View news from the 2021 SABCS, including session summaries, poster write-ups, and interviews with key opinion leaders.

Coverage of the 2021 San Antonio Breast Cancer Symposium

View news from the 2021 ACAAI Annual Scientific Meeting, including session summaries, poster write-ups, and interviews with key opinion leaders.

Coverage of 2021 ACAAI Annual Scientific Meeting

If 2020 was dominated by the news of how COVID-19 spread across the globe, then 2021 has so far been focused on ending the pandemic through vaccine distribution.

A Timeline of COVID-19 Vaccine Developments in 2021

This AJMC® Profiles in Care provides an in-depth look into the results of the outcomes-based agreement between Boehringer Ingelheim and Highmark Inc.

AJMC® Profiles in Care Launches

Travis Broome is senior vice president of policy and economics at Aledade, which helps doctors stay independent and thrive in the transition to value-based care. Joining Aledade early on, Travis helped Aledade grow from 2 accountable care organizations (ACOs) to 20 ACOs. Today, he is a thought leader on accountable care and is responsible for strategy development, policy analysis, and economic modeling. Prior to Aledade, Travis was a regional director at CMS. He earned his MPH and MBA from the University of Alabama at Birmingham.

Michael McWilliams, Alice Chen, and Michael Chernew recently 

 the next frontier in total cost of care accountability: Eventually, there will not be a pure fee-for-service (FFS) comparison. In several counties in the country, this may already be the case. The 

 of Medicare Shared Savings Program (MSSP) penetration and Medicare Advantage (MA) penetration is high enough that there is no longer a significant population of Medicare beneficiaries for whom neither health care providers nor MA plans are accountable for the total cost of care. Arriving at this desirable goal has profound implications.

MA rates combine lagging historical spending in traditional Medicare, policy choices altering that history (qualifying counties, Stars bonuses), and a bidding process. MSSP uses an annual determination of county-level spending in traditional Medicare to determine regional benchmarks. Direct contracting uses a more complicated version of the MSSP determination to do the same. On our current trajectory, this means that eventually, MSSP will both suppress MA rates and MSSP rates. This trajectory will eventually change the incentive from reducing the total cost of care to consolidation among health care providers to avoid this negative feedback loop. Yet a future where there is so much participation in value programs in traditional Medicare that pure FFS is functionally extinct is desired by the advocates of the transition to value.

In their paper, McWilliams, Chen, and Chernew propose solving this by moving to administratively set rates. These projections replace the retroactive experience of an FFS comparison group and provide certainty to Medicare on future costs with actual cost below the projection deemed savings in which the taxpayer should continue to share but primarily accrue to accountable care organizations (ACOs). The challenge with administratively set rates is how to make them relatable to health care providers. We need to incentivize greater health at a lower cost in a way that generates positive behavior changes at the practice level.

The first benchmarking methodology of MSSP only recognized what I term improvement value. Did an ACO reduce its health care spending compared to previous years? ACOs who already had lower costs were told everyone could improve and that their past efforts had no value. ACOs with higher costs made savings relatively easily, especially in areas of the country where the use of national update factors created positive arbitrage. It is no coincidence that early success in MSSP was geographically concentrated. This arbitrage was even more important than starting from high costs. As CMS refined MSSP, the program has recognized what I term relative value. Does a beneficiary’s use of one primary care practice over another result in lower costs? Relative value flips the script where efficient ACOs are given a head start by getting a bonus to the benchmark valuing their past efforts. Inefficient ACOs have their benchmark lowered and are told it is easier to lower costs from a high baseline. At the same time, CMS removed most of the national trend vs regional trend arbitrage from MSSP by shifting to the aforementioned county cost comparisons.

MA is a 100% relative value calculation where the cost experience of MA beneficiaries is not included in the benchmark at all. In our experience at Aledade, our primary care practices place great emphasis on relative value, while commercial payers understandably place greater emphasis on improvement value. MA, with its 100% relative value rates, is the exception as the government limits profit margins available to MA plans. As we look toward a future where pure FFS can no longer define either improvement or relative value, we still need to keep in mind the differences they have on health care provider behavior.

Much has been made of the slowdown in MSSP enrollment that occurred in 2019 and 2020. To us, the reasoning is obvious: disruption. While the changes in Pathways to Success were largely championed by the ACO community, CMS was so late getting them out that it had to hold a special midyear enrollment period in 2019. Then COVID-19 hit, and there was no 2020 enrollment period for 2021 starts. As I believe the reason for the slow down was primarily disruption, I am skeptical that the solution for reinvigorating growth in the program is more disruption. I would therefore address the intermediate concerns raised by McWilliams et al with the simplest modifications to the MSSP possible to add the least amount of disruption possible.

Problem 1: Small Practices Unwilling or Unable to Go to Risk

Most of the gain in value-based health care is from creating a positive financial incentive to lower the total cost of care. CMS created revenue-based risk first in Track 1+ and then in the Basic track within Pathways to Success. Currently, a low-revenue ACO can spend 10 years in the Basic track with only 8% of its Medicare revenue at risk. I believe it is unlikely that these levels of risk are what are holding practices back. I believe what is needed is 

. This model is the shallowest of shallow ends of the pool with no risk and no formal governance requirements. Yet it ensures everyone gets in the pool, no more sitting on the deck.

