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Each year, tens of thousands of people in the U.S. try to conceive using in vitro fertilization (IVF), a process through which eggs are fertilized in a lab, then transferred to the patient’s uterus. Even though IVF has become relatively common, it’s not a sure bet: About 70% of people younger than 35 who were first-time IVF patients in 2019 and used their own eggs had a baby within two years, according to a fertility industry report. Success rates decline as patients get older.

Given the physical, financial, and emotional tolls of failed cycles, researchers around the world are working to make IVF more effective. “In medicine, nobody can guarantee success,” says Dr. Zev Williams, chief of reproductive endocrinology and infertility at Columbia University Irving Medical Center. “The question is, how close can we get?”

Baby steps toward better tests

Some of those efforts focus on how to improve screening tests meant to help patients optimize their chances of having a healthy baby through IVF. One of the most common tests is called preimplantation genetic testing for aneuploidies (PGT-A). After eggs are fertilized to create embryos, clinicians take biopsies to look for aneuploidies, or chromosomal abnormalities that may increase the risk of IVF failure, miscarriage, or genetic disorders at birth. Proponents of PGT-A argue that it increases the odds of success by identifying embryos most likely to result in a healthy pregnancy.

But these tests are controversial. Some studies suggest PGT-A does not increase the likelihood of giving birth and results in enough false positives that viable embryos are routinely discarded—potentially making it harder for people to get pregnant because they have fewer embryos to work with. Genetic tests also add even more fees to an already pricey process.

Almost 10 years ago, Dr. Norbert Gleicher, founder of the Center for Human Reproduction in New York City, became so disenchanted with PGT-A that he began getting patients’ permission to implant embryos the test had flagged as having a high chance of failure. “Lo and behold, we started seeing healthy, chromosomally normal pregnancies,” he says.

Some embryos with certain chromosomal abnormalities self-correct during pregnancy, Gleicher and colleagues from Rockefeller University demonstrated in a small study published last year. Of 32 women in the study, only five gave birth—but the results demonstrate that at least some imperfect embryos can lead to normal pregnancies, Gleicher says. That’s especially important for older IVF patients, who typically have fewer embryos to start and thus need as many as possible to maximize their chances of conceiving. “Imagine how many embryos are out there that are currently not being transferred,” Gleicher says.

That question haunts California resident Lital Gilad-Shaoulian, who went through PGT-A testing when she decided to try for a fourth child at age 39. She was surprised to learn that the test classified all of her embryos as abnormal, especially since her three older children were all conceived through IVF. “I remember telling myself, ‘[The results] are wrong,’” she says.

For years, she repeated the emotional and costly process of harvesting and fertilizing eggs, only for most of the resulting embryos to be deemed abnormal. Finally, after consulting with clinicians at the Center for Human Reproduction, she convinced her local doctor to move ahead with one of her highest-graded but abnormal frozen embryos—a scary decision, but one she felt was worth a try.

She got pregnant, which Gilad-Shaoulian remembers shocked her doctor. Additional chromosomal testing at 10 weeks of pregnancy came back normal. And about 18 months ago, she gave birth to a baby girl. Her daughter had some unrelated health issues following a delivery complication, but Gilad-Shaoulian says she is developing normally and is “perfect” and “so smart.”

While genetic testing may be right for some people, Gilad-Shaoulian wishes she’d never done it. “There’s possibly tens of thousands of good embryos that are thrown away from people who are working so hard and are so eager to have a baby,” she says. “I’ve been there. I know.”

Experts like Williams, however, stand by the utility of testing. While some embryos in the gray area between viable and nonviable may result in a healthy baby, he says preimplantation testing can identify those that are very unlikely to succeed, which can come with significant benefits for patients.

In 2022, Williams’ team at Columbia developed new technology to deliver genetic test results in hours rather than days or weeks, potentially allowing viable embryos to be transferred on the same day they’re tested. While the test can’t fix any problems it detects, Williams says quickly identifying a patient’s best embryos can help them get pregnant faster, with fewer expensive failed cycles and emotionally difficult miscarriages. “The big difference will be how long does it take to get pregnant, and how many losses does she have to go through before she gets pregnant?” Williams says.

