CCDS-O ACDIS Certified Clinical Documentation Specialist-Outpatient (CCDS-O) Free Practice Exam Questions (2026 Updated)

The only conclusion that is directly supported by the table is that Clinic A’spercent RAF captured is higher in every month of 2023 compared with the corresponding month in 2022. The monthly values rise year-over-year (e.g., January 21% vs 17%, February 33% vs 25%, and continuing through December 84% vs 76%), showing a consistent improvement pattern across the entire calendar year. In outpatient CDI and risk adjustment work, “RAF capture” is commonly used as a performance indicator reflecting how completely documented and coded risk-adjusting conditions (e.g., HCC-supported diagnoses) are being captured within the measurement period. However, the tabledoes notprove why the improvement occurred. It cannot confirm provider engagement (A) without workflow/participation data, cannot compare to other clinics (B) because no other clinic data are shown, and cannot establish that the population was sicker (C) because RAF capture measures documentation/coding completeness relative to opportunity, not inherent patient acuity. Therefore, D is the verified conclusion.

Compliant querying principles taught in outpatient CDI allow the CDI/coding professional to present a multiple-choice query that includes reasonable diagnostic optionssupported by the current encounter’s clinical indicators. Including a “new” diagnosis as an option is acceptable when it is clinically supported by documented findings (signs/symptoms, test results, treatments, clinical course) and the query is written in a non-leading manner—typically with balanced options and an “other” and/or “unable to determine” choice. This approach helps the provider clarify the most accurate condition being evaluated or treated without steering toward a particular response. Option A is not compliant because relying solely on prior encounter documentation (without current relevance) risks coding historical conditions that are not addressed today. Option B is generally discouraged because calling out HCC status can be perceived as prompting for payment impact rather than clinical accuracy. Option D is incorrect because including relevant clinical indicators is essential; omitting them weakens the clinical basis and does not make a query less leading—rather, it makes it less defensible.

The CMS-HCC model is arisk adjustmentmethodology used primarily to setcapitated paymentsfor Medicare Advantage (MA) organizations based on the expected cost of caring for their enrolled beneficiaries. Under this approach, CMS calculates a Risk Adjustment Factor (RAF) for each member using demographic variables (such as age/sex and certain entitlement factors) plus disease burden captured from ICD-10-CM diagnoses that map to Hierarchical Condition Categories (HCCs). The resulting RAF increases or decreases the plan’s payment to better match predicted healthcare needs—higher RAF for sicker, more complex patients and lower RAF for healthier patients. ACDIS outpatient CDI education emphasizes that the purpose is not physician reimbursement based on a “principal diagnosis” (an inpatient concept) and not payment distribution tied directly to quality performance (that aligns more with MIPS/VBP frameworks). It also does not adjust capitation payments specifically “to physicians,” nor does it exclude advanced practice providers in the way described. The correct use is todetermine MA plan capitation paymentsthrough risk-adjusted member-level projections.

In MSSP-style ACO financial reconciliation, performance is evaluated against a benchmark (expected costs). Here, the ACO’s actual spending ($52M) exceeds the expected benchmark ($50M) by $2M, meaning the ACO generatedshared lossesrather than savings. In risk-bearing ACO arrangements, when costs exceed the benchmark and the ACO is in a track that includes downside risk, the organization may owe CMS a portion of those losses. The shared savings/loss rate (50% in this scenario) represents the percentage of the difference from the benchmark that the ACO shares with CMS, assuming applicable thresholds are met. Thus, instead of receiving a shared savings payment, the ACO would be accountable topay backa share of the excess spending (conceptually 50% of the $2M overage, if all model requirements are satisfied). Option D is not correct because reconciliation is typically performed on a performance-year basis rather than only at the end of the full agreement period, and option C is not how MSSP eligibility works.

In outpatient CDI and coding education, selecting the correct E/M code starts with identifying theencounter category(e.g., office/outpatient vs inpatient/observation vs ED) and whether the patient isnew or established, because these define the applicable CPT code range. Next, thelevel of serviceis selected within that range based on the documentation supporting the required elements for that code family. For most E/M services, “site of service” (place/setting) and “new vs established” are foundational code-selection drivers, while “level” is determined by the record’s support for the applicable leveling methodology (commonly medical decision making and, when allowed/appropriate, time). Time can be a valid leveling method for many office/outpatient E/M visits, but it is not universally the basis for the majority of E/M services across all categories; it is an alternative pathway when documentation supports it. Physician specialty and patient age do not define the majority of E/M code selection. Therefore, the best overall statement is new/established status + site of service + level of service.

