The 2024 Physician Fee Schedule Final Rule—all 2,709 pages worth—was released on November 3, and the significance of the “Post-COVID” rule cannot be understated. With the Public Health Emergency expiring earlier this year, these finalized policies are intended to get the proverbial train back on its tracks, following the massive derailment in March 2020.

Although many policies were finalized as proposed, there are plenty of exceptions and caveats, and providers and practices need to be keenly aware of the details. CMS is using this rule to advance its value-based care goals through data aggregation and attention to health equity. Those who simply stay the course will find unwelcome surprises in their reimbursements, referrals, and market presence.

The flip side of that coin is that this Rule creates opportunity for providers to transform healthcare on their own terms, rather than simply following rules handed down from public and private health plans. Organizations and providers should consider five key themes in this Rule as they develop and refine their value-based care strategies for 2024 and beyond.

1. The Traditional MIPS Pot is Near the Boiling Point – Hop Out Now!

CMS continues to trumpet its goal of having all Medicare patients in an accountable care relationship with a provider responsible for Total Cost of Care by 2030. Traditional MIPS is a barrier to that goal, and policies within this Rule are intended to move providers out of that system in advance of a to-be-determined Traditional MIPS sunset date.

The strategy is two-fold: The first is to broaden the MIPS Value Pathway (MVP) library, facilitating greater participation among MIPS-eligible clinicians. The second is to add challenges to Traditional MIPS, making it a less attractive option.

MIPS Value Pathways (MVPs) are intended to streamline MIPS by limiting providers to more specific and relevant sets of quality and cost measures. This will facilitate more meaningful comparisons between providers than Traditional MIPS, as providers—especially specialists—can “fly below the radar,” being scored on measures reported by others in the practice. For 2024, CMS has finalized five new MVPs, which brings the total to 16:

• Focusing on Women’s Health
• Prevention and Treatment Infectious Disorders Including Hepatitis C and HIV
• Quality Care in Mental Health and Substance Use Disorders
• Quality Care for Treatment of Ear, Nose and Throat (ENT) Disorders
• Rehabilitative Support for Musculoskeletal Care

On the Traditional MIPS front, the biggest challenge will be the raised data completion threshold for quality measures. In 2024, for a quality measure to be scored, there must be a response for at least 75 percent of the eligible denominator, up from 70 percent over the last several years. It sounds like a very small adjustment, but for some measures, this can mean hundreds, or even thousands of additional responses.

In addition to reporting on more patients, the annual process of quality measure deletions, additions, and substantial changes make it impossible to devise a reporting strategy that lasts longer than one year. The measure benchmarks are still to be determined, as well, meaning that even if you do have measures that work in both 2023 and 2024, there is no guarantee that a score earning top marks in 2023 will do so in 2024, even if your performance is consistent.

2. Advancing Health Equity

Health Equity policies are primarily found in the Accountable Care Organization (ACO) section of the Rule, as CMS believes that one of the most critical strategies for advancing health equity is to ensure that all patients are in accountable care relationships.

This is also a multi-pronged strategy, utilizing updates to cost-benchmarking methodology, Advanced Incentive Payments, changes to the attribution model, and incentivization of all patient reporting.

To the delight of ACOs, the regional benchmark adjustments were finalized as proposed. HCC risk growth on the ACO’s Service Area is capped between PY1 and PY3, independently of the ACO. This means that the regional component of the ACO’s benchmark is increased when the ACOs serve areas with prospective HCC scores above the cap. The result is that ACOs can thrive in regions with proportionately more high-risk beneficiaries, which will encourage the formation of new ACOs and the expansion of existing ACOs.

Updates to the Advanced Incentive Payment (AIP) structure is also intended to drive ACO participation and link more patients to accountable care relationships. Previously, ACOs could only be in a one-sided arrangement for the duration of the agreement if receiving AIPs. Those who understood how they could generate significant savings (in excess of AIP revenue) were barred from doing so, unless they were willing to immediately repay these AIPs to CMS. This Rule allows AIP recipients to take on risk in their third year. These ACOs will still have to pay the AIPs back through subsequent earnings of shared savings, but that’s less jarring than an immediate recoupment, and they can still come out ahead. The slower payback period and opportunity for additional upside revenue is sure to entice new entrants.

ACO attribution is also used to advance health equity. The Rule finalizes (as proposed) attribution changes that account for the role NPs, PAs, and CNSs play in primary care delivery. This will also increase the number of underserved beneficiaries who would be able to receive care through an ACO. In prior years, these patients would have been excluded, and it is anticipated that the incorporation of these patients will generate a 1.3 percent increase in beneficiaries attributed to ACOs. Although this will not take effect until 2025, ACOs should plan now for changes to their patient mix.

Quality reporting changes are also tied to advancing health equity. ACOs who adopt APM Performance Pathway (APP) Reporting, regardless of whether using Electronic Clinical Quality Measures (eCQMs), MIPS CQMs or Medicare CQMs, are eligible to earn additional points to their quality scores through a Health Equity Adjustment. Furthermore, to account for the breadth of the eligible population, performance standards are relaxed— an ACO that achieves the tenth performance percentile in one of the APP outcome measures can still earn shared savings.

3. Bringing Specialty Providers into Value-Based Care Efforts

When looking at Total Cost of Care, the focus is understandably on the primary care providers who are managing their patients’ care. While data-driven strategies can help you identify which providers have historically superior outcomes in acute and procedural episodes, the specialist role has not been as visible, particularly in ACOs comprised of large, multi-specialty practices. In the APP, for example, quality reporting consists of three measures, all of which are driven by primary care.

To highlight specialty care in ACOs, CMS floated a potential quality bonus for specialists within an ACO who also report MIPS Value Pathways. The goal would be to enable both patients and ACO participants to compare specialty care outcomes at a more granular level than is feasible now. There were no specifics in the Proposed Rule to finalize here, but CMS did use this Rule to solicit specific feedback on implementation, payment adjustments, and more. ACOs looking to stay ahead of the curve should take note!

For specialists participating in MIPS, CMS has added five specialty-specific cost measures. In MIPS, unless a provider has a minimum case number of patients meeting a cost measure (it varies by measure), the measure cannot be scored. The provider’s cost score becomes dependent on a general cost measure, rather than a more specific and meaningful measure. These five new cost measures ensure that providers who treat depression, heart failure, low back pain, or psychoses, or who practice emergency medicine are assessed on more relevant criteria.

4. CMS Continues to Push Data Integration

The sunset of the CMS Web Interface for ACO quality reporting has catapulted data integration into the spotlight. Rather than reporting on a sample of 248 patients per measure, the APP looks at the total population across three measures. The relatively small Web Interface sample meant that ACOs could manually scour records and enter results. No more!

As we have described, there are too many patients for that process to work. Furthermore, because the measures must be reported at the unique patient level and include the most recent value, adding QRDA results between practices is not an acceptable option.

ACOs have pushed back against this, as there is a persistent myth that data aggregation is prohibitively expensive and time consuming. As a concession, CMS developed the Medicare CQM option for ACOs, allowing them to report on the three APP measures, but only for Medicare patients. The Final Rule even created a provision wherein the ACO will have access to their complete denominator, which was not available in the initial proposal.

Nevertheless, the need for data aggregation still exists. With ACOs treating tens (and sometimes hundreds) of thousands of Medicare patients, the sheer volume of patients precludes the manual chart-by-chart approach. Regardless of APP reporting method, ACOs with disparate EHRs will need a data aggregation solution to succeed in APP reporting and remain eligible for shared savings.

The Promoting Interoperability (PI) category, worth 25 percent of the total MIPS score, is also featured in the Rule. CMS finalized the policy that, rather than a 90-day minimum performance window, the PI performance period must last for a minimum of 180 consecutive days. The implications go beyond MIPS—with Advanced APMs and ACOs on the cusp of having to require 100 percent CEHRT participation amongst participants and report PI, those without CERHT who want to participate in an APM will have less time to implement CEHRT than previously thought.

