In this relatively well-insured population, annual health care utilization significantly increases primarily because of more intensive use of outpatient care at retirement. This increase in outpatient care stems from a decline in the patient cost-sharing rate, the reduced time constraints upon retirement, and the interaction of these factors with supply-side incentives such as prescribing antibiotics. There is no evidence of change in inpatient care at retirement.

The economics of medical expenditure growth and its interaction with population aging is of considerable policy importance for countries in all income groups. “Our findings may provide useful evidence as one consideration for policymakers in other cities in China and elsewhere looking to increase insurance benefits and control medical spending for burgeoning elderly populations.

India is facing a mounting burden of noncommunicable diseases (NCDs) such as diabetes, cancers, and cardiovascular diseases. NCDs affect more than 20 percent of the Indian population and their prevalence is projected to expand substantially as the population aged 60 and over increases. Left unchecked, the costs of managing chronically ill and aging sectors of the population grow exponentially.

To control costs and address the growing chronic disease burden, India’s public programs must integrate curative hospital services with the most cost-effective preventive and primary interventions, argue Karen Eggleston, APARC’s deputy director and the director of the Asia Health Policy Program (AHPP), and Radhika Jain, a postdoctoral research fellow with AHPP. India must also urgently expand and improve the evidence base on economic evaluations of both preventive and curative health interventions in the country.

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In a correspondence piece published by BMC Medicine, Eggleston and Jain examine the features and limitations of a study that takes an important first step in that direction: a cost-effectiveness study of the Kerala Diabetes Prevention program (K-DPP) that adds such evidence on how to prevent diabetes cost-effectively in India and other low- and middle-income countries.

The study’s authors present a cost-effectiveness analysis of 1007 participants in the K-DPP, and their estimates indicate that K-DPP was cost-effective. Indeed, Eggleston and Jain determine that the analysis shows potential cost-effectiveness in “nudging” the participants towards a healthier lifestyle through suggestive reductions in tobacco and alcohol use and waist circumference. The results of the cost-effectiveness analysis of the K-DPP “highlight the importance of continued research on community-based promotion of healthy lifestyles,” say Eggleston and Jain.

Evidence-based approaches to chronic noncommunicable disease intervention are essential for providing cost-effective care and creating models for future programs like the K-DPP. Eggleston and Jain conclude that future studies advancing evidence-based approaches to chronic noncommunicable disease intervention — ones that cover larger and more representative populations over longer time periods — remain important for more generalizable assessments to inform policy decisions.

Most Americans don’t realize there are silent brokers helping to fix the price of their prescription drugs — or that it’s a $100 billion annual business accounting for half of Big Pharma sales.

They’re called pharmacy benefit managers (PBMs), with CVS Caremark, Express Scripts and Optum RX dominating the market. Their chief function is to develop and maintain a list called the “formulary,” a list of drugs that will be covered by health-care plans. The formulary groups drugs into tiers with different levels of patient cost sharing.

They also pool volume across health plans to negotiate with drug manufacturers and retailers on prescription drug pricing. And PBMs reap rewards from rebates and fees that drug manufacturers pay them, as well as from a ‘pharmacy spread’ where PBMs bill health plans more than they reimburse pharmacies.  

All of this comes at a cost to patients.

“Patients typically only think about what they pay out-of-pocket at the pharmacy counter,” said Alex Chan, a PhD candidate in health economics at Stanford Health Policy. He and Kevin Schulman, a professor of medicine and professor of economics, by courtesy, at the Stanford Graduate School of Business, have just published a paper in JAMA Health Forum that examines these silent and powerful intermediaries.

“As PBMs leverage the formulary design to secure more and more rebates and fees from manufacturers, these drug manufacturers raise the list price in response,” Chan said. “The patients’ out-of-pocket cost at the counter would increase but at a less noticeable rate given that they co-pay are just a percentage of the list prices.”

Unless these rebates are passed along to consumers as reduced premiums, the net effect is an increase in premiums. Furthermore, if formulary design is used to help PBMs secure better rebates, PBMs may prioritize expensive drugs over more cost-effective drugs.

Transparency

These pharmacy benefit managers have come under scrutiny as health policy experts learn more about the scale of prescription drug rebates and other questionable practices used by these intermediaries in the prescription drug market. For example, PBMs can include “gag clauses” that prohibits pharmacists from telling customers about cheaper drug options.

