ACOs have used “old school” data sources for many years to focus coordination of care activities. Perhaps your ACO has done the same, using reports such as admissions and ER discharges, post-acute admissions, visit history and missing labs to target patients for outreach. Similarly, your ACO might use HCCs to identify patients with higher risk factors for population health.

Basic, easily found data like these sources provided a means for ACOs to launch valuable efforts in population health, when comprehensive claims and EHR data were not easily available. But as the pendulum swings toward financial Risk, your ACO needs to shift from Fee-for-Service to value-based payment models, upping the ante on data to protect your bottom line.

Three Ways that Better Data Opens ACO Opportunities to Thrive Under Risk

Your ACO will need deeper analytics and data-driven interventions to ensure financial sustainability and growth. You can’t intelligently manage Risk without being able to predict and control total patient care costs. Collecting data from easy sources like admissions, ER, and HCCs is certainly not enough and is not predictive of future costs. More importantly, this piecemeal approach does not provide the detail you need to address costs or outcomes. Retrospective data has only partial clinical relevance to the status of those patients in the future.

For your ACO to operate with confidence under value-based payment models, think about how you can use data to achieve these three objectives that heavily impact your aggregate patient care costs:

• Systematically identify patients with chronic conditions who are in decline or not improving. These are the patients who will impact your future bottom line as their health further erodes. Better data creates the opportunity for you to target clinical and social services interventions based on key indicators, and potentially improve the course of their lives and cost trajectory.
• Identify cost drivers in specialty care, with data packaged in procedural or condition-based patient episodes of care. By examining each patient within the group against others, linked with specialty providers, you will identify variations as well as notable observations and outcomes. Share these results with specialty providers to evaluate and improve, engaging them in your ACO goals.
• Provide meaningful and relevant cost data to your clinicians to involve them in improvements. These should include more than general analytics and encompass the provision of point-of-care tools for questioning and considering specific interventions for patients at the time of the visit.

Five Data Sources and Their Value for Value-Based Payment Models

Now let’s examine the sources of data that you should be tapping. First, understand that if you are to achieve any of the goals listed above, you will need to integrate the data from these sources into a patient-centric database. Why? Because at the heart of each goal is a set of actions to examine or act upon for each patient. Whether population health, clinical change in treatment, or examination of variations in care for patients with the same condition—each intervention or improvement is based on findings from patient-level data. Therefore, you must layer the data from each of the five sources into patient histories, outcomes, and costs.

1. EHR Data

Your ACO has probably considered Claims data from CMS as the nucleus of your ACO data empire. Nope. While Claims data is valuable for revealing most patient care costs and utilization, you need EHR data to provide the foundation of clinical information necessary for analyzing costs and outcomes, and certainly for targeting interventions.

Unless you are a single group ACO supported by a common EHR, the concept of aggregating data from multiple EHRs may be new. With APP reporting on the horizon in 2025, many groups are just starting to understand the dimensions of EHR data-driven opportunities.

These are just a few of the essential data types that the EHR offers for meeting the three ways to thrive under Risk, none of which are available through Claims alone:

• Lab and other test values for conditions, enabling you to stage patient risks;
• Prescribed drugs and history of prescriptions;
• All diagnoses, not just those billed during the year;
• Trend of critical lab values such as A1C, blood pressure;
• Other patient history that can explain poor outcomes or events.

2. Claims Data

Claims data contributes to your patient information in three important ways. First, it adds data about your patients, including conditions or procedures and some clinical status indicators of which you may have been unaware. This information should be blended into your patient’s data history.

Second, it provides information on other providers giving services to your patients. Knowing providers outside your network should enable you to better evaluate your referral sources and help cultivate your specialty referral strategy. Your specialty relationships could include data sharing or involvement of the specialty group in your ACO initiatives.

Finally, it reveals essential cost of care and utilization information that can be analyzed by patient episodes to identify variations and cost drivers.

3. Patient-reported Outcomes and Devices

Many patients are now collecting information through wearable devices, and this data is rarely flowing into EHRs. Whether captured through portals or devices, patient-origin data both supports the patient’s efforts to document and improve their health status and also incorporates vital feedback into the clinical data. Why depend on survey data or limit your patient contributions to feedback on services, when you could benefit from rich lifestyle data or incorporate clinical values into your repository? Patient-reported data can also provide valuable information on the patient’s level of engagement in treatment, or how effective the treatment is.

Despite the value, however, there’s a hitch. Clinicians and organizations are often opposed to such data being directly ingested by the EHR. If that is the case, ACOs should consider instead how to incorporate this data into the ACO patient-centric repository.

4. Social Determinants of Health (SDOH)

Many ACOs are enthusiastic about improving health equity yet distressed about the staffing and process required to collect SDOH data, and still struggling as a result. In the long term, the use of standardized tools and Z codes may improve the incorporation of SDOH data in EHRs, but input from provider offices will be required for the ACO to reap the rewards of good SDOH data. The ACO has a legitimate leadership role in this area because the value-based agreements negotiated by the ACO incorporate health equity requirements. As such, the ACO may consider working with community organizations or creating better strategies for collection of SDOH data going forward.

In the meantime, ACOs can use the other sources of data they are aggregating to target patients for examination of SDOH issues. For example, condition episodes such as diabetes should identify patients with stagnant, poor outcomes and no change in medication. This and other indicators signify that investigation is necessary to determine affordability or other issues contributing to the patient’s situation. Targeting patients for identifying SDOH issues will lessen the burden of collecting data on everyone, while providing a path forward for the ACO to address the most critical and obvious cases.

5. Specialty Provider Data

As discussed previously, significant sources of specialty care make an important contribution to ACO patients, and all efforts to formalize the relationship between the specialty providers and the ACO mission is key. One aspect of this relationship must center on data sharing.

There are several options for this if the specialty practice is not ACO-participating, all of which require good faith negotiations for the benefit of each party. First, the specialty practice can provide EHR data to the ACO, which can be ACO-limited (only with technical capability). Second, the ACO could also arrange for its data vendor to aggregate and separately categorize ACO patients and provide analytics to the ACO and practice alike. This would provide the full benefit of episode-based cost analysis to the specialty practice while also providing detail on ACO patients to the ACO. Finally, the specialty practice could independently aggregate and furnish the data to the ACO.

Building ACO data prowess will take some time, and funding but will be required to sustain the revenues of the ACO as Risk proceeds. The cost of aggregation is lowest and the data value highest using a holistic data gathering approach, rather than measure-specific or single purpose. With Claims for Medicare patients already available, additional data sources can be added and enhanced over time.

ACO reluctance to adopt data aggregation has occurred for various reasons—cost, history, lack of value in data, provider pushback. Now is the time to get smart about data. Equity-backed providers have already invested in the technology needed to really address costs. To manage Risk and compete for providers and patients, ACOs emerging from legacy provider groups must do the same.

