CCDS-O Certified Clinical Documentation Specialist-Outpatient (CCDS-O) Questions and Answers

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.

In outpatient CDI and coding guidance, an “uncertain diagnosis” is identified by wording that indicates the provider has not confirmed the condition (e.g., possible, probable, suspected, rule out, question of, concern for). These terms reflect diagnostic consideration rather than an established diagnosis. Option A uses the phrase “concern for,” which is a classic uncertainty qualifier and signals the provider is considering streptococcal pneumonia but has not definitively diagnosed it. In contrast, options B and D describe active treatment “for streptococcal pneumonia,” which implies the provider is managing the condition as a working diagnosis; however, in outpatient coding, treatment alone does not automatically make a diagnosis confirmed if the documentation still reflects uncertainty—CDI would look for explicit provider confirmation. Option C (“evidence of”) generally suggests supportive findings and is commonly interpreted as stronger than “concern for,” though CDI would still assess whether the provider has clearly stated a confirmed diagnosis in the assessment/plan. Therefore, the clearest uncertain descriptor is “concern for.”

A prospective query is initiated early enough (before or during the visit workflow) so the provider can evaluate, assess, and document the condition in real time while the patient is present. This is a major provider benefit because it supports better clinical accuracy and completeness: the clinician can ask targeted questions, perform relevant exam elements, review results, and determine whether the condition is present, active, being monitored, or ruled out—then document the final clinical impression and plan. From an ACDIS outpatient CDI perspective, prospective querying improves efficiency and reduces retrospective “chart-chasing,” late addenda, and documentation gaps that occur when clarification is requested after the encounter is closed. Importantly, prospective queries must remain non-leading and cannot direct the provider to a particular diagnosis (eliminating option A). They also cannot “guarantee” risk-adjusted capture because the diagnosis must be clinically supported and addressed (eliminating option B). Defining the purpose of the encounter is driven by the clinical reason for visit, not by CDI (eliminating option D).

Atrial fibrillation (AF) type is determined largely by episode duration and whether the rhythm self-terminates. In outpatient CDI education,paroxysmal AFis intermittent and typically terminates spontaneously, commonly within7 days(often within 48 hours).Persistent AFis sustained and lastsmore than 7 days, or requires active intervention (e.g., cardioversion) to restore sinus rhythm. This scenario documents AF “for10 days,” which exceeds the 7-day threshold and therefore best fitspersistentAF. The management also aligns with a sustained arrhythmia strategy: rate control (atenolol), rhythm control/antiarrhythmic therapy (sotalol), stroke prevention anticoagulation (rivaroxaban), and discussion of catheter ablation, which is often considered for symptomatic or recurrent/persistent AF. “Chronic” is a nonspecific descriptor and not the preferred current classification term, andpermanent AFimplies a decision has been made not to pursue rhythm control (accepting AF long-term), which is not supported here because rhythm-control options are being considered.

In hospital outpatient settings paid under OPPS, Ambulatory Payment Classifications (APCs) are influenced by the coded services and, in many workflows, the clinical documentation that supports correct CPT/HCPCS selection, units, modifiers, and—when applicable—medical necessity linkages to diagnoses. Accurate documentation ensures that the record supports what was actually performed (e.g., complexity, laterality, supplies, drug administration details, observation criteria, or separately payable procedures) and that coding can correctly apply bundling/packaging rules without losing legitimately reportable services. While APCs are primarily procedure-driven, documentation remains decisive because incomplete or ambiguous notes lead to downcoding, missed charges, incorrect status indicators, or denials during medical review. From an outpatient CDI standpoint, the goal is to ensure the clinical story supports codeable services and their necessity: clear indications, findings, assessment/plan, and any required elements (time, start/stop, dose/route for medications, device details, etc.). This supports appropriate APC grouping and reimbursement integrity, reducing rework, denials, and compliance risk.

The most compliant query is the one that is clinically supported, non-leading, and focused on clarifying documentation for correct reporting and medical necessity—without directing the provider to “add” diagnoses or document conditions for payment purposes. Option A presents relevant clinical context (no GI symptoms; family history) and asks the provider to clarify whether the planned colonoscopy is screening or diagnostic, which is a legitimate documentation clarification affecting correct code selection and coverage rules. It does not imply a desired answer and does not instruct the provider to document additional diagnoses. Option B is problematic because it instructs the provider to “document these conditions” if treated, which can be perceived as prompting and is not tied to encounter-specific indicators. Option C is based primarily on historical information and asks a yes/no about remission, which can be leading and may not reflect current-visit evaluation. Option D effectively asks the provider to add a diagnosis based on nursing documentation, which risks leading language and requires provider confirmation and assessment. Therefore, A is most compliant.