5. One-Year Delays are for Transitions—Don’t Procrastinate!

Several proposals will not take effect in 2024 in order to give organizations the lead time they need to prepare.

The first is that the MIPS Performance Threshold will remain at 75 points, rather than being bumped up to 82. CMS was swayed by comments that many have been on a 3-year MIPS hiatus during the PHE, and even the existing 75-piont threshold is higher than it was in 2020. Forcing a reengagement in conjunction with an even higher performance standard all but doomed those coming back into the fold. It was also noted that there was a self-selecting group who continued to report during a time when Extreme and Uncontrollable Circumstance (EUC) exemptions were so easy to come by. This artificially inflates MIPS scores, and so a policy of looking at prior periods to determine a performance standard is inherently flawed.

For ACOs, there are also policy delays. One concerns the mandatory CERHT requirement for participants in Advanced APMs and ACOs. This will not take effect until 2025, putting it in sync with the elimination of the CMS Web Interface for Quality Reporting. The result is that ACOs have a one-year transition period before being put on a mandatory path to digital quality measurement.

The change to the patient attribution policy described previously will also be delayed for one year. Although CMS does not anticipate that incorporating care from NPs, CNSs, and PAs (rather than just physicians) will cause large-scale changes for ACOs, they are providing an extra year to account for unintended downstream effects.

The most notable consequence stems from CMS’s inability to distinguish whether NPs, PAs, and CNSs are providing primary care, or specialty care. Bringing them into the attribution methodology exacerbates a known issue in beneficiary assignment. Specialty practices with a high volume of non-physician practitioners have been hit particularly hard in total cost of care measures, as so many of their attributed beneficiaries with chronic conditions are not being managed by that practice, or are going to be high-cost based on the nature of the care they receive at the specialty practice (a PA at an oncology practice, for example).

Furthermore, since many of these patients are being seen for acute conditions, they will not be included in the ACO’s population in subsequent years, making it impossible for the ACO to develop effective care coordination strategies.

These policies are bound to cause some growing pains, and the best way to mitigate them is to being the process now. There will be unexpected challenges, and those who have addressed them in advance are poised to succeed at the expense of those who have not.

Founded in 2002, Roji Health Intelligence guides health care systems, providers and patients on the path to better health through Solutions that help providers improve their value and succeed in Risk.

Image: Ladd Green

As Value-Based Care expands, payers are emphasizing cost reduction all the more. Newer CMS payment models like ACO REACH reinforce cost control by capping reimbursement in total global payments to ACOs. In turn, global payments enable ACOs to directly negotiate rates with preferred provider specialists.

In addition to focusing on controlling costs delivered through primary care, your ACO should pursue strategies to stem total patient care costs (TCC) through specialty services. Between 40 to 60 percent of total patient care costs are driven by specialty physicians. While rate negotiations address the price of individual specialty services, the greater opportunities lie in addressing cost variation of services, outcomes that drive up utilization and cost, and avoidance of low-value services.

For specialists participating in your ACO panel and for your referral network, you have the opportunity to develop strategies that are win-win for both you and specialists. It just takes a collaborative attitude and data. These five tips show how:

1. Create a data sharing relationship that includes aggregation of patient data as part of your collaboration. Many specialty practices do not have this capability. They may depend on their EHRs to perform quality reporting, but the value of data goes well beyond these basics. Data will help specialists address other issues, such as cost variation and variable outcomes. The specialty group will want to keep some financial data private, but if you are already aggregating your participating provider EHR data and integrating claims, you can use the claims data to calculate costs for payers that provide it. The data is essential for the next step of identifying cost issues.
2. Create episodes of care for high-volume procedures and conditions to generate comparable patient events for examining cost variation and outcomes. Share the results with specialists and start the conversation about why the variation occurs and ways to mitigate. An analytics vendor capable of creating episodes with clinical elements to provide insights to how these have affected cost or quality will help your ACO and specialists. Eventually, your episodes may become part of an overall, results-based scheme to include specialists in your network.
3. Provide specialists with seamless access to the ACO Value-Based Care technology for viewing their patients’ comorbidities and relevant treatment plan/population health information. This provides an avenue for specialists to create strategies to help guide their own services to these patients and to prevent specialty treatment complications.
4. Help specialists succeed in quality reporting. MIPS or other quality scores can be one criterion for selecting specialists for your referral network. While not perfect, these scores can flag issues to discuss and ensure that there is an effort at consistent, evidence-based medicine within the practice. Furthermore, as specialists become eligible for MIPS Value Pathways (MVPs), CMS is asking ACOs to encourage MVPs among specialty physicians. By ensuring aggregation of specialty data and assistance with quality reporting services, you can make it more economical for the specialty group and more beneficial for you to enable their MVP reporting.
5. Involve specialists in ACO improvement programs. Your strategies for improving care and related costs are exponentially increased with the involvement of specialists and the use of episodes. By collegially designing pathways for chronic conditions that establish criteria for referrals, medications, and population health, you can engage specialists in success for your ACO—and for their own practices.

Download more Roji TIPS here.

Founded in 2002, Roji Health Intelligence guides health care systems, providers and patients on the path to better health through Solutions that help providers improve their value and succeed in Risk.

Image: Judi Neumeyer

If CMS’s new proposed option for APP Reporting becomes part of the Final Rule, ACOs will have the ability to limit quality reporting to Medicare patients only. Your ACO must now determine whether reporting Medicare-only patients saves work and money and best demonstrates your quality. Use these Roji TIPS to decide what approach will work for you.

Considerations for Choosing Medicare CQMs versus All-Patient Reporting

ACOs have resisted APP Reporting to avoid data aggregation from different physician EHRs. ACOs also want to limit their work to the core of Medicare patients included in the ACO. The following considerations are key to your decision about your APP Reporting approach:

Eligible Patients: Medicare CQMs still include 100 percent of eligible patients in the denominator of measures. If CMS provides a claims-based list of eligible patients after the performance year, that will amount to less than 100 percent. Why? Because the 3-month claims run-out period will exclude many fourth quarter services. CMS may try to fix this, but as it stands in the Proposed Rule, you may need to aggregate data to ensure inclusion of all Medicare patients.

Size of Your Patient Population: Volume of attributed patients determines if you can potentially avoid data aggregation to satisfy measure values. However, without aggregated data you must manually look up the latest value for each quality measure, for every patient and for each seen provider. That’s many lookups. You will need technology to track your measures, and cost is not zero.

Large Organizations or ACOs Aggregating Data: If you intend to aggregate data anyway because of your size, understand that the option to use Medicare CQM or All-Patient Reporting gives you the advantage of using your performance to make a good choice. Make Certain that your Qualified Registry or Qualified Clinical Data Registry will show both alternatives. Then choose to report your best scores publicly.

Three Tips to Make Your Quality Stand Out with Reporting

1. Prepare for the future of data aggregation, regardless of your APP Reporting method. Your ACO will ultimately need aggregated data to deploy data-driven tools to manage costs, outcomes, and health equity. You can also work with your practices to centralize them on fewer and more compatible EHRs.
2. For small ACOs using Medicare CQMs, invest in a system to store Medicare CQM data to track values by patients across practices. You need a method to withstand an audit and ensure that you are reporting the latest single value for your patients seeing multiple physicians. Choose a technology interface to store values by patient that optimizes both aggregated and input data. It’s also best if data is visible to practices so they can access and add to the measures. An authorized Registry should be able to do this for you.
3. For all ACOs aggregating data, track both Medicare and All-Patient Measures, and choose your APP Reporting approach when the Performance Year data is complete. CMS is putting greater emphasis on publicly reporting scores. Tracking all-patient quality is a key performance activity for your overall patient quality and will also contribute to your ability to successfully undertake private health plan contracting.

Download Roji TIPS here.

Founded in 2002, Roji Health Intelligence guides health care systems, providers and patients on the path to better health through Solutions that help providers improve their value and succeed in Risk.

Image: Natalia Trofimova

With the advent of APP Reporting, ACOs face a fundamental change in not only how they report quality measures, but also how they use data to drive results. That’s true whether APP Reporting involves reporting quality for all patients or for Medicare-only patients via Medicare CQMs.