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: Guillaume Bourdages

Many ACOs are in the throes of planning to adopt APP Reporting. It’s a massive undertaking that can be costly, depending on your ACO’s configuration of practices. If your ACO is scrambling to sort this out, you’re not alone in your abrupt initiation into the world of EHR data. Welcome to the joy ride.

In our last post, we explained how to maximize the value of data aggregated for quality, as produced by either the HL7 and flat file method, or the QRDA method. Here we break down the data you need to achieve better quality in terms of patient outcomes. Why? Because if you’re aggregating data for quality, you don’t want to miss the important stuff that will make a real difference for your organization and patients in the long run.

Different Goals for Quality-Cost Improvement and Quality Reporting

Achieving better quality and cost performance is an entirely different game than quality reporting. The first is part of the Triple (or Quadruple) Aim at the root of the ACO model. Its goal is to improve outcomes while reducing costs. APP Reporting, on the other hand, provides the aggregate quality status about the ACO’s population and also checks the box to get savings, incentives, or penalties-avoidance. APP Reporting will also standardize how ACO and non-ACO providers measure quality, so that, eventually, there can be some comparisons between the traditional providers and ACOs.

The two “quality” goals, Triple Aim and quality reporting, are not the same, nor do they require the same data.

APP Reporting data is not highly actionable, because the three APP measures give only a limited view of patient status. You can discover the percentage of the population that does not meet standards and which individual patients comprise the population. But that data does not help you to identify any solution to improve the patient’s status. It simply calls out the patient without further enlightenment as to the clinical status of the patient over time.

Three Data Types Essential for Implementing Improvements

By whatever method you aggregate patient data from ACO practices for APP Reporting, you will also need to capture additional quality data that permits an in-depth analysis of your ACO’s patient outcomes and quality of care. This is not for reporting, but for guiding your improvement of outcomes and cost prevention. These three types are key components for your quality analysis and intervention guidance:

1. Time-specified Values for All Quality Numerators

APP Measures, like other Quality Payment Programs (QPP), are satisfied by the latest single instance of the measure’s numerator, e.g. Hemoglobin A1C value at the latest lab visit by any provider. How this value relates to other A1Cs over time is more important, and provides both the clinician and your ACO’s population health initiatives with critical information for interventions:

• Is the patient improving or worsening?
• Has the patient been in poor status over an extended period, or does the value signify a change?
• Across all the patients with poor control, has an improvement occurred over time?

These data, along with other time-related data (visit adherence, for example) can help you determine what actions to take to improve the patient’s status and prevent admissions, emergency care, and progression of disease.

2. Clinical Events

Condition-related events like exacerbations, hypoglycemia or other clinical diagnoses, and disease progressions are important markers for predicting patient crises. Claims data only offers a retroactive view of utilization and lacks the predictive clinical elements for future risk. These data types are essential to view patient risk profiles and establish improvement plans that involve clinicians, as well as outreach and potential social services.

3. Provider and Patient Actions

The previous two data types will reveal patients who are succeeding or at risk. The next task is to examine both provider and patient actions. These include prescribed medications, specialty referrals, patient self-management programs, patient outreach or education, behavioral health or social services, and so on. Populations of patients who have not improved over time, yet for whom no changes are made, can be referred for clinician review. Likewise, patient actions such as poor visit timeliness, missed visits, and no visits are important indicators for ACO action.

There is growing pressure on ACOs to move the needle on costs. Doing so depends on improving patients who are failing in their current therapies. Good EHR data is a gold mine of information that reveals patient histories of diagnoses and therapies, information that can guide your ACO to more targeted strategies for cost and outcomes improvement. Keep your eye on the data horizon, as you plan to expand your data field of view.

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: Simon Berger

If you’re an ACO worried about APP Reporting, we get it. Your concerns about the feasibility and costs of aggregating data from multiple systems are completely valid. But don’t let data complexity hoodwink you into a simplistic solution that will cost you more than the data is worth. Your solution to data aggregation needs to focus on “value,” which means that your data aggregation should also garner the most return for your investment.

If you are a one-EHR type of ACO, your data aggregation is relatively straightforward, and the cost will be reasonable. But you’re facing very different challenges if your ACO has multiple practices, both employed and independent, using different systems. Whether it’s even feasible to retrieve the data you need is a real issue, depending on the age, type, and brand of your physicians’ systems. Likewise, the cost associated with data retrieval and integration for multiple practices varies. The cost is not solely contingent on practice or patient volume. It varies by data format, by amount or size of the data, type of processing used, and storage.

Here’s the truth—and the fiction—about aggregating data specifically for quality reporting through APPs. Quality reporting data requirements have led some ACOs to adopt a “QRDA (Quality Reporting Data Architecture) mindset” for data aggregation. This presumes that QRDAs are the answer to achieving feasibility and lower cost for APP reporting, and that all EHRs can export QRDA 1s. But is this assumption about the value of data versus the cost of data acquisition actually valid? Let’s break it down:

Truth or Lie: All EHRs can produce QRDAs for APP-required aggregation.

LIE. APP Reporting requires a patient-centric database that includes all patients in ACO practices, regardless of payer, but counts each individual patient only once per measure. This means that individual patient data must be retrieved to determine whether the patient qualifies for the measure, and the latest response for the measure must be submitted as the numerator. This patient-specific data is called a QRDA 1. Feasibility of retrieving QRDA 1s is questionable for untested older or cloud-based systems. Some systems have no means to report out individual patients easily, even if they are ONC-certified.

ONC-certification for eCQM reporting requires that the EHR can create an aggregated QRDA 3 report to submit to CMS. But that does not mean that the system can also generate QRDA 1 files externally. QRDA 1s are necessary to identify individual patients across all practices and to accurately choose the correct data for reporting. Even if the system is internally generating QRDA 1s, it’s often difficult for technical support staff to produce that QRDA 1 feed. The fact is that EHRs often equate QRDAs with QRDA 3s, which do not provide the patient-specific information needed to populate measure numerators and denominators.

You will almost certainly find systems used by your physicians for which no QRDA 1s can be produced. If that’s the case, your reporting will be MIPS CQMs by default. You’ll need to depend on your data aggregation vendor to use an approach that depends on the capabilities of the source systems.

Truth or Lie: Among methods of data collection, QRDA offers the most reasonable cost for value.

LIE. The costs of these processes will vary by system, methodology for data collection, processing, and storage. For ACOs with a lot of independent physician practices on multiple systems, it’s hard to estimate in advance how difficult or costly data aggregation will be. But here is the truth: QRDAs are heavy users of processing capability—in fact, they use 3 to 4 times as much processing capability in terms of servers. Due to volume, extra staff are also required to manage data processing queues for QRDAs. This is especially true of files from big systems, such as Epic, which generally have much more data in the QRDA 1 file than smaller systems.

