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NEW QUESTION # 67
Which of the following illustrates an example of a compliant, prospective query?
Answer: B
Explanation:
A compliant prospective query is initiated before the next encounter so the provider can clarify documentation during the upcoming visit, using clinically relevant indicators without directing a specific diagnosis. Option A does this appropriately: it references an existing CHF history and a supportive medication (Lasix), then asks the provider to confirm whether CHF is pertinent at the next visit and, if so, to specify type and acuity. This supports accurate outpatient reporting because heart failure coding requires specificity (systolic/diastolic/combined; acute/chronic/acute on chronic) and should reflect what is actually evaluated/managed at the encounter. Option B is retrospective and attempts to justify a prior test. Option C is leading because it asks the provider to "add" a diagnosis to a past note rather than clarify current clinical status. Option D is also retrospective and uses "please add CHF," which is leading and can be perceived as prompting. Therefore, A best demonstrates a compliant prospective query.
NEW QUESTION # 68
An elderly patient with a PMH of CHF, DM type 1, arthritis, and HTN is seen in the clinic for a follow-up appointment after a recent hospitalization. After an evaluation of the patient's current health status, the provider documents the following: "HFrEF: lungs clear, no edema, continue meds. DM: no changes to insulin pump. Arthritis: asymptomatic joint destruction. HTN: BP stable. Continue meds." Which of the following is the clarification opportunity in the above scenario?
Answer: B
Explanation:
This encounter documents both hypertension and heart failure management, creating a key outpatient documentation/coding clarification opportunity: whether the heart failure is related to hypertension (hypertensive heart disease with heart failure). Outpatient CDI principles emphasize capturing the true clinical relationships that affect code assignment, risk adjustment, and longitudinal disease management. When HTN and HF coexist, coding may require combination coding and correct sequencing, plus an additional heart failure code to describe the specific HF type. Provider documentation that explicitly links (or explicitly rules out) a causal relationship supports compliant selection of the most accurate diagnosis codes and reduces ambiguity during chart review. The other options are weaker: the provider already documents HFrEF (type), and while added severity detail can help, the scenario's primary clarification "opportunity" is the HTN-HF relationship. DM type 1 inherently involves insulin, so "insulin status" is not the key outpatient clarification point here, and there is no typical direct linkage between DM and arthritis supported by the note.
NEW QUESTION # 69
Calculate the expected yearly cost for this patient based on the RAF score.
Answer: C
Explanation:
In outpatient risk adjustment (commonly Medicare Advantage), the patient's predicted cost is derived from the Risk Adjustment Factor (RAF), which is the sum of component risk contributions. Here, the RAF is calculated by adding the HCC diagnoses score (0.166), disease interactions (0.112), and demographic score (0.330). That total equals 0.608. The PMPM (per-member-per-month) baseline cost is $800. To estimate the patient's expected monthly cost, multiply PMPM by RAF: $800 × 0.608 = $486.40 per month. The question asks for the expected yearly cost, so convert PMPM to annual: $486.40 × 12 = $5,836.80. ACDIS outpatient CDI teaching emphasizes that accurate documentation and compliant coding directly affect RAF through captured HCCs and interactions (when supported), which in turn drives expected resource needs and plan payment. Missing or unsupported diagnoses can understate RAF; vague documentation can prevent valid HCC capture.
NEW QUESTION # 70
Which of the following payment models enables Medicare to forecast costs for Medicare Advantage members for the coming year?
Answer: C
Explanation:
Medicare Advantage (MA) payments are risk adjusted so CMS can predict expected healthcare costs for each enrollee in the upcoming payment year. The model used for this forecasting is the CMS-HCC (Hierarchical Condition Category) risk adjustment methodology. It converts demographic factors (such as age/sex and eligibility status) plus documented, coded diagnoses (ICD-10-CM codes that map to HCCs) into a Risk Adjustment Factor (RAF). CMS then uses the RAF to adjust capitation payments to MA plans to reflect the member's anticipated resource needs. This is why outpatient CDI places heavy emphasis on accurate, specific capture and annual "recapture" of active chronic conditions that are monitored, evaluated, assessed/addressed, or treated during the encounter-because the prior year's valid HCCs drive the next year's predicted cost and payment. By contrast, APCs relate to OPPS facility outpatient payment, RVUs/RBRVS relate to physician fee schedule valuation, and GPCIs adjust payment geographically; none of those are the MA risk forecasting model.
NEW QUESTION # 71
Which of the following BEST defines a risk score under the CMS-HCC model?
Answer: A
Explanation:
Under the CMS-HCC model, a beneficiary's risk score (RAF) is intended to represent the expected cost of caring for that individual relative to an average beneficiary. The score is calculated using two primary inputs: (1) the beneficiary's demographic factors (such as age, sex, Medicaid status/dual eligibility, disability status, and original reason for Medicare entitlement, depending on the model segment), and (2) the beneficiary's documented disease burden captured through ICD-10-CM codes that map to Hierarchical Condition Categories (HCCs). Those HCCs reflect the person's health status and severity, with hierarchy rules preventing "stacking" of related conditions and with certain interaction terms in some model versions. Social determinants are not generally described as the defining basis of the traditional CMS-HCC RAF in CDI education, and "family demographics" are not used. The model is not a mortality predictor; it is a cost/risk prediction tool for payment adjustment. Therefore, the best definition is the beneficiary's individual demographic and health status.
NEW QUESTION # 72
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