Practice Brief - Clinical Validation

Practice Brief

Clinical

Validation

(2023 Update)

Authors:

Karen Marini Carr, MS, BSN, RN, CDIP, CCDS

Cheryl Ericson, MS, RN, CDIP, CCDS

Margaret M. Foley, PhD, RHIA, CCS

Pamela Hess, DBA, MA, RHIA, CDIP, CCS

Michael Stearns, MD, CPC, CRC, CFPC

Anny Pang Yuen, RHIA, CCS, CDIP, CCDS

Acknowledgements:

Roberta Baranda, MS, RHIA, CHP

Lateka M. Benson, PhD, MHA, RHIT, CCS

Deb Boppre, MSM, RHIA, CCS, CCS-P, FAHIMA

Rebecca Conroy Bargfrede, RHIA, CCS-P, MS, SHRM-SCP, CHC

Vicki Buchanan, RHIA, CHPS

Patricia Buttner, MBA/HCM, RHIA, CHDA, CDIP, CPHI, CCS

Angela Campbell, MSHI, RHIA, FAHIMA

Gretchen Catlett, RHIA, CHPS, HCISPP

Tammy Combs, MSN, RN, CNE, CDIP, CCS

Phillip Duong, MS, RHIA, CCA

Brandi Durkin, RHIA

Julie Engelland, RHIT, CCS, CIC

Cherri Fields, RHIT

Sally Gibbs, MA, RHIA, CCS

Ashley Hendry, MBA, MSL, RHIA

Theresa M. Honsey, RHIA

Mary Hopkins, MSHI, RHIA

Shannon Houser, PhD, MPH, RHIA, FAHIMA

April Insco, PhD, RHIA, CHDA, CPHI, CCS

Chelsea Kemp, RHIA, CCS, COC, CPC, CPCO, CDEO, CPMA, CRC, CCC, CEDC, CGIC, AAPC Approved

Instructor

Regina Kraus, RHIA, CDIP

Donna S. Lehner, RHIA, CDIP, CCS

Monica Leisch, RHIA, CDIP, CCS

Sharon Lewis, MBA, RHIA, CHPS, CPHQ, CAE, FAHIMA

Carole Liebner, RHIT, CDIP, CCS

Wil Limp, MS, RHIA, FAHIMA

Rosann M. McLean, DHSc, MS, RHIA, CDIP

Melany Merryman, RHIA, MSL

Will Morriss, CCS

Vicki Olson, RHIT

Heather Pinske, MBA, RHIA

Casey Richard, MBA, RHIA, CPC, CRC

Dr. Susan H. Richardson, MHSA, RHIA, CPHQ, CHTS-CP

Veronica Richardson, RHIA, CHPS

Reba Sanders, RHIA

Nicole Shearer, RHIA

Elizabeth L. Sheridan, RHIT, CHPS

Gayla Smith, RHIT

Tracy Stanley, RHIT

Vivian Thomas, RHIA, CHDA, CPHQ, CHPS, CDIP, CPHIMS

Rhonda Ward, RHIA

INTRODUCTION

The concept of clinical validation may appear simple; however, its application is complex as medical

conditions may not have universally accepted diagnostic and management criteria. The term clinical

validation is used broadly within the industry. For the purpose of this practice brief, clinical validation will

be discussed as it was defined by the Centers for Medicare and Medicaid (CMS) in the 2011 Statement

of Work (SOW) for the Recovery Audit Program: “Clinical validation is a separate process, which involves

a clinical review of the case to see whether or not the patient truly possesses the conditions that were

documented.”

(p. 23) Although the SOW for the most recently awarded recovery auditor contract (RAC)

in 2021 specifically states, “clinical validation is prohibited in all RAC reviews,” clinical validation has

become a primary denial tool for many commercial payors.