Problem 2: Higher-Cost Health Care Providers Not Participating

When CMS introduced a positive incentive for health care providers generating relative value, it introduced a penalty for higher-than-average-cost health care providers. There is a feeling of fairness here. However, I suggest that it does not further the goal of reducing wasteful health care spending. In order to believe this is a money-saving policy, CMS would need to believe that the forgone savings from high-cost providers choosing not to participate are less than the penalties paid by those high-cost providers who do participate. Given the decline in participation, it seems unlikely that this balance is currently working in CMS’ favor. CMS should remove the penalty for regional efficiency and add the recommendations of McWilliams et al to encourage alternative payment model (APM) participation through other policies.

Recently, I, with others, outlined a strategy to use MSSP as an innovation 

. The essential packages to add to MSSP are primary care capitation, incentives to increase the number and equity of primary care relationships, value-based benefit design, and a “Next Generation” ACO package. The Next Generation ACO package would include a discount instead of shared savings (though a higher one than in Next Generation to ensure savings), the use of TIN/NPI combinations, and Medicare facilitated affiliations affected downstream payments. None of these packages would include a different benchmarking methodology as our goal is to minimize disruption to increase participation.

MSSP already has the strongest risk intensity protections of any program. I agree that a better risk model that is less sensitive to the effort spent on the inputs to the model is needed. I note that MSSP has taken the only meaningful step to improve the model in the last decade with its eligibility-specific normalization factors. It is not 

, but MSSP already does it better than anyone else, so no fundamental disruption is needed while we wait for the development of a better risk model. MedPAC and others have advocated for change in MA. Such changes are beyond the scope of this editorial.

MA has always been a 100% relative value opportunity for MA plans. For the subset of health care providers taking accountability for total cost of care under MA plans, that accountability is similar to what it is in MSSP. MA plans calculate a historical medical loss ratio (MLR) for a group of health care providers, and the group then negotiates for a few percentage points to be added to their historical MLR, functionally equivalent to the MSSP regional bonus. I note that a majority of MA beneficiaries receive health care services paid on a purely FFS basis. If APMs are defined as paying health care providers differently, there is at least much growth in APMs needed in MA as in traditional Medicare. I see opportunity in how MA contracting has evolved to be similar to MSSP to bring them even closer together and encourage even greater participation. Risk adjustment challenges in MA are well 

 and need to be addressed beyond the APM context.

First and foremost, to get beyond FFS, we need to grow accountability of total cost of care. The two biggest opportunities are to increase participation in MSSP and increase health care provider accountability for total cost of care in MA plans. By stabilizing MSSP (not disrupting it yet again) and adding tools for more innovation under its umbrella, we can restart MSSP growth by making it simple for any health care provider who is taking accountability for total cost of care for one Medicare population to do so for all Medicare populations.

Administratively set benchmarks can reward both improvement and relative value. The starting point can be bonuses for efficiency just as it is currently. McWilliams et al propose just using an ACO’s MSSP benchmark as the starting point when the transition is made, thereby locking in the MSSP bonus and penalty if that is not removed. Improvement value comes in the form of beating the administrative updates. The hard part is how do we get the correct administrative update for New York and the right update for Lafayette, LA, and the right update for Los Angeles, CA. We know that updates that were universal for the nation in MSSP created arbitrage across the country, rewarding some health care providers with savings not driven by their efforts and making savings nearly impossible for other health care providers despite their efforts. CMS solved this problem in MSSP by using local FFS comparison trends. In a local market with multiple ACOs and multiple MA plans, how do we administratively set rates that are localized enough so that they do not drive consolidation? This balance is the challenge of the next few years as we look forward to the day when pure FFS goes away, and we truly have made the transition to value.

Articles

In a local market with multiple accountable care organizations and multiple Medicare Advantage plans, how do we administratively set rates that are localized enough so that they do not drive consolidation?

Contributor: The Future of Accountability for Total Cost of Care

® since 2019 after receiving his Bachelor's degree at Rutgers University–New Brunswick in journalism and economics.

) may help predict response to adjuvant therapy in patients with epidermal growth factor receptor (EGFR)-mutant stage 2 and 3 non–small cell lung cancer (NSCLC). Findings were published in 

After curative surgery for stage 2A-3B resected NSCLC, cisplatin-based adjuvant chemotherapy serves as the current gold standard for treatment. However, 5-year survival rates remain unsatisfactory for these populations, noted the researchers, with alarming levels of grade 3 toxicity observed in more than 60% of the patients.

In findings of the phase 3 ADJUVANT study, adjuvant gefitinib exhibited significant prolonged disease-free survival (DFS) in patients with EGFR-mutant stage 2–3A NSCLC compared with chemotherapy with vinorelbine and cisplatin (VP). Moreover, positive findings were also shown in the SELECT, EVAN, and ADAURA trials regarding the use of tyrosine kinase inhibitors (TKIs) in these patient populations.

“However, approximately 19% to 40% of TKI-treated patients still relapse after these trials, suggesting the inadequacy of EGFR-sensitizing mutants alone as a biomarker for adjuvant treatment selection,” the researchers said.


Noting the necessity for further biomarker assessment, they performed comprehensive genomic profiling (or, NGS) of 171 tumor tissues from patients with EGFR-mutant NSCLC from the ADJUVANT trial.

