In order to understand how a patient’s diagnosis code profile is assembled and how its accuracy is assured, one must have knowledge of the organization’s Clinical Documentation Integrity (CDI) department, their Coding Department partners, the federal guidelines relating to coding, and the processes that lead to the submission of the final bill and its associated diagnosis codes. In this chapter, we provide an overview of the evolution of CDI from finance to quality and illustrate how processes and tools have been aligned accordingly in our health system. We also describe our efforts in optimizing one of the critical tools, the physician query.

1 Inpatient Payment Methodology Shift

Historically, under the Centers for Medicare & Medicaid Services (CMS) inpatient prospective payment system (IPPS), hospitals pursued opportunities for enhanced revenue capture by launching a formal Clinical Documentation Improvement (CDI) program comprised of dedicated staff concurrently reviewing patients’ charts to improve both the accuracy and completeness of the medical record. This finance-driven approach was the rationale for the program implementation at Ochsner Health, and a team of registered nurses was established reporting within the organization’s Revenue Cycle in the department of Health Information Management.

1.1 Inpatient Prospective Payment System

Under the IPPS payment system, hospitals are reimbursed based on the volume of Medicare Severity diagnosis-related group (MS-DRGs) assigned. MS-DRGs are intended to describe resource consumption and severity of diagnoses. MS-DRG assignment is driven by the selection of principal diagnosis, procedures performed, identification of complications/comorbidities (CC), and major CCs (MCCs) such as age, gender, and discharge disposition. Each MS-DRG is also assigned a relative weight (RW). A higher relative weight is associated with longer length of stay, greater severity of illness, and higher reimbursement. Hospital reimbursement is then calculated by the specific MS-DRG relative weight multiplied by the hospital blended rate. A hospital is assigned its specific blended rate based on a formula that includes geographic location, services provided, etc. (Fig. 8.1).

Fig. 8.1
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DRG payment inputs. (© Ochsner Health). (© Ochsner Health)

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1.2 Diagnosis Codes and Quality

The early mission of the CDI department was the optimization of the MS-DRG but evolved to include a new focus on capturing severity of illness (SOI) and risk of mortality (ROM) using the 3M™ All Patient Refined DRG (APR DRG) Classification System [1]. APR DRG helps provide a higher level of detail about a patient’s condition and the care provided by addressing the differences in relationship to “how sick” and the “likelihood of death.” This was a first step to correlate with the hospital’s mortality index, an early measure of health-care quality.

The classification system is driven by a section of principal diagnosis, procedures performed, most secondary diagnoses, age, and gender. It groups similar DRGs between four different categories (1 – minor, 2 – moderate, 3 – major, and 4 – extreme). By having CDI specialists focus on the APR DRG, they are helping physicians and coders improve the depiction of patient acuity. This classification, along with cost and charges obtained from claims data and other discharge data associated with patient care, enables payers and others to profile patients and providers. By analyzing practice patterns and resource utilization, it allows for comparison of items such as the actual mortality vs. the expected mortality; patient length of stay and cost; and facility and physician performance compared to similar groups, to name a few. Figure 8.2 shows the change in DRG and SOI based on documentation and the corresponding relative weights.

Fig. 8.2
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Examples of DRGs with differing relative weights and impact on expected LOS and SOI/ROM

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The relationship between quality measures and reimbursement continued to evolve as CMS made changes to the inpatient methodology mandated within the Patient Protection and Affordable Care Act (ACA) signed into law in 2010. The approach to health-care performance is focused on three dimensions known as the “Triple Aim”: improving the patient experience of care (including quality and satisfaction), improving the health of populations, and reducing the per capita cost of health care [2]. To operationalize this, the Department of Health and Human Services implemented three value-based programs: Hospital Value-Based Purchasing Program (HVBP), Hospital Readmission Reduction Program (HRRP), and Hospital-Acquired Condition Reduction Program (HACRP).

Implementation of Value-Based Care (Fig. 8.3) transforms CMS from a passive payer to an active purchaser of higher-quality, more efficient health care. It incentivizes the best care and improves transparency for Medicare Beneficiaries by making comparative data available on the Hospital Compare website. Measurable goals were set to link 85% of the Medicare fee for service payment to quality or value by 2016 and 90% by the end of 2018. The impact of the program includes a 2% reduction in reimbursement across all MS-DRGs, and then hospitals are awarded money based on their total performance. The bottom 25% of hospitals are penalized with 1% payment reduction and hospital-acquired conditions (HACs) not reimbursed as CCs and MCCs.

