Free Practice Questions for ACDIS CCDS-O Exam

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.

In outpatient CDI chart review, a key skill is recognizing when medications and treatment plans suggest a specific diabetic complication that is not explicitly documented. Gabapentin is commonly prescribed for neuropathic pain, and in a diabetic patient it is frequently used to treatdiabetic peripheral neuropathysymptoms (burning, tingling, numbness, shooting pain). ACDIS outpatient CDI guidance supports querying when there are strong clinical indicators that a more specific, clinically relevant diagnosis may be present and is being treated at the encounter, because diabetes codes require complication specificity when supported (e.g., “diabetes with neuropathy” rather than unspecified diabetes). The elevated glucose and A1C confirm ongoing diabetes management but do not, by themselves, indicate CKD, macular degeneration, or ketoacidosis. Ketoacidosis would require documentation of acute metabolic decompensation and supporting clinical/lab findings, which are not provided here. Therefore, the most appropriate clarification is whether the patient has diabetic peripheral neuropathy (and whether it is painful neuropathy) being managed with gabapentin, so the provider can document the condition clearly and accurately.

Under Medicare billing rules applied in outpatient CDI education,observation services are outpatient(typically paid under Part B), even though the patient may stay in a hospital bed and receive ongoing monitoring and treatment. Therefore, anED visit that converts to observationremains an outpatient encounter from a billing and documentation perspective, and the services are reported/paid as outpatient. By contrast, when an ED visit results in aninpatient admission, the encounter transitions to inpatient status, and many hospital ED services immediately preceding admission are commonly bundled/packaged with the inpatient stay rather than billed as a separate outpatient encounter. A scheduledsigmoid resectionis generally a major procedure that is not typically performed as ambulatory/outpatient surgery in routine circumstances, so it is not the best outpatient choice here. Finally, “admission for COPD exacerbation with LOS less than two midnights” is ambiguous because “admission” implies inpatient, even though short stays may sometimes be observation/outpatient depending on medical necessity and the 2-midnight guidance. The clearest outpatient encounter is ED leading to observation.

For outpatient/observation encounters, the first-listed diagnosis is the condition chiefly responsible for the services provided during that encounter. In this scenario, the patient’s ambulatory surgery (herniorrhaphy) has already occurred, and the reason the patient is now in observation is explicitly documented as “post procedural urinary retention.” That makes urinary retention the condition driving the extended monitoring, evaluation, and management in observation status. Benign prostatic hyperplasia and an adverse reaction to anesthesia are documented only as possible etiologies (“likely related to…or…”), and outpatient guidelines do not support coding uncertain diagnoses expressed as “likely” or as alternative possibilities without definitive confirmation. Therefore, those potential causes would not replace the confirmed problem that necessitated observation. The hernia was the reason for the procedure, but it is not the reason for the postoperative observation services described. Outpatient CDI practice reinforces documenting the clinical reason for observation and clearly distinguishing confirmed postoperative complications from suspected causes to support correct first-listed selection.

Targeted Probe and Educate (TPE) is an education-focused review initiative intended to improve billing accuracy and reduce future denials by combining targeted claim review with direct provider/supplier feedback. In outpatient CDI terms, TPE aligns with a “fix-forward” approach: auditors identify specific error patterns (often documentation, medical necessity, coding, or coverage rule issues), then provide one-on-one education so the provider can correct processes and documentation habits. This is distinct from Recovery Audit Contractors (RACs), which primarily identify and recoup improper payments, often after the fact, and are not structured as an individualized education cycle. The OIG Work Plan identifies oversight priorities and areas of potential fraud/waste/abuse; it does not deliver provider-level coaching to reduce denials. CERT measures Medicare improper payment rates through sampling and can drive policy/education broadly, but it is not designed as individualized, iterative provider education. Because TPE is specifically built around targeted review plus direct education to prevent repeat errors and reduce appeals, it is the best answer.

MIPS (Merit-based Incentive Payment System) is the default Medicare Quality Payment Program pathway for most eligible clinicians who are not sufficiently participating in an Advanced APM. In practice, if a clinician is MIPS-eligible and does not meet reporting requirements (or performs poorly), Medicare applies a negative payment adjustment—so “non-participation” effectively carries financial risk. APMs (Alternative Payment Models), especially Advanced APMs, are not automatically required for all clinicians; they are model-based arrangements (often tied to specific payers, contracts, patient populations, and risk/quality terms) that clinicians typically enter through organizational participation decisions. A key operational difference emphasized in outpatient CDI education is that MIPS performance hinges on accurate, complete documentation supporting quality measures and resource use across a broad clinician population, whereas APM participation depends on being in a qualifying model and meeting its participation/threshold rules. Therefore, MIPS functions as the required/default track with potential penalties, while APM participation is elective and model-dependent.

The HHS-HCC risk adjustment model (used for ACA Marketplace plans) calculates a member’s risk score using a combination ofdemographic factorsanddiagnosis codesthat map to HHS-HCCs. Among the listed health record elements,genderis a core demographic variable used in the model’s coefficients because expected healthcare utilization and cost patterns differ by age/sex groupings. In outpatient CDI terms, this is why accurate demographic data capture (including sex) matters alongside complete and specific condition reporting. CPT codes do not drive HHS-HCC risk scores; the model relies on diagnosis reporting (ICD-10-CM) rather than procedure codes for risk category assignment. Discharge status is an encounter/billing element relevant to certain facility payment and quality measures, but it is not a standard HHS-HCC risk score input. Ethnicity is not used as a direct risk adjustment variable in the HHS-HCC model for score calculation. Therefore, gender is the correct element that impacts HHS-HCC risk scores.

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 lowagree rateindicates 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 reflectsquery 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.

In the CMS-HCC model, certain disease groupings are arranged in hierarchies so that when multiple related conditions are reported for the same patient, only the most severe (highest-ranked) HCC in that hierarchy is counted for risk adjustment. This prevents “double counting” of clinically related conditions that represent the same underlying burden of illness. The cancer-related HCCs in the 35–38 range are an example of this hierarchical design: if a patient has diagnoses that map to more than one of these HCCs, the model retains the highest-ranked category and suppresses the lower ones. Therefore, the correct hierarchy order is from the most severe category (HCC 35) down sequentially through HCC 36, HCC 37, and HCC 38. From an outpatient CDI perspective, this reinforces why accuracy and specificity matter: documentation should clearly establish the most clinically severe, active, and treated condition so the correct (highest) HCC is captured, rather than relying on nonspecific or less severe descriptors that could under-represent patient complexity.

This question applies the outpatient risk adjustment “reserve” concept: predicted cost is estimated by multiplying the member’s risk factor contribution by a baseline per-member-per-month (PMPM) amount, then annualizing. The morbid obesity HCC factor is 0.186, and PMPM is $800. First compute the monthly cost impact: $800 × 0.186 = $148.80 per month per patient. Convert to yearly: $148.80 × 12 = $1,785.60 per patient per year. The year-over-year increase in patients with morbid obesity documentation is 11,000 − 10,000 = 1,000 additional patients. Multiply the annual per-patient impact by the additional patient count: $1,785.60 × 1,000 = $1,785,600. Outpatient CDI programs emphasize that improving documentation specificity (when clinically supported) can change whether an HCC is captured, which can affect RAF-based projections and resource planning. However, documentation must still be accurate, supported, and reflect conditions assessed/managed during the encounter.