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 CMS-HCC risk adjustment (commonly applied to Medicare Advantage), qualifying diagnoses must come from acceptable encounter/claim sources and eligible provider types. Hospital-based outpatient services (including a hospital ambulatory clinic) are among the standard, acceptable settings where diagnoses documented, coded, and submitted on qualifying encounters may be used for risk adjustment—assuming they are supported, assessed/managed, and submitted per program requirements. In contrast, certain facility claim types do not typically contribute to CMS-HCC capture in the same way. Hospice care is generally treated as a carve-out/unique payment environment and is not relied upon as a routine source of risk-adjusting diagnosis capture for the member’s ongoing RAF. Renal dialysis centers (ESRD facilities) likewise operate under specialized payment constructs and are not the typical outpatient setting used to drive CMS-HCC diagnosis capture for risk adjustment in standard CDI workflows. Freestanding ambulatory surgical centers also frequently fall outside the usual risk-adjustment-eligible encounter sources emphasized in outpatient CDI programs. Therefore, the hospital ambulatory clinic is the correct setting among these choices.

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.

The documented clinical picture and treatment plan better align with pneumonia than uncomplicated bronchitis, creating a clear documentation/coding consistency opportunity. ALLL infiltrate on chest x-rayis a classic clinical indicator for pneumonia, and prescribinglevofloxacinsupports treatment of a likely bacterial lower respiratory infection rather than routine viral bronchitis. The patient also hasfever, dyspnea, cough, and required an in-officenebulizer treatment, all of which can accompany pneumonia and increase clinical significance. In outpatient CDI practice, the most appropriate query is the one that clarifies the provider’s definitive diagnosis when objective findings and management suggest a more specific condition than what is stated (e.g., “possible bronchitis”). Querying for diabetic complications or heart failure specificity is not as directly supported by the encounter’s indicators and treatment actions provided, and “acuity of bronchitis” is secondary if the true condition is pneumonia. Clarifying whether pneumonia is present ensures accurate reporting, medical necessity support, and appropriate risk/quality capture.

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.

CMS-HCC risk adjustment assigns a baseline coefficient (weight) to each qualifying HCC condition, but certaincombinations of conditionscan increase predicted cost beyond what would be expected by simply adding the two individual weights. These added increments are captured throughdisease interaction factors, which apply when specific conditions coexist (for example, diabetes with certain severe complications, or other paired conditions defined by the model). In outpatient CDI, this is why documentation must clearly support both diagnoses—each must be clinically evaluated/managed and meet reporting rules—because accurately capturing the interacting conditions can legitimately increase the beneficiary’s risk score. By contrast,hierarchiesare designed to prevent double-counting within related condition families (the more severe manifestation typically supersedes a less severe one), which often limits—not adds—separate weights.Resource-based relative valuesandconversion factorsbelong to physician fee schedule payment methodology for services/procedures (RVUs and payment conversion), not HCC risk score calculation. Therefore, disease interactions are the correct concept that adds risk score weight beyond individual HCC coefficients.

Chronic kidney disease (CKD) is defined by evidence of kidney damage or reduced kidney function that persists for at least three months. An estimated glomerular filtration rate (eGFR/GFR)below 60 mL/minsustained over that timeframe is an objective indicator of chronically decreased renal function and supports CKD identification and staging in the outpatient record. This is why outpatient CDI programs frequently use trended eGFR as a clinical indicator to prompt documentation of CKD stage (e.g., stage 3a/3b, stage 4, etc.) when appropriate. BNP >1000 is more aligned with heart failure severity/volume status rather than kidney damage. BUN <12 is within/near normal and does not indicate renal impairment (elevated BUN may be seen with renal dysfunction but is less specific and affected by hydration, diet, GI bleed). Glucose >100 is a screening indicator for impaired fasting glucose/prediabetes but does not, by itself, establish chronic kidney damage. Therefore, sustained GFR <60 is the best objective lab-based measure of chronic kidney damage over time.