They searched for important comutations and key predictive biomarkers for adjuvant treatment, and then they integrated discovered biomarkers into a robust predictive score, known as the  Multiple-gene Index to Evaluate the Relative benefit of Various Adjuvant therapies (MINERVA) score, which categorizes patients into subgroups with distinct survival benefits under either adjuvant gefitinib or chemotherapy for precision care.

Of the tumor tissues examined, 5 predictive biomarkers were identified by NGS (

 alterations, and copy number gains of NKX2-1, CDK4, and MYC). After integrating them into the MINERVA score, 3 subgroups with relative DFS and overall survival benefits from either adjuvant gefitinib or chemotherapy were identified (highly TKI-preferable [n = 60], TKI-preferable [n = 87], and chemotherapy-preferable [n = 24] groups).

The 3 subgroups demonstrated distinct treatment responses and underlying molecular profiles:

The highly TKI-preferable group expressed significant superiority with adjuvant gefitinib (HR, 0.21; 95% CI, 0.10-0.44) and was enriched with copy number gains of NKX2-1, CDK4, and MYC, and 

The TKI-preferable group showed improved DFS among the precategorized and intention-to-treat populations (HR, 0.61; 95% CI, 0.35-1.07); this subgroup was characterized by the absence of most predictive biomarkers, except for sporadic coexistence of NKX2-1 and 

A small subset of patients from the chemotherapy-preferable group, despite having EGFR-positive tumors, showed greater response and enhanced DFS (HR, 3.06; 95% CI 0.99-9.53) under VP treatment, and harbored 

“This study demonstrates that predictive genomic signatures could potentially stratify resected 

-mutant NSCLC patients and provide precise guidance toward future personalized adjuvant therapy,” concluded the researchers.


Liu SY, Bao H, Wang Q, et al. Genomic signatures define three subtypes of EGFR-mutant stage II–III non-small-cell lung cancer with distinct adjuvant therapy outcomes. 

. Published online November 8, 2021. doi:10.1038/s41467-021-26806-7

Next-generation sequencing uncovered 3 subtypes of epidermal growth factor receptor–mutant stage 2 and 3 non–small cell lung cancer (NSCLC) that predicted patient outcomes to adjuvant therapy.

Genomic Profiling Identifies 3 NSCLC Subtypes Predictive of Adjuvant Therapy Outcomes

 of adalimumab biosimilars by Cardinal Health anticipates that possibly 2 more could be approved and launched in 2023, the year that 6 FDA-approved adalimumab biosimilars are already scheduled for launch.

Cardinal Health estimates that Idacio, an adalimumab biosimilar under development by Fresenius Kabi, and CHS-1420, an adalimumab biosimilar under development by Coherus BioSciences, could launch in September and December 2023, respectively. Neither product has so far received FDA approval.

A third biosimilar version of adalimumab, AVT02, developed by Alvotech and with US licensing by Teva, has the potential to launch in 2023, although it has yet to obtain FDA approval, too.

Two other adalimumab biosimilars are in development, although Cardinal Health is making no bets as to whether they will surface on the market in 2023 or beyond. Those are CT-P17 by Celltrion and ABP-501 HC by Amgen.

“The US biosimilars market is in for a very exciting year in 2023, largely owing to the slate of potentially 10-plus biosimilar competitors anticipated to launch against the world’s top-selling drug of all time, Humira,” Cardinal Health wrote in an introduction to its adalimumab biosimilars data chart.

Adalimumab was originally approved in the United States in 2002 and has generated in excess of $170 billion in revenues. The drug is indicated for 

Owing to a formidable portfolio of at least 136 patents, Humira has over the past 2 decades withstood attempts by biosimilar companies to come to market prior to 2023. In fact, settlements with AbbVie have been the primary means by which biosimilar companies have been able to penetrate legal barriers and schedule reliable market entry dates.

Below is the 2023 market entry timetable for the 6 FDA-approved adalimumab biosimilars:

Even as the year of adalimumab biosimilar competition draws nearer, the picture of what that competition will look like is in constant flux, as the various competitors adjust their game plans according to court battles and product enhancements.

Rather than settle with AbbVie, Icelandic company Alvotech has opted to take the company to court over patent obstructions; and a court-issued timetable for arbitrating that dispute will not conclude before October 2022. It’s possible the biosimilar, AVT02, will 

 and come to market before 2023, but that assumes that AbbVie is unsuccessful in defending its patent protections.

Biosimilar developers are now attempting to distinguish their adalimumab products by obtaining interchangeable status for them. This would enable pharmacists to dispense an adalimumab biosimilar for Humira without consulting the prescribing physician.

Alvotech has sought interchangeable status for AVT02, and Boehringer Ingelheim has so far obtained interchangeable status for 

. Both Amgen and Pfizer are seeking interchangeable status for Amjevita and Abrilada, respectively.

Three of the newer adalimumab biosimilar candidates will be high-concentration, citrate-free products: AVT02, CT-P17, and ABP-501 HC. Citrate is a buffer that controls pH, or stabilizes the drug, but it sometimes causes intense pain upon injection. The high-concentration, citrate-free formulation of Humira has enabled AbbVie to retain market share in Europe and could be a factor in the success or failure of biosimilar contenders in the United States.

Amgen’s Amjevita is a low-concentration, citrate-free formulation, and ABP-501 HC represents its bid for a share of the high-concentration market in the United States.

Cyltezo, Hulio, and Abrilada are also citrate-free products, and Hulio, Hadlima, and Abrilada are also latex free, according to Cardinal Health.

