CRC (Court Reporting Certifications) cheat sheet

HCC (Hierarchical Condition Category) models map ICD-10-CM diagnosis codes to condition groups; each enrollee's risk score is the sum of HCC category weights plus demographic factors, normalized so the average score equals 1.0.

In the CMS-HCC model, only diagnoses captured on accepted encounter/claims data during the data collection period count toward the risk score; the model uses a look-back year of claims to predict the following payment year.

Hierarchies suppress lower-severity codes within a disease family: when a higher-ranked HCC in the same hierarchy is present, the lower HCC is not paid separately (for example, a more severe diabetes complication category supersedes uncomplicated diabetes).

Interactions add weight when two conditions co-occur (for example, diabetes with CHF, or diabetes with CKD); the interaction weight is added on top of the individual HCC weights, so both conditions must be documented.

Demographic factors in the community model include age/sex bands and, for institutional models, originally disabled status and Medicaid eligibility; these adjust the base score independently of diagnoses.

The ACA (HHS) risk adjustment model uses enrollee-level EDGE data, billable ICD-10-CM codes, and its own HCC groupings and coefficients; it is a separate model from CMS-HCC and weights cannot be substituted across models.

Risk Adjustment Payment System (RAPS) and the Encounter Data System (EDS) are the two Medicare Advantage data sources; CMS blends RAPS and EDS risk scores per published phase-in percentages, and diagnoses must be supported in the medical record to survive RADV audit.

ICD-10-CM conventions: code to the highest level of documented specificity, use combination codes when one code fully describes the condition and its manifestation, and sequence the principal/first-listed diagnosis as the condition chiefly responsible for the encounter.

A diagnosis is reportable only when the provider's documentation supports it as a current, treated, or monitored condition; a history of a resolved condition, or a condition 'ruled out,' is not coded as active.

MEAT criteria (Monitor, Evaluate, Assess/treat) describe the evidence needed to support a chronic condition on an encounter; documentation must show at least one element tied to that condition at that visit.

Specificity requirements: diabetes requires type and complication status; CKD requires stage; heart failure requires type (systolic, diastolic, combined); COPD and asthma require the documented type and, where applicable, exacerbation status.

Status codes (for example, tobacco exposure, long-term insulin use, dialysis status, transplant status) add risk weight only when documented; they are frequently missed and are common chart-review targets.

Documentation gaps include unlinked manifestations (e.g., CKD attributed to diabetes without a causal statement), unspecified codes when specificity exists in the record, and conditions mentioned in problem lists but not addressed in the note.

CMS HCC coding rules prohibit using a code based solely on a medication list, a problem list, or a prior-year note; the condition must be documented and assessed in the current encounter to be submitted.

RADV audits compare submitted diagnoses to the medical record; unsupported diagnoses are deleted, which lowers the risk score and can trigger repayment and, for patterns of error, civil monetary penalties.

Compliance programs require internal auditing, provider education, and monitoring of high-risk codes (e.g., major complications, sepsis, respiratory failure) because these carry high weights and high audit scrutiny.

Diabetes coding: E11.9 (type 2 without complications), E11.65 (with hyperglycemia), E11.22 (with diabetic CKD), E11.21 (with diabetic nephropathy), E11.40 (with neuropathy); always add the manifestation code (e.g., N18.3 for CKD stage 3) after the diabetes code.

Diabetes with CKD requires a causal link in documentation ('diabetic CKD' or 'CKD due to diabetes'); without the link, code CKD and diabetes separately, which changes the HCC assignment.

Heart failure: I50.2x systolic, I50.3x diastolic, I50.4x combined; specify acuity (acute, chronic, acute on chronic) because these map to different HCCs and weights.

COPD: J44.0 (with acute lower respiratory infection), J44.1 (with acute exacerbation), J44.9 (unspecified); documentation should state the type (e.g., chronic obstructive asthma, emphysema) and exacerbation status.

