Kenji Asakura
Erik Ordal

Hospital finance executives, take note: Your organization’s clinical documentation improvement program may soon be under a microscope.


At a Glance

Hospitals and health systems should consider four strategies for improving documentation:

  • Develop a short list of the most commonly underdocumented or incorrectly documented clinical conditions at the facility.
  • Develop definitions for each of the conditions on this list.
  • Ask the medical director of each specialty area to educate the clinicians in their group on these definitions.
  • Measure and manage documentation performance.

Running a compliant clinical documentation improvement program requires dealing with an array of common, potentially noncompliant practices that can easily undermine the program’s integrity. Foremost of these practices is the often-cited “leading query,” in which documentation improvement specialists appear to lead clinicians to document a particular condition, which can result in overpayments and charges of fraud. Beyond this concern, many other, less prominently discussed issues also exist that are potentially just as problematic for hospitals.

Consider, for example, the findings of a 2010 survey by the Association for Clinical Documentation Improvement Specialists in which only 54 percent of the clinical documentation specialists surveyed stated that their hospitals’ query forms fully followed guidance from the American Health Information Management Association (AHIMA). Failure to follow AHIMA’s query and documentation guidance could result in legal headaches for hospitals—and thousands or even millions of dollars in fines. In 2009, the U.S. Department of Justice investigated one prominent hospital for False Claims Act violations after the hospital tried to claim such secondary diagnoses as malnutrition and respiratory failure. Although the hospital denied the allegations, it settled the case for $2.75 million.

AHIMA and other organizations have provided hospitals and health systems with guidelines for clinical documentation improvement programs to establish the ground rules for clinical documentation. However, as noted previously, there is evidence that the level of adoption of these guidelines varies among hospitals. Meanwhile, Medicare recovery audit contractors (RACs) appear to have stepped up their investigation of clinical documentation improvement programs.

There are reports that some RACs are requesting query forms as part of their audits, presumably to look for leading queries. RACs also appear to be turning to analytical approaches to uncover patterns of abuse in clinical documentation. Using such analyses, RACs could easily identify hospitals with the largest increase in case mix index (CMI). (See the exhibit below.) Although the average hospital has increased its CMI by 0.08 since 2006, 175 hospitals increased CMI by 0.30 or more—a nearly fourfold difference. By reviewing query forms of these top-performing hospitals, RACs could easily uncover those using questionable practices.

Exhibit 1

f_asakura_exh1

How can healthcare finance professionals help to ensure that their organizations’ clinical documentation improvement programs are compliant? Finance professionals should encourage their organizations to avoid four practices related to queries and documentation that can inadvertently promote noncompliance.

Ensuring Compliance: What to Consider

By now, most hospital finance executives are aware of AHIMA’s guidance around leading queries. Clinicians should never be led to document a particular condition. However, there are gray areas regarding what constitutes a leading query, as well as questions surrounding practices that give clinical documentation specialists performance-based incentives.

Multiple-choice queries. This type of query provides clinicians with a list of conditions from which to choose. The query is deemed to comply with AHIMA guidelines as long as the list is not biased toward conditions that have a more favorable impact on payment. However, hospitals typically use standard query forms, so over time, if clinicians are provided with a list of conditions to choose from, they will learn to select the desired response. This tendency of physicians has led some to openly question how a multiple-choice query differs from a leading query.

Verbal queries. A simple one-on-one interaction between the clinical documentation specialist and the clinician could influence a clinician’s choice. Verbal queries are most effective when clinical documentation specialists develop good working relationships with clinicians. For example, when physician advisers are involved, they rely on their ability to influence their peers.

Verbal queries are problematic for hospitals because they are difficult to police. With some RACs now requesting query records, the absence of such records could alert RACs to the use of verbal queries by the hospital or health system. Hospitals should protect themselves by establishing clear policies against verbal queries. The survey by the Association for Clinical Documen- tation Improvement Specialists found that many hospitals have policies in place regarding written queries, but fewer have policies for verbal queries.

Selective queries. Recent settlements by hospitals with the U.S. Department of Justice over alleged violations of the False Claims Act have highlighted the risk hospitals face from leading queries, but there are many other potential risk areas related to documentation. One questionable practice is what we call the “selective query.” Such queries can take many forms; following are three examples.

One practice involves focusing query efforts on a single diagnosis—for example, by systematically searching for a particular condition (e.g., malnutrition) among all patients.

Another involves cessation of query efforts after identifying a single comorbid condition or major complication or comorbidity. This practice is especially problematic in critically ill patients, who tend to have numerous complications and comorbidities and so would be expected to generate several queries.

A third is selectively querying Medicare patients. This practice leaves documentation deficiencies in the charts of all non-Medicare patients, who account for approximately 60 percent of all inpatients nationally. Selective queries differ from leading queries in that the query itself may be compliantly written, but it nevertheless results in an incomplete and unbalanced medical record. If the goal of clinical documentation improvement is to ensure complete documentation, selective queries cause such programs to miss the mark.

Use of metrics and incentives for clinical documentation improvement specialists. Another questionable practice is the use of metrics and incentives that encourage financially motivated queries or clinician agreement with queries. Clinical documentation specialists are often measured on the volume as well as the monetary value of the queries they submit. When incentives are used, this is a powerful motivator for these specialists to focus on queries with the potential to have the highest impact on payment.

Many clinical documentation improvement programs track and report back to clinicians their query agreement rate. This practice encourages clinicians to go along with queries whether or not they agree with them. In the case of a leading query, most clinicians are unfamiliar with AHIMA guidelines, so there is no reason for them to disagree with the query. It seems only a matter of time before clinicians become aware of AHIMA guidelines and begin to question such practices.