In outpatient CDI, the foundational aim is documentation integrity—making sure the medical record clearly and consistently tells the clinical story: why the patient is being seen, what conditions are evaluated/managed, the current severity and associated risks, what was done (assessment and treatment), and how this supports medical necessity and accurate code assignment. While reimbursement can be affected, it is an outcome—not the purpose. ACDIS-aligned CDI education emphasizes completeness and specificity so the record reflects true acuity and complexity (e.g., chronic conditions with current status, complicating comorbidities, medication management, and risk/decision-making). This improves downstream quality reporting, risk adjustment accuracy, continuity of care, and compliance because coders must code what is documented, not what is presumed. Strong CDI reduces denials and audit exposure by ensuring diagnoses are clinically supported (MEAT—monitor, evaluate, assess/address, treat) and linked to the encounter’s work. In short, CDI exists to ensure the record accurately represents the patient’s condition and the care delivered, enabling correct coding, quality measurement, and appropriate payment.

In the CMS-HCC risk adjustment methodology, each qualifying condition maps to an HCC with an associated coefficient (weight). However, CMS also recognizes that certaincombinationsof conditions can drive costs and complexity more than the simple sum of individual HCC weights. To account for this, the model includesdisease interaction terms—additional coefficients applied when specific conditions coexist in the same beneficiary (for example, selected interactions involving diabetes and particular complications, or other defined pairings). This is why outpatient CDI focuses not only on capturing each chronic condition accurately, but also ensuring both conditions are clearly documented as assessed/managed and meet reporting requirements, because capturing both can legitimately trigger interaction weights. By contrast,hierarchiesprimarily prevent double-counting within related disease groups by allowing the most severe manifestation to “trump” a less severe one; this generally controls/limits weight rather than adding extra.Resource-based relative valuesandconversion factorsare physician fee schedule payment components (RVUs and payment calculation), not HCC risk scoring elements. Therefore, disease interactions are the correct answer.

In outpatient CDI and coding, the Official ICD-10-CM Guidelines that apply are the universal rules plus the outpatient-specific rules. Section I contains conventions, general coding guidelines, and chapter-specific guidance that govern code assignment in every setting (e.g., code structure, “use additional code,” laterality, sequencing instructions, and condition-specific rules). Section IV is specifically written for outpatient services and drives core outpatient behaviors such as selecting the “first-listed” diagnosis based on the main reason for the encounter, reporting additional diagnoses that are evaluated/assessed/treated or impact care, and applying outpatient-only restrictions (for example, diagnoses documented as “rule out,” “probable,” or “suspected” generally are not coded in outpatient the way they may be for inpatient reporting). ACDIS outpatient CDI education emphasizes teaching providers to document clearly the reason for visit, the assessment/clinical relevance of each condition addressed, and the linkage between conditions and services rendered so Section I and Section IV rules can be applied accurately for compliant reimbursement and reporting.

Symbicort is an inhaled combination medication containing an inhaled corticosteroid (ICS) and a long-acting beta-agonist (LABA). In outpatient chart review, this medication class is most strongly associated with chronic airway inflammatory diseases requiring controller therapy—especiallypersistent asthma(and also maintenance therapy for COPD, though COPD is not an option here). For CDI purposes, medication-to-diagnosis linkage can act as a clinical indicator supporting clarification when the visit note lists respiratory symptoms but does not clearly document the chronic condition being treated or its acuity/status. Symbicort is not used to treat musculoskeletal degenerative disease (osteoarthritis), peripheral nerve pain from diabetes (diabetic neuropathy), or cardiac pump failure (congestive heart failure). When Symbicort appears on the active med list, outpatient CDI commonly checks that the provider’s documentation appropriately reflects asthma classification (intermittent vs persistent), current control, exacerbation status if applicable, and that the condition is being monitored/assessed/treated during the encounter to support reportability and accurate coding.