(p. 23)

Clinical validation should not be confused with clinical practice. Clinical practice refers to the provider’s

role of diagnosing and treating the patient. Clinical validation pertains to provider documentation and

how it translates into medical codes. It is the organization’s responsibility to ensure all documented

and reported diagnoses are clinically valid. The introduction to the

Official Guidelines for Coding

and Reporting (to be referenced in the remainder of this practice brief as “Coding Guidelines”)

advises, “[a] joint effort between the healthcare provider and the coder is essential to achieve complete

and accurate documentation, code assignment, and reporting of diagnoses and procedures.”

(p. 1).

Increasingly, the clinical documentation integrity (CDI) professional is also involved in this process and

acts as an intermediary between the provider and coding professional to concurrently obtain additional

documentation needed to support the accurate reporting of diagnosis and procedure codes on claims.

“The importance of consistent, complete documentation in the medical record cannot be

overemphasized. Without such documentation, accurate coding cannot be achieved,”

(p.1) states the

Coding Guidelines. Determining if a diagnosis is reportable is often the domain of the coding professional

who collaborates with providers and CDI professionals. The process of determining if a diagnosis/code is

reportable on a claim is different from clinical validation. When a diagnosis is documented in the health

record by the medical provider, the coding professional may consider it reportable based on the Coding

Guidelines, Section I.A.19, but it may not be fully supported by the clinical evidence (clinically valid)

available within the health record.

Clinical validation should not be confused with the validation process used for risk adjustment. The

American Hospital Association (AHA) Coding Clinic® addressed this topic (Second Quarter, 2022, page

30) explaining that risk adjustment coding is not restricted to the codes included on a single claim related

to a specific episode of care; it is based on conditions collected during the calendar year. Regardless

of the payment mechanism being used and the healthcare setting, professional coders must follow

applicable coding guidance for the reporting of diagnoses on a claim. This practice brief seeks to explain

and clarify the clinical validation process.

The Clinical Validation Process

As mentioned above, the clinical

validation process involves a clinical

review of the health record to identify

potential gaps between documented

diagnoses and the corresponding

clinical evidence. Sometimes the gaps

are easily remedied by querying the

provider for additional documentation

to support the diagnosis in question.

At times, the clinical evidence may

be so sparse that when queried, the

provider determines the diagnosis

is not sufficiently supported.

Subsequently, the diagnosis would not

be considered valid and should not

be reported. When this occurs, the

documentation in the health record

should be updated to support the

ruling out of the diagnosis.

In general, all diagnoses documented in the patient’s health record should be substantiated by clinical

criteria accepted by the medical community. When performing a review for clinical validation, a good

practice is to ask if other providers who evaluate this patient, based on the same clinical evidence, would

arrive at the same diagnosis. When defining the clinical validation process for an organization, it is

important to first determine who will perform the clinical validation reviews.

Depending on the needs of the organization, the clinical validation process can be performed by

professionals with a variety of backgrounds (e.g., coding, nursing, physician, CDI, etc.). Clinical validation

reviews require a strong clinical knowledge base and may not be feasible for all CDI and/or coding

professionals without additional training. Ideally, this process is incorporated into the concurrent CDI

professional review process as the reviewer should already be considering clinical indicators when

identifying documentation gaps and/or discrepancies requiring additional provider clarification. The

professional performing clinical validation reviews should possess strong critical thinking skills as well,

especially when using assistive technology. Clinical validation requires an understanding of the complete

clinical picture to validate the technology recommendations and identify false positives that result from

inappropriate pattern recognition. For example, assistive technologies often focus on key phrases in the

health record but may fail to identify conflicting documentation in other parts of the same clinical note,

such as review of systems or physical exam, which nullify the technology suggested diagnosis.

Because the clinical validation reviews are not always clear cut, it may be necessary to create a second

level clinical validation review process. The purpose of a second level clinical validation process would be

to collaborate with denials management to identify diagnoses that may require closer scrutiny due to a

high risk of denial. If an organization cannot provide information regarding clinical validation denials, the

AHIMA Denials Management Toolkit may be referenced as an additional resource. Some diagnoses are

always vulnerable to denial due to a lack of universal consensus as to how the condition should be defined

by the medical community. Other diagnoses may be vulnerable to denials on a case-by-case basis due

to ambiguity or inconsistency within the associated health record. It is recommended that the facility

address and correct the root cause leading to the ambiguity and, if the root cause cannot be corrected,

create a second-level process to allow an in-depth review that includes all clinical notes (e.g., provider,

nursing, therapist, etc.) that may support the clinical validity of the documented diagnosis. As mentioned

above, a strong understanding of clinical indicators is necessary to perform clinical validation reviews.