Other researchers are also trying to tweak PGT-A to make it more effective. Currently, clinicians take biopsies from what becomes the placenta, so “you really don’t know what goes on inside the cells that go on to form the baby,” says Kylie Dunning, a reproductive biologist at the University of Adelaide in Australia. Dunning recently co-authored a paper describing a new approach: taking a molecular photograph of the embryo to assess fetal cells, rather than those that form the placenta. She believes that will clarify which embryos are truly nonviable. “Hopefully, that will result in more patients taking home a baby,” she says.

Another research team, this one led by scientists from Australia’s RMIT University and Monash IVF, published a pair of studies in 2021 describing another possible target for pre-IVF testing. They described a “golden window” for treatment: the several-day period in a woman’s natural reproductive cycle when levels of a molecule called PCX are lowest. PCX makes the surface of the womb slippery, potentially preventing embryos from attaching. Theoretically, if clinicians can determine when PCX levels are lowest and transfer embryos then, it could improve the chances of pregnancy.

Study co-author Guiying Nie, a reproductive biologist, says her team is still working to validate its findings, so no such test is currently available to patients. The challenge is finding a fast, non-invasive way to test PCX levels. Some kind of imaging test could work, she says, but it’s too soon to say.

A similar screening technique, called endometrial receptivity analysis, analyzes tissue from a uterine biopsy to try to determine the best time for an IVF cycle, but some research suggests it’s not as accurate as promised.

Looking beyond tests

There is a limit to what any test can do, Williams says, so his lab is trying to find other ways of boosting success rates. For example, his clinic uses a robotic arm to prepare the tiny trays where embryos grow to eliminate human error.

Other companies are also turning some tasks over to robots. Startup TMRW created automated tanks for storing frozen eggs and embryos, ideally eliminating mishaps like freezer failures. Sensors in the tanks detect changes in storage conditions, then alert staff so they can fix problems before they become critical.

Artificial intelligence also holds promise for fertility. Research teams are trying to teach AI systems to select the best embryos for transplantation by analyzing images of them, and various consumer apps use AI to help women pinpoint when they’re most likely to conceive based on fluctuations in hormone levels and other factors.

Making fertility care more convenient

Improving the logistics of fertility care is also important. New York-based New Hope Fertility offers a program called “At Home IVF,” which makes the process as remote-friendly as possible. A patient starts with an online consultation, then, when appropriate, gets fertility medication delivered to their door. Patients only need to come into the clinic for major appointments like egg harvesting and embryo transfers.

Some clinics, including New Hope, also offer what’s known as “mini” IVF, a process that is similar to traditional IVF but uses fewer or lower-dose fertility drugs to keep costs down. Because patients receive fewer stimulating drugs, they may produce fewer eggs that can be fertilized—but mini IVF can be the right choice for patients with budgetary constraints or certain health conditions, according to the Cleveland Clinic.

Williams’ lab has also been working to make IVF more convenient for couples. They developed a new transport technique, using a substance that keeps sperm samples warm and viable for several hours, to allow men to produce samples at home and then drop them off at the clinic, rather than going through the process in a medical office. It may seem like a small shift, but Williams says sperm samples tend to be higher quality when they’re collected at home, potentially because men feel more at ease.

Every refinement counts when it comes to fertility care. “We really fight for every percent improvement in success rates,” Williams says, because each one can be life-changing for families.

Write to Jamie Ducharme at [email protected].

Each day, thousands of patients get a call or letter after being discharged from U.S. hospitals. How did their stay go? How clean and quiet was the room? How often did nurses and doctors treat them with courtesy and respect?

The questions focus on what might be termed the standard customer satisfaction aspects of a medical stay, as hospitals increasingly view patients as consumers who can take their business elsewhere.