When a CDI query references information from an externally shared note, best practice is to include enough identifying detail so the provider can locate and validate the sourceeven if access is later revokedor if the shared record becomes unavailable. From an outpatient CDI and HIPAA-aligned workflow perspective, the query should clearly cite: where the information came from (thelocationof the shared note within the EHR/external record set),whoauthored it (provider name),whenit was created (date of shared note), and thespecific clinical documentationbeing referenced (the relevant statement/findings). This supports transparency, auditability, and minimizes the risk of misattribution or relying on inaccessible information. Options B–D are missing one or more critical elements—most notably the date and/or location of the shared note—making it harder to verify the source. Including “follow-up procedure” is not the priority for HIPAA-compliant source identification; the key need is traceability of the external documentation used to support the clarification request.

The clinical indicators strongly supportalcohol dependence, not merely alcohol “use” or “abuse.” The patient reports heavy, compulsive intake (early-morning drinking and at least a pint daily), and the provider explicitly documents that she “continues to be dependent on alcohol” and discusses treatment options—this aligns with a dependence-level disorder being addressed.Hypertensionis also supported because the BP is elevated (165/89) and the provider documents management activity (medications and diet counseling), meeting encounter relevance/reportability expectations.Diabetesis listed among chronic conditions, but the scenario provides no indicators of complications (no neuropathy, CKD, ulcers, retinopathy, etc.), so the supported choice is DM type 2without complicationsrather than “with complications.” Although COPD is listed in the “including” statement, no COPD-specific assessment/monitoring/treatment is described in the indicators provided, so the best-supported grouped option focuses on the conditions with clear supporting indicators and management in the note: DM2 without complications, HTN, and alcohol dependence.

A yes/no query format is considered compliant when it is used toresolve a clear documentation conflictand the provider is being asked to confirm which statement accurately reflects the patient’s condition for that encounter. In these situations, the intent is not to introduce a new diagnosis or steer the provider toward a particular coded outcome, but to reconcile inconsistent information already present in the record (e.g., one clinician documents a condition and another documents the opposite, or different notes describe different statuses). A focused yes/no confirmation can be appropriate because the clinical question is essentially binary: which interpretation is correct. By contrast, obtaining a new diagnosis generally requires an open-ended or multiple-choice format with balanced options (including “unable to determine”) and strong encounter-specific indicators to avoid leading. Likewise, organism specification and acuity clarification often involvemore than two clinically valid possibilities(different organisms, acute vs chronic vs acute-on-chronic, etc.), making yes/no overly restrictive and potentially leading. Therefore, resolving conflicting documentation is the best fit for a compliant yes/no query.

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.

Outpatient diagnosis reporting requires coding conditions that are evaluated, assessed, treated, or that influence care/management at the encounter. The chief reason for the visit is the persistent cough, which is assessed and attributed to an adverse effect of an ACE inhibitor (enalapril). For outpatient coding of medication adverse effects, the documentation supports reporting both the manifestation (cough) and the adverse effect of the drug (ACE inhibitor adverse effect), because the provider identified the causal relationship and changed therapy by discontinuing enalapril. In addition, the provider addresses chronic conditions that are clinically relevant to the visit: COPD is assessed as “stable” and the patient is instructed to continue COPD/asthma medications, demonstrating ongoing management. Hypertension also remains relevant because medication therapy is adjusted due to the adverse effect; the patient still has HTN even though one agent is discontinued. Therefore, all five items—cough, ACE inhibitor adverse effect, COPD, asthma, and hypertension—are supported and should be reported, making option D the most appropriate.

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.

Stage 3 pressure ulcers are defined byfull-thickness skin losswhere the injury extends through the dermis and involvesdamage or necrosis of subcutaneous tissue. Clinically, the ulcer may present as a deep crater and can include undermining or tunneling, but the key boundary is thatbone, tendon, and muscle are not exposed. That deeper involvement (exposed muscle/tendon/bone) is characteristic of Stage 4, making option C incorrect. Option D describes partial-thickness loss, which aligns with Stage 2 (epidermis/dermis involvement such as abrasion or blister). Option A reflects early skin changes that correspond more closely to Stage 1 (intact skin with non-blanchable erythema and possible localized edema/induration). In outpatient CDI chart review, accurately distinguishing Stage 3 from Stage 2 and Stage 4 is essential because staging drives severity capture, care planning (wound care interventions, debridement considerations), and quality reporting. Documentation should clearly support “full thickness,” the tissue layers involved, and the absence of exposed bone/tendon/muscle.

