30 studies involved minor procedures (mostly dental) and 17 involved procedures of moderate extent (mostly orthopedic and general surgery).

"We found that prescribing opioids had no impact on patient-reported postoperative pain compared to simple over-the-counter analgesics, but it significantly increased the risk of adverse events, such as nausea, vomiting, constipation, dizziness and drowsiness," says study principal investigator Julio Fiore Jr., Ph.D., a scientist in the Injury, Repair, Recovery Program at the RI-MUHC. "Prescribing opioid-free analgesia may prevent these adverse effects, improve patients' recovery experience, and also help mitigate the opioid crisis by reducing the risk of postoperative opioid misuse, addiction and diversion."

The researchers found no differences in other aspects of recovery, which challenges common beliefs that the prescription of opioids positively impacts patient satisfaction with pain management, pain interference on daily activities and postoperative emergency visits.

Risky but widely used

Opioid drugs act on many areas of the nervous system to provide pain relief, but also have other effects such as euphoria and sedation. Among the opioids most commonly prescribed by surgeons are oxycodone, hydromorphone, tramadol and codeine, which have an addictive potential.

"Approximately six percent of surgical patients who are opioid-naïve become persistent opioid users after receiving a prescription at surgical discharge. In addition, of all opioid tablets obtained by surgical patients, up to 70 percent go unused and become a readily available source for diversion," says Julio Fiore, who is an Assistant Professor in the Department of Surgery at McGill University. "Given this alarming situation, it is urgent to mitigate postoperative opioid overprescribing while ensuring adequate pain management for patients."

More than 300 million people undergo surgery worldwide each year. However, opioid prescriptions following surgery are most prevalent in Canada and the United States, where opioid overdose deaths have skyrocketed over the past 20 years.

"Opioid analgesics are not widely used in the postoperative setting in Europe, Asia, the Middle East and South America. The reasons contributing to the widespread use of postoperative opioids in North America are multifactorial but include clinicians' concerns regarding inadequate pain control, patient dissatisfaction and risk of increased emergency visits due to uncontrolled pain," explains Charbel El-Kefraoui, co-first author of the study and research trainee at the RI-MUHC. "Findings from our study indicate that none of these concerns are supported by evidence."

"Alternatives to opioids are often overlooked, while they should be incorporated as the foundation of postoperative analgesia whenever possible," adds Julio Fiore. "Our work aims to build a strong body of knowledge to inform evidence-based analgesia prescribing and mitigate opioid-related harms after surgery."

A comprehensive and rigorous analysis of existing data

To obtain these results, the researchers performed a meta-analysis, i.e., a review of the literature followed by statistical work combining data from several studies to extract general trends and common findings. First, they searched seven major bibliographic databases for randomized clinical trials comparing opioid versus opioid-free analgesia in patients aged 15 years and older discharged after undergoing a surgical procedure of minor, moderate, major or major-complex extent. Opioid-free analgesia was defined as any pain management regimen (pharmacological, non-pharmacological or combined) that does not include opioid drug. The researchers then excluded crossover trials (where patients received two types of treatment subsequently), single-dose trials (where a drug is given in a single dose, contrary to standard practice in the postoperative setting), trials aimed at treating chronic pain, and trials where at-home drug administration was invasive (intravenous or other). At the end of this screening process, 47 clinical trials involving minor to moderate interventions were selected for inclusion in the analysis.

"The quality of the selected studies was variable, and none of them addressed non-opioid analgesia during discharge from major or major-complex surgery," says Charbel El-Kefraoui. "It will therefore be important to conduct studies on different surgical procedures and on different postoperative pain management regimens, including pharmacologic and non-pharmacologic interventions like expectation setting, relaxation and ice packs."

This research was based on extensive multidisciplinary work, bringing together the expertise of scientists, clinicians, librarians, and biostatisticians. It also counted on the collaboration of a patient partner who was actively involved in all stages of the research project and contributed her lived experience and knowledge to inform the research design and interpretation of the study results.

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Explore further

Duloxetine added to multimodal pain management reduces opioid use after knee replacement

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More information: Julio F Fiore et al, Opioid versus opioid-free analgesia after surgical discharge: a systematic review and meta-analysis of randomised trials, The Lancet (2022). DOI: 10.1016/S0140-6736(22)00582-7

https://medicalxpress.com/news/2022-06-opioids-home-surgery-benefits.html

Study CDC Cited In Arguing For COVID-19 Vaccines For Babies Being Updated

 by Zachary Stieber via The Epoch Times (emphasis ours),

A non-peer-reviewed study that U.S. government scientists cited in asserting COVID-19 is a leading cause of death for children is being updated after inaccuracies were detected.