But other crucial questions are absent from these ubiquitous surveys, whose results influence how much hospitals get paid by insurers: They do not poll patients on whether they’ve experienced discrimination during their treatment, a common complaint of diverse patient populations.

Likewise, they fail to ask diverse groups of patients whether they’ve received culturally competent care.

And some researchers say that’s a major oversight.

Kevin Nguyen, a health services researcher at Brown University School of Public Health, who parsed data collected from the government-mandated national surveys in new ways, found that — underneath the surface — they spoke to racial and ethnic inequities in care.

Digging deep, Nguyen studied whether patients in one Medicaid managed-care plan from ethnic minority groups received the same care as their white peers. He examined four areas: access to needed care, access to a personal doctor, timely access to a checkup or routine care, and timely access to specialty care.

“This was pretty universal across races. So Black beneficiaries; Asian American, Native Hawaiian, and Pacific Islander beneficiaries; and Hispanic or Latino or Latinx/Latine beneficiaries reported worse experiences across the four measures,” he said.

Nguyen said that the surveys commonly used by hospitals (called Consumer Assessment of Healthcare Providers and Systems, or CAHPS) could be far more useful if they were able to go one layer deeper — for example, asking why it was more difficult to get timely care, or why they don’t have a personal doctor.

It would also be more helpful if CMS publicly posted not just the aggregate patient experience scores, but also showed how those scores varied by respondents’ race, ethnicity, and preferred language.

Such data can help discover whether a hospital or health insurance plan is meeting the needs of all versus only some patients. Nguyen did not study responses of LGBTQ+ individuals or, for example, whether people received worse care because they were obese.

Hospital surveys — and how to game them — has become big business

The health care provider surveys are required by the federal government for many health care facilities, and the hospital version of it is required for most acute care hospitals. Low scores can induce financial penalties, and hospitals reap financial rewards for improving scores or exceeding those of their peers.

The CAHPS Hospital Survey, known as HCAHPS, has been around for more than 15 years. The results are publicly reported by the Centers for Medicare & Medicaid Services to give patients a way to compare hospitals, and to give hospitals incentive to improve care and services. Patient experience is just one thing the federal government publicly measures; readmissions and deaths from conditions including heart attacks and treatable surgery complications are among the others.

Dr. Meena Seshamani, director of the Center for Medicare, said that patients in the U.S. seem to be growing more satisfied with their care:

“We have seen significant improvements in the HCAHPS scores over time,” she said in a written statement, noting, for example, that the percentage of patients nationally who said their nurses “always” communicated well rose from 74% in 2009 to 81% in 2020.

But for as long as these surveys have been around, doubts about what they really capture have persisted. Patient experience surveys have become big business, with companies marketing methods to boost scores. Researchers have questioned whether the emphasis on patient satisfaction — and the financial carrots and sticks tied to them — have led to better care. And they have long suspected institutions can “teach to the test” by training staff to cue patients to respond in a certain way.

National studies have found the link between patient satisfaction and health outcomes is tenuous at best. Some of the more critical research has concluded that “good ratings depend more on manipulable patient perceptions than on good medicine,” citing evidence that health professionals were motivated to respond to patients’ requests rather than prioritize what was best from a care standpoint, when they were in conflict.

Hospitals have also scripted how nurses should speak to patients to boost their satisfaction scores. For example, some were instructed to cue patients to say their room was quiet by making sure to say out loud, “I am closing the door and turning out the lights to keep the hospital quiet at night.”

A new push to survey hospitals about discrimination

About a decade ago, Robert Weech-Maldonado, a health services researcher at the University of Alabama-Birmingham, helped develop a new module to add to the HCAHPS survey “dealing with things like experiences with discrimination, issues of trust.” Specifically, it asked patients how often they’d been treated unfairly due to characteristics like race or ethnicity, the type of health plan they had (or if they lacked insurance), or how well they spoke English.

It also asked patients if they felt they could trust the provider with their medical care. The goal, he said, was for that data to be publicly reported, so patients could use it.