Sertraline is a selective serotonin reuptake inhibitor (SSRI) most commonly used to treat depressive disorders and several anxiety-related conditions. In outpatient chart review, recognizing medication–condition relationships supports accurate problem list maintenance and compliant diagnosis reporting, but the diagnosis must still be clearly documented as assessed/managed at the encounter. Depression is the best match because SSRIs like sertraline are first-line pharmacologic therapy for major depressive disorder and are frequently continued long-term with monitoring for symptom control, side effects, and functional status. Schizophrenia is primarily treated with antipsychotic medications; sertraline may be used only as an adjunct if a comorbid depressive or anxiety disorder is present, so it is not the common primary treatment. Asthma management centers on bronchodilators and inhaled corticosteroids, not SSRIs. Heart failure therapy involves guideline-directed cardiac medications (e.g., beta-blockers, ACE inhibitors/ARNI, diuretics), and sertraline is not a standard heart failure treatment. Outpatient CDI education emphasizes documenting the specific mental health diagnosis, current status (stable/worsening), and treatment plan to support coding.

In the outpatient setting, diagnoses documented as uncertain (e.g., “possible,” “probable,” “suspected,” “rule out”) are generally not coded as confirmed conditions; instead, coding is based on confirmed diagnoses or, when not confirmed, the presenting signs/symptoms. Here, the provider documented only “possible Zika,” which is not a confirmed diagnosis for outpatient reporting. Even though the CDI specialist sees a positive serology result, lab data alone does not replace provider diagnostic confirmation in the assessment/plan. The appropriate next step is to query the provider to confirm whether Zika is the established diagnosis based on the positive test (and whether it is clinically addressed during the encounter). If confirmed, Zika can be coded appropriately and sequenced based on the reason for the visit; if not confirmed or still under evaluation, the symptom (fever) remains first-listed. Option B is incorrect because coders do not “code the result” of a serology test as a diagnosis; they code the condition the test supports once clinically confirmed.

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.

For RAF impact in the CMS-HCC model, the most valuable provider education targets are conditions that (1) map to HCCs or interact with HCC hierarchies, and (2) are clearly within the specialist’s scope to assess and manage during visits. In this scenario, the endocrinologist is actively treatingdiabetesand its complications. Diabetes withperipheral neuropathy/vascular diseaseplus an activenon-healing foot ulcerreflects significant diabetic disease burden and often supports additional required coding (e.g., diabetes complication code plus a separate site/severity ulcer code). The history oftoe amputationsis also important because amputation status can represent ongoing complexity, affects care planning (risk of recurrent ulcer/infection), and may contribute to risk capture depending on the model and associated complications. By contrast, CAD/COPD/HF may not be evaluated by the endocrinologist at the visit, “A1C” is a lab value (not a diagnosis), and “history of prostate cancer” generally does not risk-adjust like active malignancy. Therefore, educating on documenting diabetes, amputation status, and ulcer details best supports RAF accuracy.

A key ambulatory CDI distinction between the two major risk models is timing. The HHS-HCC model (used for ACA Marketplace risk adjustment) is commonly described as a concurrent model: it uses the enrollee’s demographics and diagnoses from the same benefit year to reflect morbidity and support that year’s risk transfer/payment balancing. In contrast, the CMS-HCC model (commonly applied in Medicare Advantage) is prospective: conditions documented and coded in the prior data collection year are used to predict expected cost for the following payment year. From an outpatient CDI perspective, this timing difference affects operational priorities. For CMS-HCC, accurate annual capture and recapture of active chronic conditions is essential because last year’s documented conditions drive next year’s risk score and revenue. For HHS-HCC, complete documentation and coding during the current year impacts the current year’s risk measurement. Options referencing CPT codes are not correct for the core HCC risk score calculation, which is driven by demographics and ICD diagnosis reporting mapped to HCC categories.

A Stage 4 pressure ulcer (pressure injury) is characterized byfull-thickness tissue losswithextensive destruction, tissue necrosis, or damage to muscle, bone, or supporting structures. The key phrase in the question—“necrosis of soft tissue through the underlying muscle”—signals a depth of injury that extends beyond the subcutaneous tissue and involves muscle, which is consistent with Stage 4. By comparison, Stage 2 involves partial-thickness skin loss with exposed dermis (no necrosis through deeper structures). Stage 3 involves full-thickness skin loss where adipose may be visible, butmuscle, tendon, or bone are not exposed; undermining and tunneling may occur, yet the defining line is that it does not extend to muscle/bone involvement. “Stage 5” is not part of standard pressure ulcer staging used in coding and documentation. Outpatient CDI practice emphasizes documenting the exact stage, anatomic location, laterality when applicable, and whether the ulcer is healing or complicated (infection/osteomyelitis) because stage drives specificity, severity capture, and appropriate care planning documentation.