They ask themselves: What is the underlying value of PBMs for both payers and patients?

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“They create value by providing information on the quality and value of products and services and by providing negotiation leverage as they amass scale by aggregating smaller buyers (or sellers),” they write. “Consumers can be sure to share in this value under three conditions: when there is competition among intermediaries, when pricing is transparent, and when it is clearly defined who is negotiating on whose behalf.”

But when these conditions are not met, they add: “We can find that intermediaries can hold a powerful and self-serving position in a market.”

Chan and Schulman found that in the drug prescription market, there are significant concerns about the value of these PBMs:

1. Rather than a market where there is competition among PBMs, consolidation has resulted in a situation in which the three largest PBMs have about 80% of market share. There are significant barriers to competition among PBMs. If a health system wants to switch PBMs, it requires a significant investment in a “request-for-proposal” process.
2. Drug-specific rebates are kept confidential between PBMs and drug manufacturers, and health plans have little ability to clearly assess the cost-savings for their members or to gauge the appropriateness of the rebate passthroughs.
3. Under the rebate model, the role of the PBM has evolved to serving as an agent of both the payer and the manufacturer. The interests of payers and manufacturers are often in conflict, especially with respect to expenditures.

"One of the largest criticisms of PBMs is the lack of transparency surrounding the structure and scale of payments from manufacturers to the PBM,” the authors write. “The current PBM business is shrouded in secrecy.”

Only the PBM knows the actual scope of payments from drug manufacturers, such as rebates and service fees. They note that in 2016, for 13 pharmaceutical companies, payments to PBMs and other intermediaries (such as wholesalers) were $100 billion — or 50% of gross sales.

 “Without transparency, a PBM might develop formularies that maximize payments to the PBM rather than maximize value to patients,” Chan and Schulman write.

Suspicion over just that led health insurance company Anthem to sue Express Scripts for $15 billion in 2016 for overpayments on drug pricing. In the end, Anthem cut ties with Express Scripts to develop its own PBM.

“The PBMs have grown out of sync with what we can reasonably expect to be a value-adding intermediary,” Chan said. “It is hard to really tell how much inefficiencies have been created due to this lack of transparency.”

Legal Solutions

The authors note that Congress has taken steps to shed light on PBMs through the Patient Right to Know Drug Prices Act and the Know the Lowest Price Act, both adopted in 2018. These laws outlaw PBMs gag clauses that forbid pharmacists from telling consumers that their price through a PBM was higher than the as price for the same product.

Chan said these laws are a move toward the direction of providing patients with more transparency about their options.

“An even more promising direction would be for legislation to make a stronger push towards public disclosure of rebates, discounts, and price concessions, along with lower barriers to entry to the PBM market,” he said.

Elderly patients hospitalized with congestive heart failure have a poor prognosis and high risk of death and hospital readmission. So, their post-discharge care can strongly influence their outcomes.

Yet despite data showing that transitional care interventions, such as home visits by nurses, can reduce death rates and hospital readmission by more than 30%, many health systems have not implemented such programs. Health policy experts say this is due in part to cost concerns and doubts about the effectiveness of these delivery services.

 Now, a team of Stanford Medicine and Veterans Affairs researchers has sought to assess whether transitional care interventions provide good value and better outcomes, as there are 5 million people living with congestive heart failure in the United States and 500,000 new cases diagnosed each year. CHF is the stage of chronic heart disease in which fluids build up around the heart, causing it to pump inefficiently.

The researchers updated a 2017 study on the impact of transitional care intervention with four years of additional data. They then used it to compare standard post-discharge management with three post-discharge regimes for patients 75 or older that they found to be most effective: disease management clinics, nurse home visits and nurse case management.

All three transitional care interventions delivered appreciable health benefits to the patient population, said Jeremy Goldhaber-Fiebert, PhD, associate professor of medicine at the Stanford School of Medicine and core faculty member of Stanford Health Policy.

The findings were published in the Annals of International Medicine. Goldhaber-Fiebert is the senior author. The lead authors are Manuel R. Blum, MD, MS in Epidemiology & Clinical Research at Stanford in 2019 and now at the Department of General Internal Medicine at the University Hospital of Bern; Henning Øien, PhD, Norwegian Institute of Public Health, Oslo; and Harris L. Carmichael, MD, a Stanford/Intermountain Fellow in Population Health, Delivery Science, and Primary Care

“Transitional care interventions for older individuals with congestive heart failure — particularly nurse home visits — offer a high-value care alternative that could improve the health and longevity of millions of Americans,” he said.

