The Truven Health Blog

The latest healthcare topics from a trusted, proven, and unbiased source.

The Five Key Components of ACO Analytics

By John Azzolini/Tuesday, August 30, 2016

Accountable Care Organizations (ACOs) were created to provide financial incentives for providers to control costs and improve the quality of care. As they continue to advance, it is important for both providers and payers to ensure that risk is being appropriately shared between the two. This creates a unique set of challenges in determining the best way to design, manage and evaluate these programs. Whether you are running an ACO or contracting with one, data is integral to determining the best model. Without the proper data, those providing the care, and those paying for it, are flying blind.

What’s more, not all ACOs are created equal, with three general types of models accounting for the bulk of ACOs: employer-sponsored, employer-direct contracted, and those leveraging existing insurer relationships. The analytic tools used to evaluate performance will depend upon which type of relationship a payer has with the ACO.

The ACO Analytic “Tool Box”

The five analytic methods listed below are key for ACOs managing program performance, and for employers and health plans assessing the value they are obtaining from these programs.

1.       Attribution

All measurement depends on a connection made between the ACO and/or its providers and enrollees. As a result, we need to uncover who the enrollees are, and for whom the ACO is bearing risk.

Often, explicit patient assignment does not exist. Where it does, the evaluation models need to incorporate it into analytic databases. In the cases where it doesn’t, the ACO needs to perform that attribution based upon the observed pattern of care received by the patient population.

2.       Population Health Management

There are multiple tools available to identify and stratify patients, such as predictive modeling, where risk scores based on age, gender, and diagnosis are employed. Other methods employ biometric or health risk assessment information. Examples of these include Health and Longevity Scores, Health and Productivity Indexes, and Health Status/Opportunity Scores, that can be used to segment patient risk levels.

3.       Network Management

If an ACO is at financial risk for the management of individuals, it’s imperative to know where people are receiving health services, what kind of utilization is taking place out of network, and where those out-of-network services are being given.

Many beneficiaries are not locked into the ACO network, which makes knowing whether these services are being given by high quality, efficient providers paramount.

4.       Program Evaluation

It’s important for everyone involved through the continuum of care that an assessment be made on the effectiveness of the ACO. As anyone who has been involved in care evaluation can tell you, there are a host of methodological pitfalls that can throw a wrench into measuring program evaluation. Controlling for differences between populations – specifically those who use the ACO and those who do not – is exceedingly important to determine the effectiveness of that ACO.

5.       Quality Measurement

In addition to evaluating ACOs on the basis of financial performance, establishing core quality measures for ACOs enables us to glean insights we would otherwise not have. Metrics such as potentially-avoidable admissions, screening rates, and specific process and care measures give us a baseline for quality measurement that is imperative in defining how well the ACO is performing.

Embrace the Risk

Risk is a fact of life in healthcare; it always has been. But in this new landscape, the ways in which both providers and payers are sharing that risk has undergone a drastic shift. Everyone will assume risk, but as we’ve outlined above, the key is to understand and properly allocate that risk between providers, patients and payers. The data is there; to guide these decisions, the key is employing the appropriate tools to establish this balance.

John Azzolini
Senior Consulting Scientist

A Data Scientist Thinks About Population Health Management

By Anne Fischer/Wednesday, August 24, 2016

(The Truven Health Advanced Analytics team is tasked with building new and differentiating analytic methods. Asked to explain some interesting new analytics that are important for managing populations, the Advanced Analytics team wanted first to explain how they’re thinking about Population Health Management.)

What is Population Health Management (PHM)? Much like the adage about the blind men and the elephant, Population Health Management can mean completely different things to different audiences. Hospital systems, practitioners, government, and private insurers all have different interpretations of what the term means. And, in fact, its implications are very different to each of these players.

For most health systems, PHM represents a complete paradigm shift from their traditional way of doing business. Think of it like this: Imagine you own an auto-repair business. Perhaps you have a single facility, perhaps a chain of facilities. You are generally responsible for fixing a car when it’s damaged, and perhaps also performing routine maintenance on that vehicle. Now imagine you are being told that:

  • You are no longer simply responsible for the car when it is in your shop, but you are responsible for the car’s general care and maintenance for its lifetime.
  • The insurance company is no longer paying for the specific services you provide, they are paying you based on the overall “health” of the cars that you service. You now need to know what happens to that car outside the walls of your facilities.
  • You are no longer simply repairing the car when it needs it, you are being paid to keep the car “healthy” and out of your repair shop.

Imagine how foreign that would seem. You have no information about the drivers of the car other than what you can gather publicly. You have no idea what kind of driving record a person has, what kind of routine maintenance they perform on their car (except that which happens to occur in one of your shops), or what kinds of roads they drive on. In short, you have no knowledge of what kind of risk they bring to the table.