Determining the clinical validity of a reported condition can be subjective, making it difficult to appeal

a denial. Furthermore, payers and healthcare organizations may have their own clinical validation

criteria, definitions, and thresholds. What is the required threshold necessary to clinically validate a

diagnosis? CMS advises, “As with all codes, clinical evidence should be present in the health record to

support code assignment.”

(p. 3) CMS does not define diagnoses unless specified in a National Coverage

Determination (NCD) or Local Coverage Determination (LCD). Otherwise, CMS requires the following:

All entries in the medical record must be complete. A medical record is considered complete if it contains

sufficient information to identify the patient; support the diagnosis/condition; justify the care, treatment,

and services; document the course and results of care, treatment, and services; and promote continuity

of care among providers. With these criteria in mind, an individual entry into the medical record must

contain sufficient information on the matter that is the subject of the entry to permit the medical record

to satisfy the completeness standard.

(p. 2)

Some diagnoses are frequently validated by their treatment (e.g., sepsis, acute respiratory failure, severe

malnutrition, etc.) but others may only require monitoring and/or clinical evaluation. Clinical validation

professionals should question denials based on the requirement that every diagnosis must be treated as

that is in conflict with the Coding Guidelines Section III, which advises that, in the inpatient setting, “only

one of the listed criteria needs to be met, such as requires clinical evaluation, therapeutic treatment,

diagnostic procedures, extended hospital stay, or increased nursing care/monitoring.”

Relying on monitoring and clinical evaluation to justify the

reporting of a diagnosis can lead to denials if there is inadequate

documentation to demonstrate that the patient is receiving more

than routine care. For example, a commonly challenged diagnosis

is acute blood loss anemia. This diagnosis may be considered

routine/expected when documented in the health record for surgical

patients having a procedure that routinely requires treatment

with blood products during surgery, such as hip replacement, and

coronary artery bypass. It is also routine practice for many providers

to order a complete blood count for hospitalized surgical patients.

Both examples may result in clinical validation denials unless the

provider specifically states in the assessment and plan why this is

not routine care. Best practice is to educate providers to document

when and why a patient requires more than routine care.

Clinical Definitions and Criteria

Organizations may choose to establish clinical definitions based on professional medical guidelines,

consensus, and evidence-based sources. It is important to note that these clinical definitions serve only

to create standardization within the organization and are not binding with either Medicare or other

payers. It is important to note that not all patients will display the same indicators for a given diagnosis

and not all providers will use the same clinical criteria when diagnosing a condition. When contracting

with payers, organizations should require that Coding Guidelines be followed when reviewing claims to

potentially mitigate future denials. According to these Coding Guidelines, if a diagnosis is documented

it is considered reportable and the coder must report that diagnosis. The AHA Coding Clinic (Fourth

Quarter, 2016, pp. 147-149) Clinical Criteria and Coding Assignment, advises that, if a provider documents

a diagnosis, it will be coded. If a clinical validation reviewer later feels that the diagnosis is not supported

by the clinical findings and documentation within the health record, it is a clinical validation issue and

not a coding error. Additionally, AHA Coding Clinic (Fourth Quarter, 2017, page 110) advises that it is

inappropriate for organizations to automatically omit a diagnosis documented by the provider if it does

not meet any established definition or clinical criteria. Ideally, only diagnoses that are supported by

clinical evidence will be documented within the health record, but that is not always the case.

