So what can Massachusetts do to address their risk adjustment woes? They are taking a step in the right direction by recognizing that data quality is at the core of any corrective action.
Recently, Healthcare Payer News detailed the risk adjustment woes of Marketplace-participating health plans in the state of Massachusetts that are also a part of the Massachusetts Association of Health Plans (MAHP).
Two statements stand out among all others in this article about the supposition that flawed data will skew the Massachusetts risk adjustment program, which operates differently than the Federal risk adjustment methodologies being used everywhere else for the implementation of the Affordable Care Act (ACA).
Both statements are from MAHP CEO Lora Pellegrini: "As implemented today, we…have no confidence in the integrity of the data…" and "risk adjustment simulations for the second and third quarters of 2014 were impacted by significant inaccuracies in the data being extracted from the all-payer claims database…the overall scope of the identified discrepancies is still unknown to MAHP and our member plans."
As a result of these discrepancies, MAHP warns of threats to the solvency of health plans facing risk-sharing transfer payments, and thus insurers and regulators are asking for a one-year delay to compare the state's risk adjustment methodology to the Federal standards being used everywhere else. It is interesting that Pellegrini stated that this delay is needed "to compare the state's risk adjustment methodology to the Federal standards being used everywhere else or to develop validation standards" -- but in reality, that "or" needs to become an "and."
The Federal standards employ validation rules that prevent the poor quality data that is described in this article as the root cause of these discrepancies, such as duplication of members, inclusion of members who are no longer eligible, or members enrolled in Medicaid.
It is important to note that if these very basic validations aren't being performed, then it is highly likely that other more critical validations affecting risk adjustment aren't being performed either. The Federal standards not only employ enrollment validations, but also basic claim validations and business rules to ensure that the data being sent by health plans is of sufficient quality to perform risk adjustment calculations. Plans, of course, are expected to remediate these errors; and additionally, if they are serious about maximizing their revenue, employ internal auditing programs inclusive of retrospective and prospective chart review to ensure that all diagnosis information can be considered for the risk adjustment calculation. The inability to submit complete and accurate diagnosis information could result in significant lost revenue for health plans, as age and gender weights rise in the risk adjustment calculation in the absence of complete diagnosis data. This, in turn, blunts the incentives of a risk adjustment program.
Though the Massachusetts dilemma and others like it may seem as if it was caused by circumstances beyond the submitting health plan's control, such as lack of data validations on the receiving end and the all-payer claims database, there are still critical activities that plans must perform to not only assure their revenue integrity, but also to arm themselves with business intelligence that will serve to enhance and improve the overall risk adjustment program being operated in the state.
These activities include monitoring key metrics and ensuring that their internal audit programs have these metrics at the core.
Accuracy: Without data validations on the receiving end, it is hard for plans to know exactly how to modify and maintain their data extractions to satisfy requirements, but at the very least employ a set of validations that is equal to what is required for inbound claims submission from providers – and use a variety of methods to address error correction. This also includes diagnosis coding accuracy, since these codes are a critical input to risk adjustment.
Completeness: Claims lag due to provider timely filing limits can prove to be a challenge when ensuring that a complete data set is transmitted in accordance with program requirements, but suffice it to say that the internal audit process should ensure that all required enrollment and claims data is submitted – including corrected data from those records that did not pass basic validation, adjustments, and integrations of supplemental diagnosis data resulting from chart reviews. It is hard to know what standard Massachusetts is applying to ensure completeness, but based on this article it sounds like that could be a major part of the issue.
Timeliness: Most risk adjustment programs have a published set of dates for final data submission, payment estimations leading up to final submission, and final payment. For example, for the Federal standards, all data must be submitted by April 30, 2015 to allow for a period of appeals for the resulting estimated payments. Plans must be able to quickly perform these critical estimation reconciliations all the way down to the member level; otherwise, they risk being out of compliance or revenue loss.
Quality: It could be argued that data quality is a combination of the previous three metrics, because if basic data validations are not performed to allow for error mitigation before submission, an incomplete dataset will result. Moreover, failure to correct data containing errors in a timely manner will result in lost revenue due to lower risk scores, since the diagnosis information on the records containing errors cannot be factored into the risk adjusted payment.
So what can Massachusetts do to address their risk adjustment woes? They are taking a step in the right direction by recognizing that data quality is at the core of any corrective action, but plans cannot wait for that to happen -- they must be proactive and arm themselves with revenue integrity preservation tools, inclusive of internal auditing. By so doing, they can confidently tell the story of their data without the pain of a surprise ending, and also to enable better inputs into the risk adjustment policies that will affect their plan operations.
Dawn Carter is a director of product analysis at Edifecs.