Over the past several years, regulatory agencies have issued numerous policies aimed at increasing accuracy and completeness of clinical information for risk adjustable programs like Medicare Advantage, Affordable Care Act populations, etc.
Regulations around what is and is not allowable for risk adjustment vary across different lines of business (for example, Medicare Advantage allows corrections in the form of supplemental submission, something Medicaid doesn’t allow at all in most states. Similarly, the ACA has regulations specifically stating that medical record reviews must be two-way (that is, not just reviewed for missed codes or under-coding, but with redaction to remove codes without suitable evidence, or instances of up-coding). For Medicare Advantage, there is, frankly, ongoing confusion and differences in interpretation and application in provider and payer organizations over what the actual regulations and requirements are. However, all of those interpretations boil down to reach one consensus: If you are reviewing codes for the purposes of risk adjustment to determine any inaccuracies or missed conditions, you are taking a corrective action. Best practices dictate that this includes redaction/deletion of unsubstantiated conditions or inaccurately up-coded severity. This is why two-way review, where redaction and addition opportunities are presented in a risk workflow, is critical to success, and why any technology platform you engage with has to provide that as a default. It’s the best way to support accuracy in submission.
Now, because chronically ill patients have greater clinical complexity and higher resource utilization–they are sicker, which is harder to treat and takes more doctors, lab equipment, beds, etc. and are therefore more expensive to care for. CMS quantifies RAF (risk adjustment factor) through past claims and supplemental diagnoses. The goal is to ensure the right amount of money is available to care for patients. Too little results in a shortfall, and too much is often linked to fraud, waste, and abuse. The accuracy of diagnoses is paramount, because organizational reimbursements are calculated, in part, based on individual clinical patient RAF.
That accuracy is ultimately ensured through the regulatory compliance described above, primarily via audits that validate codes linked to associated clinical evidence. If a code says a diagnosis is for a condition at a designated degree of severity, there needs to be a clinical narrative, with supporting lab results, treatment plans, or some other valid clinical data to back up that code. The goal is to mitigate fraud, but to also address any instances of accidental upcoding through systemic issues, lack of coder and physician education, or technological errors. The penalties are severe, too. Attempts to resolve discrepancies have also resulted in legal action taken on behalf of the United States Government. In those eventualities, taking as many steps as possible, but especially the three outlined below, to ensure accuracy (and therefore compliance) is critical, if for anything to bring a hurried resolution to any cases.
The first steps to supporting that accuracy with technology includes a two-way review as a baseline functionality. If it’s difficult for coders to identify and remove inaccurate codes that expose organizations to external audit risk, those codes may not be corrected.
Beyond that, in instances where conditions are added, automated chart-linking ensures clinical data validates any coding decision that impacts the risk adjustment factor. When an organization’s accuracy is measured by CMS in various audits that look at the information submitted to CMS (claims, and supplemental RAPS/EDPS data), when compared to the clinical documents which derived that data. The clinical documentation always serves as the ultimate source of truth. The more directly connected it is to an organization’s coding choices, the better they fare if and when that audit takes place.
Finally, given the volume of review coders will be undertaking, an intelligent prioritization of charts with the highest likelihood of inaccuracy flagged for coders is crucial. All of this functionality needs to be native and provided without additional cost; it’s a key component of success. Coders are experts and need to be free to apply that expertise to their work, but there is little that can beat the relentless attentiveness of technology and its ability to parse through all available data to guide those coders and help them prioritize their work.
Using a workflow enabled by technology that natively enables, and actively supports, both additions and redaction (deletion), isn’t just easy and cost effective, it has untold value beyond its intrinsic ROI through catching missed codes or coder productivity lifts, by helping to avoid CMS penalties in audits. It’s very difficult to fully quantify how expensive a negative result in an audit situation can be. In addition to the immediate outcome of a negative decision, there have already been cases resulting in 180 million-dollar penalties. There are also longer-term ramifications. If the subsequent adjustment of the corrected coding impacts an organization’s risk score enough, it will affect benchmarking, resulting in an additional multi-year adjustment of forecasting and financial resource availability.