For example, if the provider has documented a diagnosis of malnutrition based on the patient’s pre-

albumin level rather than the American Society for Parenteral and Enteral Nutrition (ASPEN) criteria, it

is still a reportable diagnosis. Many providers have not adopted ASPEN criteria and there is no federal

requirement stating that ASPEN criteria must be utilized by a provider in making the diagnosis of

malnutrition. AHA Coding Clinic (First Quarter, 2020, pp. 5-6) also addressed this topic when asked which

clinical criteria coding professionals should use when reporting a code for malnutrition. The response was

that it is not within the scope of the AHA Coding Clinics to designate which diagnostic criteria should

be used for any condition. Code assignment is based on the provider documentation that the condition

exists and not the clinical criteria they used to make that diagnosis. While coding and CDI professionals

educate providers on the importance of documentation, it is equally important to encourage providers to

emphasize the clinical evidence they relied upon to make the diagnosis.

What is a Reportable Diagnosis?

The Coding Guidelines provide guidance on when a diagnosis is reportable. Regarding coding advice,

there is a hierarchy. Coding conventions (which apply to both the inpatient and the outpatient setting)

within ICD-10-CM take precedent over all other coding advice. The most important coding guideline

that impacts clinical validation is in Section I A.19: Code Assignment and Clinical Criteria of the Coding

Guidelines:

The assignment of a diagnosis code is based on the provider’s diagnostic statement that the

condition exists. The provider’s statement that the patient has a particular condition is sufficient.

Code assignment is not based on clinical criteria used by the provider to establish the diagnosis. If

there is conflicting medical record documentation, query the provider.

(p. 12)

The statement, “If there is conflicting medical record documentation, query the provider,” was

added to this guidance for fiscal year 2023. The Coding Guidelines do not provide a definition for the

term, “provider’s diagnostic statement,” leaving it open to some degree of interpretation. It is useful to

supplement this guidance with the AHA Coding Clinic advice (First Quarter, 2014, pp. 11-13) regarding

provider documentation, which advises that the assignment of codes in the inpatient healthcare setting

can be based on the documentation of other providers involved in the care and treatment of the patient if

it is not conflicting.

Inpatient Coding Guidelines and Other Considerations Impacting Inpatient Clinical Validation

Section III of the Coding Guidelines

(p. 107): Reporting Additional Diagnoses, further defines criteria for

reporting diagnoses in the inpatient setting. This guideline advises:

For reporting purposes, the definition for “other diagnoses” is interpreted as additional conditions that

affect patient care in terms of requiring:

For reporting purposes, the definition for “other diagnoses” is interpreted as additional conditions

that affect patient care in terms of requiring:

• clinical evaluation; or

• therapeutic treatment; or

• diagnostic procedures; or

• extended length of hospital stay; or

• increased nursing care and/or monitoring.

The Uniform Hospital Discharge Data Set (UHDDS) item #11-b defines other diagnoses as ‘all

conditions that coexist at the time of admission, that develop subsequently, or that affect the

treatment received and/or the length of stay. Diagnoses that relate to an earlier episode which have

no bearing on the current hospital stay are to be excluded.’

(p. 107)

Any reported secondary diagnosis should meet at least one of the above stated criteria.

Chronic conditions can present another coding and clinical validation challenge. Clinical validation

professionals should reference AHA Coding Clinic for guidance. For example, there are chronic conditions

that are systemic and will affect a patient’s health status throughout their life such as chronic pulmonary

obstructive disease (COPD), hypertension, and diabetes mellitus, among others. In the inpatient setting,

these types of lifelong chronic conditions should be coded even if they are documented as “a history of”

(Third Quarter, 2007, pp. 13-14). Additionally, obesity was added as a chronic condition when documented

by the provider since it is always clinically significant (Third Quarter 2011, pp. 3-4). Although these

diagnoses are not typically classified as complications/comorbidities (CC) or major complications/

comorbidities, they can impact risk adjustment. For coding, no further documentation is needed but this

could lead to a clinical validation denial. Best practice would be to educate providers to include relevant

clinical indicators in their documentation for every diagnosis.