Fig. 8.3
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Transformation to value-based approach through the inpatient payment methodology shift

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Hospital performance for HVBP is based on an approved set of measures grouped within domains (Fig. 8.4). Each domain is assigned weights (percentages), used to score each domain. Fiscal year 2021 domains include Clinical Outcomes (25%), Person and Community Engagement (25%), Safety (25%), Efficiency and Cost Reduction (25%). Within the Safety Domain are specific patient safety indicators (PSIs) identified by the Agency for Healthcare Research and Quality (AHRQ) as potentially avoidable in-hospital safety events and the Centers for Disease Control and Prevention (CDC) National Healthcare Safety Network (NHSN) healthcare-associated infection (HAI) measures, which include central line-associated bloodstream infection (CLABSI), catheter-associated urinary tract infection (CAUTI), surgical-site infection for abdominal hysterectomy and colon procedures (SSI), methicillin-resistant Staphylococcus aureus (MRSA) bacteremia, and Clostridium difficile infection (CDI). The Clinical Process of Care Domain measures how often a hospital performs care for specific conditions.

Fig. 8.4
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Overview of CMS value-based purchasing (VBP) program [3, 4]. (© Ochsner Health)

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2 Organizational Changes with Value-Based Hospital Reimbursement [5]

The shift to value-based reimbursement requires organizations to evaluate the efforts of the CDI specialist, coding and operations including staffing, workflow, available technology, and performance metrics to address the requirement for detailed coding and documentation. Within our organization, the full-time equivalent staffing was calculated to allow for a lower percentage of total discharge patient account coverage and a lower percentage of daily chart reviews to account for the increased review efforts focusing on quality measures. Implementation of CDI software allowed for the identification of PSI and HAC during the CDI review process.

Adaptation to the new CDI software allowed for the ability to identify and share real-time data with the quality team to conduct PSI and HAC review instead of the quality team waiting for administrative data to conduct a retrospective review. Led by the chief quality and patient safety officer, a committee composed of system quality improvement leaders, documentation specialists, and data manager, the team was trained on the new review process. This collaborative approach helps the organization ensure accurate data and minimize penalties under the HVBP. Similar efforts have been described by others [6, 7].

A significant structural change within our health information management (HIM) division was the adoption of a service line model that allows for enhanced review of documentation through the implementation of a concurrent coding process in addition to concurrent CDI review within service specialties. The focus of the model was to create coding and CDI experts within their own discipline and specialty. Workflow redesign helped to minimize duplicate work and post billing adjustments while creating a stronger partnership between the two disciplines. This collaborative effort of the two disciplines (Fig. 8.5) helps to support achieving the goal of complete and accurate coding by ensuring the right information is being captured in a complete and timely fashion.

Fig. 8.5
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Collaboration between clinical documentation improvement and coding groups. (© Ochsner Health)

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3 Ochsner Health Clinical Documentation Guidelines

With a service line model in place, certain diagnoses were identified as opportunities for provider education due to the high number of queries, discrepancies between documentation and coding, and the frustrations among the providers as well as the HIM team reflecting that clinical language does not always equate to coding language. This was the basis to form a team focusing on documentation improvement initiatives, including system-wide clinical definitions for provider documentation known as the Ochsner Health Clinical Documentation Guidelines (see Fig. 8.5). The team included stakeholders, leadership, quality, and compliance. Our physician advisor took the lead to collaborate with CDI, coding, compliance, and specialty-specific providers on the development of evidence-based clinical criteria. Prioritization was determined by a steering committee based on available internal data.

Each guideline was developed as an educational tool to communicate health system clinical definitions and fundamental coding guidelines for certain diagnoses, though never intended to replace the provider’s clinical judgment. In addition to the definition, guidelines include criteria for a specific diagnosis, approved abbreviations, documentation tips for coding accuracy, documentation examples, as well as references. Since clinical language does not always equate to coding language, these tip sheets include specific examples of documentation that cannot be captured as coders cannot make any assumptions. Commonly used terminology by our providers that did not translate into codable language was identified using chart audits and was termed “words to avoid” in the tip sheets. Examples include recommendations to avoid documenting “creatinine doubled, if you mean acute renal failure,” avoid documenting “use of continuous home O2 if you mean chronic respiratory failure,” and avoid documenting “chest pain if you mean angina” (Fig. 8.6).

Fig. 8.6
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Example of an Ochsner Health Clinical Documentation Guideline. (© Ochsner Health)

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Although these clinical documentation guidelines were developed to standardize medical diagnosing and clinically support documentation for diagnoses across the organization, they have evolved to be the basis of smart phrases builds and query form optimization. The first phase of rollout of the Ochsner Health Clinical Documentation Guidelines included making the content available in the electronic medical record as linked resources. The reference can also be found on the health system provider portal, an intranet resource (see Fig. 8.7).