If you are set on a path of QRDAs because you want to use electronic CQMs for reporting, there is really no advantage over the regular MIPS CQMs, if you use qualified registry APP Reporting. Don’t overspend on QRDA processing because you think it standardizes the data. It doesn’t. There’s data variation among QRDAs produced by different providers and by different systems. It just costs more if there is more data in the record.

Truth or Lie: You should try and gather the minimum amount of data you need to meet a measure for APP Reporting.

LIE. The principle behind QRDAs is to create a dedicated data source specifically for quality measures. A QRDA 1 does, in effect, consolidate diagnosis information and other population criteria for measure denominators, plus clinical data such as A1C and blood pressure, and visit information. But the return on your investment is limited, due to the high cost of processing quality data, alone.

Since the cost is tied to data retrieval, your better approach is to maximize the amount of data you are gathering each time to build a patient-centric database, not only for quality reporting, but also for evaluating patient outcomes, costs, and conducting ACO performance improvement.

Truth or Lie: Getting the best data value depends on using multiple data aggregation methods, including QRDAs on a limited basis when no other method is available.

TRUTH. You can expand the amount of data available to your ACO while using fewer resources by deploying a hybrid approach to data. For some smaller systems, QRDAs may be the only method of obtaining data from practices with no technical support; whatever method the EHR has to export patient-specific data at lowest cost will be your best bet. For larger systems and large groups, using flat files or other methods of retrieving large datasets will be the most economical and data-rich. This can be enhanced by filling in clinical data through additional separate flat files.

Your optimal path to data sufficiency will combine both provider data and payer data, especially CMS claims. Expanding your options for data aggregation paves the way to enriching the information for your ACO. Your future depends on it.

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: Sander Sammy

No way out. That’s the message of the CMS 2023 Final Payment Rule regarding APP quality reporting for ACOs. ACOs hoping for a reprieve to avoid all-patient quality reporting did not get it. APP Reporting will go forward by 2025, and ACOs must aggregate the patient data from provider systems to enable it. CMS has made it clear that accountable health care requires all-patient data to support both quality and equity in patient health care.

You will need to act quickly. It takes experience, technology, and time to create the framework for a multi-practice database. You will need to become data sufficient in order for the data to measure quality and meet health equity requirements. Many ACOs don’t know where to begin. So, we at Roji Health Intelligence have put together the Ultimate Guide to APP Reporting for ACOs as a step-by-step guide to the process of aggregating data and reporting measures. You can download this e-book for free here.

Roji Health Intelligence is your trusted and experienced guide for data aggregation and quality reporting. As a CMS-qualified registry for reporting eCQMs and CQMs, we have aggregated hundreds of provider EHRs and other systems. We have been reporting for provider clients to CMS and health plans since 2008. Let us help your ACO prepare for quality measurement and better patient results with data-driven solutions. Download our free Ultimate Guide to APP Reporting for ACOs today!

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.

After an intense few years in health care, will 2023 deliver more punches? While 2022 was dubbed a COVID “recovery” year, as patient volume rebounded, health care staffing shortages festered. Burnout prompted physicians to retire, sell practices to corporate owners, or leave traditional health care for other employment. Simply put, 2022 was short on recovery and stability.

Even still, 2022 fostered important new trends and discoveries. Despite inflation and recession fears, corporate health care continued its growth undaunted, with new startups and equity-backed practice expansion. Value-Based Care spurred corporate territorial reach into legacy health care preserves. Optum, ACO enablers like Aledade, and CVS and Walgreens all expanded their patient care services. Physician employment in corporate health care outpaced hospitals and traditional organizations.

Meanwhile, CMS and commercial health plans reaffirmed the push to Value-Based Care. CMS new rules assuaged provider concerns about financial risk and enticed providers to participate in VBC. Private health plans expanded ACO Agreements with providers, some shifting emphasis to population-based payments. CMS also initiated ACO Reach for organizations willing to participate in risk.

Consumers also weighed in on Value, choosing health care based on convenience and costs via retail clinics for basic primary care and digital apps for health maintenance. Older adults favored private Medicare Advantage plans over traditional Medicare to lower their costs, continuing a trend.

Finally, scientific knowledge made big advances in 2022, regarding Artificial Intelligence; breakthrough pharmaceuticals for patients with diabetes, obesity, and high cholesterol; and cost -effective medical technology.

What’s next? In 2023, watch for these fledgling trends to take flight:

1. Medicare Advantage growth will tip the balance toward Medicare privatization.

Inflation and rising out-of-pocket costs have strained consumers’ pocketbooks. As more older consumers opt for Medicare Advantage to save on health care, politicians who want to revamp entitlement programs may push for privatization. If traditional health care doesn’t lead health care transformation, economic realities will prevail.

2. Corporate health care will continue its advance on legacy primary care.

Expect to see further partnerships, acquisitions, and encroachments. Amazon will create more access points, as will corporations like Optum, Walgreens, and CVS—and more corporate players will join in. Employers, following Chase, will create dedicated health care teams for employees. Expect regional battles between corporate health care and legacy health systems, as this sorts out geographically.

3. Specialty care will increase private equity standing, and bundled payments will fuel returns.

Equity-backed specialty practices are growing and will continue to expand, especially those with common procedures like cataract surgery and plastic surgery. Expect them to create dedicated facilities to lower expenses. Lured by bundled payment plans promised by Medicare and private players, equity-backed professionals want to preserve their independence and grow.

4. Provider-owned ACOs and Value-Based Care initiatives will remain stable. Don’t expect new payment models.

The future of provider-driven VBC is a toss-up. Investment by some health systems and physician-backed ACOs have had variable results; some delivered good savings, others had weaker returns. ACOs’ failure to deliver more savings or limit cost escalation will inevitably reduce support. Pressure is mounting. Is health care listening?

5. Artificial Intelligence will leverage data for Value-Based Care.

VBC success hinges on actionable data. Corporate health care uses data to gain strength, develop platforms, and increase clinician access to data for decision-making. As AI matures, it can harness better interventions for outcomes and costs, especially building on patient episodes of care. As more data—including genomics and social determinants—flood systems, AI will be key to convincing clinicians to buy into the transformation.

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: Lucrezia Carnelos

Health care systems that have struggled to survive pandemic pressures won’t get a reprieve from competition any time soon. Since Covid shook the world, private investors in health care delivery have emerged as the most potent force driving change in delivering Value-Based Care. Equity-backed medical groups, ACO enablers with venture capital funding, and corporate health care have built their future around Alternative Payment Models (APMs) with population-based payments, which create a predictable revenue stream for their operations and investors, while drawing physicians and patients away from legacy systems.

In this November 21, 2022 interview on Race to Value with Dr. Eric Weaver and Daniel Chipping, ROJI CEO Terry Hush discusses what’s at stake for legacy health care systems, why adopting APMs is essential to their survival, and how this turning point can actually benefit both patients and providers.