CKD staging: N18.1 through N18.5, N18.6 (ESRD), N18.9 (unspecified); stage 5 and ESRD map to the highest renal HCC, while stage 1-2 generally do not carry HCC weight.

Cancer coding: code the primary site and, when documented, the metastatic site; a history of cancer (Z85.x) is not the same as active cancer and must not be coded as active unless the record supports it.

Cardiovascular conditions such as AMI (I21.x), unstable angina (I20.0), and peripheral arterial disease (I73.9) have distinct HCC weights; specify site and laterality where the code set requires it.

Sequencing: the principal diagnosis is the condition after study chiefly responsible for admission; chronic conditions that are managed but not the reason for the visit are coded as secondary, with linkage to manifestations stated explicitly.

Risk score capture: the score is a sum of HCC weights, demographic factors, and interactions; a missing HCC lowers the score, while an unsupported HCC raises it and is recoverable on audit.

Chart review workflow: select a sample (or full population) for high-risk codes, compare submitted diagnoses to the record, and classify each as supported, unsupported, or needing provider clarification.

Audit findings should be quantified: number of HCCs deleted, dollar impact, and error rate by provider or code family; this drives targeted education.

Quality reporting uses HEDIS and Star Ratings measures (e.g., HbA1c control, blood pressure control, medication adherence); these are separate from risk adjustment but rely on the same documentation.

Value-based initiatives (MSSP, ACOs, shared savings) use risk adjustment to set benchmarks; accurate coding affects both the benchmark and the measured performance, so audits must be consistent across years.

Data accuracy requires complete encounter submission (all diagnoses, not just the primary), correct use of EDS vs. RAPS, and verification that the encounter date falls within the collection period.

Inter-rater reliability testing on chart reviews uses a second reviewer on a sample; agreement below a threshold indicates a need for coder retraining or clearer query templates.

Documentation improvement programs should use compliant physician queries that ask for clarification without leading the provider to a specific diagnosis or code.

HCC (Hierarchical Condition Category) models map ICD-10-CM diagnosis codes to condition groups; each enrollee's risk score is the sum of HCC category weights plus demographic factors, normalized so the average score equals 1.0.

In the CMS-HCC model, only diagnoses captured on accepted encounter/claims data during the data collection period count toward the risk score; the model uses a look-back year of claims to predict the following payment year.

Hierarchies suppress lower-severity codes within a disease family: when a higher-ranked HCC in the same hierarchy is present, the lower HCC is not paid separately (for example, a more severe diabetes complication category supersedes uncomplicated diabetes).

Interactions add weight when two conditions co-occur (for example, diabetes with CHF, or diabetes with CKD); the interaction weight is added on top of the individual HCC weights, so both conditions must be documented.

Demographic factors in the community model include age/sex bands and, for institutional models, originally disabled status and Medicaid eligibility; these adjust the base score independently of diagnoses.

The ACA (HHS) risk adjustment model uses enrollee-level EDGE data, billable ICD-10-CM codes, and its own HCC groupings and coefficients; it is a separate model from CMS-HCC and weights cannot be substituted across models.

Risk Adjustment Payment System (RAPS) and the Encounter Data System (EDS) are the two Medicare Advantage data sources; CMS blends RAPS and EDS risk scores per published phase-in percentages, and diagnoses must be supported in the medical record to survive RADV audit.

ICD-10-CM conventions: code to the highest level of documented specificity, use combination codes when one code fully describes the condition and its manifestation, and sequence the principal/first-listed diagnosis as the condition chiefly responsible for the encounter.

A diagnosis is reportable only when the provider's documentation supports it as a current, treated, or monitored condition; a history of a resolved condition, or a condition 'ruled out,' is not coded as active.

MEAT criteria (Monitor, Evaluate, Assess/treat) describe the evidence needed to support a chronic condition on an encounter; documentation must show at least one element tied to that condition at that visit.