The Medicare Shared Savings Program (MSSP) is designed to move reimbursement away from pure volume-based payment and toward value by rewarding organizations that reduce the total cost of care for an assigned Medicare population while meeting defined quality performance requirements. In MSSP, eligible provider groups participate as Accountable Care Organizations (ACOs) and are compared against a financial benchmark. If the ACO’s actual spending comes in below the benchmark and quality standards are achieved, the ACO can earn a portion of the savings—hence “shared savings.” Outpatient CDI supports MSSP success by ensuring documentation accurately reflects patients’ true disease burden (supporting appropriate risk adjustment for benchmarking), and that conditions addressed during visits are clearly documented as evaluated/managed to support reliable coding and quality measurement. While improving transitions of care may be a strategy that helps achieve savings and quality goals, it is not the core purpose of the program itself. Likewise, MSSP is not intended to increase fee schedule payments or simply optimize risk scores; the primary aim is participating in value-based care and sharing in savings when performance supports it.

The patient’s RAF is calculated by adding the applicable HCC weights plus the demographic factor, but only after applying the HCC model’s hierarchy rules. In outpatient risk adjustment education (as emphasized in ACDIS-based training), certain condition groups are hierarchical—meaning multiple related diagnoses in the same hierarchy do not “stack.” Instead, only the highest-ranked HCC in that disease group contributes to the RAF. Here, “diabetes with nephropathy” and “diabetes with retinopathy” both carry the same HCC weight (0.166) and fall within the diabetes complication hierarchy, so they do not add together; only one 0.166 value is counted. Atrial fibrillation contributes separately (0.299), and the demographic risk factor contributes (0.332). Therefore, the final RAF is 0.166 + 0.299 + 0.332 = 0.797. This illustrates why outpatient CDI focuses on documenting all clinically supported conditions for care accuracy, while understanding that some related diagnoses won’t increase RAF beyond the highest applicable HCC in that hierarchy.

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.

In outpatient CDI, a prime query opportunity is any diagnosis with unclear “status” that materially affects coding, risk adjustment, surveillance, and care planning. “History of colon cancer” paired with “18 months s/p bowel resection” creates ambiguity: the provider must clarify whether the malignancy is still active (current disease, recurrence, metastasis, ongoing treatment) versus no longer present (history of malignancy, in remission, disease-free status, post-treatment surveillance only). This distinction changes code selection substantially and prevents inappropriate reporting of an active cancer when the encounter is actually follow-up after curative treatment. By contrast, ostomy status is not documented as present, and OSA/COPD “status” may be clinically useful but is not inherently ambiguous from the prompt in the same way (they are listed as chronic problems without a conflicting timeline event). ACDIS outpatient CDI practice prioritizes clarifying cancer status because it impacts longitudinal documentation integrity, accurate problem list management, and compliant diagnosis reporting at each visit.

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.

Outpatient CDI programs should share provider-facing metrics that are clinically meaningful, aligned with ambulatory documentation goals, and unlikely to be perceived as payment-driven prompting.RAF scoresare an appropriate metric because they reflect how well the documented and coded condition burden represents the patient panel’s complexity in risk adjustment models. Discussing RAF supports education around accurate diagnosis capture, specificity, and annual recapture of active chronic conditions that are monitored, evaluated, assessed/addressed, or treated. In contrast,APC payment ratesare facility OPPS payment constructs and typically are not actionable for individual ambulatory provider documentation improvement.HCC per member per month paymentsis explicitly financial and can create compliance risk by tying documentation discussions directly to payment, which outpatient CDI guidance warns against in provider messaging.MCC ratesare primarily an inpatient DRG severity concept and are not the most relevant outpatient performance measure. Therefore, RAF scores best balance provider relevance, program goals, and compliant education focus.

A core outpatient guideline difference is how to handle uncertainty in diagnoses. In the inpatient setting, facilities may code diagnoses documented as “probable,” “suspected,” “likely,” or “rule out” at discharge if they meet inpatient reporting rules. In outpatient/office settings, however, uncertain conditions generally are not coded as established diagnoses because the encounter is often focused on evaluation rather than confirmed final diagnoses. Instead, outpatient coding relies on confirmed conditions and/or signs and symptoms when a definitive diagnosis has not been made. This is why outpatient CDI education emphasizes precise provider language: if the clinician is still evaluating, they should document the symptom/abnormal finding and the assessment plan; if the condition is confirmed, they should state it clearly and link it to evaluation/management performed. Options A, B, and D are incorrect because chronic conditions may need to be reported whenever they are assessed/managed, “first-listed” is an outpatient concept distinct from inpatient “principal,” and documentation should support all clinically relevant conditions addressed, not only the chief complaint.