Leading the way to data quality

Karen Snyder

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This year’s Healthcare Information and Management Systems Society (HIMSS) Annual Conference had another record-setting year for attendance, with over 40,000 attendees present in Orlando, FL. Since it’s Health Information Professionals (HIP) Week, let me put it in terms that Coders might appreciate. With so many people in attendance, it felt like the only folks absent from the conference were individuals diagnosed with:

  • Agoraphobia – those with a fear of being in crowed, public places (Diagnosis Code F40.00), or
  • Astraphobia – those with a fear of thunderstorms (Diagnosis Code F40.220). Unfortunately, Mother Nature wasn’t very cooperative.

The top themes at this year’s conference, as reported by Becker’s Hospital Review, included:

    1. Big Data & Analytics – extracting data and then using the “Ginsu Knife of Big Data” to chop, slice, and dice it to drive actionable insights
    2. Artificial Intelligence (AI) & Cognitive – revolutionizing healthcare by marrying unstructured data and natural language processing to deliver personalized treatment recommendations (a good example is IBM’s Watson
    3. Value-Based Care – shifting the care delivery model from fee for service to pay for performance models
    4. Interoperabilityleveraging innovative ways to share and exchange patient data
    5. Telehealth – using telecommunication technology to treat patients and provide health education remotely

This year, I had the unique opportunity of facilitating a YourTurn@HIMSS session with 90 conference attendees.  The topics for these participant-driven, discussion-based sessions were submitted to HIMSS well before the conference, with the top 10 selected through an online voting process.

My session focused on Data Quality and Integrity, and covered a number of timely topics. Using polling questions, here’s what we learned:

  • 60% of the respondents have some quality controls or a systematic data quality management program in place
  • However, less than a ¼ of the respondents have a best practice duplicate rate (of 2% or less) in their EHR
  • Over 40% of the respondents have enterprise-wide or facility-level EHR data quality policies, and finally
  • Almost a third of respondents (28%) believe that a National Patient Identifier would facilitate information sharing.

As a small token of gratitude for sharing their thoughts and experiences, each participant at my session received an infographic that I created which highlights 10 Best Practices for Data Quality & Integrity.  And, because it’s HIP Week, I’d like to share these best practice tips as a gift for you as well.

Data Quality and Integrity Best Practices Infographic Blue_Snyder

 

As a Health Information Management professional, it’s your responsibility to manage the quality and integrity of data as a continual process, not just a one-and-done project, and I’d encourage you to share these tips with others in your department and broader organization. Poor data quality due to the lack of systematic data quality management can have broad organizational impacts, with consequences ranging from disruptive or even dangerous breaks in the care process.  Armed with these easy-to-digest best practices, you can be both an advocate and role model when it comes to data quality and integrity within your organization.

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