The researchers said these transitional care services should become the standard of care for post-discharge management of patients with heart failure.

Heart failure causes 1 in 8 deaths nationwide

The prevalence of heart failure is estimated to be 26 million people worldwide and growing. In the United states, heart 5.7 million adults have been diagnosed with HF, with an estimated annual direct cost of $39.2 billion to $60 billion. Total heart failure costs in the United States are expected to exceed $70 billion by 2030, the authors wrote. According to the Centers for Disease Control and Prevention, heart disease costs the United States about $219 billion each year from health-care services, medicines and lost productivity.

Of the 15 million Americans in their mid-70s to 80s today, about 1 million suffer heart failure.

“So population gains from more effective post-discharge care would be hundreds of thousands of life years,” Goldhaber-Fiebert said. “Likewise, tens of thousands of costly rehospitalizations could be prevented each year if these interventions were delivered successfully.”

Heart failure primarily affects older people and is the second-most common inpatient diagnosis billed to Medicare. Yet the authors cite a recent study of 18 million Medicaid charges which found that only 7% of eligible patients at risk of rehospitalization received transitional services.

The standard post-hospital care for those patients includes sending them home with some advice and scheduling follow-up visits for them with cardiologists within 14 days of discharge. The researchers found that patients who received this standard post-hospitalization care with an average age of 75 had an average life expectancy of 2.9 years and 2.9 hospitalizations during their remaining lifetime. In comparison, nurse home visits decreased the number of hospitalizations by 10 readmissions per 100 patients and increased life expectancy by approximately four months, the study found.

“If these interventions were successfully implemented at scale, they could provide important substantial benefits with very good value,” said co-author Douglas Owens, MD, the Henry J. Kaiser Jr. Professor and professor of medicine at Stanford.

Reduced hospitalizations for congestive heart failure, according to the research, produces substantial cost savings that partially offset the costs of delivering the interventions. Though nurse home visits increase lifetime health care costs by $4,622, the substantial health benefits that they deliver justify their costs: $19,570 quality adjusted life years gained, which is considered highly cost-effective.

Hospital and insurance administrators take note

“Our results have important implications for decision-makers in hospital administration as well as in insurance and policy settings,” the authors wrote. They concluded:

• Transitional care services should become the standard of care for post-discharge management of patients with heart failure;
• The increasing reimbursement restrictions and regulations affecting HF hospital readmissions, through such programs as the Centers for Medicare & Medicaid Services Hospital Readmission Reduction Program, makes this research particularly informative to decision-makers;
• Hospital administrators could use the research to determine which transitional services are most cost-effective for its rural population, overall patient base and hospital system.

The other Stanford researcher on the study was Paul Heidenreich, MD, a professor of medicine and health research and policy at the Stanford University School of Medicine and, by courtesy, professor of health research and policy at the Palo Alto Veterans Affairs Health Care System.

Stanford Health Policy researchers, led by Josh Salomon, have been awarded a five-year grant from the Centers for Disease Control and Prevention (CDC) to conduct health and economic modeling to guide national and local policies and programs focusing on some of the most important infectious diseases in the United States.

The CDC grant establishes the Prevention Policy Modeling Lab at Stanford, continuing a multi-institution collaboration that began when Salomon was a professor at Harvard prior to joining Stanford in 2017.

“The overall mission of the Prevention Policy Modeling Lab is to leverage the best available evidence to inform strategic decision-making about major public health problems,” Salomon said. “We do this by combining techniques from decision science, simulation modeling and health economics to estimate and project major patterns and trends in these diseases and to evaluate different clinical and public health strategies to address them.”

The initiative will focus on policy and practice in the areas of tuberculosis, HIV, hepatitis, sexually transmitted infections and adolescent health. The grant from the Centers for Disease Control and Prevention supports a wide range of modeling activities, including those that assess: 

• Projections of future morbidity and mortality
• Burden and costs of diseases
• Costs and cost-effectiveness of interventions
• Population-level program impact
• Optimized resource allocation

Stanford researchers who are involved in the Modeling Lab include Douglas K. Owens, Margaret Brandeau, Eran Bendavid, Jeremy Goldhaber-Fiebert, Jason Andrews, Samuel So and Mehlika Toy. The consortium also includes partners at Harvard, Yale, Michigan, Boston University, Boston Medical Center and the MA Department of Public Health.