The preprint paper, published in May, says that COVID-19 has been the fifth-leading cause of death during the pandemic for children aged 1 to 5. The authors, primarily British scientists, also concluded that COVID-19 has been a top cause of death for all children.

“Our findings underscore the importance of continued vaccination campaigns for [children ≥5 years] in the US and for effective Covid-19 vaccines for under 5 year olds,” they wrote.

But the paper has flaws, Seth Flaxman, a professor in Oxford University’s Department of Computer Science, and one of the authors, acknowledged on Twitter on June 19.

“We have received some feedback and criticism along several dimensions. We are planning to update the preprint to take into account some of this feedback,” he said.

The study was cited in three separate presentations across two meetings during the week of June 12 as government officials and expert advisers weighed whether to authorize and recommend vaccines for young children.

Dr. Katherine Fleming-Dutra, a CDC official, twice cited the study while presenting data on how COVID-19 has affected children while speaking to government advisory panels.

“COVID-19 was a leading cause of death among children and adolescents during the pandemic. Previously, we showed data to ACIP that during 2020 COVID-19 was the 11th cause of death among children ages five through 11 years. But this has changed over the course of the pandemic. And looking at data through April 2022, COVID-19 now ranks as the fourth and fifth causes of death among children zero through 19 years of age,” Fleming-Dutra said on June 17 while speaking to the Advisory Committee on Immunization Practices (ACIP), which advises the CDC.

Read more here...

https://www.zerohedge.com/covid-19/study-cdc-cited-arguing-covid-19-vaccines-babies-being-updated

Single brain scan can diagnose Alzheimer's disease

 The research uses machine learning technology to look at structural features within the brain, including in regions not previously associated with Alzheimer's. The advantage of the technique is its simplicity and the fact that it can identify the disease at an early stage when it can be very difficult to diagnose.

Although there is no cure for Alzheimer's disease, getting a diagnosis quickly at an early stage helps patients. It allows them to access help and support, get treatment to manage their symptoms and plan for the future. Being able to accurately identify patients at an early stage of the disease will also help researchers to understand the brain changes that trigger the disease, and support development and trials of new treatments.

The research is published in the Nature Portfolio Journal, Communications Medicine, and funded through the National Institute for Health and Care Research (NIHR) Imperial Biomedical Research Centre.

Alzheimer's disease is the most common form of dementia, affecting over half a million people in the UK. Although most people with Alzheimer's disease develop it after the age of 65, people under this age can develop it too. The most frequent symptoms of dementia are memory loss and difficulties with thinking, problem solving and language.

Doctors currently use a raft of tests to diagnose Alzheimer's disease, including memory and cognitive tests and brain scans. The scans are used to check for protein deposits in the brain and shrinkage of the hippocampus, the area of the brain linked to memory. All of these tests can take several weeks, both to arrange and to process.

The new approach requires just one of these -- a magnetic resonance imaging (MRI) brain scan taken on a standard 1.5 Tesla machine, which is commonly found in most hospitals.

The researchers adapted an algorithm developed for use in classifying cancer tumours, and applied it to the brain. They divided the brain into 115 regions and allocated 660 different features, such as size, shape and texture, to assess each region. They then trained the algorithm to identify where changes to these features could accurately predict the existence of Alzheimer's disease.

Using data from the Alzheimer's Disease Neuroimaging Initiative, the team tested their approach on brain scans from over 400 patients with early and later stage Alzheimer's, healthy controls and patients with other neurological conditions, including frontotemporal dementia and Parkinson's disease. They also tested it with data from over 80 patients undergoing diagnostic tests for Alzheimer's at Imperial College Healthcare NHS Trust.

They found that in 98 per cent of cases, the MRI-based machine learning system alone could accurately predict whether the patient had Alzheimer's disease or not. It was also able to distinguish between early and late-stage Alzheimer's with fairly high accuracy, in 79 per cent of patients.

Professor Eric Aboagye, from Imperial's Department of Surgery and Cancer, who led the research, said: "Currently no other simple and widely available methods can predict Alzheimer's disease with this level of accuracy, so our research is an important step forward. Many patients who present with Alzheimer's at memory clinics do also have other neurological conditions, but even within this group our system could pick out those patients who had Alzheimer's from those who did not.