Data is an asset that ACOs have never had. But data has the potential to influence all ACO functions and its success. Rather than depending on past admissions and ER utilization to retrospectively contact patients, ACOs that initially aggregate data will be able to use it to proactively identify patients who need more specific help. From development of high-risk patient registries to managing the cost of care for specific patient cohorts, your ACO is about to learn how data can be your most effective resource for changing the future of health care.

If that’s the dream, how does your ACO get there? ACOs are struggling right now to make sense of APP Reporting requirements and how to make the process easier and efficient. However, the landscape for APP Reporting implementation has traps that are easy to fall into. We are seeing ACOs complicate their process because of lack of familiarity with all-patient reporting (like MIPS and the APP) and with data sourcing.

That’s why we’re developing a series of tips for ACOs about key steps in APP implementation. Beginning with how to organize your effort, we’ll cover all the details of your APP implementation process, sharing the knowledge from our years of experience in data aggregation and CMS Quality Reporting. Each Roji TIPS sheet will be a quick read that highlights a particular point in the implementation process or a decision you must make. We are providing these as free downloadable resources for sharing among ACO leadership and administrators.

Will Your ACO Need to Aggregate Data?

Let’s say you’ve already decided to report via Medicare CQMs. Will you need to aggregate data to do this? While the 2024 Proposed Rule states that CMS will provide patients meeting eligibility for measures based on claims data, it doesn’t state how it will address the three-month claims run-out period after the end of the year. Patients will continue to become eligible as a result of those visits, so unless this gap is clarified by CMS guidance, it may still be necessary to aggregate data to identify eligible patients.

After that step, ACOs will need to populate measure numerators, which will not be in CMS claims. Despite CMS’s proposed alternative to limit reporting to Medicare patients, a larger practice could have thousands of patients meeting eligibility, an impractical amount for culling medical records for measure values. The more practical— and lower cost—approach is to aggregate the data to fulfill the measures.

Introducing Your First Roji TIPS Sheet: Five Tips to Organize Your APP Reporting for Lowest Cost

Is your ACO ready to kickoff APP Reporting with data aggregation? Then you already know that your first step will be to aggregate patient data from physician systems. Data collection know-how, security, storage needs, and patient matching requirements will likely lead you to acquire expertise to accomplish the task.

Many ACOs are searching for an APP Reporting vendor. This is new territory. We see ACOs struggling through the RFP bidding process. These are tips for ACOs to get top vendors and the best proposal.

The Best Proposal Depends on Confidence in Your Approach

Achieving lowest price and best vendor for APP reporting will largely depend on three factors:

• Assessment of the complexity and difficulty of data aggregation for your ACO.
• Responsibility for working with practices directly; and
• Flexibility in data formats to make it both do-able and cost-effective.

Note that none of these issues have to do with the reporting platform itself but, instead, with collecting data.

Five Actions to Get Best Proposal

Here’s what you need to do to address the factors that influence price:

1. Before the RFP, organize your practice and system information.
2. Identify an ACO intermediary to be central point of contact with practices.
3. Adopt a process to educate practices on all aspects of APP Reporting, from data collection to quality performance requirements.
4. Be flexible with data sources to achieve quick progress.
5. Get the best value for your data.

To get more details on these action steps, download your free Roji TIPS sheet HERE.

About Roji Health Intelligence and APP Reporting

As you undertake this journey, contact Roji Health Intelligence to be your guide for APP Reporting implementation:

• We have 21 years in aggregating data from a variety of EHRs and other systems, and integrating other sources of data, using a variety of formats.
• Roji Heath Intelligence has ONC-Certified technology for reporting eCQMs. We also report MIPS CQMs, quality measures to health plans.
• Roji Health Intelligence is a CMS-qualified Registry for MIPS Reporting and will be performing APP Reporting.
• In addition to quality reporting, Roji provides other services for cost and quality performance improvements. Our most advanced services and analytics are Roji Episodes, which use condition- and procedure-based Episodes of Care to fuel population health, clinical interventions for patients, and cost improvement programs.

Founded in 2002, Roji Health Intelligence guides health care systems, providers and patients on the path to better health through Solutions that help providers improve their value and succeed in Risk.

Reading between the many lines in the 1,920-page 2024 Medicare Physician Fee Schedule (PFS) Proposed Rule, one thing is clear: CMS is still struggling to move providers into Advanced Alternate Payment Models (APMs) and keep existing ACOs moving forward on the path to value-based payments. The APP Reporting tug-of-war between CMS and ACOs results in a slight concession for providers worried about difficulty and cost of all-patient APP Reporting.

We’ve seen this before, of course. Remember the delay in sunsetting the Web Interface for ACOs in the 2022 Rule and the retreat from mandatory transition to risk in the 2023 Rule? This year is no different.

The concession in the 2024 Proposed Rule is a new data submission type for ACOs: Medicare Clinical Quality Measures (Medicare CQMs). These measures will allow ACOs to report via the APP, but in a manner that only includes Medicare patients. While a seeming departure from previous APP guidance, Medicare CQMs are less of an about-face than they initially seem. As we know, the devil is in the details, and Medicare CQMs are just one of the seven key components in this Proposed Rule that walk the line between participation goals and value.

Click here for a one page summary of the Proposed Rule.

1. Medicare Clinical Quality Measures: A Superficial Concession—Read the Fine Print!

Medicare Clinical Quality Measures are the headliner of this year’s Proposed Rule. Even though it is in your ACO’s best interest to aggregate the entirety of your practices’ data, the ACO community has steadfastly opposed all-patient reporting via the Alternate Payment Model Performance Pathway, or APP.

As a compromise, CMS has introduced the concept of the Medicare Clinical Quality Measures. At first pass, this data submission type seems like a complete reversal. But watch out! Even if you choose to report Medicare CQMs, your ACO will still need an APP strategy built on data aggregation. Here’s why:

Medicare CQMs are the same measures as those in the existing APP, with one critical difference. Despite the language in the 2021 CMS Innovation Center’s Strategic Refresh advocating for increasing beneficiary participation—including non-Medicare Fee For Service (FFS) Patients—Medicare CQMs will only encompass Medicare FFS patients, and only those who have encounters with the types of providers driving patient alignment to the ACO (i.e. a primary care provider) and who had a claim during the measurement period. This second condition is meant to prevent measure eligibility when a specialist triggers the measure, but where the ACO doesn’t have a primary care relationship with the patient. As an additional concession to ACOs, CMS indicates that it will share a list of the eligible patients at the beginning of the submission period.

The use of claims data might seem to be sufficient to provide all the denominator data (eligible patients) required for APP Reporting. You might think you could delay aggregating provider data indefinitely. But here’s where the fine print kicks in. The list that CMS provides will most likely be incomplete. Further, except for very small ACOs, it will still be too large for manual data collection of quality measure values for those eligible patients.

There is a run-out period on Medicare claims, so a denominator list on patients at the beginning of the submission period (January 1, 2025) will not include all patients meeting denominator criteria in 2024. The Proposed Rule explicitly states that ACOs will still be on the hook for some of their own denominator identification.

Those who only report back on the list of patients they receive are showing their cards, admitting that they have not reported on the complete 12-month performance period. While the data completion threshold is 75 percent, it cannot be used to circumvent reporting on a complete denominator. In other words, yes, it’s mathematically probable that if you report on 100 percent of patients from January through November, you will net 75 percent of the year, but that’s not how it works—that 75 percent data completion must be based on the entire eligibility period.

There is also the size of the list to consider. For all but the smallest ACOs, the list of denominator-eligible patients will still be too large to manually reconcile measure responses. Medicare CQMs may prevent you from having to report on potentially hundreds of thousands of patients—it can easily be tens of thousands—a far cry from the 248-patient sample of today. Without aggregating your practices’ EHRs, there simply will not be enough time to search each name from CMS’s denominator list, compare it to the claims file to see who recorded the most recent value, and then find and enter that value into a template that exports into a CMS-approved file type.

