Important ACDIS CCDS-O Exam Questions

Answer: C

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.

Answer: C

Explanation:

To establish and query for a patient's baseline renal function in the outpatient setting, eGFR is the most direct and standardized measure because it estimates kidney filtration capacity using serum creatinine (and patient factors such as age/sex, and sometimes race depending on the equation used). Outpatient CDI concepts emphasize that chronic kidney disease staging is based primarily on eGFR categories (G1--G5) and persistence over time, making eGFR trends particularly useful for determining whether the patient has CKD, whether it is worsening, and what stage should be documented. Serum creatinine alone can suggest decline but does not translate cleanly to CKD stage without calculating eGFR and considering patient characteristics. BUN is influenced by hydration status, protein intake, bleeding, and catabolic states, so it is less reliable for baseline kidney function assessment. ACR is important for detecting albuminuria and refining CKD classification/risk stratification, but it complements eGFR rather than replacing it as the primary indicator of baseline filtration function.

Answer: D

Explanation:

In the outpatient/ambulatory setting, ICD-10-CM reporting rules applied in CDI education distinguish clearly between confirmed diagnoses and ''uncertain'' or ''rule out'' conditions. Terms such as ''rule out,'' ''suspected,'' or ''probable'' generally are not coded as established diagnoses in the outpatient record because the encounter is often for evaluation and testing rather than definitive confirmation. Instead, coders report the patient's presenting signs and symptoms when a definitive condition has not been documented as confirmed by the provider. Here, the clinician ordered diagnostic testing (ECG and chest x-ray) specifically to rule out myocardial infarction (MI), but no final diagnosis of MI or angina is documented in the scenario. Therefore, ''rule out MI'' is not reportable, and neither is acute MI or angina unless explicitly diagnosed. The reportable conditions are the symptoms that drove the visit and required evaluation: chest pain (captured as ''other chest pain'' in the options), shortness of breath, and nausea.

Answer: C

Explanation:

A high query rate with a strong physician response rate shows the CDI specialist is generating many queries and providers are opening/responding to them. However, a consistently low agree rate indicates providers frequently select ''disagree,'' ''clinically undetermined,'' or otherwise do not validate the query's suggested clarification. In outpatient CDI program management, that pattern most often reflects query quality problems---for example, queries that are not well-supported by encounter-specific clinical indicators, queries that are vague or overly speculative, or queries that do not align with outpatient reportability standards (e.g., prompting for diagnoses not clearly monitored/evaluated/assessed/treated). While leading queries are a compliance concern, the more direct operational inference from ''high volume + answered + not agreed with'' is that the queries are not clinically compelling or are poorly constructed, resulting in frequent provider non-concurrence. Case complexity alone would not reliably drive low agree rates if the queries were appropriately targeted and evidence-based. Therefore, the most likely interpretation is poor-quality queries requiring coaching on clinical support, clarity, and compliant construction.

Answer: B

Explanation:

Outpatient CDI performance is best measured by metrics that reflect ambulatory documentation quality, risk-adjustment accuracy, and provider engagement. HCC capture rate is central because outpatient CDI frequently supports risk adjustment (e.g., CMS-HCC/HHS-HCC) and aims to ensure chronic conditions are accurately documented, linked, and reported when they are actively managed. Unspecified code utilization rate is a practical quality metric for provider education because high unspecified use often signals missed clinical specificity (severity, laterality, acuity, manifestations, staging) that can reduce coding accuracy, obscure patient complexity, and weaken data used for benchmarking and quality reporting. Query response rate is also a core operational KPI: it reflects provider participation, workflow effectiveness, and the CDI team's ability to obtain timely clarifications that support compliant coding and complete clinical representation. In contrast, Medicare CMI and severity of illness are predominantly inpatient-focused constructs and are not the primary yardsticks for outpatient CDI program success. While aggregate RAF and quality indicators matter, the best ''program performance'' set is the one directly tied to outpatient CDI levers: HCC capture, specificity/unspecified reduction, and query responsiveness.