Steps Toward Improving Documentation

What hospitals and health systems require is an approach to clinical documentation that is consistent with the goals of clinical documentation improvement: to achieve an accurate and complete medical record. A hallmark of an effective clinical documentation improvement program is that it avoids the noncompliant practices so prevalent in many existing programs. Before describing the steps required to create such a program, it is important to first define what is meant by “accurate” documentation.

The proof of documentation accuracy can be seen when you put the same patient in front of a group of clinicians and get exactly the same documentation. Documentation is a subjective exercise. A clinician documents a patient’s condition if he or she believes it exists in the patient. This determination is based on past experience or what the clinician learned in medical school, which often differs from clinician to clinician.

What if clinicians were provided with a definition for each condition? Having this information would prompt them to document a certain condition only when patients met the specific criteria for that condition. When reviewing the same data, each clinician, regardless of his or her background or training, would document the same conditions. For example, if 10 percent of all patients admitted to the hospital met a preapproved definition for acute renal failure, all of these patients should have this condition documented in their charts.

Definitions are a key requirement for accurate documentation. They also provide hospital finance executives with a way to assess clinician documentation objectively and use the findings to drive improvements in documentation performance.

That said, building a compliant clinical documentation improvement program that ensures the accuracy of documentation requires four steps.

Develop a short list of the most commonly underdocumented or incorrectly documented clinical conditions at the facility. Each condition on this list should be targeted for improvement, beginning with the most common condition. This list need comprise no more than 75 conditions. When broken out by specialty group, the list can be even shorter.

One might argue that this approach misses the majority of the more than 14,000 ICD-9 diagnoses. The reality is, however, that most organizations encounter only a small number of diagnoses often enough to make them rational targets for improvement. For example, a typical 300-bed hospital with 12,000 patient discharges per year will see only 6 percent of all conditions classified by ICD-9 codes in a typical month. Moreover, physicians will have already documented most conditions, so the trick is to identify those that the physicians have missed or incorrectly documented.

It is important to note that the short list of conditions will be different for every facility, as no two physician groups document conditions in exactly the same way. Building this list can be labor-intensive, involving chart review, but a hospital that has data-analytic capabilities can identify these conditions relatively quickly and efficiently.

Once the short list of commonly under- or incorrectly documented conditions is available, the organization should focus initially on just three to five conditions per specialty to ensure rapid clinician adoption. After clinicians have mastered the first set of conditions—a process that normally takes three to six months—the organization can return to the list and tackle the next group of conditions.

Develop definitions for each condition on the list. This process should be led by the hospital medical director or another physician leader. Some conditions will already have a widely accepted definition (e.g., decubitus ulcers). Others, such as acute renal failure, have no standard definition, so the organization will need to choose one. Clinician adoption will be more rapid if definitions are developed based on consensus among physician leaders. The organization might also consider having the medical executive committee approve the definitions, thereby creating a hospitalwide standard.

Enlist the help of the medical director of each specialty area to educate the clinicians on these definitions. The medical directors usually can quickly complete these discussions with their groups (often in no more than 15 minutes), as the clinicians already will be familiar with the clinical definitions. It is important to anticipate resistance from certain clinicians and involve them early in the process to avoid any barriers to progress.

Measure and manage documentation performance. This step can be accomplished by periodically reviewing each clinician’s documentation and verifying that the documentation meets hospital-approved definitions. The percentage of correctly documented charts is called the documentation accuracy rate. Unlike the query agreement rate, the documentation accuracy rate promotes the type of behavioral change that absolutely conforms with the goals of clinical documentation improvement.

Exhibit 2

f_asakura_exh2

The medical directors should be asked to measure documentation accuracy rate for each physician in their specialty areas and report back on the clinician’s performance at least quarterly. Although this process may seem labor-intensive, it is considerably less taxing than the common practice of having clinical documentation specialists review large numbers of charts daily. This approach to performance management also promotes rapid adoption, with the possibility of achieving a greater than 90 percent documentation accuracy rate in less than three months.

The implications of this approach for the organization’s clinical documentation program will be dramatic. Physicians will document conditions accurately the first time, without the need to go back and modify their documentation. The process is Lean because it eliminates rework. Clinical documentation specialists will no longer have to query physicians and clinicians; instead, they will be able to focus on educating clinicians on preapproved definitions. Conditions will be documented for all patients, not just for select patients. Clinicians will continue to document even after achieving the highest-severity DRG. Metrics will be properly aligned as clinicians are measured on their documentation accuracy rather than their compliance with queries. Clinical documentation specialists will be measured on the quality of their education. Finally, the organization will no longer have to police clinical documentation specialists out of fear that they will ignore AHIMA guidelines and put the hospital or health system at risk.

Final Thoughts

Healthcare finance executives face an ever- challenging payment environment. Clinical documentation improvement is an effective but challenging method for improving revenue. Choosing not to participate in clinical documentation improvement is no longer an option: Low-performing hospitals will be disproportionately affected as higher-performing hospitals drive even greater adjustments by the Centers for Medicare & Medicaid Services. The challenge for healthcare executives is to design clinical documentation programs that promote both accuracy of documentation and compliance.


Kenji Asakura, MD, is cofounder, ClinIntell, Inc., Seattle; a physician at Swedish Medical Center, Seattle; and a member of HFMA’s Washington-Alaska Chapter (kenji@clinintell.com).

Erik Ordal is cofounder, ClinIntell, Inc., Seattle, and a member of HFMA’s Washington-Alaska Chapter (erik@clinintell.com).

Publication Date: Monday, October 01, 2012

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