The bottom line: Even if reporting Medicare CQMs, your ACO will still need a plan for data collection, aggregation, and turnaround, with the experience to help you improve throughout the year.

2. Updates to Patient Attribution Methodology in ACOs Will Align More Patients with ACOs

This Proposed Rule reiterates CMS’s goal that all Medicare patients will be in a model that is accountable for quality and total cost of care by 2030. According to the proposal, one of the barriers to this goal is the pre-step requirement in the ACO patient attribution methodology, and the definition of an assignable beneficiary.

Specifically, the concern is that patients who receive primary care from Nurse Practitioners, Clinical Nurse Specialists, and Physician Assistants are not being attributed to ACOs, despite the fact that they are receiving primary care from an ACO’s clinicians. This issue is critical from a health equity standpoint. As these primary care delivery practices are more common in underserved communities, the current patient alignment protocols prevent—rather than promote—the delivery of equitable care.

To address this shortfall, CMS proposes adding a third step: beneficiaries who received at least one primary care service with a non-physician professional in the original 12-month window—and received a primary care service with a primary care physician in the ACO within a newly-proposed 24-month period—could be assigned to the ACO. CMS calculates that almost 3 percent of patients could be added to the total Attributable Beneficiary count, and would more accurately reflect the manner in which patients in different settings access primary care services.

3. Revised Regional Benchmarking Calculations Help ACOs Breathe Easier

Although there have been updates to benchmarking methodology intended to prevent the “ratcheting effect,” where ACOs are penalized for their own success, this Proposed Rule indicates that benchmarking is still a work in progress. To that end, a proposed update in benchmarking methodology would put a cap on the regional service area risk score between benchmark year 3 and the performance year, using an adjustment factor including the ACO’s market share.

For ACOs in areas where prospective Hierarchical Condition Category (HCC) scores are above the growth cap, this change would increase the regional component of the ACO’s update factor. Limiting risk score growth in both the ACO population and the ACO’s region is expected to provide a more accurate update factor, especially in the later years of the ACO’s agreement period. CMS anticipates that this would drive ACO participation in areas with a proportionately high number of at-risk beneficiaries, both by encouraging the formation of new ACOs, and decreasing the ACO attrition rate.

In conjunction with this Proposed Rule, CMS is offering to hold ACOs harmless in instances where the regional adjustment is negative. Those who may have received a downward adjustment are now relieved of that burden. Furthermore, those at risk of having savings payments cut via this adjustment are also exempted.

4. Additional Opportunities for Providers to Participate in MIPS Value Pathways (MVPs)—and Not Just in MIPS

MIPS Value Pathways continue their march toward an eventual “MIPS 2.0”, i.e. the end of Traditional MIPS. To bring more providers into the fold, CMS has proposed five new MVPs, centered around the following clinical areas:

• Women’s Health
• Infectious Disease (focused on Hepatitis C and HIV)
• Mental Health and Substance Use Disorder
• Quality Care for Ear, Nose, and Throat
• Rehabiliative Support for Musculoskeletal Care

MVPs also make a splash in the ACO section of the Proposed Rule. Because ACOs report quality measures tied to primary care, there is an absence of quality reporting for specialists within an ACO. In order to enhance the amount of performance data coming from specialty care, CMS has floated the idea of giving ACOs bonus points for specialists reporting MVPs. They are asking for comments on how else they can illuminate the role specialists play in ACOs.

5. MIPS Cost Component: More Measures, More Visibility

Even though the Cost and Quality components of MIPS have each counted for 30 percent of the total score, the feedback on Cost has been opaque. Data made available to providers through the QPP has been limited, and nothing is available for consumers. The Proposed Rule seeks to address this by—finally—reporting cost data on CMS’s Care Compare website.

Unfortunately, the detail that goes into these measure calculations (risk adjustment, specialty adjustment, regional adjustment, statistical outlier corrections) creates a dilemma. With so many factors in play, how can these results be displayed in a manner that is fair to providers and informative to consumers? The answer is “we aren’t sure,” and so CMS requests feedback on how this information should be displayed.

The Cost category is also expanding, adding five new proposed measures. None of the measures target a procedure; all focus on chronic or acute conditions. If at least 20 cases are triggered, providers can expect to see scores on the following Cost measures in 2024:

• Depression
• Emergency Medicine
• Heart Failure
• Low Back Pain
• Psychoses and Related Conditions

6. Continued Challenges for Traditional MIPS Participants

Once again, the Proposed Rule tightens the belt on Traditional MIPS while incentivizing participation in MIPS Value Pathways and other Alternate Payment Models, especially Accountable Care Organizations (ACOs). Although sunsetting Traditional MIPS was not proposed, there is a considerable effort to move providers into other methods of QPP participation.

As proposed, 2024 will be the most challenging year yet for Traditional MIPS participants. The performance threshold—the line between incentives and penalties—is going to increase from 75 to 82 out of 100 points. To put that in context, just a couple of years ago, 85 points put providers in the “Exceptional Performance” range, earning additional incentives. In 2024, that score barely constitutes a “pass.”

The high bar was expected. Over the last several years, PHE-related Extreme and Uncontrollable Circumstance exemptions were rubber-stamped by CMS, and many took this route in lieu of MIPS participation. Those who did report were a self-selecting group; they knew that their scores would be high enough to earn incentives, and unsurprisingly, MIPS scores were skewed. As required by statute, the performance threshold is derived from average prior period scores, and the bill is due. CMS points out that this will mean a greater payoff for those who participate, but since the program is budget-neutral, those incentives will come at someone’s expense!

As if that wasn’t enough, keeping your Quality score in a favorable range will be more challenging than before. As finalized last year, the 2024 data completion threshold—the minimum required reporting rate for MIPS CQMs to earn points—is being bumped to 75 percent through 2026. After that, the data completion threshold will be 80 percent. That’s the same level required in the PQRI (pre-PQRS!) days, wherein only three measures were required, and only Medicare Fee for Service patients were included. These proposals are in addition to the flurry of measure additions, deletions, and updates that occur each year. Some are minor, but others can be jarring. For example, several mainstay population health measures, though not topped out, are set to be retired, and replaced with a single composite measure. You may have just gone from having six measures under your belt to one measure that requires six responses!

More is at stake in 2024 MIPS than ever; the ability to avoid the program with an Extreme and Uncontrollable Circumstance exceptions will fall drastically with the end of the PHE. Increased requirements and mandatory participation will lead to higher penalties, but also the potential to earn more meaningful incentives. To continue to succeed in MIPS, you cannot afford to let any data remain hidden, nor can your performance remain stagnant. If you have not previously considered a partner to help you through, now may be the time.

7. Value-Based Care Program Alignment

If all of the individual guidelines within each program has you going in circles, you are not alone. In addition to the advancement of health equity, value-based program alignment is a theme of this Proposed Rule.

Proposals to accelerate Interoperability span across all programs. Rather than requiring a certain percentage of providers use Certified EHR Technology (CEHRT), CMS proposes that ACOs and other Alternate Payment Models require CEHRT as a condition of participation. Furthermore, ACOs and APMs will need to report the same Promoting Interoperability measures as MIPS participants.

While important on its own, this change has significant implications to APP Reporting. One of the issues ACOs cited in their opposition to APP Reporting was that their membership included “paper practices”—practices that billed electronically, but who do not have an EHR from which data can be integrated—all clinical information is hand-written in paper charts. By implementing mandatory EHR use for APM participation, CMS is removing the relevance of the “paper practice” argument from the APP debate.

Both MIPS and APM participants will also need to attest to a longer performance period for these PI measure: a minimum 180 consecutive days, up from the 90-day period in effect since the start of MIPS.