“Since first launching in the United States in 2003, Humira as a product has evolved in many ways, including new concentrations, citrate-free versions, latex-free delivery devices, and smaller needle gauges. Given the numerous product attributes that have arisen over the last 18 years, understanding what to anticipate from a product differentiation standpoint is a challenging task,” Cardinal Health wrote.

The list of potential adalimumab biosimilars has now lengthened to 10, according to a Cardinal Health summary of these products and their distinguishing features.  

Field of Potential Adalimumab Biosimilar Contenders Continues to Grow

First Case of Omicron Variant Found in United States

The United States recorded its first confirmed case of the Omicron COVID-19 variant, according to the 

. The carrier was a vaccinated traveler who returned to California following a trip to South Africa. The person experienced mild symptoms prior to testing positive and had not been vaccinated long enough to receive a booster dose of a COIVD-19 vaccine. Currently, scientists are still working establish whether the new mutant version of the virus that causes COVID-19 is more dangerous than previous ones. Anthony Fauci, MD, stated in a White House announcement that officials knew that it was only a matter of time before the first case of the Omicron variant would be found in the United States.

Supreme Court Signals Support for Abortion Limitations

, conservative judges on the Supreme Court indicated support for upholding a restrictive Mississippi abortion law that directly challenges the 1973 

 ruling. The court heard almost 2 hours of oral arguments in the Mississippi’s appeal to revive its ban on abortions starting at 15 weeks of pregnancy, which was blocked by lower courts. The Supreme Court currently has a 6 to 3 conservative majority, and the liberal justices sternly warned against ditching long-standing legal precedents like 

. Jackson Women’s Health Organization, the only abortion clinic in Mississippi, challenged the law and has support from the Biden administration. A ruling is expected by the end of June 2022.

Federal Judge Blocks Vaccine Mandates for Health Care Workers

, a federal judge issued a preliminary injunction to halt the start of President Joe Biden’s national vaccine mandate for health care workers, which was set to begin December 6. The injunction, drafted by Judge Terry A. Doughty, expanded a separate order issued by a federal court in Missouri, which had applied to only 10 states that joined in a lawsuit against the president’s decision to require health care workers in hospitals and nursing homes to be fully vaccinated by January 4. The judge wrote that a mandate that applied to 10.3 million health care workers should be issued by Congress rather than a government agency.

The first case of the Omicron COVID-19 variant has been detected in the United States; Supreme Court justices signal support for upholding Mississippi’s abortion law; a federal judge blocks the Biden administration’s vaccine mandate for health care workers.

What We’re Reading: Omicron Variant Detected in US; Supreme Court Signals Support for Abortion Restrictions; Federal Judge Blocks Vaccine Mandate

These findings arising from the EMPULSE trial show that patients with heart failure were decongested, because not only did N-terminal pro–brain natriuretic peptide levels decrease, but so did the clinical signs and symptoms of congestion. Patients actually got rid of fluid, Adriaan Voors, MD, professor of cardiology and director of the Heart Failure Clinic, University Medical Center Groningen, the Netherlands, said in an interview conducted prior to this year’s American Heart Association Scientific Sessions.

What about the mechanism of action of empagliflozin makes it especially beneficial to patients with acute heart failure?

That’s the most difficult question that you can pose to me. Nobody knows, because there's multiple mechanisms possibly related to the effects of empagliflozin. Like with so many other drugs that we've used before, we thought we knew how the drug worked, and after a few years, we learned more and we thought, “Oh, it’s a completely different mode of action.” Then, even if we know the mode of action of the drug, we still don't know whether that has caused the beneficial effects. Now, 

, it was particularly interesting to see that there was hemo concentration, there was a decrease in NT-proBNP [N-terminal pro–brain natriuretic peptide], there was a decrease in clinical signs and symptoms of congestion, there was weight loss. All 4 point toward the same direction: that patients were actually decongested and got rid of fluid. So, the SGLT2 inhibitor might have contributed to the effect, but you hear my careful wording, because we cannot be sure.

Videos

Adriaan Voors, MD, discusses possible mechanisms of action of empagliflozin that produce such beneficial results among patients with heart failure, in an interview about the EMPULSE trial prior to this year’s American Heart Association Scientific Sessions.

Dr Adriaan Voors Explains Potential Decongestive Benefits of Empagliflozin

Shared insight on the differences between ACG and IDSA/SHEA treatment guidelines for patients with clostridium difficile infection. 

Treatment Guidelines and Recommendations for C. Diff Infection

 To understand the investments that Medicare Shared Savings Program accountable care organizations (ACOs) in the ACO Investment Model (AIM) made to participate in the program and the costs that they incurred as a result of their efforts to lower spending and improve quality.

 We conducted a systematic review and categorization of all available and approved quarterly expenses reported by AIM ACOs.

We reviewed final approved quarterly expense reports submitted by ACOs detailing how they spent funds in the quarter. All distinct line-item descriptions were classified into a more informative and consistent set of categories. We then applied higher conceptual dimensions (type of care input and type of ACO strategy) to these newly categorized expenses to facilitate additional analysis of spending patterns.

AIM ACOs reported expenses of $264.8 million over the 3 performance years (2016-2018). The majority of the $264.8 million in expenditures was incurred for personnel (55.5%), followed by infrastructure (22.3%), management firm expenses (15.3%), and internal programs and systems (6.9%). The dominant identifiable ACO strategy was care coordination and management, accounting for 52.9% of related ACO expenses.

