THCB

Would You Take a Bullet For Your Clinical Data?

flying cadeuciiMillions of important pieces of health information are entered into systems of record daily. Without an information governance play book, we are asking our patients to take a trust fall with their health. How confident are you that this is the single source of truth and care is being accurately reflected?

Data has become the vital component against which all things are measured— from determining short-term efficacy to developing long-range strategies. As a result, a new role is emerging in many industries, the Data Quality Officer (DQO), who is entrusted with ensuring data health, analyzing trends, and deriving actionable insights from the information. While this role may be new to Fortune 500 companies, its core competencies have existed in healthcare for years, championed by health information management (HIM) professionals.

In healthcare, data has always been the lifeblood of better patient care — and accurate documentation is an essential first step to ensuring integrity. Data integrity not only helps improve patient care, it has downstream effects on regulatory compliance, case mix index (CMI), quality reports and your organization’s bottom line, as well.  But it won’t stand up today’s pressures and levels of scrutiny unless it all starts with an information governance strategy.

Create a playbook

A lot has been written about health IT and the vast amounts of patient data that is being entered into systems every day. How do we organize it, track it, analyze it, and leverage it to improve patient outcomes? Before we can execute against any of these initiatives, we first have to know that the information is accurate and uniform. Creating a playbook that includes protocols and processes, such as, who is allowed to enter clinical information into a record, what information is included and how it is presented, and a process for amending possible discrepancies is vital. Outlining these procedures and policies will help maintain dataintegrity.

Example:  Who is entering patient problem lists (a core for Meaningful Use)? You may believe these are being documented solely by physicians and, if so, you might be very surprised to find out there is a variance in who is entering this information.  If you don’t have a playbook, you will continue to have multiple sources of input.

Socialize it with stakeholders

After creating a playbook, it is imperative that these policies are socialized with all relevant stakeholders, from clinical to administrative, throughout your organization. The complex nature of the healthcare industry makes it easy for silos to form, especially when it comes to HIM, but as more data is entered into systems of record every day, and with the ICD-10 transition just around the corner, accurate and consistent information is key to ensuring the best clinical outcomes for patients, even post-discharge.

Look at the big picture

When you look at your entire documentation value chain, which consists of physician documentation, your clinical documentation improvement (CDI) program, and coding and compliance processes, the input should match the output. If you have different people from all different parts of your healthcare organization using different data sets for reporting externally, what picture does that paint to the community?  Conducting an internal audit will help you identify discrepancies and highlight what links in the chain need to be strengthened or re-forged. Keep in mind that regulatory bodies have different focuses when they evaluate your records, but the goal is to present your organization as positively and consistently regardless of whether it is to CMS, the Joint Commission, Leapfrog, etc.  Internal auditing will help ensure that the right information is accurately documented and coded up front so it can support accurate reporting and scorecards, while protecting your organization from penalties, denied claims and costly rework.

Properly implemented technology plays an important role in dataintegrity and can provide a system of checks to ensure accurate and detailed information is consistently entered. However, true success is contingent upon the commitment from all stakeholders across the care continuum to adhere to the processes and standards set forth by your information governance policies.

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@BobbyGvegas
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“Data has [sic] become the vital component against which all things are measured— from determining short-term efficacy to developing long-range strategies.” __ With too often scant attention to either data quality of clinical applicability. ‘Data Quality Officer (DQO)” In the field wherein I began my IT career in the 80’s in Oak Ridge (forensic environmental radioanalytics), “DQO” meant “Data Quality Objectives” (a risk-tiered compliance phrase coined by the EPA). Data computed for gross preliminary screening assessments were subjected to less rigor than those used as evidence in dose/exposure litigation or enforcement actions. “Properly implemented technology plays an important role in… Read more »

@BobbyGvegas
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e.g., “Consider that no clinical datum has any actionable patient or provider value in isolation. For one thing, as a patient, you get a abnormally high lab analyte result back, and you’ll be anxiously demanding a re-do promptly. Moreover, the most fundamental measures of, say, BP, pulse, temp, weight, blood or UA parameters, etc derive their dx significance from their mutual context (often in terms of the one-to-many flowsheet trending variety). For that context (and its diagnostic utility) to be precise over time, you benefit from metadata standardization. Now, within the “walls” of a single EHR, this is not an… Read more »