As we described above, the measures in the APP are MIPS CQMs, and even with the introduction of Medicare CQMs, the same information is being measured, and the data completion threshold is the same. The MIPS/ACO line continues to blur with the possibility of ACO participants earning incentives when their specialists report specialty-specific MVPs. On a broader scale, CMS hints at a “Universal Foundation” of ten quality measures across six categories that are intended to play a role in programs beginning in 2025:

• Wellness and Prevention
  • Colorectal Cancer Screening
  • Breast Cancer Screening
  • Adult Immunization Status
• Chronic Conditions
  • Diabetes – Hemoglobin A1c Poor Control
  • Hypertension – Controlling High Blood Pressure
• Behavioral Health
  • Screening for Depression and Follow-Up Plan
  • Initiation and Engagement of Substance Use Disorder Treatment
• Seamless Care Coordination
  • Planned All-cause Readmissions OR Unplanned Readmissions
• Person-Centered Care
  • Consumer Assessment of Healthcare Providers and Systems (CAHPS)
• Equity
  • Screening for Social Drivers of Health

As a reminder, this is a Proposed Rule, meaning that it is open to public comment. To support or critique a proposal (or lack thereof), or to respond to a question in which CMS has solicited feedback, you can visit http://www.regulations.gov and follow the “submit a comment” instructions, referencing CMS-1784-P.

Image: Tim Mossholder

Founded in 2002, Roji Health Intelligence guides health care systems, providers and patients on the path to better health through Solutions that help providers improve their value and succeed in Risk.

Since the adoption of the 2023 Final Rule requiring ACOs to adopt Alternate Payment Model Performance Pathway (APP) quality reporting by performance year 2025, many ACOs have been scrambling to understand how to make the leap. There’s a huge difference between the old method of quality reporting using the CMS Interface to report on a 248-patient sample and the new requirement for APP reporting on all practice patients, regardless of payer type.

The sheer size of reporting volume and mechanics means that your ACO will need to aggregate practice EHR data for the first time, even with fewer measures under the APP. If yours is a multi-practice ACO with no prior investment in data infrastructure—the norm, except for population health— this is a major undertaking. To meet the deadline, your ACO may be one of many feeling pressured to look for the “easy, fast” path to APP reporting. But that’s just magical thinking. Here’s the reality:

The Four Hurdles of APP Implementation

APP Reporting requires a solution that overcomes four major obstacles to achieve accurate reporting:

1. APP reporting requires the measure to be patient-centric. If your patients are seeing participating primaries and specialists in your ACO, that requires matching patients across separate data feeds to report the patient only once for the measure. Patient matching is messy and ACOs rarely have the internal expertise to accomplish this.
2. APP measures must include the entire provider’s population in the measure denominator. You must collect data on all patients and determine who is eligible for the measure.
3. There are no shortcuts for matching patients, either through CMS claims identifiers (Medicare only) or patient ID numbers (different numbers for different systems). You must use the patient matching programming to do it.
4. APP measures require the latest value for the measure numerator collected in the performance year. After your patients are aggregated and matched, you must align the values for the measure and report the most recent one for both HgbA1C and blood pressure. This requires a measures engine or algorithm for accurate reporting.

The bottom line: APP reporting will require an experienced entity, either a qualified registry or certified EHR (for single-TIN ACOs only), to provide the data crunching and reporting under the APP.

Are eCQMs Really the Easy-Peasy Answer?

It’s no surprise that some ACOs are panicking that the path to APP reporting is requiring resources and work. Naivete about data has led to some truly remarkable, mistaken conclusions:

1. Belief that eCQMs, or electronic measures, are automatically designed to be the fastest and easiest way to report measures, because they are “automatic.”

ACOs often think CQMs, which are the MIPS version of the same measure and can be constructed from a variety of non-automatic aggregated data systems, must be harder because they are not “automatic.” This conclusion is based on an underlying assumption that the digital future should be built on eCQMs because system-to-system transmission is the modern goal.

But the idea that any measure system is—or ever will be—“automatic” does not account for the fallible humans who create data or systems. Data does not always automatically “flow” into measures easily, for two reasons. First, organizations develop customized templates to accommodate specialty workflow in the EHR, causing the data to flow into a separate data field— and not to the pre-defined EHR reporting field that captures measure results. Second, the physician may record a measure value in progress notes. Likewise, an attached PDF from a remote lab or other provider may be in the patient’s record. Either way, the data is not where it must be to populate the measure. While these two issues may get resolved as technology progresses, there will still be failures.

Here’s the kicker: For eCQMs, any missing data causes the measure for that patient to FAIL. Missing data is always a surprise to providers, who can see the data in the record but don’t understand why it isn’t populating the numerator of a measure.

2. Expectation that eCQMs will produce higher measure results than CQMs.

In addition to the missing eCQM data, your ACO needs to understand the differences between eCQM and CQM measure calculations. Most importantly, CQM measure performance is based on the percentage of measures that are “completed,” which must be at least 70 percent. eCQM measures are calculated based on all measures. You won’t know, going into APP reporting, which will produce a better result against the benchmark unless you test both measure types. But this will be cost-prohibitive because the two methods require different data sources for calculation, and the measures are benchmarked differently.

In addition, because of slight variations in the measure specifics, there will be different measure results. For example, CQMs apply to a patient with a diagnosis of diabetes prior to the Performance Year (PY), but eCQMs apply to patients with a diagnosis during the PY. The exclusion of patients with good control—and who may have less frequent visits that trigger the measure—can result in a lower result for the eCQM versus the CQM.

3. Perspective that eCQMs are less expensive.

You may think of eCQMs as a one-step process, with data flow from the EHR to CMS. If you are a new ACO previously reporting eCQMs for the MIPS program, your perspective is based on the fallacy that one-EHR reporting is the same as multiple-EHR reporting. Consider the requirement of patient-centricity and matching measures discussed above.

More importantly, understand that aggregation for CQMs and eCQMs requires different data sources. For reporting eCQMs across multiple practices, you will be required to collect and process QRDA 1s for every practice, and then work out a patient matching mechanism on top of the QRDA file structure. Multi-practice QRDA 1s will require you to transform these file formats. Note that QRDA 1 processing is expensive, three to five times more expensive than flat files. Your total aggregation cost will be much higher than the norm for a reporting method that may produce lower results.

Finally, you may find that many practices on cloud-based or smaller EHRs cannot produce QRDA 1s. This is not unusual, even if the system is certified—it is certified to turn QRDA 1s into the reporting-ready QRDA 3, not to export QRDA 1s. Here’s the risk: if only one practice cannot provide QRDA 1s, your method of reporting eCQM fails. Should that happen, you will need to restart your initiative.

Be sure that your staff or contractor is extremely experienced with multiple practice data aggregation before you commit to reporting eCQMs, or you will hit delays and rack up extra expenses in the process.

4. Belief that CQMs are too much work, or missing advantages because they are built on different data sources.

Here’s what we have learned at Roji, a qualified registry that reports both eCQMs and CQMs across many clients: CQMs are often more advantageous to clients, because

• The calculation of measures often favors CQMs;
• The flexibility of additional data sources for CQMs, including QRDA 1s, allows us to improve measure results;
• Processing data from flat files is cheaper and easier for clients than QRDA 1s;
• QRDA 1s have a huge disadvantage in that the value of the data is so limited for the cost of aggregation. Flat files can provide a much richer data base to be used for analytics, population health, and other initiatives.

As both EHRs and digital quality measures evolve, we will see improvements in efficiency as well as data. But a decision to aggregate data solely for the purpose of APP reporting will not serve ACOs to deliver better quality care at lower cost; it will only satisfy one requirement.

Interoperability and APP Reporting

The National Association of ACOs (NAACOS) has promoted the use of eCQMs in reporting but recommended against APP Reporting without the existence of standardized interoperability features of EHRs. The report correctly corroborates some of the deficiencies in eCQMs noted above, such as the lack of QRDA 1 production in some EHRs, but there is still an underlying commitment to eCQMs as the easier, magical solution to quality reporting. The NAACOs report emphasizes that the obstacles to eCQM reporting should be cleared before CMS requires APP reporting.

There are several good suggestions in the task force report, such as moving toward better certification requirements for EHRs to produce data formats needed for quality reporting. But the underlying belief that system-generated reporting can ever be automatic, flawless, and cheaper is simply not realistic, for reasons stated above.