AIM ACOs invested most heavily in personnel, information technology, and care management, with less than half of the investments explicitly tied to a strategy for improving quality or reducing spending. Efforts to change clinician practice patterns, alter the way patients access the health care system, and institute other practice redesigns were not primary targets for investment.

We conducted a systematic review and categorization of all available and approved quarterly expenses reported by accountable care organizations (ACOs) participating in Medicare’s ACO Investment Model to better understand how participants in the model invested to achieve program goals.

Knowing how ACOs are allocating resources to achieve the goals of reducing spending and improving quality is critical to understanding the costs of these efforts, what strategies ACOs are pursuing, and in turn how future models can be designed to better facilitate these goals.

Understanding what ACOs do when provided financial assistance can help policy makers understand how investments can best facilitate the expansion of value-based care into areas with lower levels of participation.

With an understanding of where ACOs are investing, we are better able to understand how to replicate successes or target interventions if outcomes no longer align with expectations.

The Medicare Shared Savings Program (MSSP), one of the most prominent value-based payment models, has shown modest savings while improving performance on some quality measures.

 However, little is known about the investments that accountable care organizations (ACOs) make to participate in the MSSP or the costs that they incur as a result of their efforts to lower spending and improve quality. Understanding the key investments and strategies that support program participation and facilitate desired outcomes is imperative for both providers and policy makers.

In 2015, CMS developed the ACO Investment Model (AIM)

 to encourage the formation of MSSP ACOs in rural and underserved areas by providing up-front and ongoing payments to participating ACOs, which ACOs paid back to CMS through any earned shared savings. Here, we analyze CMS-required expense report data submitted by AIM ACOs to understand where and how they chose to invest: the types of expenses reported, the broad areas that ACOs chose to prioritize with investments, and the specific strategies in which ACOs invested.

Final approved quarterly expense reports consisted of ACO-reported line-item expenses in 6 broad CMS-defined categories: clinical staff, nonclinical staff, contracted labor, information technology (IT) (software and hardware), education and training, and other. We analyzed expense reports from quarter 3 of 2015 through quarter 4 of 2018 for 45 AIM ACOs. Note that CMS considered augmenting provider salaries, providing bonuses to executives or administrators, and purchasing imaging equipment as unacceptable uses of CMS funding.

We reviewed the line-item expenses and classified them into a more informative and consistent set of categories: access to care, accounting systems, administrative staff/support, behavioral health, benefits, boards/committees, care coordinators/management, compliance, data analytics, data security, electronic health records (EHRs)/health information exchange (HIE), executive staff, financial management, insurance related to ACO operations, IT hardware, IT staff, legal, licensing and credentialing, management staff, management/consulting fees, marketing, memberships, and other.

We then distinguished the recategorized expenses along 2 conceptual dimensions: (1) type of care input and (2) type of ACO strategy. The type of care input domain includes all expenses, which are categorized into personnel, infrastructure, internal programs/systems, and management firm expenses. Type of ACO strategy includes only those expenses related to lowering spending or improving quality: care coordination and management, patient access, patient education, practice redesign, and provider coaching/education. The categories within each dimension are mutually exclusive.

We subcategorized personnel spending as either internal or external, with external personnel defined as expenses that the ACO categorized as contracted labor or described as consulting or a management firm in the expense description.

Three individuals independently reviewed the expense categorizations, with 0.06% of expenses needing reconciliation.

AIM ACOs reported expenses of $264.8 million over the 3 performance years: $92.9 million (35%) in CMS-provided funds and $172 million (65%) in ACO-provided funds. Almost 25% of total spending was on care coordinators or other care management, followed by investments in EHRs and HIE at 18.1%, and management staff at 14.3%. The remaining 27 categories each represented less than 10% of spending and accounted for the remaining 43.3% of spending. ACOs focused CMS-provided funds more on administrative items (eg, organization memberships and staff recruiting) and infrastructure (eg, data security), each of which was fully attributed to CMS-provided funds. Consulting fees, patient education programs, and expanding access to care largely used ACOs’ internal funds.

We also identified expenses related to fulfilling the participation requirements of the MSSP. This accounted for $9 million, or 3.4%, of total reported spending. These expenses include quality reporting (eg, fielding the required beneficiary survey, reporting quality measures), compliance activities, application renewals, legal fees, licensing and credentialing, and financial activities such as obtaining the required letter of credit. Almost 79.7% ($7.2 million) of participation-related expenditures used CMS-provided funds.

Looking at expenses by type of care input (

), most of the $264.8 million in expenditures were incurred for personnel (55.5%), followed by infrastructure (22.3%), management firm expenses (15.3%), and internal programs and systems (6.9%). As described in the Methods section earlier, we were able to identify which personnel were reported as internal to the ACO and which were reported as external, finding that almost all personnel spending was for internal personnel (93.5%). As such, spending for external personnel was likely captured under “management firm services.”

Approximately half of the total expenditures (49.2%; $130.2 million) were related to strategies aimed at reducing costs or increasing quality (type of ACO strategy). We report these results in 

. The dominant identifiable strategy was care coordination and management, accounting for 52.9% of related ACO expenses. This strategy largely used CMS-provided funds, unlike the remaining strategies, which were largely ACO funded. Non–care coordination strategies ranged from 4.2% of related spending (patient access) to 20.7% (practice redesign).

