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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

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