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.

Across both inpatient and outpatient CDI, the single expectation that must remain consistent isquery compliance. While productivity targets, the types of query opportunities, and the way “impact” is measured can differ significantly by setting (e.g., DRG/CC-MCC focus in inpatient vs. HCC capture, specificity, and MEAT support in outpatient), the compliance framework for querying does not change. A compliant query must be clinically supported, non-leading, clearly written, and must allow the provider to independently determine the most accurate documentation based on the record. It should include relevant clinical indicators, present reasonable options (including “other”/“unable to determine” when appropriate), and avoid language that appears to request diagnoses for payment purposes. These principles protect documentation integrity, support defensible coding, and reduce audit risk regardless of whether the encounter is hospital-based or ambulatory. By contrast, “review productivity” and “revenue impact” vary widely by program design and setting, and “query opportunities” differ because inpatient vs. outpatient have different reportability rules and documentation drivers. Therefore, query compliance is the metric held to the same standard in both environments.

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.

In stage 3 chronic kidney disease, impaired vitamin D activation and early disturbances in calcium-phosphate regulation commonly drive a compensatory rise in parathyroid hormone (PTH), known as secondary hyperparathyroidism of renal origin. Outpatient CDI chart review looks for clinical indicators that suggest a condition being evaluated or requiring management, and an elevated iPTH in a CKD patient is a classic indicator that supports querying the provider for CKD-related mineral and bone disorder, specifically renal secondary hyperparathyroidism, if it is clinically being assessed/treated (e.g., monitoring trends, prescribing vitamin D analogs, calcimimetics, dietary counseling, nephrology follow-up). Primary hyperparathyroidism is less supported here because it typically requires a different biochemical pattern and clinical context (often hypercalcemia) rather than being driven by CKD physiology. Hypoparathyroidism is the opposite process (low PTH), making option C inconsistent with the lab finding. Option D is not supported because phosphorus is normal, not low, and hypophosphatemia is not documented as a driver. Therefore, querying for renal secondary hyperparathyroidism is most appropriate.

Year 2 shows a higher total volume of MDD diagnoses (185,090 vs. 155,501), but the key CDI signal is the shift in coding specificity: “MDD, specified” increases substantially (118,516 vs. 76,318), while “MDD, unspecified” decreases (66,574 vs. 79,193). In outpatient CDI terms, this pattern is consistent with improved documentation quality and code capture—providers are describing the condition with greater clinical detail (episode type, severity, remission status, recurrence, etc.), allowing assignment of more specific ICD codes. When an HCC value (0.299) is associated with MDD, improved capture of qualifying, specific MDD codes supports more accurate risk adjustment. That increases the accuracy of projected resource need and affects future cost benchmarking (and potentially quality/utilization comparisons) because the population’s documented burden of illness is better represented. Therefore, the appropriate inference is increased patients plus increased “specified” use and decreased “unspecified,” with an impact on future benchmarking.

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.

For reporting Evaluation and Management (E/M) services, the longstanding “key components” framework recognizeshistory, examination, and medical decision making (MDM)as the core elements used to determine the appropriate E/M level when the service is not reported based on time. In outpatient CDI education aligned with ACDIS concepts, MDM is emphasized because it reflects the clinician’s cognitive work and risk-based thinking: the complexity of problems addressed, the amount/complexity of data reviewed and analyzed (labs, imaging, external notes, independent interpretation), and the risk of complications and/or morbidity from additional testing or treatment. “Review of systems” is a sub-element of the history component, not a separate key component. “Nature of presenting problem” and “coordination of care” can be clinically relevant and may support medical necessity or time-based billing (when documented appropriately), but they are not one of the three key components that define E/M reporting structure. Therefore, the best answer is Medical decision making.

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.

APCs and DRGs are both prospective payment classification systems designed to group services that consume similar resources, supporting standardized reimbursement. DRGs group inpatient stays largely around the principal diagnosis, key procedures, complications/comorbidities, and discharge status to estimate expected hospital resource use for the admission. APCs, used primarily for hospital outpatient services, group billable procedures and services that are clinically comparable and expected to require similar levels of resources (staff time, supplies, equipment, intensity). While APCs often allow multiple payment classifications within a single outpatient encounter (because multiple procedures may be performed), that feature is not the fundamental similarity to DRGs—it’s a key difference in operational payment mechanics. Likewise, APC assignment is generally driven by CPT/HCPCS and revenue codes rather than being primarily diagnosis-dependent. The shared concept emphasized in outpatient CDI education is that both systems aim to align payment with anticipated resource utilization, which is why complete, accurate documentation is essential to support correct coding of the services and conditions that justify the level of care provided.