Some of the questions made it into an optional bit of the HCAHPS survey — including questions on how often staffers were condescending or rude, and how often patients felt the staff cared about them as a person — but CMS doesn’t track how many hospitals use them, or how they use the results. And though HCAHPS asks respondents about their race, ethnicity and language spoken at home, CMS does not post that data on its public patient website, nor does it show how patients of various identities responded compared to others.

Without wider use of explicit questions about discrimination, Dr. Jose Figueroa, an assistant professor of health policy and management at the Harvard School of Public Health, doubts HCAHPS data alone would “tell you whether or not you have a racist system” — especially given the surveys’ slumping response rates.

One exciting development, he said, lies with the emerging ability to analyze open-ended (rather than multiple-choice) responses through what’s called natural language processing, which uses artificial intelligence to analyze the sentiments people express in written or spoken statements as an addendum to the multiple-choice surveys.

One study analyzing hospital reviews on Yelp identified characteristics patients think are important but aren’t captured by HCAHPS questions — like how caring and comforting staff members were, and the billing experience. And a study out this year in the journal Health Affairs used the method to discover that providers at one medical center were much more likely to use negative words when describing Black patients compared with their white counterparts.

“It’s simple, but if used in the right way can really help health systems and hospitals figure out whether they need to work on issues of racism within them,” said Figueroa.

Press Ganey Associates, a company that a large number of U.S. hospitals pay to administer these surveys, is also exploring this idea. Dr. Tejal Gandhi leads a project there that, among other things, aims to use artificial intelligence to probe patients’ comments for signs of inequities.

“It’s still pretty early days,” Gandhi said, adding, “With what’s gone on with the pandemic, and with social justice issues, and all those things over the last couple of years, there’s just been a much greater interest in this topic area.”

Direct outreach to improve cultural competence

Some hospitals, though, have taken the tried-and-true route to understanding how to better meet patients’ needs: talking to them.

Dr. Monica Federico, a pediatric pulmonologist at the University of Colorado School of Medicine and Children’s Hospital Colorado in Denver, started an asthma program at the hospital several years ago. About a fifth of its appointments proved no-shows. The team needed something more granular than patient satisfaction data to understand why.

“We identified patients who had been in the hospital for asthma, and we called them, and we asked them, you know, ‘Hey, you have an appointment in the asthma clinic coming up. Are there any barriers to you being able to come?’ And we tried to understand what those were,” said Federico.

At the time, she was one of the only Spanish-speaking providers in an area where pediatric asthma disproportionately affects Latino residents. (Patients also cited problems with transportation and inconvenient clinic hours.)

After making several changes, including extending the clinic’s hours into the evening, the no-show appointment rate nearly halved.

Patient satisfaction surveys are embedded in American health care culture and are likely here to stay. But CMS is now making tentative efforts in surveys to address the issues that were previously overlooked: As of this summer, it is testing a question for a subset of patients 65 and older that would explicitly ask if anyone from a clinic, emergency room, or doctor’s office treated them “in an unfair or insensitive way” because of characteristics including race, ethnicity, culture, or sexual orientation.

KHN (Kaiser Health News) is a national newsroom that produces in-depth journalism about health issues. It is an editorially independent operating program of KFF (Kaiser Family Foundation). KFF is an endowed nonprofit organization providing information on health issues to the nation.

A new screening programme in India leverages machine learning to reduce the risk of preventable blindness due to retinopathy of prematurity among premature babies.

ROP is a condition that occurs when abnormal blood vessels grow in the retina.

WHAT IT’S ABOUT

CleaVision, a social venture supported by enterprise software provider SAP, developed a solution that automates the identification of retina and blood vessel features and makes a recommendation on plus disease, which is associated with severe ROP in preterm infants. It does this by integrating image data processing with SAP Business Technology Platform, SAP AI Platform, and SAP Analytics Cloud. 