"Waiting for a diagnosis can be a horrible experience for patients and their families. If we could cut down the amount of time they have to wait, make diagnosis a simpler process, and reduce some of the uncertainty, that would help a great deal. Our new approach could also identify early-stage patients for clinical trials of new drug treatments or lifestyle changes, which is currently very hard to do."

The new system spotted changes in areas of the brain not previously associated with Alzheimer's disease, including the cerebellum (the part of the brain that coordinates and regulates physical activity) and the ventral diencephalon (linked to the senses, sight and hearing). This opens up potential new avenues for research into these areas and their links to Alzheimer's disease.

Dr Paresh Malhotra, who is a consultant neurologist at Imperial College Healthcare NHS Trust and a researcher in Imperial's Department of Brain Sciences, said: "Although neuroradiologists already interpret MRI scans to help diagnose Alzheimer's, there are likely to be features of the scans that aren't visible, even to specialists. Using an algorithm able to select texture and subtle structural features in the brain that are affected by Alzheimer's could really enhance the information we can gain from standard imaging techniques."

Story Source:

Materials provided by Imperial College London. Original written by Maxine Myers. Note: Content may be edited for style and length.

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Journal Reference:

1. Marianna Inglese, et al.. A predictive model using the mesoscopic architecture of the living brain to detect Alzheimer’s disease. Communications Medicine, 2022; 2 (1) DOI: 10.1038/s43856-022-00133-4

https://www.sciencedaily.com/releases/2022/06/220620100827.htm

Gene discovery indicates motor neuron diseases caused by abnormal lipid processing

 A new genetic discovery adds weight to a theory that motor neurone degenerative diseases are caused by abnormal lipid (fat) processing pathways inside brain cells. This theory will help pave the way to new diagnostic approaches and treatments for this group of conditions. The discovery will provide answers for certain families who have previously had no diagnosis.

Motor neurone degenerative diseases (MNDs) are a large family of neurological disorders. Currently, there are no treatments available to prevent onset or progression of the condition. MNDs are caused by changes in one of numerous different genes. Despite the number of genes known to cause MNDs, many patients still remain without a much-needed genetic diagnosis.

A University of Exeter team led by Professor Andrew Crosby and Dr Emma Baple has a long history of research in motor neurone degenerative diseases. The team developed a hypothesis to explain a common cause of MNDs stemming from their discovery of 15 genes responsible for MNDs. The genes they identified are all involved in processing lipids -- in particular cholesterol -- inside brain cells. in the new hypothesis published in the leading neurology journal Brain, describes the specific lipid pathways that the team believe are important in the development of MNDs.

Now, the team has identified a further new gene -- named "TMEM63C" -- which causes a degenerative disease that affects the upper motor neurone cells in the nervous system. Also published in Brain, their latest discovery is important as the protein encoded by TMEM63C is located in the region of the cell where the lipid processing pathways they identified operate. This further bolsters the hypothesis that MNDs are caused by abnormal processing of lipids including cholesterol.

Professor Andrew Crosby, at the University of Exeter, said: "We're extremely excited by this new gene finding, as it is consistent with our hypothesis that the correct maintenance of specific lipid processing pathways is crucial for the way brain cells function, and that abnormalities in these pathways are a common linking theme in motor neurone degenerative diseases. It also enables new diagnoses and answers to be readily provided for families affected by some forms of MND"

MNDs affect the nerve cells that control voluntary muscle activity such as walking, speaking and swallowing. There are many different forms of MNDs which have different clinical features and severity. As the condition progresses, the motor neurone cells become damaged and may eventually die. This leads to the muscles, which rely on those nerve messages, gradually weakening and wasting away.

If confirmed, the theory could lead to scientists to use patient samples to predict the course and severity of the condition in an individual, and to monitor the effect of potential new drugs developed to treat these disorders.

In the latest research, the team used cutting-edge genetic sequencing techniques to investigate the genome of three families with individuals affected by hereditary spastic paraplegia -- a large group of MNDs in which the motor neurons in the upper part of the spinal cord miscommunicate with muscle fibres, leading to symptoms including muscle stiffness, weakness and wasting. These investigations showed that changes in the TMEM63C gene were the cause of the disease. In collaboration with the group led by Dr Julien Prudent at the Medical Research Council Mitochondrial Biology Unit at the University of Cambridge, the team also undertook studies to learn more about the functional relevance of the TMEM63C protein inside the cell.