Listen to the podcast here.

For a comprehensive strategy for transitioning to APMs, download our free eBook, Smart Guide for APM Success, 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: Harshil Gudka

In a previous post, we demystified the Alternate Payment Model Performance Pathway (APP) and explained how, by partnering with a Clinical Data Registry experienced in data aggregation and result submissions to CMS, you can avoid the bugaboos falsely attributed to APP reporting—perceived high costs and impossible timelines. Here we’ll show you how to leverage your new skills to elevate your ACO’s performance across the board, from quality scoring to effective patient management—and achieve data sufficiency, in the process.

Achieve Better Scores and Insights from Quality Reporting

Once your ACO’s data from all practices is aggregated, you will be ready to report either the Electronic Clinical Quality Measures (eCQMs) or the MIPS Clinical Quality Measures (MIPS CQMs). (Learn about the differences here.) In either case, the 2023 Physician Fee Schedule Final Rule eases performance requirements and offers potential bonus points for those with a high rate of underserved patients.

For those who make the APP transition before it’s required, the standards that ACOs must achieve to earn Shared Savings are reduced: In 2023, as long as the data completion threshold (70 percent of the total denominator) is met, one of the APP outcome measures need only reach the 10th percentile for quality, with others needing to reach the 30th in order to be eligible for maximum shared savings.

By comparison, Web Interface reporting currently requires the 30th percentile on all measures. In 2024, APP reporters can still have an outcome measure in the 10th percentile, provided the others reach the 40th; Web Interface reporting will require all measures at or above the 40th performance percentile.

In addition to these performance safety nets, there are opportunities for positive scoring adjustments. ACOs who serve a high proportion of underserved patients are eligible for a Health Equity Bonus, which can boost your quality score by up to 10 points.

Successfully reporting quality measures via the APP is your starting point toward improving health care—identifying gaps in care, patients who have not met performance standards and are candidates for ACO interventions, patients with adverse events who need visits, risk scoring, and so on. Identifying patients with poor outcomes, alone, is not actionable without a deeper data dive to pinpoint possible explanations, which is much easier to do with data that tracks patients across the entire network.

If a patient has a behavioral health diagnosis but has not seen a clinician who specializes in behavioral health, you have identified a potential contributing factor to high intermediate outcomes. By addressing the reason for this persistent poor control, you can act before these intermediate outcomes lead to disease progression, complications, Emergency Room visits, and admissions. This proactive approach is not only better for your patients, but also your efforts will be reflected in the next round of quality reporting and, ultimately, will lower costs.

Promote ACO Ability to Manage Risk, Costs, and Outcomes

Your clinicians don’t operate in a vacuum of payer-specific clinical care. Neither should your ACO be limited in its ability to create a high standard of care for all patients, so that your clinicians are engaged in accountable care. Including all patients in your database enhances your ACO’s ability to manage complex populations and ensures that you won’t be caught in “small numbers-based” assumptions about your data. Conversely, clinicians who are required to base their services in a population-specific way are less likely to engage in your improvement strategies, because it requires more work.

In addition, data that is missing elements hurts ACO improvement efforts. For example, if a patient has a diagnosis of chest pain at a primary care practice and follows up at a cardiologist, an ACO can see that the patient is being managed aggressively. Without integrated data that identifies unique patients and their services, you cannot distinguish a patient who has not been seen at all and a patient who was seen at a different location. In this situation, the ability to be proactive can be, quite literally, a life saver.

Aggregated and integrated data create the potential for creating episodes of care in specific chronic conditions and for procedures and treatments, enabling comparisons of costs and outcomes from patient to patient and from provider to provider.

For patients with chronic conditions, the behavioral health example above illustrates how the ability to track a unique patient across the network can reveal barriers to better health. There are dozens of similar scenarios: knowing whether a patient with a high hemoglobin A1C and who is obese has seen a nutritionist or dietician, or whether a patient with COPD who has had an exacerbation in the last 12 months has seen a pulmonologist.

With additional SDOH data, you can decode these episodes to determine if progressive clinical failure actually stems from poor patient compliance or other factors. Does the patient have persistent poor control in HgbA1C because they aren’t following the treatment plan or because they can’t afford more effective medication? Interventions must be targeted to the actual cause of therapeutic failure, in order to fix it. Distinguishing therapeutic inertia from legitimate reasons for poor compliance helps your ACO map strategies for community referrals and other population health activities. Being proactive and setting priorities are essential—but without integrated data, you severely limit your ability to use data most effectively and efficiently.

On the procedural side, you must be able to identify specialists who are helping to produce the best outcomes at the lowest cost for your patients. Integrating your claims and all-patient data from providers will enable you to compare results across practices and providers. You can use this data to create stronger partnerships with specialty practices, addressing the 40-60 percent of costs generated by these clinicians.

ACO-specialty collaboration need not be punitive, and it can be mutually beneficial for both parties. Comparing outcomes and services among providers can help you ask the right questions. For example, if one specialist’s procedures tend to produce more potential drivers of high cost compared to another, you can investigate. It could have nothing to do with the provider in question—perhaps an issue with the facility, a patient clinical issue, or the use of a particular anesthesia agent—but without being able to see the data from each practice, your ability to compare costs associated with an episode of care is informal, at best.

Expand Value-Based Care Arrangements with Private Health Plans

Your ACO will have a stronger financial foundation if your patient base is larger and younger on average. If you are formed exclusively for Medicare, it is much harder to take risks. But to make this leap to ACO contracting with commercial plans, you will need the technology and data to support payer-specific data, quality measures and reporting, and analytics. Your clinical interventions may need to be payer-specific because of benefit plan inclusions or exclusions.

In any case, your data must start with provider data systems while you negotiate and build the payer claims data that many commercial plans are unwilling to release. Your ability to contract with private health plans in addition to Medicare will fuel growth and engagement for your clinicians, but requires a knowledgeable contracting strategy. Of course, before entering into these arrangements, do your homework—patient-identified claims won’t be a part of your arrangement unless they are in your private health plan agreement!

Some ACOs balk at the idea of a two-sided risk model in addition to all-patient reporting, but it makes contracts with private health plans much easier to negotiate. Although the market continues to evolve, a current advantage of private health plan arrangements is that risk-based payments have been less common. Create your capacity now for these arrangements with small, payer-specific populations. This strategy can build your expertise while you are adopting technology and gaining data. This is increasingly recognized by providers—in fact, the number of patients currently covered by private plan ACO arrangements is greater than those in Medicare ACOs.

Build Capacity to Live in the Population-Based Payment World

CMS and other payers have united against continuing Fee-for-Service reimbursement. Most in the payer industry are moving toward population-based payments, but many also acknowledge that it might be necessary for the industry to create mandatory models to lure providers away from Fee-for Service.

