Making the Data Work for You: How to Turn Medical Coding Audits into Actionable Insights

Making the Data Work for You: How to Turn Medical Coding Audits into Actionable Insights

 

We asked JJ Crumbley, Director, Project Management & Operations, to author this article and share his expertise on how healthcare organizations can get the most insights from medical coding audits. Crumbley is a certified Project Management Professional (PMP) who has 11 years of experience integrating project management and client-centered consulting skills to deliver comprehensive solutions specific to our healthcare industry’s needs and challenges.

Coding audit data can be extremely beneficial to the success of a healthcare organization – however, oftentimes, the vast amounts of data being collected can suffocate the organization, especially those that don’t know how to cultivate value and act on the insights received from the audit process. Most medical coding compliance audit programs will objectively evaluate multiple data sets and generate reports on the findings, but, the data is not being used to its fullest potential if the reports are not properly cleaned, analyzed, and examined to develop strategic next steps toward the company’s quality improvement. “Data and quality improvement go hand-in-hand”, says Crumbley.

So, how do organizations take these vast amounts of data and turn them into strategies?

The answer lies within this article, which will walk readers through the entire process of how to reap the most reward from medical coding audit data. The process, outlined below, begins with identifying the key performance indicators (KPIs) organizations should set in their coding audits, then moves to translating that data into understandable information for the company’s decision-makers.

medical coding audits

Properly Identify & Develop Key Performance Indicators for Medical Billing Audits

1. Identify the organization’s/department’s goals. The first step in the process is to identify the organization’s core values and the objectives for each HIM department regarding coding audits and its data application. These values and objectives need to be clear, realistic goals for the company that will serve as benchmarks throughout the entire process. A great example goal for the HIM department could be maintaining the industry-standard MS-DRG accuracy rate of 95%. The HIM department could also strive to reach a financial breakdown of overcoded cases vs. undercoded cases that is close to 50/50.

2. Select the KPIs for the coding audits. Next, pinpoint the KPIs that will drive the organization toward achieving the desired goal or objective (see examples below). The Quality KPI Decision Matrix* that YES developed, displayed below, provides some characteristics organizations should use to identify the KPIs to use in medical coding compliance audits.

key performance indicators for medical billing

These characteristics include:

  • It is available and measurable.
  • It aligns with a strategic company goal.
  • It drives clear actionable next steps.
  • It is generated in an allotted time frame.

In addition, each KPI that is chosen should include the following details, compiled by Unanet (2019):

  • Concrete, specific details about the company’s goals; including, the success criteria that clearly indicates what needs to occur in order for the stakeholders to consider the KPI has been met.
  • Realistic goals for the organization.
  • A way to measure the audit progress.
  • A realistic deadline of completion.

The table below provides an example of the KPIs that YES measures in our client coding audits. Notice that the objectives and success criteria for each KPI are also clearly identified.

audit data analytics

During this KPI selection process, it is important for healthcare organizations to understand the difference between metrics and KPIs. As noted by the founder and managing principal of Catalyst Strategic Marketing, Richard Hatheway, “The easiest way to understand the difference between metrics and KPIs is to first define them both as a quantifiable measurement of a strategic or tactical activity” (LinkedIn, 2016).

A KPI is a quantifiable or measurable value that reflects an overall business goal or objective (strategic). A metric is also a quantifiable or measurable value, but it reflects how successful the activities are (tactical) in support of achieving the KPI. In other words, metrics support the KPIs.

Translate the Audit Findings Into Information to Fuel Strategic Planning

3. Clean and organize the coding audit data. Going beyond simply generating the audit data reports, the organization needs to examine the data for insights and take action. But, first, the statistical findings need to be “cleaned” and organized so it is easily readable for analysis. Cleaning or “scrubbing” the data will directly affect the organization’s ability to analyze and provide recommendations based off the most relevant information.

Data cleansing is the process by “which you go through all of the data within a database and either remove or update information that is incomplete, incorrect, improperly formatted, duplicated, or irrelevant” (Blue-Pencil Information Security, 2018).

In the coding audits conducted by YES, the data is cleansed by plugging it into a database with several automated SQL queries, which will identify the data points that have been defined by the auditor and separate them from hundreds or even hundreds of thousands of rows of raw data. The auditor identifies which data points are relevant by determining those that directly support or link to a KPI.

For instance, if one of the KPIs is the MS-DRG coder accuracy rate, two relevant data points to pull would be the number of cases coded and the number of coding errors. Additional data, such as patient demographics, may also be deemed relevant – it is up to the organization.

4. Perform statistical analysis. After the statistical findings are cleaned and organized, a story begins to take shape from the final reports, and the information can be analyzed. The auditor can review the relevant data points and determine if the KPIs and overall objectives were met.

In this stage, the auditor should review the audit data analytics and identify outliers that do not meet the KPIs, such as a low coding accuracy rate, undercoded cases, and overcoded cases. These outliers will serve as the basis for the recommendations that will drive the organization toward achieving the KPIs.

5. Generate recommendations based off of analysis, and tailor decisions from recommendations. Based on the examples above after reviewing the audit data analytics, a recommendation to remedy a low accuracy rate may include more education and coder mentoring (if it is a single coder issue), or a policy/documentation update from the company (if it is a multi-coder issue). If there are undercoded cases, the recommendation would be to issue a rebill, and, if there are overcoded cases, a bill correction and refund would be recommended.

Our previous article, “Coding Compliance Audit Statistics: What to Do With Them?” provides more examples of how to generate recommendations for improvement from coding audit KPIs.

Stay tuned for the article on the next important step in leveraging coding audit data analytics, which is using the data to drive sustainable, continuous quality improvement.

Guiding healthcare organizations in understanding and acting on coding audit data is one of YES HIM Consulting’s specialties. Our coding compliance audits provide insights on outliers that affect coding quality, accuracy, revenue, ad more. Contact our team of qualified coding and auditing experts today to receive personalized recommendations that are aimed at the organization’s quality improvement.

JJ Crumbley

JJ Crumbley, MBA, PMP – Director Project Management & Operations
medical coding audits

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