ACOsAPP ReportingValue-Based Health Care

Three Lies and a Truth About ACO Data for APP Reporting

By February 2, 2023 One Comment

Roji Health Intelligence ACO Data APP Reporting

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.

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