Physicians are already recognizing that population-based payments and Value-Based Care arrangements are inevitable. They are moving to corporate health care through equity or payer practice purchases and ACO enablers backed by capital. Much of the change in physician attitudes is due to the volume drop-off during the pandemic, where health care spending decreased at a greater rate than overall consumer spending. Physicians have become acutely away of the inconsistency of fee-for-service revenue, as well as how a population-based reimbursement ensures a stable revenue stream.

But you must have built the Value-Based Care infrastructure to be able to succeed under population-based payments. That’s the key promise that corporate medicine has made to physicians and the reason why physicians are willing to take the gamble. Your key first step, aggregating all-patient data that can be activated in Value-Based Care Technology, starts with the very data you need to report for APP.

Value-based reimbursements supported by both provider patient data and all-inclusive, patient-identified claims data will give you the fundamental ingredient you need to participate and succeed in value-based reimbursements: data sufficiency.

In short, you can turn the APP into a springboard for improvement, growth, and engaging your clinicians. Partner with a Clinical Data Registry that is qualified as a Third-Party Intermediary. Then use your data in real Value-Based Care technology to perform the best quality reporting, episodes of care analytics, and interventions to target and improve patient outcomes and costs. Using that information, align your compensation and reward structure internally, expand your patient reach, and empower your population health.

The APP is about a lot more than how you report quality. It is your segue to having greater knowledge and tools to transform the health care of your patients and community.

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: Jörg Angeli

With the release of the 2023 Physician Fee Schedule Final Rule, CMS upheld its commitment to sunset its Web Interface for ACO quality reporting after 2024. Beginning in 2025, ACOs will be required to report through the Alternate Payment Model Performance Pathway, or APP.

Some have expressed concerns about the APP. But this new reporting process actually has some significant advantages. It presents ACOs with a valuable trove of data to advance along the path toward better outcomes, health equity, and curtailed costs. In fact, the baseline for APP—data from provider systems, including their EHR data—is the foundation for data sufficiency needed for Alternative Payment Models, including risk-based reimbursement.

To ensure that your ACO is ready for the APP transition and to reap those benefits, it’s imperative that you understand the APP itself, where the challenges lie, and how you can harness it to improve your ACO’s standing and patient care, both in the short- and long-term.

What Exactly is the APP?

The APP is a method of reporting quality measures for APMs, including ACOs. The CMS Web Interface is sunsetting after the 2024 performance year, meaning that ACOs have a maximum of two more performance years to transition from reporting on a subset of Traditional Medicare patients to reporting on all patients. Note that “all” doesn’t just mean “All Medicare” (including Medicare Advantage, for example); it truly means all patients, regardless of whether they are covered by private insurance, other public coverage, or paying out-of-pocket.

ACOs report three measures via the APP, rather than ten when reporting through the Web Interface. These three will look familiar, as they are part of the existing Web Interface pool:

• Diabetes: Hemoglobin A1c (HbA1c) Poor Control (Quality ID 001);
• Preventive Care and Screening: Screening for Depression and Follow-up Plan (Quality ID 134);
• Controlling High Blood Pressure (Quality ID 236).

The APP also includes a pair of measures that CMS will calculate through an analysis of its administrative claims, along with the CAHPS for MIPS survey. Those three metrics do not need to be reported by the APM entity, but that entity will need to find a CAHPS survey vendor.

The sharpest contrast between the APP and the CMS Web Interface is that the number of patients goes from a maximum of 248 per Web Interface measure to an uncapped APP denominator that will likely include tens of thousands of patients. For an ACO that has been auditing charts and manually entering quality data into the CMS Web Interface, the potential APP denominators are daunting. Chart abstraction is simply not a feasible solution. The only way for an ACO to report on these measures is to electronically harvest all of the results.

Some have questioned the legality of all-patient reporting, as CMS has neither the ability to see which non-Medicare beneficiaries are eligible for measurement, nor the authority to view their records. This is addressed in the manner of the submission. Rather than reporting the individual patient details to CMS, the measures are reported in the aggregate—the number of denominator-eligible instances, the number of total responses, and the number of responses by type: performance met, performance not met, or a denominator exception (e.g. a patient refuses to participate in a screening for clinical depression). No individual patient data is submitted to CMS; patient privacy remains protected.

To summarize: The APP requires fewer measures, but all patients. It is an accepted reporting option because the results may be captured electronically and submitted to CMS at the aggregate level. Many EHRs are already able to perform this function, reporting specific versions of these measures called Electronic Clinical Quality Measures (eCQMs).

Everything sounds like smooth sailing until you look at the measures themselves. That’s where the process can seem daunting.

All-patient reporting has been part of the non-APM MIPS reporting process since MIPS was introduced by MACRA legislation, beginning in performance year 2017. However, while MIPS reporting practices are often on the same EHR, making it easier to harvest the data, this is not universal. Many large systems have groups on multiple systems and with multiple TINS, making it necessary to integrate the data to ensure that patients can be cross-populated by provider services in the aggregated group.

So, What’s the Controversy?

APP measures require the most recent value for each unique patient, and the connections between EHRs are not so straightforward as a data submitter’s connection to the CMS API. Many ACOs with disparate EHRs are not able to identify unique patients from one source to the next. Medical Record Numbers vary by system, and data privacy concerns mean that fewer patients are providing Social Security numbers, ruling out that method of matching. (For the record, however, experience has shown us that SSN was less of a useful identifier than expected.)

So, while each EHR may be able to perform these calculations within its active provider lists, there’s no “all ACO” view unless the ACO integrates practice data and uniquely identifies individual patients across the ACO. This aggregation is not as simple as adding each EHR’s scores together, which produces invalid results. Since measures require the most recent values for unique patients, simple EHR aggregation will double- (or more) count patients in APP measure denominators, although only one of the measure numerators should be used.

This means that an ACO comprised of multiple practices will need to deploy more sophisticated technology that tracks a patient across the continuum of care, calculating quality measure numerators and denominators at the ACO level for all patients. That’s a new bar for ACOs.

But APP Concerns are Based on False Assumptions

The belief that all-patient reporting through the APP will not be feasible for ACOs is tied to the two Big APP Myths, both of which are demonstrably false:

• Big Myth 1: APP reporting is prohibitively expensive.
• Big Myth 2: APP reporting cannot be accomplished within such a short time.

Here’s how you solve the data aggregation conundrum: partner with an Advanced Clinical Data Registry that has qualified as a Third-Party Intermediary. These firms can take data from disparate sources, aggregate the information and use their experience to match patients between one entity and another, and create a unique patient record that reflects all services from across the system. Simply put, they ensure that the John and Jane Does in one practice should (or should not!) be matched with the John and Jane Does in another.

This gives you the true count of unique patients and the most recent results for each, meaning that you can accurately see and submit your quality measures to the APP. The system works for both eCQMs and MIPS CQMs, so if your partner is ONC-certified, they can submit either version, depending on your ACO’s needs.