The automated deep learning screening technology has been piloted at Narayana Nethralaya Eye Institute (NNEI) in Bangalore, one of the leading eye hospitals in India that has conducted over 2,000 screening sessions for ROP in babies. Now, it has generated a huge database of retinal images from infants in different stages of the disease.

Following this pilot, CleaVision seeks to expand the rollout of its solution through the Karnataka Internet Assisted Diagnosis of ROP telemedicine network.

WHY IT MATTERS

About 20% of 15 million premature babies in the world are born in India. There, around 200,000 infants are said to be at risk of developing an advanced stage of ROP where abnormal growth of blood vessels in babies’ eyes can cause bleeding, scarring, and retinal detachment, ultimately leading to irreversible blindness. According to CleaVision, early diagnosis is essential to help babies get timely treatment to fully recover from this disease.

“With India having the highest number of premature pregnancies and the fact that there are relatively few qualified ROP practitioners, the more we can digitise and automate pre-screening the more time those practitioners can spend on actual treatment,” said CleaVision co-founder Chirag Gupta.

“Using the power of machine learning and data analytics we can help time-pressed doctors focus on treating at-risk babies,” added Narayan V.K., CleaVision co-founder.

Dr Anand Vinekar, the head of the Paediatric Retina Department at NNEI, said the CleaVision screening solution has the potential to assist technicians and ROP specialists in providing a more accurate diagnosis. “That, in turn, would help treat these babies on time, giving a better outcome which prevents blindness from ROP,” he added.

With this technology, the screening programme can also be scaled to reach low-resource settings.

MARKET SNAPSHOT

A similar automated deep learning system to detect advanced ROP in premature babies is being developed in the United States through the support of the National Eye Institute. In 2020, the device was given breakthrough status by the Food and Drug Administration.

Meanwhile, in Australia, researchers from the University of South Australia also used AI to develop a computer vision system to remotely monitor the vital signs of preterm infants and detect their faces while lying in hospital beds.

If the past two years have taught us anything, it’s that testing for viral diseases is complicated. Sometimes, the tests are difficult to get, like in the early days of COVID-19. And even if people have access to testing, they might not feel they need it. People with COVID-19 often don’t have symptoms and may not always know to get tested. And now, with the availability of at-home self-tests, most people test themselves and don’t report the results. With other diseases—such as monkeypox—stigma surrounding the disease and the group most affected can deter access to testing.

These limitations hinder health authorities’ ability to learn more about infectious diseases and control their spread. If you can’t detect a problem, you can’t direct resources to help fix it.

Wastewater analysis can help skirt some of these issues. Scientists have tracked COVID-19 through wastewater since early in the pandemic, and now they’re doing the same for monkeypox. A new program led by researchers at Stanford University, Emory University, and Verily, an Alphabet Inc. company, is monitoring monkeypox cases by analyzing sewage from 41 communities in 10 states. So far, they have detected the monkeypox virus in 22 of those sites. As monkeypox case numbers around the country continue to climb, such information is proving valuable as doctors and patients wrestle with testing challenges. “We have now detected monkeypox DNA in sewersheds before any cases were reported in those counties,” says Bradley White, senior staff scientist at Verily. The group is planning to publish their first findings from their monkeypox work in a preprint soon. Other academic and public-health groups are working with their local sewage facilities to track the virus, but this program, called WastewaterSCAN, is focused on getting a national picture of where cases are.

The data are shared publicly on a website hosted by Stanford, and the group is sharing its findings with the U.S. Centers for Disease Control and Prevention (CDC).

Read More: How the Monkeypox Virus Does—and Doesn’t—Spread

Because sewage is a composite from the thousands of people, it provides an ideal, anonymous way to detect levels of virus in communities. “We are capturing cases even if people are asymptomatic,” says Marlene Wolfe, professor of environmental health at Emory and co-principal investigator of WastewaterSCAN. “When there is limited testing capacity, and there is stigma associated with the disease, to have a population-level measurement of infections that isn’t impacted by those things is really powerful.”