“As a multi-institution consortium, on any given problem we’re able to assemble a team that includes both subject matter experts and collaborators who specialize in statistics, epidemiology, data science, economics and decision analysis,” Salomon said. “The policy models that we develop allow us to synthesize a wide array of different types and sources of evidence to shed light on the essence of the problem and to weigh the likely benefits and costs of responding in different ways.”

Prior work from the consortium on the potential impact and cost-effectiveness of expanding testing for hepatitis C virus was cited in the recent decision by the U.S. Preventive Services Task Force to revise their screening recommendations to cover all adults. The Modeling Lab has also examined prospects and strategies for eliminaitng tuberculosis in the United States and policies relevant to the rising threat of antimicrobial-resistant gonococcal infection among other topics.

When it comes to rooting out wasteful spending in federal entitlement programs, attention has long focused on preventing beneficiaries from gaming the system.

A new Stanford study identifies a fresh cause for concern: the for-profit companies that the U.S. government increasingly tasks with providing benefits to Americans who are often poor, elderly or both.

In a new working paper, Maria Polyakova, an assistant professor of medicine, finds that outsourcing public assistance services to third parties can lead to unanticipated effects on prices as well as on which beneficiaries gain the most from public dollars.

That’s because companies are in the business of making money. And when they know which of their consumers are likely to get certain levels of public support, they will try to use this information to maximize their profits, according to the research published this week by the National Bureau of Economic Research.

Polyakova shows that when companies act in their self-interest, unforeseen inequities and inefficiencies can arise that may hurt some consumers while helping others. At a time when governments in the United States and around the world are increasingly turning to the private sector to provide public benefits — namely in health care and in education — Polyakova says policymakers need to better understand how these intermediaries are affecting welfare programs.

“Policymakers have to be more careful about introducing intermediaries into public services,” says Polyakova, who is a faculty fellow at the Stanford Institute for Economic Policy Research (SIEPR), and teaches at the Stanford School of Medicine. She is also a core faculty member of Stanford Health Policy. “They may want to revisit how they think about outsourcing when research is showing that there are unintended consequences that may be positive or negative.”

Health Insurance Pricing under the Microscope

Intermediaries are central to a number of public services where the U.S. government provides subsidies to consumers, often based on income, age or employment status. Prominent examples include privately-managed Medicare Advantage Plans, drug benefits under Medicare Plan D, and charter schools in secondary education.

According to Polyakova, most research into wasteful spending within government subsidies has focused on consumers and how they try to trick the system by, for example, hiding income to qualify for a tax credit or cash assistance. Governments, though imperfect, have long been seen as benign players.

The increasing involvement of for-profit companies, she says, shows there’s a need to closely examine what’s happening on the supply side of public welfare.

To do that, Polyakova found an ideal setting: the federal health insurance marketplace created by the Affordable Care Act of 2010. Most consumers who shop for coverage through www.healthcare.gov receive a subsidy in the form of a tax credit that covers all or part of their insurance premium. The amount of their tax credit is tied to their household income.

The dollars at stake are significant. The Congressional Budget Office estimates that in 2019 the federal government will pay $560 billion in subsidies for privately-provided health insurance, including the spending on the Affordable Care Act marketplaces as well as other similarly designed programs. That figure is expected to hit $1.2 trillion over the next decade.

The Neighborhood Effect

Polyakova and her co-author — Stephen Ryan of Washington University’s Olin Business School — analyzed data from 2017 covering more than 9 million enrollees across some 2,570 counties around the country. They find that the presence of an intermediary significantly impacts insurance prices and key measures economists use to calculate the effects of a policy beyond a given benefit’s face value.

Specifically, they show that health insurance companies will have an incentive to raise premiums in markets where more consumers receive the higher tax credit because their incomes are low and the government is required to subsidize them.

On the flip side, insurers will charge lower prices in places where such subsidized consumers are less willing to buy coverage if they think it costs too much.

To illustrate the unintended consequences of the insurers’ actions, the researchers point out that, in the first instance where prices increase, consumers with incomes that are slightly higher than other community members will end up paying more for the same coverage. Under the second scenario, consumers who don’t qualify for the tax credit because their incomes are too high benefit from the lower premiums aimed at nearby residents.