Not only does a Third Party Intermediary solve the reporting problem, but also it can execute the process more quickly and efficiently, for less cost, than a series of vendor-driven EHR-to-EHR interfaces. Better still, should an EHR within the system have limited options for packaging and sending data, some Third Party Intermediaries can blend the QRDA files used for eCQMs with non-standard files. If a required data element is missing, your Clinical Data Registry partner can work with you to determine the most cost-effective manner of retrieving it (e.g. a targeted data query, an established standard, or a combination). For those who have waded into the depths of EHR migrations, implementations, and interfaces, you can rest assured that the timeline is weeks, rather than months (or even years).

Two Options for APP Reporting

As for the reporting itself, there are two options for reporting these measures: Electronic Clinical Quality Measures (eCQMs) or their MIPS counterparts (MIPS CQMs). Both track the same information, but they’re calculated slightly differently.

The eCQM version prohibits any manual intervention; the measure is calculated by the EHR based on patient eligibility and whether the clinical data is documented in the appropriate spot.

MIPS CQMs provide more latitude. Patient eligibility is still fixed, but the numerator data may be obtained in several ways, including targeted data queries. Customized workflow templates can help speed up documentation during a visit, but when that eCQM is calculated, the information in the template may not be synced with the field that the EHR is using for calculations, and performance will suffer.

On the other hand, a MIPS CQM’s numerator can use the results from the template, even if they’re stored in a different table than the one that the EHR uses to populate measures. In an ACO where documentation is inconsistent from one practice to the next (and sometimes, even in that same practice), having a partner who can use files that can be manually cobbled together or direct entry, this can be a game changer.

Having a comprehensive view of your ACO will also bring advantages far beyond quality reporting. In a future blog, we’ll explain how ACOs can leverage the view they need for quality reporting into a more holistic, value-based care approach, including the management of complex populations—particularly the ability to identify patients who are at risk for high-cost outcomes (or worse) and appropriate interventions. It will also give you the ability to demonstrate clinical excellence to other health plans and use this to your advantage during contract negotiations. Having the full picture enables you to create a proactive, rather than reactive approach, and will promote shared savings. Most importantly, it will mean better health and a better clinical experience for your patients.

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: Oliver Cole

It’s here. The 2023 CMS Physician Fee Schedule Final Rule has been released, and in a mere 3,304 pages, CMS has largely finalized its proposals from over the summer. To save you from pouring through all the minutiae, here’s what you need to know.

Overall, in this Final Rule, CMS has codified principles to fulfill the goals outlined in the Innovation Center’s Strategic Refresh of October 2021. Most notably, CMS has committed to having all Traditional Medicare beneficiaries in an accountable care program by 2030, and to prioritize health equity.

To make this happen, CMS needs to shake up the status quo. ACO participants have plateaued, and underserved and minority patients are underrepresented. So, here are CMS’s eight key strategies to break down barriers for new ACOs, move clinicians out of Traditional MIPS, and provide entities the resources they need to care for patients from all walks of life:

1. Provide Advance Incentive Payments (AIPs) to Accelerate ACO Growth

Among the biggest barriers to entering the ACO market are startup costs. These are particularly problematic for smaller, physician-led groups, and groups in rural markets. To overcome this obstacle, CMS will provide advance shared savings payments to Low Revenue ACOs that do not have experience in two-sided risk models. As a refresher, a Low Revenue ACO is one with combined A and B expenditures that are less than 35 percent of its population’s total A and B expenditures. These tend to be physician-led ACOs, rather than hospital-led ACOs, as a hospital or health system will account for more than 35 percent of costs.

These Advance Incentive Payments (AIPs) may be used to staff up, to invest in the technical infrastructure needed to measure and improve patients’ health, to provide care for underserved beneficiaries, and to address Social Determinants of Health (SDOH). AIPs will consist of a one-time, upfront payment of $250,000, with two years of quarterly payments to follow. These payments will vary and will be higher for ACOs whose populations reside in a high deprivation area (measured by the Area Deprivation Index) or who are dually eligible. CMS expects these AIPs to increase ACO participation and the number of beneficiaries covered under ACOs, and, specifically, to bring in patients who are underrepresented in the existing ACO beneficiary pool.

2. Allow ACOs to Delay Two-Sided Risk

In a major departure from the “Pathways to Success” Rule, CMS will allow ACOs without performance-based risk experience to take additional time before transitioning to a two-sided model. These ACOs can remain in a one-sided arrangement for the entire five-year agreement, plus the first two years of the next agreement, rather than automatically graduating to risk after two years.

There is also good news for existing ACOs. Those without performance-based risk experience can remain in a one-sided model for the remainder of their agreement. ACOs who do have experience with risk may remain in the final level (Level E) of the BASIC Track in perpetuity, rather than being forced into the ENHANCED Track. Both BASIC Track Level E and the ENHANCED Track qualify as Advanced APMs, but the ENHANCED Track carries more risk.

3. Address the Ratcheting Effect in Existing Benchmarking Methodologies

One of the most frustrating issues for ACOs has been benchmarking. When an ACO performs well and generates savings, the existing benchmarking methodology raises their bar for the next year—the better they do, the more is expected of them. This “Ratcheting Effect” is felt in the Regional benchmarking and prior-beneficiary spending components of benchmark calculations, continually diminishing an opportunity for savings, and potentially leading to losses.

As an ACO’s market penetration increases, CMS will assign less weight to the regional component of the regional-national blend and add more to the national component. The amount that can be negatively adjusted based on region has decreased from 5 to 1.5 percent. This is particularly good news for ACOs who comprise the majority of their respective markets. In earlier years, ACOs with high market penetration would produce savings in their area, only to find their cost benchmark reduced as well. Since spending was reduced in the region, the ACO was expected to spend less, even though the reduced spending was the direct result of that ACO’s efforts.

Benchmarks will also account for prior savings, which was a frequently lamented issue in past years. Previously, if an ACO demonstrated success and earned shared savings, their benchmark would be lowered to reflect decreased beneficiary spending. In other words, by performing well in one year, the ACO sabotaged its chances of success in future years. Benchmarks will now have per capita savings added back into their benchmark, which will limit the ratcheting effect on the rebased historical benchmark. Furthermore, CMS finalized its proposal to factor the Accountable Care Prospective Trend (ACPT), a growth factor similar to Per Capita Cost, in its benchmarking methodology. It will be established at the beginning of the ACO’s agreement period, and it will be fixed. This will provide consistency and help to mitigate an ACO’s impact on its own benchmark.