Outpatient Coding Guidelines and Other Considerations

Although the concept of clinical validation

continues to expand and evolve in the inpatient

setting, review activities in the outpatient

setting would not typically meet the definition

of clinical validation. Most of the denials in

the outpatient setting are not challenging the

clinical validity of the documented condition but

challenging the reportability of the condition

and the medical necessity of services provided.

Requirements outlined in Medicare NCDs, LCDs

and by commercial payers help the claims

auditor determine if the service is considered

medically necessary and eligible for coverage.

Some organizations may have staff assigned

to validate the diagnosis and documentation

required by a payer to be eligible for coverage

and seek clarification from the provider as

needed, but this is not a clinical validation

review.

It is also important to recognize that the process of abstracting diagnoses for Medicare Advantage and

other risk-adjustment models, which often occurs in the outpatient setting, is a different approach from

traditional clinical validation.. Specifically, these challenges in the outpatient setting are questioning

whether a diagnosis should be reported, not whether the condition exists. CMS publishes the

Medical

Record Reviewer

Guidance for Medicare Advantage Recovery Audit Data Validation (RADV)

organizations. Per the introduction, “these guidelines are used by coders to evaluate the medical records

submitted by plans to validate audited diagnoses,” submitted during the RADV medical record process.

(p. 6) It also advises that “the reviewers must first apply their expertise in documentation and official

coding guidelines to each scenario. This guidance does not give advice for specific diagnosis coding.”

(p.

7) RADV auditors can consider diagnoses in the problem list if they are adequately supported by relevant

clinical indicators:

Evaluate the problem list for evidence of whether the conditions are chronic or past history and

if they are consistent with the current encounter documentation (i.e., have they been changed or

replaced by a related condition with different specificity). Evaluate conditions listed for chronicity

and support in the full health record, such as history, medications, and final assessment.

(p. 42)

This guidance is supported by the AHA Coding Clinic Second Quarter, 2022, pp. 30-31, AHA Coding Clinic

Third Quarter,2021, pp. 32-33 and AHA Coding Clinic Third Quarter, 2020, page 33.

It is important for those performing clinical validation in the outpatient setting to not extrapolate CMS

guidance issued for Risk Adjustment (e.g., CMS-HCC, HHS-HCC) into their process as this guidance is

focused on the validation of the data submitted for a specific risk adjustment calculation model and

not coding guidance related to claim submissions. Coders must follow the instructions and conventions

of ICD-10 coding, Coding Guidelines, and the AHA Coding Clinic when assigning codes for claim

submissions.

Many auditors, coders, and CDI professionals use the acronyms MEAT (monitor, evaluate, assess, or

treat) or TAMPER™ (treatment, assessment, monitor/medicate, plan, evaluate, or referral) to determine if

a diagnosis is reportable in the outpatient setting. The applicability of these acronyms should be limited

to reporting diagnoses in the setting of risk adjustment. It is important to remember that these acronyms

are not official coding guidance. Regardless of healthcare setting, official coding guidelines will take

precedence over payer-specific requirements or other policies.

Clinical Validation Queries

During a clinical validation review it may be determined that a diagnosis lacks sufficient clinical

indicators based on organizational requirements. These requirements may include but are not limited to:

• a documented diagnosis that lacks clinical indicators that are generally accepted by the

medical community

• a documented diagnosis that appears to be no longer valid, but the documentation does not

confirm the condition as ruled out/eliminated/resolved

• clarification of an uncertain diagnosis that has been copy pasted/copy forwarded from the

history and physical (H&P) to the discharge summary

• seeking justification of a documented condition with an atypical patient presentation

In these situations, a clinical validation query will be necessary to support accurate diagnosis reporting.

Organizations should have policies and procedures that clearly define who will perform clinical validation

reviews and issue clinical validation queries. This may be part of the concurrent CDI review process, a

second level review process, and/or the coding process. In addition, organizations should address how the

clinical validity of a diagnosis will be considered during the coding process. Specifically, this policy should

address how to manage the reporting of a diagnosis when a provider’s response to a clinical validation

query conflicts with the clinical scenario. This may require an escalation process for medical review and

coordination with the denials management team.