Using state-of-the-art microscopy methods, the Cambridge team's work showed that a subset of TMEM63C is localised at the interface between two critical cellular organelles, the endoplasmic reticulum and the mitochondria, a region of the cell required for lipid metabolism homeostasis and proposed by the Exeter team to be important for the development of MNDs. In addition to this specific localisation, Dr Luis-Carlos Tabara Rodriguez, a Postdoctoral Fellow in Dr. Prudent's lab, also uncovered that TMEM63C controls the morphology of both the endoplasmic reticulum and mitochondria, which may reflect its role in the regulation of the functions of these organelles, including lipid metabolism homeostasis.

Dr Julien Prudent, of the MRC Mitochondrial Biology unit, said: "From a mitochondrial cell biologist point of view, identification of TMEM63C as a new motor neurone degenerative disease gene and its importance to different organelle functions reinforce the idea that the capacity of different cellular compartments to communicate together, by exchanging lipids for example, is critical to ensure cellular homeostasis required to prevent disease."

Dr Emma Baple, of the University of Exeter, said: "Understanding precisely how lipid processing is altered in motor neurone degenerative diseases is essential to be able to develop more effective diagnostic tools and treatments for a large group of diseases that have a huge impact on people's lives. Finding this gene is another important step towards these important goals"

The Halpin Trust, a charity who support projects which deliver a powerful and lasting impact in healthcare, nature conservation and the environment, part-funded this research. Claire Halpin, the charities' co-founder with her husband Les said "The Halpin Trust are extremely proud of the work ongoing in Exeter, and the important findings of this highly collaborative international study. We're delighted that the Trust has contributed to this work, which forms part of Les's legacy. He would also have been pleased, I know."

The HSP Support Group is a UK charity providing help for people diagnosed with Hereditary Spastic Paraplegia (HSP). Adam Lawrence, the Group's Chair said "Finding a new type of HSP is extremely important as it helps reduce the uncertainty which people with the condition often have on their diagnosis journey. The work of the team in Exeter investigating HSP and its genetic causes over many years is world-leading and has increased the global understanding of HSP. Their work is important providing much needed answers for people with HSP, and developing treatments."

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Story Source:

Materials provided by University of Exeter. Note: Content may be edited for style and length.

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Journal Reference:

1. Luis Carlos Tábara, Fatema Al-Salmi, Reza Maroofian, Amna Mohammed Al-Futaisi, Fathiya Al-Murshedi, Joanna Kennedy, Jacob O Day, Thomas Courtin, Aisha Al-Khayat, Hamid Galedari, Neda Mazaheri, Margherita Protasoni, Mark Johnson, Joseph S Leslie, Claire G Salter, Lettie E Rawlins, James Fasham, Almundher Al-Maawali, Nikol Voutsina, Perrine Charles, Laura Harrold, Boris Keren, Edmund R S Kunji, Barbara Vona, Gholamreza Jelodar, Alireza Sedaghat, Gholamreza Shariati, Henry Houlden, Andrew H Crosby, Julien Prudent, Emma L Baple. TMEM63C mutations cause mitochondrial morphology defects and underlie hereditary spastic paraplegia. Brain, 2022; DOI: 10.1093/brain/awac123

https://www.sciencedaily.com/releases/2022/06/220620100834.htm

New model helps identify mutations that drive cancer

 Cancer cells can have thousands of mutations in their DNA. However, only a handful of those actually drive the progression of cancer; the rest are just along for the ride.

Distinguishing these harmful driver mutations from the neutral passengers could help researchers identify better drug targets. To boost those efforts, an MIT-led team has built a new computer model that can rapidly scan the entire genome of cancer cells and identify mutations that occur more frequently than expected, suggesting that they are driving tumor growth. This type of prediction has been challenging because some genomic regions have an extremely high frequency of passenger mutations, drowning out the signal of actual drivers

“We created a probabilistic, deep-learning method that allowed us to get a really accurate model of the number of passenger mutations that should exist anywhere in the genome,” says Maxwell Sherman, an MIT graduate student. “Then we can look all across the genome for regions where you have an unexpected accumulation of mutations, which suggests that those are driver mutations.”