4. Encourage Quality Reporting on All Patients

The 2024 year will be ACOs’ last opportunity to report quality measures through the CMS Web Interface. With this transition looming, CMS has been attempting to entice ACOs to report electronic clinical quality measures (eCQMs) or MIPS Clinical Quality Measures (MIPS CQMs) through the Alternate Payment Model Performance Pathway, or “APP.” These measures include all patients (e.g. private health plans, Medicaid, self-pay, etc.), rather than a subset of Medicare patients. Reporting on the entire population promotes equity by adopting a single, high standard of care for all patients. However, these efforts have been largely unsuccessful. As of 2021, only 12 ACOs opted to report eCQMs/CQMs instead of the Web Interface.

There are two primary reasons for this delay. First, for ACOs comprised of different practices on different EHRs, the ACO has not developed a data aggregation solution that enables them to track a patient from one practice to the next. CMS claims data only includes Medicare patients, and so the remainder of patients are unaccounted for. Aside from the obvious quality gap this will cause with respect to outcomes and costs, it also precludes accurate numerator and denominator calculations, as measures apply at the patient level (not the patient-practice level) and may require the most recent value. Those who cannot track patients across the network cannot report through the APP.

Second, by including all patients, performance may suffer for ACOs with large underserved populations. Social Determinants of Health and income inequality play a significant role in poor outcomes for patients with chronic disease, and so ACOs are likely to see performance rates drop when reporting globally. This is the polar opposite effect that CMS has intended with regards to health equity, and this Rule needed to incentivize ACOs to report through the APP, and to do so before the 2025 requirement.

They have addressed this issue in several ways. In particular, they have eased performance requirements for those reporting eCQMs/CQMs for all patients.

In 2023, if the ACO meets the data completion threshold (70 percent of eligible patients, just like in MIPS), the ACO’s quality performance score only needs to equate to the 10th percentile of the performance benchmark for one of the outcome measures, and the 30th percentile for the others. CMS Web Interface reporters are held to a higher standard, needing to achieve a score at or above the 30th percentile in all categories.

In 2024, the ACO will need to achieve the 40th percentile on the other measures, but the outcome measure will still only require performance at the 10th percentile. Those reporting via the Web Interface have their bar raised, as well, needing to achieve a score equivalent to the 40th percentile in all categories. Once eCQMs/CQMs reporting becomes mandatory (beginning in 2025), an ACO must report via the APP and achieve the 40th percentile in all measures to earn the maximum rate of shared savings.

In addition to these eased performance standards in 2023 and 2024, ACOs who report the all-patient measures and who serve a high rate of underserved patients may receive a Health Equity Adjustment consisting of up to 10 points towards their Quality Score. To further sweeten the deal, CMS is instating a sliding scale approach for quality performance. Rather than the previous “all-or-nothing” approach, ACOs will still be able to share some savings, even if their quality performance is lacking.

5. Reduce the Appeal of Traditional MIPS

Even though CMS has offered a bounty of benefits for those who start or continue on the ACO path, many would rather stay the course in Traditional MIPS. After all, scores have been high, and while the bonuses have been underwhelming, penalties have largely been avoided. To get people out of Traditional MIPS, CMS must either sunset the program (which was mentioned, but no timeline was adopted) or make it challenging enough to prompt entities to consider alternate methods of Quality Payment Program participation. In this rule, they have opted for the latter.

Although there are 200 quality measures to choose from in Traditional MIPS, they are not distributed evenly among specialties. As a result, certain specialties (e.g. anesthesiologists, hospitalists) are locked into a relatively small set of measures. When these measures are not benchmarked, or where a quirk in the denominator limits the number of eligible patients, these measures have previously earned 3 points out of a possible 10.

This has hurt scores, but at least 3 points was something, and could be made up in bonus points earned by reporting additional outcome or “high-priority” measures. In 2023, both the 3-point floor and those bonus points are going away, meaning that scores in 2023 can plummet, even if reporting on the same measures used in 2022. With participants again needing to earn an overall MIPS score of 75 to avoid a penalty, the elimination of these points can be profoundly detrimental.

6. Transition to MIPS Value Pathways

CMS continues the MIPS Value Pathway (MVP) rollout, finalizing the five new proposed MVPs along with the previously established seven. Their goal is to eventually replace Traditional MIPS with MVPs; additional MVPs are in development, and groups will be allowed to submit MVP candidates to CMS for approval. This will ensure that all clinicians will have a valid participation option.

For multispecialty groups, CMS has reaffirmed that, by 2026, subgroup reporting will be mandatory, but optional from 2023 through 2025. Subgroups will be defined using Part B Claims data, but during registration, subgroups will have the opportunity to describe their construction (e.g. “this subgroup represents our orthopedics service line, consisting of orthopedic surgeons, sports medicine physicians, physical therapists, and nurse practitioners”). For scoring purposes, a provider (defined by TIN/NPI combination) may only participate in one MVP. Of course, a provider may be involved in care related to another MVP, but that provider would only be scored in the MVP in which they participate.

MVPs are intended to replace traditional MIPS, but no timeline for that has been finalized, and so MVPs will remain optional for the foreseeable future.

7. Increase Focus on Interoperability

All programs under the QPP umbrella are required to report Promoting Interoperability (PI) measures to demonstrate how effectively their EHR facilitates communication between providers, patients, and other entities. Updates to these measures affect everybody, and 2023 brings significant changes that reflect CMS’s strategies to improve data security and patient safety, to eliminate “Information Blocking,” and to facilitate data sharing between EHRs and Public Health and Clinical Data Registries.

More providers will be required to report on these measures. Nurse Practitioners, Physician Assistants, Clinical Nurse Specialists and Certified Registered Nurse Anesthetists receive automatic PI reweighting in 2022, but beginning in 2023, they must participate.

PI scoring has also been revised, with more weight placed on the Public Health and Clinical Data Exchange objective and less on the Health Information Exchange objective. Furthermore, the definition of “Active Engagement” with respect to the Public Health and Clinical Data Exchange measures has been changed from three options to two. Participants will need to submit whether they are in the Pre-production/Validation stage or have moved to Validated Data Production. Beginning in 2024, clinicians will only be allowed to submit the first option in one performance period, unless they are establishing a connection with another Registry.

8. Request Feedback on How to Incentivize APM Participation

One hitch that CMS has encountered in transitioning people into APMs is that the final 5 percent lump-sum APM payment incentive is being paid in 2024, based on 2022 performance. It will not be available for 2023 APM participants. CMS recognizes that this may act as a disincentive to Advanced APM participation, and they are looking for feedback on how to address this, but there will be no action until 2024. There will be a conversion factor applied to APM Qualified Participants (QPs), but it will not eclipse the incentives that CMS expects MIPS participants to earn.

In the meantime, though, the Generally Applicable Nominal Risk Standard of 8 percent (the total risk shouldered by the APM) will not expire, and in fact, will become permanent. This also applies to Advanced APMs under MIPS, as well as to ACOs. With maximum MIPS penalties set at 9 percent, even the most risk-averse entities should consider APM participation.