Further, progress in the development of digital quality measures, standardization of patient data formats, and interoperable means of transporting data from one system to another have been twenty years in development and will take another ten to twenty years to mature. Most large health systems do not have the imperative or even the staffing to invest in developing the simplest FHIR capabilities right now. Even large systems have often not invested in Value-Based Care technology and initiatives to produce higher volume savings on the scale needed to curtail costs and advance outcomes.

Interoperability between systems is intended for transmitting patient clinical information at points of care, for both the safety and coordination of patient care. Designing interoperability to promote flawless quality reporting is not its best use, and compounds the costs of moving forward with clinically-focused initiatives.

Value of Data Aggregation Goes Beyond APP Reporting

Magical thinking has a cost. In particular, it focuses on a method of reporting and not the value of data for ACOs—data that would enable ACOs to push beyond current limits of savings and to vastly improve outcomes for patients, identify patients receiving inequitable health care, and prioritize patients for interventions.

A NAACOS blog recently projected true data aggregation costs based on an alleged proposal of $4 million to $37 million to a large ACO. That this would represent a typical charge from vendors is fantastical, not even within the ballpark of reality. If the named ACO actually received a quote of $4 million to $37 million for data aggregation, either the ACO-stipulated requirements were unrealistic and massive, or the vendor was highly opportunistic. But presenting such information as an accurate depiction of data aggregation charges is misleading.

As your ACO moves both to create your Value-Based Care infrastructure and to implement APP reporting, your ticket for lower cost and better results is this: realism in the assessment of data aggregation, reporting mechanisms, and future opportunities. Call us today to help you prepare.

Founded in 2002, Roji Health Intelligence guides health care systems, providers and patients on the path to better health through Solutions that help providers improve their value and succeed in Risk.

Image: Johannes Plenio

Artificial Intelligence (AI) advances are big news, but the daily onslaught of AI applications in health care is overwhelming. There’s no question that health care is fertile ground for AI. Health care is expensive, highly technical, complicated, and equally frustrating for patients and providers alike. It’s also rich in data—a mostly untapped resource for both clinical and performance improvement. These factors make health care a perfect environment for AI, which can lead to potentially better and faster treatment for patients. And, there’s lots of money in the system.

Health care is also struggling with a worsening physician and staffing shortage. It threatens to become a crisis. AI has a solution for that, too, by filling roles previously occupied by humans. But can AI really substitute for physicians and other providers?

As your ACO navigates its path to Value, you will undoubtedly begin to consider AI and how it might benefit your organization. But be careful and smart. AI is pushing the envelope on health care roles, patient services, and data security. It’s showing up, unexpectedly, everywhere. Before you leap into AI applications, you need to understand not only the potential benefits, but also the short- and long-term consequences—for better and worse.

Here’s what’s at stake:

Are Chatbots Really Better than Physicians at Communicating with Patients?

That’s the surprising implication of a recent study, which maintains that AI chatbots not only deliver higher quality responses than physicians in patient communication, but also appear to show greater empathy. In the study, 195 patient questions from Reddit’s r/AskDocs were fielded to chatbots or physicians for response. Health care professionals then evaluated the responses for quality and empathy. They preferred chatbot responses to those of physicians, 78.5 to 22.1 percent for quality of response, and 45.1 to 4.6 percent for being highly empathetic. Ouch! That stings.

These findings seem to have been readily accepted, if you believe the press accounts and various blogs that propose using chatbots for patient education, navigation, coaching, and outreach. One reporter suggests that chatbots could even respond to direct questions in patient portals.

But before unleashing chatbots on patients, here are a few points to consider. First, did anyone ask the patients how they felt about reviewing their treatment plan with chatbots? Second, where is the usual vetting of the findings? The credentials of the health care evaluators notwithstanding, what potential biases does the study incorporate, and what were the constraints on physicians’ responses?

Time is probably one constraint and venue, certainly, another. Physicians were almost certainly cautious in their responses to the patient questions, given liability concerns. Since the study was based on human and subjective evaluations of physician and chatbot responses, could the findings reflect internal biases or existing belief systems that physicians are not good communicators? The full study sits behind the JAMA paywall, limiting many readers’ access to complete data. Enthusiastic acceptance of the findings most likely reflects only headlines about the conclusions.

This is the danger with rapid adoption of AI technology. It’s all too easy to be mesmerized by the shiny technology that promises powerful new ways to save money and time. But Artificial Intelligence incorporates the very human biases of its creators. Particularly in health care, there is a real risk that AI can lead to inequities—programmed biases in the form of gender and race-biased algorithms.

This is not to say that chatbots are a detriment to health care. Deploying chatbots to write patient education materials, contribute to health literacy efforts, and otherwise support human roles in medicine could be very effective. But we need to fully understand implications for physicians and patients, and to evaluate the potential for unintended consequences.

When we consider ceding direct communications to technology so that physicians have more time “to treat patients,” what do we actually mean? Isn’t the intent of a patient portal to converse with your own providers about your condition or treatment? Why would we cede such essential conversations to technology, potentially eroding trust between patient and physician?

Three AI Guidelines for ACOs

Your ACOs may not be thinking about AI right now. This spring’s NAACOS conference had no agenda items on AI. But that will change quickly, as pressure to live under Risk will force ACOs to invest in technology and solutions for substantial improvements in performance.

Additionally, many are eager to deploy AI solutions for the work that ACOs do, including ACO stakeholders. To avoid getting swept up by the momentum, carefully consider your options, support your participating clinicians in their clinical applications that involve AI, and see how you might collaborate.

Here are some guidelines for how AI might strengthen your organization—and weaken it:

1. Do: Use AI to analyze complex data for identifying risk, patterns and variations of health care services and costs.

The proven value of AI is its ability to dig into data. AI can rapidly and effectively analyze compiled data from multiple sources—genetic data, utilization, clinical data, costs. This aligns well with Value-Based Care. Without AI, using data to develop personalized treatment plans based on multiple patient data points is virtually impossible.

For example, as explained in previous articles, Episodes of Care is an essential method for ACOs to compare costs of procedures and work with specialists to reduce variations, to address persistent poor control in patients with chronic conditions, and to target patients for clinical review based on medication regimens. At the root of Episodes are AI algorithms that process clinical variables across a full patient dataset to identify opportunities for improvement. Without the use of AI-driven Episodes, your ACO’s ability to examine cost drivers, evaluate improvements, and generate data-driven initiatives falls short.

Here’s another good application. Radiology has used AI to advance exponentially in identification of tumors and other images. AI has the potential to make clinical facts clearer and to enable more timely decisions that could be less costly. Already AI has fostered big improvements in diagnostics and, with deep learning, built capability for precision medicine.

Once again, a caveat: Algorithms and their results must be scrutinized to determine effects on population groups and health equity, so that biases are not baked into ACO solutions.

2. Do: Evaluate the use of AI to create patient materials (for review by clinicians).

ACOs have a responsibility to help patients navigate medical decisions and provide cost transparency. Patients will need factual material to understand their conditions and treatment plans, examine choices and the effects of decisions, and engage family members in the process. Chatbot-created communications, with clinical review, could be a great, efficient way of building the tools that patients need.

3. Don’t: Replace direct communications with patients with AI.

Use an iterative, thoughtful approach that assesses the benefits and impacts at each step. Solving staff shortages with AI puts you on a downward spiral for permanent understaffing. You may be able to judiciously explore the use of AI-driven communications and education, such as providing tools and feedback for self-management programs, if the program is piloted and has human resource involvement and guidance. Be sure to understand that your data evaluation needs with AI-adopted programs will increase, not decrease, your costs of data analysis to assess their effects!

The urgency to use data more wisely will push your ACO into AI solutions. Be aware that technology is never neutral, and carefully plan your human and non-human resources. AI will create both immense benefits and harms. Your steerage of AI adoption will help to ensure that your ACO reaps more benefits. Now is the time to learn, so your organization won’t drown in the tidal wave of AI enthusiasm.