Hospital systems are in this situation. Historically, they have not needed to know much about their patients outside of what occurs within their facilities. They don’t have much information on where their patients are seeking care outside of their facilities, what kind of preventive care they are taking, what their social determinants of health are, nor how risky each patient is in terms of lifestyle and overall health, and they don’t have any input to their patients’ health benefit programs.

Now imagine you are the auto mechanic. Your repair shop owner is now asking you to understand the entire spectrum of a given vehicle you are servicing. Perhaps your specialty is body work, but you have to start thinking about the gas mileage and the health of the exhaust system in every car you see. Similarly, practitioners – particularly those who are not primary care physicians and are not used to thinking about “the whole patient” – struggle with the concept of population health because their focus is typically on one patient and one problem at a time.

Taking the analogy further, imagine you are the auto insurer (payer). You have historically managed payment for all the expenses for a given driver (and adjusted your rates to that driver based on their record/perceived risk). However, in this analogy as a healthcare insurer, your ability to refuse coverage to someone is diminishing, and your ability to assess risk is out of date, given that all drivers seem to be getting progressively worse and consequently more expensive. You are eager to shift some of that payment risk to the auto mechanics who are far more “hands on” with the cars, but there is no framework in which to plan and agree to terms. Plus you are still expected to maintain the risk for random “Acts of Nature” such as trees falling on cars, lightning strikes, and accidents caused by others. You are used to thinking about risk stratification and management at the group level, less so at the individual level.

Finally, imagine that you are the civil engineer responsible for designing the infrastructure on which the cars travel. You design roads to accommodate certain volumes, speeds, and types of vehicles, and support laws to enforce speed limits and construction zones. (Besides being the largest healthcare payer, this is the other role government plays in healthcare.) But now you’re being asked to help understand and contribute to improving the overall “health” of the vehicles on your roads, to do this in a way that minimizes the frequency and scope of needed repairs, and to do it all on a reduced budget. Oh, and at the same time, you have to be thinking about how to ensure safe roadways and service for new kinds of cars – self driving, connected, and beyond. . .

So how can Truven Health help? Our job as the analytics specialists is to help provide the information needed to expand the view of patients, and to present the information so that it’s actionable. Providing information on the full spectrum of care, even for something as specific as a surgical patient receiving a joint replacement (as our Bundled Care consultants do), can be invaluable in helping facilities, practitioners and payers understand the downstream implications of the care that is delivered. Helping them understand which patients are at high risk for “collision” (such as our new Risk of Hospitalization models) can lead to timely, cost-effective interventions. Identifying which segments of the population could most benefit from management (such as our forthcoming population classification method) can help focus activities for guiding patients and members towards health and well-being. Bringing valuable analytics to life can only happen if we first understand where our clients are coming from, and second, where they need to go to continue to be successful.

In coming blog posts, I will offer insights into the work of data scientists and into the analytics we are developing to help our clients continue to be successful.


Anne Fischer
Senior Director, Advanced Analytics

How Ready Are You for Value Based Payments?

By Truven Staff/Tuesday, August 16, 2016

There is a great deal of discussion and analysis about the shift to value based care as healthcare payers – employers and health plans -- contemplate new models of care. The Department of Health and Human Services (HHS) is already driving the change – by setting a goal that 30 percent of fee-for-service Medicare payments be tied to quality or value through alternative payment models (such as bundled payment arrangements) by the end of this year, and 50 percent by the end of 2018. Is your organization ready to make the move?

Truven Health has been consulting with payers on everything from their payment strategy to their risk tolerance, and we’ve learned that organizations are in varying stages in their journey to value based payments. Some are very far along, some are just starting, and others are unsure of where to start. In helping payers think about their journey to value-based care, we’ve developed some guidelines on how to begin.

If your organization is just beginning the journey, we recommend you ask yourself a few key questions: 

     What are our biggest opportunities and challenges? Have we validated potential financial and operational risks?

     Do we have adequate market and volume to justify the investment and minimize risk?

     How are we aligning with physicians to support adoption and population health management needs?

     Does our approach support our identified value based payment model strategy and objectives?

     Is our strategy agile and sustainable as new models continue to emerge?

A thorough assessment of your readiness for a new payment strategy should include:

     Analysis of your proposed payment model, including design implications, incentive structures, quality, provider alignment, and integration

     Evaluation of your opportunities, challenges, and readiness to implement bundled payment definitions and pricing

     Review of your performance measurement reporting, including gaps and an impact analysis

     Assessment of data feed adequacy, quality, and clinical and financial implications

The journey to value-based care and payment will not happen overnight. Payers and providers will need to collaborate, learn, and adjust their approach to various approaches before finding their best fit. The key is to have information and analytics to support the process, and a partner with holistic and deep experience across the entire claims and revenue lifecycle. 

For answers to your questions about value-based payments, or for help devising a payment strategy, contact us at payersolutions@truvenhealth.com.