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: Keith Hardy

If you’ve followed the Smart Guide articles so far, your APM is ready for take-off. You’ve developed a data-sufficient technology infrastructure with both provider and claims data, carefully constructed your clinical network and engaged your clinicians, and implemented strategies for payers and consumers. Your APM may be operating already, with data ready to use.

Now you are at the crossroads, and your choice will determine whether your APM will really transform outcomes for your patients and achieve maximum Value, or whether your APM will be average. That choice pivots on interventions. Only through specific interventions with clinicians and patients can you change the trajectory of costs and outcomes. Let’s dig in.

Interventions as a Data-Driven Queue-Up for Patient Treatment Changes

The point of intervening is to change the course of events before those events happen—patient crises, for example. But many APM entities go about dealing with events in the reverse order: identify a patient crisis that culminated in an admission, and use population health outreach to bring the patient in for a visit or other intervention. This is appropriate to do. But it is better to do more with your data before the events occur, potentially averting a crisis. Your data should be able to identify patients at risk of failure before it happens.

We all know the saying about lightning not striking in the same place twice. If you believe that your patient who was called in after a crisis has improved because of outreach, that may be true. But relying on that strategy means that each measured improvement depends on having a patient in crisis, to begin with, necessitating an expensive event. A better strategy is to create a system that ensures your patients are improving without entering crisis mode, which means you need to engage clinicians in reviewing outcomes and intervention criteria before the crisis occurs.

What are intervention criteria? They are clinical and treatment criteria that point to an impending problem. Longitudinal outcomes that show persistently poor control in Type 2 diabetes are one such indication, because failure to deal with diabetes will result in its exacerbation and likely crises. But more important, combining this characteristic with medication evaluation, lack of appropriate specialist involvement, visit adherence, and potential social determinants of health will create the opportunity for specific improvements in patient treatment and avoid further deterioration of the patient’s health. Other conditions have similar constellations of outcomes and clinical symptoms that can be used predictively to stratify patient risk.

As a result of this data process, a patient may be queued into interventions for clinician review of medications (which could result in SDOH revelation and referral to financial resources), referral to a specialist, and prescribed nutritional services. Review of A1C levels may also result in continuous glucose monitoring and implementation of a self-management program.

Interventions to Refine Clinical Pathways and Clinician Engagement

You can also use interventions to help clinicians improve treatment plans. By creating episodes of care for conditions and procedures, you can plot variations in costs or outcomes across groups of patients. This allows you to differentially identify contributing factors to the episode costs or outcomes.

The point is to investigate variation, not judge, so that clinicians can collaboratively address refinements in pathways for both conditions and surgical procedures. Because longitudinal data and costs (especially patient-identified) have been so rarely provided to clinicians, a learning process is critical. By using episodes of care, all clinicians across disciplines can share in the investigation.

Five Intervention Strategies to Fuel Your APM Liftoff

1. Create a two-prong intervention strategy that empowers clinical interventions in (a) chronic disease and (b) specialty medical/surgical.

ACOs and other primary-care-focused APM entities frequently focus interventions on chronic disease patients, adding higher utilizers and other patients at high risk. Because these are the patients of primary care participating providers, this makes sense. However, it’s not enough.

With 40-60 percent of costs driven by specialists, you need to include specialty partnerships in your intervention strategy. You can achieve this with specialty partnerships that cement your referral network into a mutually beneficial collaboration based on data sharing, communication, and collaboration on referral criteria and treatments. This strategy enhances value to your patients and both primary and specialty physicians, providing avenues down the line for streamlining care as well as improvements.

Clinical interventions, which can be supported administratively through patient navigators and other clinician support means, are essential. The only way to reach ultimate value is to deliver better care that prevents advancement of disease as long as possible.

2. Use clinical episodes of select conditions and treatments as the basis for review of costs and outcomes.

Don’t limit your view of costs to category of service. Fee-for-service categories don’t make much sense in the APM world, where cost is calculated by all the care delivered to patients over a time period (per patient per year). For conditions, this time period is generally described as a year; for procedures or specialty incidents, for the period covered by the incident and any appropriate pre- or post- services such as imaging or physical therapy.

Clinical episodes enable you to create a unit of comparison. Consider these questions to get you started:

• What effect does differential use of anesthesia agent have on your costs or patient recovery?
• In how many of your patients may therapeutic inertia be a problem, and why?
• Which patients with both obesity and diabetes are on insulin-only?
• Why were some cholecystectomies performed as open procedures with higher costs versus laparoscopically?

Episodes of care are not magic, but allow your clinicians to evaluate the inputs of one case against the inputs of another and assess the results of each. And episodes of care also allow clinicians to examine costs in a way that makes sense to them—as a total of all services provided to a patient within a finite time frame.

Construct your episodes only for key areas of chronic disease and specialty services in your patient population—unless you are an academic or specialty-driven organization, where delving into episodes through the specialty side makes sense for specialty care models, research, and care pathways.

3. Start with clinical questions, and then activate data to identify potential interventions.

Interventions are the test of your data sufficiency, but only if you ask the right questions, first.

For conditions, the question of whether the patient is on track starts with clinical data, notably outcome values over time. If your data is not identifying these outcome values, there is more to do. Either your clinical data is not integrated with your claims data, or your clinical data is not being transported correctly into your repository. If your data is missing medications, then you will need to find prescribing or filled-benefit information from your EHR and/or claims data, most likely the former.

For procedures, claims data will provide a good supply of transactional information, but you may be missing diagnoses and outcome values coming from EHRs. This is one reason why specialty partnerships are important.

The less sufficient your data to fuel interventions, the harder you’re making it for your clinicians to review cases, which is both unfair and less effective.

4. Create a connection between interventions and health equity efforts.

You will immediately reveal health equity issues in reviewing patient episodes, especially for conditions. Cases where patients had no referrals, no treatment changes over years, and lower-level medications should all trigger reviews of patient circumstances that could point to lack of health equity. One solution is to use your patient navigators to interview (or visit) patients for a full understanding of their situations. Alternatively, a better approach may be to connect with community organizations who are already working with your patients.

Enriching your social determinants of health data is an important conduit for both improving your Value and for providing support for patients. You may also be able to include patient family and other support to your patient care team and magnify the effects of your interventions.

5. Test the effectiveness of your interventions.

Don’t make your interventions an intuitive program. Rather, back it up by verified data. You want to know that your clinical interventions are working, and in what patients, and how long it takes. You should be able to examine the critical points of failure in your process as well as in the data or the interventions themselves. The key to improvement is understanding what works, and what has not. Ensure that your system is capable of tracking every intervention event, the effect of that event, and the data results going forward. That creates the knowledge for changing the process or the people involved in it.

Interventions foster change. They have the power to transform the inevitable trajectory of a patient’s story into a better narrative, altogether. Well planned and executed interventions can completely transform the lives of many patients—and your organization. This is the nexus where all your organization’s efforts coalesce to create Value. Make the most of it!

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: Brian McGowan