Outpatient CDI performance is best measured by metrics that reflect ambulatory documentation quality, risk-adjustment accuracy, and provider engagement.HCC capture rateis 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 rateis 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 rateis 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 CMIandseverity of illnessare 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.

In ICD-10-CM diabetes coding (as reinforced in outpatient CDI education), some diabetes manifestations are fully captured by a single diabetes “combination” code, while others require a diabetes complication codeplus an additional codeto identify the specific manifestation. Diabeticnephropathyand many forms of diabeticretinopathyare commonly represented by diabetes combination codes that already describe the manifestation with built-in specificity options (e.g., diabetes with nephropathy; diabetes with retinopathy with/without macular edema and severity).Osteomyelitis, however, is typically captured using a diabetes code such as “diabetes with other specified complication” (e.g., E11.69) to establish the linkage to diabetesandan additional code from the osteomyelitis category (e.g., M86.-) to specify the site, acuity, and type of osteomyelitis. From a chart review standpoint, CDI often queries to confirm the causal relationship (“due to diabetes”) and to ensure the osteomyelitis details (site, acute vs chronic) are documented so both codes can be assigned accurately and compliantly.

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.

In outpatient CDI, “pre-visit” or prospective preparation focuses on chronic, clinically significant conditions that are likely to remain active and that should be reassessed and documented with clear MEAT support (monitor, evaluate, assess/address, treat) during the upcoming encounter. Epilepsy, chronic heart failure, and Crohn’s disease are all long-term conditions that commonly require ongoing medication management, monitoring, and periodic reassessment, making them strong candidates for reminder/education to ensure the provider documents current status (controlled vs uncontrolled, exacerbation, complications, and treatment plan). This also supports accurate risk adjustment because chronic conditions with ongoing impact are the ones expected to be recaptured when addressed. In contrast, option C includes “family history,” which is not a current active condition for risk adjustment, and options D includes acute/self-limited problems (syncope episode, pharyngitis) that are less appropriate as pre-visit chronic-condition prompts. Option B mixes chronic disease with items that may be historical or encounter-specific (compression fracture timing/status), making it less consistently targetable than option A.

In outpatient risk adjustment, the highest-impact clarification is often the one that determines whether a condition is currently active (and therefore risk-adjustable) versus historical/resolved. “Leukemia” listed on the problem list, plus active review of CBC/WBC and referral to oncology, strongly suggests ongoing disease evaluation/management. ACDIS outpatient CDI principles emphasize querying to confirm whether the leukemia is active, in relapse, or in remission because that distinction can change code selection from an active malignancy to a history code, and history codes typically do not carry the same risk adjustment impact as an active HCC-bearing diagnosis. While heart failure type/acuity and malnutrition severity are also important for specificity and may affect risk capture, they generally represent refinement of already-established chronic conditions rather than a potential “on/off” determination of a major disease category. Likewise, atrial fibrillation subtype differentiation is clinically useful but usually does not materially change risk adjustment compared with confirming an active hematologic malignancy. Therefore, clarifying leukemia status/acuity is the most impactful risk-adjusted query opportunity.

In outpatient CDI practice, a common reason to query is a mismatch between what is being evaluated/treated and what is explicitly documented as an active condition for the encounter. A diagnostic chest x-ray aligns with the already-documented symptom (chronic cough), and a nutrition specialist referral aligns with an established diagnosis (obesity); neither inherently suggests an undocumented condition. Prescribing captopril aligns with documented HTN management, so it generally would not create documentation ambiguity requiring clarification (even though ACE inhibitors can be associated with cough, the plan alone does not establish a new reportable diagnosis). In contrast, ordering an HbA1c often signals assessment for diabetes, impaired glucose regulation, or monitoring of known diabetes. Because diabetes is not listed in the history provided, the HbA1c order may prompt the CDI specialist to query whether the provider is evaluating a suspected or existing glycemic disorder, whether there is a diagnosis such as prediabetes/diabetes being addressed, and to ensure the record clearly supports the medical necessity and any reportable condition.

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.