Another reason why sewage is a sophisticated way to track monkeypox relates to the fact that it contains effluent from not just urine and feces, where the virus can be excreted, but also from saliva and water that drain while people brush their teeth and shower. Because monkeypox virus is active in skin lesions, such secretions are particularly effective vehicles for trapping and detecting the virus.

Researchers have analyzed wastewater for decades, most notably during the 1940s to track polio in the U.S. But the COVID-19 pandemic proved its utility on a large scale. Studies have shown that waste samples generally pick up signs of SARS-CoV-2 up to a week before clinics in a region start seeing positive cases. Wastewater can even detect new variants of SARS-CoV-2—something a rapid test can’t do.

In late 2020, the CDC launched the National Wastewater Surveillance System (NWSS), the first federal system to track an infectious disease pathogen—in this case, SARS-CoV-2—in sewage. It’s an attempt to standardize the way wastewater is collected, analyzed, and interpreted. NWSS now includes data from local programs—like WastewaterSCAN—and cities with their own tracking systems. New York City’s Biosurveillance Program, for example, has been testing wastewater for signs of SARS-CoV-2 since February, and now 11 hospitals in the group will start scanning for monkeypox and polio, which have been detected in New York City sewage.

When monkeypox cases first began popping up in the U.S., the researchers at Stanford, Emory, and Verily saw an opportunity to apply a wastewater lens to the disease, especially since testing for monkeypox wasn’t widely available. They had been tracking SARS-CoV-2 at a few sites in California through the Sewer Coronavirus Alert Network (SCAN) since November 2020, and had been adding analyses of other viruses, including influenza and RSV. When monkeypox cases began spreading around the world and while access to testing was still limited, they added that virus to their investigation as well and expanded their network to include more sites around the country. WastewaterSCAN was born.

Wolfe says the group’s platform for isolating the genetic material of microbes made it relatively easy to create the proper assay for detecting the monkeypox virus in mid-June. They targeted a portion of the monkeypox genome that was relatively unique, and the probe successfully identified the virus in their lab tests. But, says White, “the first few tests we ran on wastewater samples didn’t pick anything up.” That might have been because the concentration of virus in sewage at that point was so low. While WastewaterSCAN’s probe is designed to pick up very diluted amounts of virus, at the time of the tests, there were few cases in northern California. On June 19, WastewaterSCAN started testing samples provided daily from two treatment plants in the San Francisco area. The next day, both sites had positive tests for monkeypox.

Read More: What It Really Feels Like to Have Monkeypox

The monkeypox virus’ genetic material differs from that of SARS-CoV-2 because it’s in the form of DNA, while the COVID-19 virus and all of the group’s previous tests had been directed against RNA. But, White says, “DNA is much more stable than RNA, so as long as the genetic material is extracted from the sample, we’re pretty confident that if people are excreting a virus in wastewater, we will eventually detect it.”

The scientists say that there are still a few important unanswered questions about monkeypox in wastewater. They don’t have enough data to say for sure how much of a lead time wastewater can give health officials about rising cases, compared to testing at clinics and hospitals. They are also continuing to analyze the data to get a better sense of how much virus needs to be circulating in the community, or how many cases need to accumulate in a given region, before their analysis can pick up signs of the virus in sewage. That could give doctors an important head start in preparing adequate numbers of tests, vaccines, and treatments for the disease before cases peak.

The WastewaterSCAN team is now applying what they’ve learned from COVID-19 and monkeypox to explore ways to monitor influenza, RSV, and other seasonal diseases. In the case of RSV, a respiratory infection that often sickens babies, knowing where cases are starting to circulate could help doctors treat the most vulnerable babies with a monoclonal antibody drug before they get exposed, and thus spare them from contracting a potentially dangerous illness.

The key to having such a national system, however, is coordination among partners who share their findings, says Wolfe. “Having a network of sites that use the same collection and analytic methods so we can compare data gives us a national picture of what is going on,” she says. “We’d love to have more federal investments in systems like this.”

Contact us at [email protected].