Health Information Management

Use encoders alongside of critical reasoning and clinical knowledge

JustCoding News: Inpatient, February 1, 2012

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by Glenn Krauss, BBA, RHIA, CCS, CCS-P, CPUR, FCS, PCS, C-CDIS, CCDS

A coder can be misled when coding directly from an encoder, and heavy dependence on one can ultimately affect a coder’s skill set.

A critical limitation of encoders is that they cannot physically reason. This inability to deduce often contributes to inaccurate ICD-9-CM code assignment at the expense of clinical accuracy in the reporting of disease processes, not to mention potential reimbursement and measures of continuity of care post-hospitalization. Coders must reason through what the physician documented. Encoders cannot possibly take into account the vast individuality of clinical scenarios and the multitude of different disease processes.

Many times coders look to their encoder to find and validate a code, when instead they need to refer to the trusty ICD-9 Manual and applicable Coding Clinics to derive the most accurate code(s) based on the clinical documentation and other pertinent content in the medical record.

Far too often coders use encoders as a crutch, simply accepting the ICD-9 diagnosis code that the encoder supplies to proceed to the next chart. This prompts a question of why coders use the tool as such. Is the coder simply focused on maintaining and adhering to strict productivity levels or does the coder accept the encoder’s suggested codes because of a lack of knowledge in clinical medicine, official coding guidelines, policies, or Coding Clinic guidance?

I would hope that neither is the case and that coders are investing the time and effort to assign principal and secondary diagnoses that accurately reflect the patient’s clinical presentation, physician workup, and documentation in the ED record, history and physical, daily progress notes, and discharge summary, even when it means looking beyond the encoder’s suggestions.

Examples of an inaccurate code selection

Let’s look at an example of how encoders, when used without any further analysis on the part of a coder, can result in inaccurate code selection.

Charcot foot is a condition that weakens the bones in the foot and often occurs in people who have significant nerve damage (i.e., neuropathy). The bones are weakened enough to fracture, and with continued walking, the foot eventually changes shape.

As the disorder progresses, the joints collapse and the foot takes on an abnormal shape, such as a rocker-bottom appearance. People with neuropathy are at significant risk of developing Charcot’s foot mainly because the neuropathy decreases sensation and the ability to feel temperature, pain, or trauma. Due to worsening neuropathy, any pain associated with the injury goes unrecognized and the patient continues to walk, further contributing to perpetuation of the injury.

When a coder inputs the diagnosis of “Charcot deformity” or “Charcot Arthropathy” into the encoder, it might produce codes 094.0 (tabes dorsalis), for which the coder would report manifestation code 713.5 (Charcot’s join disease). How did it get those code options? I’m not sure, but certainly you would not want to report a syphilis (i.e., tabes dorsalis) diagnosis for this patient when your intention was to code Charcot foot/deformity.

Regardless of whether this is just a random occurrence or a shortcoming of one particular encoder, it still highlights the problems that could result from depending on encoders without applying any sort of analysis.

The diagnosis of Charcot foot always has an underlying cause such as diabetes or infection—but syphilis? How can an encoder be so misleading? Is it the lack of logic or the system’s inability to reason?

Note: Be sure to also review the record for any underlying relationship that the physician may have documented, such as diabetes, neuropathy, or infections. If the underlying cause is not documented, then generate a query.

Inputting “postobstructive pneumonia” also seems to produce an erroneous or misleading code. Postobstructive pneumonia is common with lung cancer, and results when a branch of the airway to a lung area is blocked off, leading to collapse of the lung behind it. This makes it a nadir for infection—like putting a wet sponge in a baggy and closing it off to air. This leads to pneumonia behind the obstructing tumor, hence the name postobstructive pneumonia.

Initial pathogens associated with postobstructive pneumonia commonly include Staph auerus, pseudomonas aeruginosa, some other gram negative bacilli, and upper respiratory anaerobes as well. Notice that these organisms are not the typical pathogens that commonly fall under those types of pneumonias categorized and classified under “simple” versus “complex” pneumonia under the MS-DRG system.

Physicians tend to document postobstructive pneumonia when clinically relevant, not recognizing that postobstructive pneumonia groups to a less severe pneumonia, similar to morbidity and mortality of “community-acquired” or viral pneumonia. In reality, patients with postobstructive pneumonia have a predilection to develop complications such as cavitations, empyemas, and resistance to antibiotics, leading to treatment failure.

Coding Clinic states that coders should report postobstructive pneumonia with code 486 (pneumonia, organism unspecified) when the physician doesn’t document the cause. If the physician identifies the causative organism of the pneumonia, then coders should use the more specific pneumonia code. Coders should report the postobstructive process (i.e., tumor, foreign body, etc.) when known. The circumstances of the admission determine the sequencing of the diagnoses. (See Coding Clinic, first quarter 1998, p. 8.)

But when a coder enters postobstructive pneumonia into the encoder, it produces ICD-9-CM code 486 (pneumonia, organism unspecified) even though the term postobstructive pneumonia actually represents a far different clinical finding worthy of a physician query. In the query, the coder would seek documentation truly reflective of patient acuity, severity of illness, intensity of service, risk of morbidity and mortality, and risk of readmission, especially as the latter is an area of focus as Medicare moves closer to its Hospital Readmission Reduction program in October.

The good practice approach

A National Government Services (NGS) article “National Government Services Mobile Review Team Reveals “Good Practice” recently caught my attention. In this article, the Medicare administrative contractor defined good practice as “exemplary documentation that clearly identifies the treatment rendered throughout the hospital stay, allowing for an accurate account of the patient health status.”

Coders must ensure the clinical accuracy and relevance of ICD-9 codes they assign prior to dropping the bill and proceeding to the next chart. Regardless of the source of assigned codes—encoder or book—they must take the time to ensure the diagnosis codes under final consideration are clinically valid and support the patient’s condition as documented in the record. To do otherwise is not doing justice to the profession of coding.

Editor’s note: Krauss is an independent revenue cycle consultant based out of Madison, WI. E-mail him at glennkrauss@earthlink.net.



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