Fig. 8.7
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Location of the Ochsner Health Clinical Documentation Guidelines on the organization’s intranet. (© Ochsner Health)

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The second phase of the rollout was developing smart phrase builds in the electronic medical record that can be used by the provider to guide documentation needs (see Fig. 8.8). Whether this smart phrase is automatically populated when a diagnosis is chosen using problem-oriented charting or whether it is brought in by the provider using a dot phrase, the provider merely needs to navigate through the phrase and answer the questions. If the smart phrase is utilized, supporting documentation is still needed to reflect the patient’s severity of illness risk of mortality and justify the provider’s level of service will be populated. The third phase of rollout included aligning the tip sheets with the physician query forms.

Fig. 8.8
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Example of smart phrase designed to improve documentation accuracy in the electronic medical record. (© Ochsner Health)

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4 The Physician Query

CDI utilizes a communication tool known as the physician query to ensure precise code assignment. Professional guidelines for use of the query are set forth in the American Health Information Management Association (AHIMA) practice briefs. Queries are not used to question the medical judgment of the provider, but rather to clarify documentation.

Queries may be submitted (but are not limited to) by the following instances [8]:

  • When documentation is conflicting, incomplete, lacking, or ambiguous

  • When documentation describes or supports a medical condition or diagnostic evaluation and/or treatment without a corresponding diagnosis or procedure

  • When documentation is not clear to support assignment of present on admission indicator

  • When documentation reports a diagnosis that is not supported by clinical indicators

The query format includes open-ended, multiple-choice, yes/no, or verbal questions. Regardless of the format, every query must be individually adapted to the patient during a particular encounter. Clinical indicators pertinent to the condition in question are included in the query and may include signs and symptoms with duration, diagnostic test results, lab findings, findings of consultants, and treatment performed. As discussed above, our query forms also include our health system definitions as a tool for providers.

The multiple-choice query is the type query utilized within our organization. It offers direction to the type of information sought; therefore, clinically significant and reasonable options are listed based on the clinical indicators. Options such as “clinically undetermined,” “other,” “not clinically significant,” or even “integral to,” along with an open space for the provider to add additional verbiage, may also be included.

Queries are identified through the CDI record review either concurrently by initiating the review within 24–48 h of patient admission or retrospectively. Once the query opportunity is identified, the appropriate form is utilized to formulate the content and assign it to the provider of record electronically. Providers may enter their response either directly on the query or within their progress notes. All queries are retained as a permanent part of the legal medical record.

When diagnoses in the medical record are not supported by clinical indicators, the CDI submits a query known as a clinical validation query. The intent of the query is to gain further clinical evidence of the condition to support accurate code assignment. This type of query allows for the provider to indicate if the condition is present and the opportunity to provide clinical support. If the provider concludes the condition is not present, a statement can be made indicating that the condition has been ruled out (Figs. 8.9 and 8.10).

Fig. 8.9
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Example of a multiple-choice physician query. (© Ochsner Health)

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Fig. 8.10
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Clinical validation query. (© Ochsner Health)

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4.1 Practical and Real-Life Considerations

Queries are the bridge between the true clinical picture and accurate clinical documentation. They are one of the pillars of success for a hospital from a documentation accuracy perspective. Optimizing queries is a multifaceted and multistep project. With clinical guidelines and coding guidelines constantly evolving, optimizing queries is a journey, not a final destination. The two major steps to optimizing queries are (1) an accurate comprehensive query template and (2) optimal and compliant utilization of the queries by the CDIs.

Query templates must be structured to include all clinical indicators for each query type, with answer options focused to achieve accurate diagnoses coding appropriate for the clinical indicators. Health-care organizations usually set up a designated medical record query committee comprised of experts from the clinical and coding worlds. Each query template may be reviewed by a physician champion. Our internal practice is to have all templates reviewed by a physician champion to make sure that the queries have the most accurate clinical indicators and answer options. This may include discussion with specialty and subspecialty experts, depending on the nature and type of the query and the clinical condition being queried. Care should be taken to ensure that the verbiage of the answer options in the queries is correct from a clinical perspective and enables compliant accurate coding.

The utilization of queries by CDI holds greater importance than the structure of the query templates. CDIs may issue queries for one or more of the following purposes: need for additional diagnosis documentation based on clinical criteria, conflicting documentation, coding purposes, higher accuracy in coding, clarifications of potential complications, requesting additional specificity for documented diagnosis and present on admission status. The timing of issuing a query, from the hospital course perspective, is as important as the purpose of and the details in the query. Queries must include all possible clinical indicators and examples of conflicting documentation to present the complete picture to the provider to get the most accurate response.

CDI professionals may consider having a compliant conversation with the provider to discuss the purpose of the query. They should be cognizant and aware of the potential response that they anticipate from the provider. The verbal query process would parallel the thought process that the CDI professionals exercise while contemplating and drafting a query. One example is the situation where clinical indicators exist to suspect that hypertension may be associated with diabetes mellitus. Our team feels that CDI professionals may explain to the physician how such documentation might lead to the assignment of a code not reflective of the patient’s actual disease if the physician instead had meant to document that hypertension was a manifestation of diabetes. Speaking with the physician in certain cases thus may be appropriate to explain why queries are written.