Founded in 2002, Roji Health Intelligence guides health care systems, providers and patients on the path to better health through Solutions that help providers improve their value and succeed in Risk.

Image: Steve Johnson

All ACOs, regardless of payment model, are built on a vision of primary care services to patients. Medicare attributes patients to your ACO based on the plurality of primary care services. CMS attributes a patient to a participating specialist only if the patient has not seen a primary care physician in the ACO or at other providers, and the specialist is providing “primary care” services to the patient.

But the vision of the primary care ACO rarely holds up to reality—for either care delivery or economics. The shortage of primary care physicians, complicated by time constraints, often dictates that patients who could be managed by primaries are referred to specialists. Conversely, complex conditions in patients are often appropriately treated by specialists, not primaries. Specialists manage uncontrolled diabetes and COPD or asthma when patients require intensive treatment. High risk, problematic conditions such as coronary artery disease, heart failure, and atrial fibrillation require specialty care.

Tackling Complex Care Requires Specialty Insight

Old school techniques to control costs often focus on limiting access to specialists. The days of HMOs requiring referral authorization to specialists still dominates some ACO thinking. But limiting patient access to specialists is not only unrealistic, it’s also not the optimal strategy to both improve outcomes and cost performance. What is a better plan? Closer involvement of primaries and specialists through shared data analytics, clinical pathways, and communication.

The lack of data-sharing between ACOs and specialists blinds both specialists and ACOs to optimal management of patients and their costs. Without data, it is impossible to develop a guide to identify which patients meet the guidelines for specialty care, as well as to develop solutions that stratify patient risk. Let’s take a closer look at the underlying issues and how data-sharing can be beneficial to all parties.

Should Specialists Be ACO Participating Providers?

An evaluation of ACO provider panels often reveals an uneasy relationship between the ACO and physicians. For organizations that are system- or hospital-driven, or anchored by large hospital-employed physician groups, ACO participating providers frequently include independent stakeholder specialty practices for political reasons. The strategy of keeping everyone on the ranch—and protecting the economics of revenue generators (hospitals and specialty practices)—is often perceived by organizational leadership as the only strategy to maintain good relationships.

Inclusion of core specialists such as cardiology and endocrinology makes sense if the physicians are integrated clinically in the same group. Inclusion of proceduralists and highly specialized practices, however, can be disadvantageous for the ACO and for specialists. Even large academic center groups should be examined to determine the effects of patient attribution. Such health systems can distinguish groups by tax identification number to avoid these effects, while maintaining a governing structure to ensure integration and coordination.

Nonetheless, broad participation of specialists helps neither specialists nor the ACO, eventually eroding the economics of both. ACO patients are attributed to specialists who draw referrals from a wide geographic area if the patients have either not visited primaries during the year or have high specialty-related expenses. For procedural specialties like orthopedics and neurosurgery, where osteoarthritis, osteoporosis, and spine conditions may be patients’ major conditions, the inclusion strategy raises the cost of the ACO, which is now responsible for all costs for the patient with no primary care management.

For specialists, aligning with one ACO also creates competitive disadvantages. And, as ACOs inevitably proceed to global risk arrangements, sub-capitation arrangements will deliver a direct strike to specialty group revenues.

CMS Directions for Specialty Value-Based Care

Late in 2022, CMS identified specialty care as a new area of focus in its Value-Based Care strategy, noting fragmentation of services, high use of specialists, and difficulty of access to key specialists as an equity issue. The agency also noted that consolidation in health care and employment of physicians is making care more expensive without improving quality.

The CMS specialty strategy outline provides a clear pathway from short-term to long-term initiatives, including incentives for ACOs to manage specialty care, development of episode-based payments for specialists that model the existing Bundled Payments for Care Improvement (BPCI) program, provision of data, and testing population-based/capitation payments to specialists.

Likewise, CMS called out specialty-focused payment models like Kidney Care Choices as examples of how care by specialists could be organized in patient-centered models with value-based payment models. These models are likely to be replicated across other higher cost conditions.

ACOs and specialists should take note of the CMS strategy, likely to be incorporated quickly in rules.

Three Approaches ACOs and Specialists Should Start Now

Meanwhile, it makes sense for both specialists and ACOs to start rethinking the divide over cost and outcomes, and start collaborating on how to improve them. Here’s how to start:

1. Share data and analytics.

ACOs are already examining how they can aggregate data to perform required APP reporting in the future. Using data aggregation methods that optimize collection of clinically rich patient data, ACOs can build collaborative projects with specialists to examine specialty service use by patient risk, outcomes, and cost variation.

Many specialists are using independent, specialty-focused EHRs; assistance of technical vendors will be essential to collect and curate the data for review. Technology for Value-Based Care must be able to match patients across all practice domains, to compile the patient’s comprehensive history.

Shared costs of data collection is key to making the process work. As the data should benefit both specialists and the ACO, sharing the cost is one way of ensuring each party’s active participation in design of analytics and agreements on data elements to be shared.

2. Create patient episodes of care for highest cost chronic conditions and procedures.

An essential component of data sharing is the construction of discrete condition and procedure episodes for comparisons. Unlike BPCI, which includes many disparate types of procedures under a single “episode,” it is important to construct episodes for improvement programs in a way that they can be compared clinically. That is, they must be defined by a single diagnosis or intervention (procedure) to have clinical integrity when evaluated by physicians.

Without clinical integrity, cost variation could be caused by differing volumes of unrelated procedures or conditions, and physicians will be exhausted by sorting out important findings. Episodes can be rebundled at any point to replicate bundled payments or cost measures, but first must be examined for clinical interventions related to conditions or procedures.

3. Create referral networks using ACO-Specialist specialty care models.

Lack of an organized CMS payment model does not preclude ACOs and specialists from organizing specialty care models across major cost areas to improve outcomes and costs. Progressive specialty groups can initiate the development of episode-driven care pathways to drive analytics, improvement activities, and communication. Patient selection criteria for referrals and interventions are important elements in the agreement between specialists and the ACO.

ACOs should be prepared to use data as a mechanism to entice specialists into collaborative initiatives, as opposed to a hammer for redirection of patients. It would be impossible for ACOs to fairly examine costs unilaterally, and without time for specialists to respond and act.

Specialists already participating in BPCI initiatives should examine how to make the episodes more clinically robust in data, since BPCI data is calculated only from claims by CMS, leaving specialists without detailed insight.

Specialists should maximize their participation in existing models, constructing analytics to guide evidence-based care within clinical conditions and procedures. Participation in Kidney Care Choices and Oncology Care models, if appropriate, will provide specialists and ACOs with both practice and data that will benefit future models in other specialties.

In the future, we are likely to see a much stronger distinction between payment models organized around primaries and specialty care. Physicians in some specialties will be integrated into primary care practices and will participate in ACOs. Other specialists who perform distinct services will be separated into specialty care models or even specialty ACOs.

Both ACOs and specialists will benefit by implementing a shared vision of patient care that relies on ensuring access to the best, but most affordable, specialty care, with contributions from both primaries and specialists. Such a collaboration will produce essential results for ACO patients and consumers: clear information to guide them to best choices about their self-care and health care services.

Founded in 2002, Roji Health Intelligence guides health care systems, providers and patients on the path to better health through Solutions that help providers improve their value and succeed in Risk.

Image: Aaron Burden

Never has it been more important for ACOs to amp up Value with significantly higher cost savings and outcomes performance. More payment models are risk-based, changing economics for providers. Corporate health care and equity-backed practices are nabbing ACO physicians, making it hard for ACOs to sustain and grow. The next two years may be the last grace period for ACOs to show that provider-directed organizations can produce Value, before Medicare Advantage health plans—now chosen by half of beneficiaries—becomes the predominant model.

That’s why our spring 2023 eBook, Supercharge Your ACO: 6 Key Strategies for Top Value, is your essential guide for ACOs under Risk. After years of operating as bootstrap-funded organizations that produce modest savings, ACOs must now put infrastructure in place and quickly scale up savings. If they fail to do that, provider-led models will be sidelined in the Value-Based Care future. The direction of health care will be determined by those organizations willing to take Risk and to reshape the health care system as affordable and equitable.