How exactly ACOs allocate resources in response to program incentives has been largely unknown. In terms of care inputs, we found the largest investments in personnel, followed by infrastructure investments, which were dominated by IT expenses. Almost one-sixth of expenses were allocated toward management firms’ expenses; this is consistent with many AIM ACOs having relied on management companies to get started.

 Our personnel investment findings are consistent with other observations that cost-containment efforts have been associated with health care employment growth, which has been associated with spending growth.

Of ACO spending tied to strategies for lowering spending and improving quality, more than half was allocated to care coordination and management programs, which is consistent with the high level of spending on personnel. Care coordination and management can connote many types of activities. To the extent that these programs engage in direct utilization management (eg, steering patients away from emergency departments, shortening skilled nursing facility stays), they may achieve savings. Other care coordination activities aim to improve patient outcomes by meeting medical and social needs, ensuring preventive care, and improving provider communication. Although they are ostensibly good for patients, popular belief is that these aspects of care coordination and management programs are also the key to savings, particularly for high-risk patients. However, this belief may not be conceptually sound

 and is not consistent with the totality of the empirical evidence.

 Research on the MSSP specifically suggests that although care management programs may improve care experiences,

 they have not been associated with improved outcomes for complex patients,

 and savings have not been driven by reductions in admissions for ambulatory care–sensitive conditions or concentrated among high-risk groups.

 Although we could not distinguish between spending on utilization management vs prevention-oriented activities, it is notable that care coordination and management programs were the focus of such a high proportion of ACO funds despite weak evidence for savings from many of the strategies employed by these labor-intensive programs.

In contrast, ACOs invested only a quarter of funds in strategies with a higher proportion of fixed to variable costs—those whose effects on spending and quality were likely to persist over the long term rather than temporarily (eg, subsiding when a case manager’s efforts cease). These strategies, which included retraining providers to change their practice patterns, altering the way patients access the health care system, and redesigning practices, received no more than 20% of total ACO spending. When looking at total reported ACO expenditures in terms of care inputs, internal programs and systems that encompass these strategies accounted for less than 10% of total reported spending.

Whether funds were indicated as CMS provided or ACO provided was largely at the discretion of the ACO. However, we can infer that activities that largely used CMS-provided funds align with what the ACOs believed CMS was incentivizing. Through this lens, care coordination and management received the most CMS-provided investment of all strategic activities at 40%.

In contrast, 76% of provider education, almost 90% of patient access and practice redesign, and 97% of patient education activities were internally funded by the ACO. This makes sense given that CMS itself defines MSSP ACOs specifically in terms of care coordination, rather than waste reduction or practice transformation.

 The temporary nature of CMS funding gave ACOs a choice between allocating AIM funds to trial the effectiveness of personnel-heavy care management strategies vs one-time investments in infrastructure, retraining, or practice redesign.

The reported expenditures may over- or understate actual ACO spending on AIM-related activities, as ACOs reported only internal funds that supplemented CMS funds. Further, CMS funds and ACO funds were fungible, so our distinctions may not be accurate.

Additionally, AIM ACO spending patterns may not represent the spending of ACOs generally. Lastly, we do not know to what extent fee-for-service profits among AIM participants changed because of AIM participation, so we cannot determine the financial impact of participation on the participating providers.

To date, absent high-level findings in CMS-funded evaluation reports,

 little is known about the financial investments that participants make to become an ACO and maintain that status. Our findings confirm that substantial investments are needed to participate in an ACO and that providing initial funding helps underresourced ACOs overcome those participation barriers.

A better understanding of where ACOs prioritize investments can inform what makes a given ACO successful or not, illuminate how policy makers might encourage those best practices, and help policy makers determine whether to set clearer expectations for how ACOs manage their patient populations when provided up-front funding. Is care coordination and management enough, or should these models encourage participants to implement approaches that more fundamentally alter the way health care is delivered and consumed? Given that the former is more costly to implement and maintain, a greater emphasis on the latter may yield a greater return on investment for both CMS and participating ACOs—particularly given the dearth of evidence that current care management programs result in reduced costs.

The authors would like thank David Nyweide, PhD; Sasha Brodsky, PhD; Kimberly Groover, PhD; Ariana Bengtsson, MPP; and Johanne Germain, MHS, for supporting this work.

 Abt Associates (CH, BF, MJT, LS), Cambridge, MA; Harvard Medical School (JMM), Boston, MA.

 This work was funded by CMS under contract HHSM50020140026I; task order No. HHSM500T0004.

 Ms Hersey, Dr Fout, Dr Trombley, and Dr Scarpati report receiving funding from CMS under contract HHSM50020140026I; task order No. HHSM500T0004. Dr Scarpati was an employee of Abt Associates at the time this article was submitted. Dr McWilliams is an unpaid member of the board of directors for the Institute for Accountable Care and a consultant to Abt Associates.

 Concept and design (CH, JMM, BF); acquisition of data (BF); analysis and interpretation of data (CH, JMM, BF, MJT, LS); drafting of the manuscript (CH, JMM, BF, MJT, LS); critical revision of the manuscript for important intellectual content (JMM, BF, MJT, LS); statistical analysis (BF); obtaining funding (BF); administrative, technical, or logistic support (BF); and supervision (BF).