In their new study, the researchers found additional mutations across the genome that appear to contribute to tumor growth in 5 to 10 percent of cancer patients. The findings could help doctors to identify drugs that would have greater chance of successfully treating those patients, the researchers say. Currently, at least 30 percent of cancer patients have no detectable driver mutation that can be used to guide treatment.

Sherman, MIT graduate student Adam Yaari, and former MIT research assistant Oliver Priebe are the lead authors of the study, which appears today in Nature Biotechnology. Bonnie Berger, the Simons Professor of Mathematics at MIT and head of the Computation and Biology group at the Computer Science and Artificial Intelligence Laboratory (CSAIL), is a senior author of the study, along with Po-Ru Loh, an assistant professor at Harvard Medical School and associate member of the Broad Institute of MIT and Harvard. Felix Dietlein, an associate professor at Harvard Medical School and Boston Children’s Hospital, is also an author of the paper.

A new tool

Since the human genome was sequenced two decades ago, researchers have been scouring the genome to try to find mutations that contribute to cancer by causing cells to grow uncontrollably or evade the immune system. This has successfully yielded targets such as epidermal growth factor receptor (EGFR), which is commonly mutated in lung tumors, and BRAF, a common driver of melanoma. Both of these mutations can now be targeted by specific drugs.

While those targets have proven useful, protein-coding genes make up only about 2 percent of the genome. The other 98 percent also contains mutations that can occur in cancer cells, but it has been much more difficult to figure out if any of those mutations contribute to cancer development. 

“There has really been a lack of computational tools that allow us to search for these driver mutations outside of protein-coding regions,” Berger says. “That's what we were trying to do here: design a computational method to let us look at not only the 2 percent of the genome that codes for proteins, but 100 percent of it.”

To do that, the researchers trained a type of computational model known as a deep neural network to search cancer genomes for mutations that occur more frequently than expected. As a first step, they trained the model on genomic data from 37 different types of cancer, which allowed the model to determine the background mutation rates for each of those types. 

“The really nice thing about our model is that you train it once for a given cancer type, and it learns the mutation rate everywhere across the genome simultaneously for that particular type of cancer,” Sherman says. “Then you can query the mutations that you see in a patient cohort against the number of mutations you should expect to see.”

The data used to train the models came from the Roadmap Epigenomics Project and an international collection of data called the Pan-Cancer Analysis of Whole Genomes (PCAWG). The model’s analysis of this data gave the researchers a map of the expected passenger mutation rate across the genome, such that the expected rate in any set of regions (down to the single base pair) can be compared to the observed mutation count anywhere across the genome.

Changing the landscape

Using this model, the MIT team was able to add to the known landscape of mutations that can drive cancer. Currently, when cancer patients’ tumors are screened for cancer-causing mutations, a known driver will turn up about two-thirds of the time. The new results of the MIT study offer possible driver mutations for an additional 5 to 10 percent of the pool of patients.

One type of noncoding mutation the researchers focused on is called “cryptic splice mutations.” Most genes consist of sequences of exons, which encode protein-building instructions, and introns, which are spacer elements that usually get trimmed out of messenger RNA before it is translated into protein. Cryptic splice mutations are found in introns, where they can confuse the cellular machinery that splices them out. This results in introns being included when they shouldn’t be.

Using their model, the researchers found that many cryptic splice mutations appear to disrupt tumor suppressor genes. When these mutations are present, the tumor suppressors are spliced incorrectly and stop working, and the cell loses one of its defenses against cancer. The number of cryptic splice sites that the researchers found in this study accounts for about 5 percent of the driver mutations found in tumor suppressor genes. 

Targeting these mutations could offer a new way to potentially treat those patients, the researchers say. One possible approach that is still in development uses short strands of RNA called antisense oligonucleotides (ASOs) to patch over a mutated piece of DNA with the correct sequence.

“If you could make the mutation disappear in a way, then you solve the problem. Those tumor suppressor genes could keep operating and perhaps combat the cancer,” Yaari says. “The ASO technology is actively being developed, and this could be a very good application for it.”

Another region where the researchers found a high concentration of noncoding driver mutations is in the untranslated regions of some tumor suppressor genes. The tumor suppressor gene TP53, which is defective in many types of cancer, was already known to accumulate many deletions in these sequences, known as 5’ untranslated regions. The MIT team found the same pattern in a tumor suppressor called ELF3. 

The researchers also used their model to investigate whether common mutations that were already known might also be driving different types of cancers. As one example, the researchers found that BRAF, previously linked to melanoma, also contributes to cancer progression in smaller percentages of other types of cancers, including pancreatic, liver, and gastroesophageal. 