We at Roji Health Intelligence started our business by helping physician networks clinically integrate and by aggregating data for shared quality initiatives. Some of those providers became the first ACOs in the program, struggling to get dedicated infrastructure and data to guide efforts. Too many of you are still in this position, producing no or small savings. You can’t be successful under Risk if you can’t produce significant savings.

When we wrote the first Supercharge Your ACO in 2021, we included a lot of strategies for ACOs to consider to advance with greater power. Those strategies are still valid. But we are in a different place now in health care, post-pandemic but not post-crisis, and there is an urgency around moving toward Value that is time-delimited. In this eBook, we concentrate on six major strategies to make your ACO scale up to the level needed to boost your savings, outcomes, and equity—and in so doing, beat the competition.

Don’t let your organization’s future slip away. Download Supercharge Your ACO: 6 Key Strategies for Top Value here.

Founded in 2002, Roji Health Intelligence guides health care systems, providers and patients on the path to better health through Solutions that help providers improve their value and succeed in Risk.

Ever since the first pandemic data revealed the enormous cost of health inequities, the pressing question of how to rectify unfair access to quality health care has become a major policy discussion. Now the debate is turning to action, as the first Value-based Payment Model to address health equity comes online.

ACO REACH is Medicare’s response to blending several key values in its most advanced payment model to date. In addition to traditional ACO quality and cost values, ACO REACH also includes population-based payments (including global payments), rather than Fee-for-Service, and promotes health equity as a central goal. If your ACO is an ACO REACH participant, one of your first requirements is to establish a health equity plan. The financial stakes are higher in ACO REACH; not only are payments risk-based, but also the costs of identifying and addressing health equities are uncertain.

As you prepare to implement the most challenging alternative payment model (APM) in the ACO spectrum, you must figure out how to get the data that will help you develop and implement that plan. It’s a herculian task. Your first challenge is how to quantify health equity and identify patients who are vulnerable because of racial bias, poverty, food or housing insecurity, and job or transportation issues. There are options for how to tackle this. But unless you can efficiently identify patients at higher risk because of unmet needs, your second challenge is that you may face cost overruns and still fail to adequately improve health equity in your patient population.

Even if you are a traditional ACO MSSP, understand that resolving health equity, even if not currently defined by your payment model, is also in your future. That’s because as you transition into Risk, vulnerable patients are where you will find opportunities for improving outcomes and savings.

Here’s the dilemma for all ACOs: The need to improve access and quality of care is more urgent than ever, but there is insufficient data on patients to identify the individual circumstances that influence their health and ability to access care. And, there is lack of consensus on how to get that data. The bottom line: your ACO must innovate to develop your own template for health equity, by cultivating both available data and data-gathering methods while you plan long term solutions.

Let’s address the fastest and most effective way to get started now.

The Challenge of Collecting Social Determinants of Health (SDOH) Data

Obtaining SDOH data is the first step toward helping patients in need to get better health care by identifying circumstances that prevent them from accessing services or quality care. In any effort to measure health equity, including CMS initiatives, using SDOH is a specific point of CMS guidance. This is based on the assumption that all patients are screened on SDOH. However, the question remains: Is it feasible to conquer the SDOH data hurdle in the short-term?

SDOH defines an individual’s circumstances, such as poverty or homelessness, that affect their ability to access care or treatments. The data is currently classified by ICD-10 “Z codes,” a set of 10 categories of 70 separate psychological, family, living environment and economic circumstances that can affect health status and/or access to quality care. Theoretically, SDOH provides the measurement construct for identifying the precise triggers for inequity and points to solutions.

SDOH is intended to identify patients who are marginalized in one of two ways: those without access to any care, and those facing obstacles in the care process itself. Capturing SDOH is an enormous undertaking, and is not a short-term project. The notion that every patient will consent to being questioning about personal vulnerabilities by their medical providers is idealistic. Lack of trust, feelings of embarassment or shame, and the level of staff interview expertise—all affect the process. Whether most, if not all, patients are able to participate in the process is also a hurdle; while some practices deploy patient-reported tools, individuals with literacy issues will be underreported.

In short, building SDOH data to help identify health equity issues is often unrealistic in the near term. In fact, there is very slow gain on SDOH data collection, with paltry results, at best. To date, SDOH data for only about two percent of the patient population in the U.S. has been collected, even among state Medicaid populations where most patients, by eligibility, should have at least one SDOH factor, and often less in aggregate patient populations.

An additional problem is that practices on the front line of patient care do not have the capacity to interview and collect SDOH data on patients. Even for those who try to do so, recent information indicates that key variables for patients are often missed

As a data aggregator, we find that provider organizations’ ability to capture SDOH data is still highly variable and, overall, insufficient to support usage of a full SDOH-data collection model as a basis for health equity.

Three Ways to Jumpstart Your ACO Health Equity with Data That’s Already Available

Without adequate SDOH data, do ACOs lack the tools to address health equity? Absolutely not! ACOs can already access a wealth of data to build an engine that will target the most vulnerable patients and jumpstart your health equity process. This approach significantly conserves resources while providing you with patients who are likely to need attention. Here’s how:

1. Use coverage data to reveal patients with income constraints.

Your ACO has coverage data that is the basis for billing. Assuming you are aggregating data from all practices for analytics, quality, and other purposes—and you already need to do that—you can identify patients by payer source or zip code as an initial proxy for patients with SDOH circumstances. Medicaid is the first place to begin segmenting your list to identify those who are dual-eligible for Medicare and Medicaid, as income is the first eligibility requirement. For both criteria, your goal should simply be to produce a smaller patient list for targeting data collection, to make your job more manageable.

2. Work with community organizations to identify patients’ insecurities in vulnerable geographies by zip code.

Let’s start with the assumption that physician practices lack the capacity and capability to elicit patient responses about circumstances, even if this is not always the case. Trust is a huge issue if patients have experienced poor access or bias. Alternatively, community organizations are well situated and already working in areas of financial and social vulnerability. Collaborating with them to interview patients in your ACO and their communities can be a powerful strategy. This will reinforce your referral relationships in the community and begin to furnish some SDOH data for your organization. By working effectively with existing organizations that also have connections to resolve the identified issues, you can have a real positive impact on patient circumstances and their health status. Deploy resources you would use internally to support, instead, sustainable outposts in the community and maximize your efforts.

3. Curate your EHR data to identify patients by criteria indicating gaps, poor outcomes, treatment issues, and utilization.

Your aggregated, patient-centric data is a second source to identify patients with issues such as persistently poor outcomes over time, poor visit profiles, missing health data, and problematic admissions or emergency room use. The data must be developed into patient episodes, by conditions and other criteria, to examine their trended values (such as hemoglobin A1C) and to find patients who are not improving, who have frequent instances of utilization or exacerbation, or who have poor visit profiles for their conditions.

From this point, you can further analyze the data to dive into such areas as lack of treatment or medication change (indicative of financial hardship for pharmaceuticals), lack of patient self-management programs or referrals to nutritional resources (possible patient transportation or employment-related obstacles) for further patient identification by the practice or your community contacts. Episodes of care are the best way of comparing patient outcomes and costs to reveal equity, outcomes and cost differences for each condition or set of circumstances.  Your clinical data is a bedrock of patient histories that can, if creatively examined, reveal patients who have unaddressed issues. If those patients are not getting what they need to improve, the reasons are often outside the health care system.

Waiting for all-patient SDOH data is not ever going to be the “easy” way to establish the foundation for tackling health equity. Creativity and collaboration are your key tools. Data plus community are your ACO’s resources to make the best use of those tools. Look beyond the health care system in a sincere quest to improve patient health, and your ACO can jumpstart the process to achieve equitable health care for all.

Founded in 2002, Roji Health Intelligence guides health care systems, providers and patients on the path to better health through Solutions that help providers improve their value and succeed in Risk.