Composing a clinical validation query may be a difficult task. It is important to remember that the intent

of the clinical validation query is not meant to question the medical judgement of the provider but to

ensure the documented diagnosis is clinically valid. As with all queries, clinical validation queries are

governed by the practice brief,

Guidelines for Achieving a Compliant Query Practice. However, it

is important to remember that the clinical validation query has a different objective. Often the goal of

a query is to add or further specify a reportable diagnosis while the clinical validation query requests

additional supportive documentation, which may result in the removal of a documented diagnosis.

When constructing the clinical validation query using the multiple-choice format, only reasonable

options should be included in addition to allowing the provider an alternative response (e.g., “other,”

“other explanation of clinical findings”). The provider may be unable to build upon the clinical evidence

already documented in the health record. When able to do so, however, the provider should include these

additional clinical indicators in the health record which may require an addendum. When providing

alternative diagnoses as response options, the query wording should clearly indicate that, when selected,

they will be reported in lieu of the diagnosis in question (e.g., sepsis ruled out and determined to be

secondary to noninfectious source [SIRS]). See Appendix A for clinical validation query examples.

Educational Considerations

Education for the Clinical Validation Professional

• Clinical Concepts: Information related to commonly queried topics including pathophysiology,

pharmacology, diagnostic evaluation, clinical indicators, and treatment modalities, should

routinely be provided.

• Organization Specific Evidence-Based Clinical Practice Guidelines: Evidence-based clinical

practice guidelines are defined as an “Explicit statement that guides clinical decision making

and has been systematically developed from scientific evidence and clinical expertise to answer

clinical questions; systematic use of guidelines is termed evidence-based medicine.”

(p. 92) The

clinical validation professional must have ongoing education on the most current evidence-

based guidelines used for diagnosing and treating various conditions. This should include the

supporting clinical indicators, risk factors, diagnostic testing, and treatment.

• Changes in Coding Guidelines, Industry Standards, and Payment Systems: There must be

ongoing education regarding any coding guideline changes concerning diagnosis selection. This

may vary by the healthcare setting and may include (but is not limited to):

° review of the ICD-10-CM/PCS Official Guidelines for Coding and Reporting,

° review of the Coding Clinics published quarterly by the AHA,

° review of the National and Local Determinations for Coverage (NDC/LDC),

° annual updates to relevant payment methodologies, and

° updates to industry practice briefs.

• Clinical Validation Query Composition: Education regarding proper clinical validation query

composition should be provided.

° The clinical validation query must follow the same guidelines for compliance outlined for

all queries in the latest update to the industry practice brief, “Guidelines for Achieving a

Compliant Query Practice.”

° The intent is to clarify the documentation needed to support a diagnosis documented

within the health record for the purpose of accurate reporting and denials prevention.

Education for the Medical Provider

• Intent of the Clinical Validation Query: The provider should know that the purpose of the

clinical validation query is to seek alignment between documented diagnoses and relevant

clinical indicators.

• Supporting Documentation: When educating the medical provider regarding clinical validation

and the clinical validation query process, documentation best practices should be discussed.

° Document the clinical indicators/criteria used to support the diagnosis.

° If a condition has been ruled out or resolved during admission, clearly note that in the

health record.

° Ensure documentation, including the problem list and discharge summary, accurately

reflects clinically valid diagnoses.

° Ensure clinical findings documented in the review of systems and physical exam support

documented diagnoses.

° Include an explanation supporting atypical presentation—when the provider believes a

particular condition is present despite the absence of the clinical indicators commonly

associated with that condition, such as immunocompromised state, reasons certain

medications cannot be prescribed for the patient, and alternative medications given.

° Provide an explanation as to why the treatment provided may vary from that commonly

associated with the documented condition.

• Electronic Health Record Templates: Use caution when using templates that auto populate

fields or add default values that may conflict with the clinical scenario.