 Catherine Hersey, MPH, Abt Associates, 10 Fawcett St, Cambridge, MA 02138. Email: Catherine_hersey@abtassoc.com.

1. Trombley MJ, Fout BT, Brodsky S, McWilliams JM, Nywiede DJ, Morefield B. Early effects of an accountable care organization model for underserved areas. 

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2. McWilliams JM, Hatfield LA, Landon BE. Hamed P, Chernew ME. Medicare spending after 3 years of the Medicare Shared Savings Program. 

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3. ACO Investment Model. CMS. Accessed July 29, 2020. https://innovation.cms.gov/innovation-models/aco-investment-model

4. Evaluation of the Accountable Care Organization Investment Model: AIM implementation and impacts over two performance years. Center for Medicare and Medicaid Innovation. September 2019. Accessed November 4, 2021. https://innovation.cms.gov/aim-second-annrpt.pdf

5. Skinner J, Chandra A. Health care employment growth and the future of US cost containment. 

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6. McWilliams JM. Cost containment and the tale of care coordination. 

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7. McWilliams JM, Schwartz AL. Focusing on high-cost patients — the key to addressing high costs? 

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8. Finkelstein A, Zhou A, Taubman S, Doyle J. Health care hotspotting — a randomized, controlled trial. 

. 2020;382(2):152-162. doi:10.1056/nejmsa1906848

9. Peikes D, Chen A, Schore J, Brown R. Effects of care coordination on hospitalization, quality of care, and health care expenditures among Medicare beneficiaries. 

. 2009;301(6):603-618. doi:10.1001/jama.2009.126

10. McWilliams JM, Landon BE, Chernew ME, Zaslavsky AM. Changes in patients’ experiences in Medicare accountable care organizations. 

. 2014;371(18):1715-1724. doi:10.1056/nejmsa1406552

11. Ouayogodé MH, Mainor AJ, Meara E, Bynum JPW, Colla CH. Association between care management and outcomes among patients with complex needs in Medicare accountable care organizations. 

. 2019;2(7):e196939. doi:10.1001/jamanetworkopen.2019.6939

12. McWilliams JM, Chernew ME, Landon BE. Medicare ACO program savings not tied to preventable hospitalizations or concentrated among high-risk patients. 

. 2017;36(12):2085-2093. doi:10.1377/hlthaff.2017.0814

13. Shared Savings Program: about the program. CMS. Accessed July 29, 2020. https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/sharedsavingsprogram/about

14. Evaluation of CMMI accountable care organization initiatives: advance payment ACO final report. Center for Medicare and Medicaid Innovation. November 25, 2016. Accessed November 4, 2021. https://innovation.cms.gov/files/reports/advpayaco-fnevalrpt.pdf

The authors of this study examined expense reports to understand how participants in Medicare’s Accountable Care Organization Investment Model spent to achieve program goals.

An Analysis of Medicare Accountable Care Organization Expense Reports

A nomogram tool utilizing 5 predictors was discovered to be a simple and reliable means for the stratification of 

 (CKD) risk among high risk populations, according to a recent analysis of patients with a high risk of cardiovascular disease.

, the investigators claimed that the tool could enable physicians to identify individuals at a high risk of developing CKD so that they can implement precise prevention strategies earlier.

“Using the demographic, clinical and laboratory variables from electronic health records, our visualised nomogram with only five variables…demonstrated good discriminative power, which enables us to identify patients at high risk of incident CKD readily,” wrote the investigators.

CKD is challenging to treat as its often asymptomatic and diagnosed late. Along with hypertension and 

, CKD has been identified as an independent risk factor for cardiovascular disease (CVD) and all-cause mortality. Populations at high risk of CVD often take medicines for multiple comorbidities, such as blood pressure medications, antidiabetic drugs, antithrombotic agents, which can increase burden on the kidneys.

Risk prediction tools to identify individual risks for incident CKD could improve primary care for CKD. However, the primary health care system in China is often faced with not enough medical personnel, insufficient government funding, and high intensity work, suggesting that use of conventional data in the medical system in addition to improving chronic disease management methods are needed to build a CKD risk prediction model.

“The ability to identify the individuals at risk of incident CKD may decrease the incidence of CVD….For these persons, early identify the high-risk CKD individuals is of great significance to guide prevention and treatment,” noted the investigators.

The participants for the study were recruited from the National Basic Public Health Service Project of Guangzhou, China between January 2015 and December 2020. To participate, the patients had to be aged 65 years or older or at least 35 years old if they had diabetes or hypertension. The current analysis included patients with a 5-year cardiovascular risk score of 20% or greater.

In total, 5730 patients with a high CVD risk were categorized into the development cohort (n = 3820) and the validation cohort (n = 1910). The mean (SD) age of the entire cohort was 68.64 (6.49) years and the median eGFR was 92.95 mL/min/1.732.

Among the patients in the development cohort, those who developed CKD were often older, had a higher body mass index (BMI), and had a bigger waistline compared with those who were CKD-free. During laboratory examinations, patients who developed CKD had lower glomerular filtration rate (eGFR) and blood platelet counts as well as higher uric acid and triglyceride contents compared with patients who were CKD-free. Patients who developed CKD during the follow-up period were also more likely to have hypertension and diabetes and less likely to be smokers or drinkers.

