To account for variations in illness burden throughout a Medicare Benefit (MA) plans affected person inhabitants, makes use of danger adjustment based mostly on affected person illness burden. Particularly, MedPAC notes that:
Medicare makes use of beneficiaries’ traits, comparable to age and prior Health circumstances, and a risk-adjustment mannequin—the CMS hierarchical situation classes (CMS– HCCs)—to develop a measure of their anticipated relative danger for lined Medicare spending.
In February 2023, CMS CMS printed a notice of proposed rulemaking to update their HCC risk adjustment algorithm (v28). These adjustments included (i) leveraging ICD-10 moderately than ICD-9 codes as the first constructing blocks, (ii) use of 115 HCC indicators moderately than 79, and (iii) constraining some coefficients to be an identical throughout severity ranges (e.g., diabetes, coronary heart failure). The brand new algorithm can be phased in throughout 2024–2026.
One key query is whether or not suppliers beneath conventional Medicare (TM) code in another way than Medicare Benefit (MA) plans. As a result of MA plan cost from CMS is determined by affected person severity, there may be an incentive to up-code diagnoses. A paper by Carlin et al. (2024) goals to judge whether or not or not this happens. They first clarify the mechanism via which MA plans might extra totally seize affected person secondary diagnoses:
MA plans have a possibility to evaluation medical data to make sure that suppliers didn’t unintentionally omit a prognosis from encounter data. These evaluations are extra vital when the suppliers’ reimbursement doesn’t incent detailed coding of the sufferers’ secondary diagnoses. MA plans to make corrections so as to add or (not often) delete a prognosis via CR data. As well as, each MA and TM suppliers could report further diagnoses via a HRA [Health risk assessment] throughout a wellness go to or a house go to for this objective.
The authors use 2019 CMS claims knowledge and divide the information into 3 cohorts: MA plans, TM beneficiaries attributed to ACOs (“TM ACO”), and TM beneficiaries not attributed to an ACO (“TM non-ACO”). ACO consists of sufferers attributable to accountable care organizations (ACO), comparable to these taking part within the Medicare Shared Financial savings Program (MSSP). The authors word that the TM non-ACO cohort serves as a key comparability since they don’t seem to be topic to the identical coding depth incentives skilled by MA plans and TM ACOs (since ACO shared financial savings is also danger adjusted).
The authors determine sufferers who had a HRA based mostly on whether or not they had an annual wellness go to, preliminary preventive bodily examination, or chosen residence Health visits (following the Reid et al. 2020 algorithm). The authors additionally use Information from encounter claims on whether or not a affected person chart evaluation happened. Utilizing these knowledge, the authors propensity-score matched the MA, TM ACO, and TM non-ACO cohorts. The authors then evaluate the matched and unmatched HCC scores and evaluated how the HRA and CR visits impacted the HCC danger scores. They discover:
Incremental Health danger on account of diagnoses in HRA data elevated throughout protection cohorts in step with incentives to maximise danger scores:+0.9% for TM non-ACO,+1.2% for TM ACO, and+3.6% for MA. Together with HRA and CR data, the MA danger scores elevated by 9.8% within the matched cohort.
Analysis codes associated to vascular circumstances, congestive coronary heart failure, and diabetes had the most important contribution to common HCC rating throughout all 3 cohorts. Vascular, pscyh, and congestive coronary heart failure had been most certainly to extend on account of HRA/CR coding depth actions.
Whereas different papers have claimed Medicare Benefit have upcoded diagnoses for extra favorable reimbursement, this paper clearly specifies not solely the magnitude of the affect, but in addition the mechanism via which IT is most certainly to happen. You’ll be able to learn the complete paper here.