• At-Risk Diagnoses: Providing real examples of denied claims within the organization may help

convey the importance of high-quality documentation and the clinical validation process.

• Implications of the Copy Paste/Copy Forward Functionality: The copy paste/copy forward

functionalities of many electronic health record programs may lead to diagnoses that have been

ruled out to continue to be documented throughout the health record. Specifically, copying and

pasting the H&P into the discharge summary may include diagnoses that were appropriately

uncertain (possible, probable, likely, etc.) at the time of admission but have subsequently been

addressed and may no longer be valid. In the inpatient setting, uncertain diagnoses that are

documented at the time of discharge may be reported, which may lead to a clinical validation

denial.

Summary

Clinical validation is a process that requires continuous collaboration between providers, CDI, and

coding professionals. Ideally, this process is incorporated into the daily workflow of the CDI and coding

professional. Some organizations may choose to develop internal criteria for specific diagnoses to help

providers and the CDI/coding team stay on the same page. These established criteria, however, are not

binding but instead a reference to guide the team. The goal of this criteria is to promote consistency

among the CDI and coding professionals when identifying diagnoses that may lack clinical evidence

and, therefore, require clinical validation. If a diagnosis is reported as documented but lacks the clinical

evidence within the health record to support it, a clinical validation query should be considered to

mitigate inappropriate reporting. It is important for organizations to establish an internal policy defining

the clinical validation process. When performing clinical validation, it is appropriate to ask whether

other providers, clinical validation reviewers, coding professionals, and auditors would come to the same

conclusion based on the totality of the health record.

Appendix A: Clinical Validation Query Examples

Below are some examples of compliant clinical validation queries. The components of a compliant

query apply to all queries and modes of query communication. These components are outlined in the

Guidelines for Achieving a Compliant Query Practice.

Acute Respiratory Failure Example:

Dr. Jones,

It is documented in the emergency department (ED) note mm/dd/year that this 60-year-old male will be

admitted for COPD Exacerbation. PMH documents “chronic respiratory failure” and advises “the patient

requires continuous home oxygen @ 2L/NC.”

The ED provider documents in the assessment “some mild dyspnea but speaking in mostly clear

sentences; respiratory rate = 22 bpm and patient with normal mentation.”

ABG drawn in ED on 2L/NC = pH 7.35; pCO2 = 45 mmHg; pO2 = 90 mmHg; HCO3 = 25 mEq/L

Per respiratory therapy note mm/dd/year this patient was placed on O2 3L/NC for 2 hours and then

decreased to 2L/NC.

H&P mm/dd/year documents “acute on chronic respiratory failure (ACRF)” without specifying any

additional clinical indicators.

Please clarify the clinical validity of the documented diagnosis of ACRF:

• Ruled out

• Confirmed as evidenced by the following clinical indicators (please provide additional

supporting documentation: __________________________________________

• Other explanation of clinical findings; ___________________________

Alternative Example:

Dr. Jones,

The H&P documents mm/dd/year: acute on chronic respiratory failure (ACRF). Based on the clinical

indicators provided below, please verify if ACRF is clinically valid?

Patient hasd chronic respiratory failure with acute exacerbation of COPD

Patient has ACRF as evidence by the following clinical indicators: __________________________

Other explanation of findings: _____________

Indicators:

ED note mm/dd/year:

• PMH: chronic respiratory failure; requires continuous home oxygen @ 2L/NC.

• Some mild dyspnea but speaking in mostly full sentences

• RR = 22 bpm; normal mentation

Respiratory therapy note mm/dd/year:

• Placed on O2 3L/NC for 2 hours then decreased to 2L/NC

Labs/ABG mm/dd/year:

• on 2L/NC = pH 7.35; pCO2 = 45 mmHg; pO2 = 90 mmHg; HCO3 = 25 mEq/L

Encephalopathy Query Example

Dr. Jones,

69-year-old male admitted from SNF for complicated UTI.

ED note mm/dd/year documents “known history of dementia. Family advises patient is known to be

frequently confused, hostile, exhibiting disruptive behavior as consequences of dementia.”