During the median follow-up period of 4.22 years, incident CKD was present in 19.09% (n = 1094) of the entire, including 19.03% (n = 727) of the development cohort and 19.21% (n = 367) of the validation cohort. Death occurred in 23 (0.4%) patients during the follow-up period, of whom 7 died after developing CKD and 16 died without developing CKD.

Through a multivariable COX regression analysis and a backward stepwise approach age (HR, 1.07; 95% CI, 1.06-1.08), BMI (HR, 1.04; 95% CI, 1.02-1.06), an eGFR between 60-89 mL/min/1.732 (HR, 5.59; 95% CI, 4.70-6.65), diabetes (HR, 1.63; 95% CI, 1.38-1.91), and hypertension (HR, 1.40; 95% CI, 1.13-1.75) were selected as predictor of incident CKD.

In both groups, the nomogram developed by the investigators demonstrated a good discriminative power with C-index of 0.778 in the development cohort and 0.785 in the validation cohort. The areas under the curve (AUC) in the development cohort at 3 years, 4 years, and 5 years were 0.817, 0.814, and 0.834, respectively. The AUCs in the validation cohort was 0.830, 0.847, and 0.839 at 3 years, 4 years, and 5 years, respectively. The nomogram also showed to be able to distinguish patients at a high risk of CKD from those with a low risk at 3 years, 4 years, and 5 years.

The investigators noted the lack of albuminuria data for a majority of patients and concerns about the definition used for their eGFR endpoint as study limitations. Additionally, there was no external validation of the investigators’ model.

“More studies focusing on the clinical meaning of different decline of eGFR are in need,” they wrote.

Zhang Q, Zhang J, Lei L, et al. Nomogram to predict risk of incident chronic kidney disease in high-risk population of cardiovascular disease in China: community-based cohort study. 

. Published online November 12, 2021. Accessed December 1, 2021. doi:10.1136/bmjopen-2020-047774

A tool utilizing 5 predictors was found to be reliable at identifying patients at a high risk of cardiovascular disease who were also at risk of developing chronic kidney disease (CKD), potentially allowing providers to implement prevention strategies sooner than ever before.

Nomogram Tool Can Predict Risk of CKD in Patients at High Risk of Developing Cardiovascular Disease

 who are overweight and obese are significantly more likely to have bronchial obstruction compared with children of normal or low body weight, according to a new study.

The study is based on a comparison of spirometric measures with body mass indicators. The results were 

Investigators, including corresponding author Tatyana I. Eliseeva, MD, DSc, of the Privolzhsky Research Medical University in Russia, wrote that from a scientific standpoint it is believed that all patients with bronchial asthma could successfully control their disease. However, as many as half of patients with the disease do not have their asthma under control, largely due to comorbid conditions such as obesity and being overweight.

Solving the problem is difficult, though, since there is conflicting data regarding how excess weight affects spirometry readings, the authors said. One reason for the conflicting data, they posited, could be the imprecision of using body mass index (BMI) as a stand-in for weight in pediatric patients.

“The same BMI values may correspond to different types of nutritional status in children of different ages and genders,” the authors wrote. “For example, a BMI of 17.0 in a boy of 11 years 1 month with average physical development (143 cm) will correspond to the median, a girl of 5 years 1 month (height 110 cm)—overweight (+1 Z-score [Z]), and a girl of 17 years (height 163 cm)—protein-energy deficiency (–2Z).”

Eliseeva and colleagues decided to supplement BMI by using a relative BMI (RBMI), which uses a ratio of the patient’s BMI to the average BMI for children with the same age and gender.

The investigators recruited 54 patients with bronchial asthma between the ages of 8 to 17 years old. Most of the patients (33) were boys. The patients had a range of nutritional statuses based on BMI Z-scores: 5 had low body weight, 18 had normal body weight, 17 were considered overweight, and 14 were considered obese.

The patients were evaluated using a number of spirogram parameters, including forced vital capacity (FVC), forced expiratory volume in 1 second (FEV1), FEV1/FVC ratio, and maximum expiratory flow at the point of 25% loop flow-volume (MEF 25).

An analysis of the readings showed that as body weight increased, FEV1/FVC ratio and MEF 25 both decreased. Notably, those findings held true not only for BMI, but also when evaluated against other measures of weight, including RBMI and percentage of body fat.

“It is obvious that there may be various pathogenetic mechanisms of the influence of obesity on the physiology of the lungs, including, inter alia, an imbalance of pro- and anti-inflammatory cytokines,” they wrote.

For instance, they said, adipokines have been linked with bronchial inflammation and hyperreactivity.

Yet, they added that it is also possible the reverse is true: that asthma leads to nutritional changes.

“And this is due not only to changes in the level of physical activity in connection with the disease and the reception of exogenous glucocorticoids, but also with the possibility of local synthesis of alpha-melanocyte stimulating hormone, respectively, and its predecessor-adrenocorticotropic hormone,” they wrote.

Overall, the authors said the potential causal links remain a topic of open scientific question. They said deeper research is needed to understand practical issues such as how to diagnose, treat, and effectively control children with bronchial asthma who are obese.

“An increase in BMI, an indirect indicator of obesity, is a predictor of worsening bronchial patency in patients with [bronchial asthma] regardless of the sex of the child,” they concluded.

Khramova RN, Tush EV, Khramov AA, et al. Relationship of nutritional status and spirometric parameters in children with bronchial asthma. 

The trend was true when investigators used body mass index to classify weight, and when measures such as relative body mass index and percentage of body fat were used.