“That says that there’s actually a lot of overlap between the landscape of common drivers and the landscape of rare drivers. That provides opportunity for therapeutic repurposing,” Sherman says. “These results could help guide the clinical trials that we should be setting up to expand these drugs from just being approved in one cancer, to being approved in many cancers and being able to help more patients.”

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The research was funded, in part, by the National Institutes of Health and the National Cancer Institute.

 

 

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JOURNAL

Nature Biotechnology

DOI

10.1038/s41587-022-01353-8 

ARTICLE TITLE

Genome-wide mapping of somatic mutation rates uncovers drivers of cancer

ARTICLE PUBLICATION DATE

20-Jun-2022

https://www.eurekalert.org/news-releases/956254

Novel treatment for rare form of kidney cancer uncovered

 Chromophobe renal cell carcinoma (ChRCC) is a rare form of kidney cancer for which there are currently no proven treatments for metastatic or unresectable disease. In a study led by investigators from Brigham and Women’s Hospital, researchers report the first evidence that ChRCC can be targeted with ferroptosis — a type of programmed cell death that occurs when large amounts of iron cause lipid peroxides to accumulate in the cell membrane. The team successfully induced ferroptosis in ChRCC cells via cysteine deprivation and found evidence that this strategy may be an effective approach for treating ChRCC.

“Targeted therapies are urgently needed to treat chromophobe RCC,” said corresponding author Elizabeth P. Henske, MD, of the Division of Pulmonary and Critical Care Medicine at the Brigham. “Through our study, we’ve found strong evidence that ChRCC can be therapeutically targeted by taking advantage of the cells’ hypersensitivity to ferroptosis. This represents an important breakthrough in our understanding as we think about treatment for patients with this rare disease.”

 

 

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JOURNAL

Proceedings of the National Academy of Sciences

METHOD OF RESEARCH

Experimental study

SUBJECT OF RESEARCH

Cells

ARTICLE TITLE

Hypersensitivity to ferroptosis in chromophobe RCC is mediated by a glutathione metabolic dependency and cystine import via SCL7A11

ARTICLE PUBLICATION DATE

20-Jun-2022

https://www.eurekalert.org/news-releases/956360

Why aren’t we hearing more about this LTC payment source?

 When it comes to senior living payments, private long-term care insurance has been exiled to the children’s table. Actually, that assessment may be too kind.

Only a handful of insurers even offer the product anymore. Of those that do, premiums have skyrocketed while coverage has been dialed way down.

Americans have voted with their feet. And here’s the collective verdict on LTC insurance: no thanks.

Which really is too bad. Because LTC insurance could have been a payment contender. The product offered the promise of market rate payments to operators and peace of mind to policy holders. Alas, the actuaries at many insurance companies wildly underestimated both how long their customers would live and how rapidly costs would rise. As they say in tennis: game, set, match.

Does that mean operators should completely write off private insurance as a funding source? Not so fast.

In fact, a new packaging twist — combining life insurance policies with LTC policies — just might get private insurers back in the game.

This hybrid option accelerates death benefits should the policy holder experience a triggering health issue. And as these are whole life policies, they have a savings component and can accrue cash value. Why is this latter provision important? It nullifies a major objection: that policyholders will spend a fortune on premiums and not see a penny in return.

Some insurers are sweetening the pot by not requiring a large upfront investment (which often reaches $100,000 or more). Instead, the amount can be spread over several years. Another selling point: policy premiums will never rise in the future.

As for the benefit operators would see, it’s pretty simple, really. Better payments.

Put another way, would you rather have an insurer paying you retail for your services, or would you rather get whatever Medicaid rate your state sees as appropriate? As choices go, that’s really not one.

Lest I sound like a shill for the insurance industry, keep in mind these are insurance companies we’re talking about. So yes, proceed with a mature adult’s level of caution. Not to cast any aspersions, but let’s just say some carriers are not above ruthless tactics when it comes to denying and delaying what’s owed. So there’s that.

Still, hybrid policies do have a potentially huge payment upside. And it’s not like most communities are flush with cash these days.

Life is full of mysteries. Senior living operators not enthusiastically supporting hybrid polices probably deserves a seat at that table.

https://www.mcknightsseniorliving.com/home/columns/editors-columns/why-arent-we-hearing-more-about-this-payment-source/