H&P mm/dd/year documents “Encephalopathy in the setting of infection.”

Per nurses’ notes mm/dd/year: “GCS scores ranging from 12-14; mental status does not change with

treatment of UTI.”

After further study and based on these clinical indicators, please clarify the clinical validity of the

documented diagnosis of encephalopathy.

• Confirmed as evidenced by the following clinical indicators (please provide additional

supporting documentation): __________________________________________

• Ruled out

• Other explanation of clinical findings; __________________________________________

Severe Protein Calorie Malnutrition Query Example

Dr. Jones,

Severe protein calorie malnutrition is noted in the H&P mm/dd/year in the problem list and is carried

through to the daily progress notes and the discharge summary. Based on the indicators below, please

clarify the clinical validity of the documented diagnosis of severe protein calorie malnutrition (SPCM) for

this admission?

• SPCM clinically valid for this admission as evidenced by the following clinical indicators (please

provide additional supporting documentation): ______________________________

• Patient only has a history of SPCM

• Other explanation of clinical findings: __________________________________________

Indicators:

H&P mm/dd/year:

• Small bowel obstruction with newly diagnosed primary cancer of the small bowel

• Well-developed and well nourished; noted to be somewhat underweight

• BMI = 18 and Prealbumin = 13.0

Dietary Consult mm/dd/year:

• Five percent weight loss in the past month with mild loss of subcutaneous fat from triceps

• Patient at 93% of normal weight

• Consuming 80% of the estimated energy requirement for the 3 days prior to this admission

• Provide Ensure with meals as a supplement

Sepsis Query Example

Sepsis is documented in the H&P assessment mm/dd/year and not carried through to the progress notes

or discharge summary.

Admitting vital signs mm/dd/year: HR 91; RR = 22; BP = 105/50; Temp = 99.1F.

Labs mm/dd/year: WBC = 12.0; Lactic acid = 2.2 mmol/L. Blood culture mm/dd/year – negative x 3

H&P mm/dd/year: PMH of COPD. Alert and oriented. C/O pain with inspiration on right side; advises some

increased SOB. Possible pneumonia noted on CXR. Start IV antibiotics. Repeat CXR in the AM

After further study and the indicators provided, please clarify the clinical validity of the documented

diagnosis of sepsis for this admission.

• Sepsis was present on admission as evidence by _________ and resolved during this admission

after treatment

• Sepsis was ruled out for this admission after further study.

• Other explanations of clinical findings: ________________________________.

References

1. AHIMA (2017) Pocket Glossary of Health Information Management and Technology (5

ed.),

AHIMA Press, Chicago, IL.

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transmittal 47, p. 2. Retrieved November 4, 2022, from: R47SOMA.pdf (cms.gov)

3. CMS (2011). Statement of Work for Recovery Audit Program, p. 23. Retrieved January 30, 2023,

from: Draft Statement of Work for the Recovery Audit Contractors (cms.gov)

4. CMS (2020, January 1). Contract-Level 15 Risk Adjustment Data Validation. Medical Record

Reviewer Guidance in effect as of 01/10/2020, Version 2.0. Retrieved November 4, 2022,from:

RADV Medical Record Reviewer Guidance in effect as of January 10th, 2020 (cms.gov)

5. CMS (March 26, 2021). Statement of Work (SOW) for Part A/B Medicare Fee-for Service

Recovery Audit Contractor (RAC) – Region 1. Retrieved January 30, 2023, from: https://www.cms.

gov/files/document/rac-sow-region-1-march-26-2021.pdf

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Sept. 19, 2022, from: ICD-10-CM Guidelines FY 2023 (cms.gov)

7. Department of Health and Human Services (HHS) (2012, July 31). Recovery Audit Program

Diagnosis Related Group (DRG) Coding Vulnerabilities for Inpatient Hospitals. MLN Matters:

SE1121, p. 3. Retrieved December 16, 2022, from: https://www.hhs.gov/guidance/sites/default/files/

hhs-guidance-documents/SE1121.pdf