“The price you pay for insurance will depend on who your neighbors are,” says Polyakova. “If you live near people who are poorer than you, you will be affected differently than if you live near people who are richer than you.”

Change the subsidy, change the calculation

Like with financial aid, tax credits for insurance coverage are calculated based on consumer income. But there is another type of subsidy that policymakers could use — flat vouchers, in which all members of a market receive the same benefit regardless of income, age or some other characteristic. For their research, Polyakova and Ryan also analyze how flat vouchers that only vary by age, but not by income, would hypothetically alter private health insurance prices in the federal Affordable Care Act marketplace.

Here, too, the scholars find different impacts on different types of consumers whether the subsidy is based on income or delivered as a flat voucher.

The analyses, says Polyakova, drive home the point that policymakers need to understand that there are trade-offs to relying on for-profit companies to provide government services and that the type of subsidy offered can alter how they calculate prices in disparate ways.

“There’s nothing wrong with companies trying to maximize their profits,” says Polyakova. “But sophisticated policymakers need to understand what happens when private markets get involved.”

I always find it hard to believe so many people are living in poverty: some 39.7 million Americans, or 12.3% of the population. It’s such a wealthy country, yet so many are poor.

In a twist that could be interpreted as good news — it doesn’t seem fair to say there is anything positive about living in poverty — I recently learned that older, low-income Americans tend to be healthier if they live in more affluent areas of the country.

Not only are they healthier, but their physical well-being is better across the board with a lower prevalence of dozens of chronic conditions, particularly if they live in rural communities. This, despite their income having less purchasing power in those better-resourced neighborhoods.

This was the key finding in new research published by Stanford Health Policy’s Maria Polyakova in the Annals of Internal Medicine.

While recent studies have reported that low-income adults living in more affluent areas of the United States have longer life expectancies, less has been known about the relationship between the affluence of a geographic area and morbidity of the low-income population.

“I was interested in figuring out whether the same relationship holds for morbidity: Are poorer people less sick in richer areas?” Polyakova told me. “And if so, are there any specific conditions that drive these differences that could be the target for policy-making?”

So Polyakova, a faculty fellow at the Stanford Institute for Economic Policy Research, and her co-author, Lynn M. Hua at the University of Pennsylvania, set out to evaluate the association between chronic conditions among low-income, older adults and the economic affluence of a local area. 

They focused on nearly 6.4 million Medicare beneficiaries in 2015 aged 66 to 100 years old who received low-income support under Medicare Part D, a prescription drug program for Medicare enrollees. They investigated the prevalence of 48 chronic conditions among these patients, including common chronic conditions such as hypertension, depression, diabetes and Alzheimer’s disease. They found the presence of all conditions is highly correlated: places, where the poor tend to have a high prevalence of one disease, are likely to have a high prevalence of all 48 conditions.

“While we cannot ascertain a causal relationship, our results clearly point towards the importance of further understanding why the socioeconomic environment of low-income, older adults is so tightly linked to such a broad measure of health,” the researchers wrote. 

The results, they said, were broadly consistent with the extensive literature on the social determinants of health. But their work takes that literature even further.

“Our study extends this research by providing measures of the prevalence of chronic conditions among low-income, older adults for a large national sample of the U.S. population,” Polyakova said. 

The researchers used clinical, rather than self-reported measures of diagnoses and reported this group’s variation in morbidity across local areas of the country, rather than nationally. 

“Our results raise the bar for researchers who are trying to find out what factors drive health disparities in the U.S.; these factors would have to be able to explain the differences in nearly 50 condition,” Polyakova said.

The study supported by the National Institute on Aging came to three key conclusions:

1. The health of low-income, older adults in the United States varies substantially across local geographic regions, and this variation cannot be attributed to one specific disease or a narrow set of conditions. 
2. Consistent with their original hypothesis, they found that more affluent local areas of the country have a lower prevalence of chronic conditions in the low-income, older adult population.
3. The researchers found that low-income, older adults have better health in rural areas of the country.

I wondered why these poor, older adults do particularly well in rural communities, as those regions often lack easy access to high-quality health care and state-of-the-art hospitals.

“We don’t know the exact answer, but there is a general sense that differences in the social fabric and lifestyle in rural areas — could contribute to this pattern,” Polyakova told me. “It appears that better health in these areas persists, despite challenges of accessing formal care.”