Specificity requirements: diabetes requires type and complication status; CKD requires stage; heart failure requires type (systolic, diastolic, combined); COPD and asthma require the documented type and, where applicable, exacerbation status.

Status codes (for example, tobacco exposure, long-term insulin use, dialysis status, transplant status) add risk weight only when documented; they are frequently missed and are common chart-review targets.

Documentation gaps include unlinked manifestations (e.g., CKD attributed to diabetes without a causal statement), unspecified codes when specificity exists in the record, and conditions mentioned in problem lists but not addressed in the note.

CMS HCC coding rules prohibit using a code based solely on a medication list, a problem list, or a prior-year note; the condition must be documented and assessed in the current encounter to be submitted.

RADV audits compare submitted diagnoses to the medical record; unsupported diagnoses are deleted, which lowers the risk score and can trigger repayment and, for patterns of error, civil monetary penalties.

Compliance programs require internal auditing, provider education, and monitoring of high-risk codes (e.g., major complications, sepsis, respiratory failure) because these carry high weights and high audit scrutiny.

Diabetes coding: E11.9 (type 2 without complications), E11.65 (with hyperglycemia), E11.22 (with diabetic CKD), E11.21 (with diabetic nephropathy), E11.40 (with neuropathy); always add the manifestation code (e.g., N18.3 for CKD stage 3) after the diabetes code.

Diabetes with CKD requires a causal link in documentation ('diabetic CKD' or 'CKD due to diabetes'); without the link, code CKD and diabetes separately, which changes the HCC assignment.

Heart failure: I50.2x systolic, I50.3x diastolic, I50.4x combined; specify acuity (acute, chronic, acute on chronic) because these map to different HCCs and weights.

COPD: J44.0 (with acute lower respiratory infection), J44.1 (with acute exacerbation), J44.9 (unspecified); documentation should state the type (e.g., chronic obstructive asthma, emphysema) and exacerbation status.

CKD staging: N18.1 through N18.5, N18.6 (ESRD), N18.9 (unspecified); stage 5 and ESRD map to the highest renal HCC, while stage 1-2 generally do not carry HCC weight.

Cancer coding: code the primary site and, when documented, the metastatic site; a history of cancer (Z85.x) is not the same as active cancer and must not be coded as active unless the record supports it.

Cardiovascular conditions such as AMI (I21.x), unstable angina (I20.0), and peripheral arterial disease (I73.9) have distinct HCC weights; specify site and laterality where the code set requires it.

Sequencing: the principal diagnosis is the condition after study chiefly responsible for admission; chronic conditions that are managed but not the reason for the visit are coded as secondary, with linkage to manifestations stated explicitly.

Risk score capture: the score is a sum of HCC weights, demographic factors, and interactions; a missing HCC lowers the score, while an unsupported HCC raises it and is recoverable on audit.

Chart review workflow: select a sample (or full population) for high-risk codes, compare submitted diagnoses to the record, and classify each as supported, unsupported, or needing provider clarification.

Audit findings should be quantified: number of HCCs deleted, dollar impact, and error rate by provider or code family; this drives targeted education.

Quality reporting uses HEDIS and Star Ratings measures (e.g., HbA1c control, blood pressure control, medication adherence); these are separate from risk adjustment but rely on the same documentation.

Value-based initiatives (MSSP, ACOs, shared savings) use risk adjustment to set benchmarks; accurate coding affects both the benchmark and the measured performance, so audits must be consistent across years.

Data accuracy requires complete encounter submission (all diagnoses, not just the primary), correct use of EDS vs. RAPS, and verification that the encounter date falls within the collection period.

Inter-rater reliability testing on chart reviews uses a second reviewer on a sample; agreement below a threshold indicates a need for coder retraining or clearer query templates.

Documentation improvement programs should use compliant physician queries that ask for clarification without leading the provider to a specific diagnosis or code.