4.2 Further Defining Medical Record Queries: Process and Timing

Physician queries are real-time-focused (i.e., while the patient is still in the hospital) requests for clarification of information within a provider’s documentation. Queries are issued because there is a clinical documentation (nurse’s notes, lab reports, etc.) that has not been captured in the provider’s documentation. Alternatively, such clinical documentation may conflict with the provider’s documentation, again necessitating that a query be issued for clarification. As mentioned, queries are generally issued while the patient is still in the hospital or while documentation is still being actively considered after discharge. In the latter situation, the query would occur between the time of patient discharge and before final billing.

Physician queries are issued by individuals who are not on the patient’s care team. Such individuals generally are CDI nurses. In some environments, specially trained professionals such as a performance improvement coordinator, physician advisor, or physician quality director might issue a medical record query, although the usual role for the physician advisor or quality director is provider education.

Queries should ideally be accomplished within the electronic medical record with the capability to track provider responsiveness and coding/CDI loop closure.

4.3 What Is Not a (Compliant) Query?

4.3.1 Provider Education

Documentation education delivered either to groups of providers is not considered a part of the query process. Likewise, documentation education to a single provider does not represent a medical record query as long as it occurs outside of the context of an active pre-billed patient. Education of a single provider on an issue concerning documentation on such a patient is discouraged and must not lead or influence the provider.

Discussions Among Providers

Discussions between members of a patient’s care team (residents, advanced practice providers, or physicians) around a diagnosis or its documentation are not considered queries.

4.3.2 Asking for or Prompting Clinical Judgment

An example of this would be when a physician in an administrative role such as a medical director of quality asks for or prompts a clinical judgment to be rendered by a treating provider (e.g., an attending or a specialty consultant in that area), such as whether an adverse patient event was an expected outcome of the procedure or an unexpected complication. Another example would be asking for more specificity related to a diagnosis, such as with verbiage similar to “You wrote CHF, can you be more explicit including whether its acute or chronic, as well as systolic or diastolic – see attached Ochsner clinical guideline?” Or asking for clinical clarification in order to ensure correct capture of acuity such as “You wrote ‘AKI’. Was that meant to convey that the patient has renal failure from an acute kidney injury or did the patient have a renal insult that did not result in renal failure?“Or asking about the presence of a diagnosis that likely existed based on record review, but was not documented (e.g., many exclusion diagnoses). Or asking physician/provider for follow up to a prior request such as mentioned earlier or responding to a request for information. As mentioned before, asking physicians or prompting them to document certain diagnoses or aspects of a diagnosis is not compliant. The compliant procedure for clarifying diagnostic information is discussed below.

5 Compliance Essentials and Physician Queries [9]

Physician queries must not contain explanations of the impact of one particular response over another – monetary or quality measurement result. To be safe, no mention should even be made of why the issue precipitating the query even came up. Sensitizing the medical staff to the reasons for queries can be safely accomplished through separate medical staff education. Medical record queries should not lead or influence the physician to answer one choice over the other based on how the query format is composed. When answering queries, medical staff should be assured that the choices presented are in random order. To be compliant, queries must not be issued repeatedly to arrive at the desired answer.

A compliant query format includes a “confirmation” query that essentially seeks a yes/no answer, such as “Please confirm if a diagnosis truly existed/was ruled in or out.” However, it is prudent to leave the provider a third choice to indicate an alternative diagnosis in case the physician believes that neither a “yes” nor a “no” answer would be correct. Other compliant query languages may ask providers to “comment on whether the diagnosis was likely present on admission, please indicate” or “indicate if a lesser or more severe level of the condition was present.” Any of these formats presuppose that clinical indicators exist in the medical record to justify issuing the query.

For complications, defined as any conditions that occurred during or after surgery or a procedure, physicians can be asked to reflect if this was a complication or a concurrent condition. This is to indicate if the occurrence was expected or inherent in the procedure. Again, clinical indicators must exist to justify issuing a query, such as the documentation in the surgeons’ operative note that the patient’s anatomy was abnormal and might have led to an enterotomy. In the absence of the surgeon’s clear documentation that the enterotomy was a surgical complication, documentation of difficult and abnormal anatomy, such as the presence of extensive adhesions, then may constitute a clinical indicator justifying a query to clarify if a complication had occurred. It is definitely not considered compliant for individuals not using the medical record query format (written or verbal) to suggest diagnoses to the physician, allude to potential adverse effects of documentation, or dissuade physicians from documenting or responding to certain choices within a medical record query. While this can be part of general provider education efforts, it is not compliant to make any of these communications while the patient’s coding profile is still being assembled, that is, during the pre-bill period.