Is Healthcare Data Different?
Sometimes it feels like everyone is whining that healthcare data is difficult to work with. Everyone except for engineer-trained computer scientists that say “data is data…“. These folks don’t think it is any more difficult to work with, they just say “data is data“. Which of course is true: if you look up ‘data’ in the dictionary twice, it is going to say the same thing both times. The mathletes out there even invented a rule about it called the transitive property : Let data = a, then a=a. Or something like that.
My point is, healthcare data is different because healthcare is different. More specifically, healthcare data reflects the differences found within the healthcare context. Some engineers remove the context from the data before solving problems, and context is everything with healthcare data. Look, if industry leaders HealthCatalyst complain that healthcare data is challenge, then I would just go with it.
[table id=2 /]When scanning over the table highlighting ‘healthcare data challenges’, one might marvel whether these challenges are unique or all that tough: “These challenges don’t look so bad..Every one of these challenges has already been solved somewhere, or at least it could be!” Our Engineer friends correctly concluded this before they even looked at the table.
If this is true, -and it might be, what is the deal with Health Data? Is it : 1) Healthcare has never attempted to fix these problems using solutions from other industries, or 2) Non-healthcare solutions applied to healthcare don’t work right or catch on. What do you think?
Data quality is very simply defined as a measure of whether data “is fit for its intended purpose“. Easy, right? The key challenge to assessing quality is two-fold: 1) You must know the purpose, and 2) You must understand the specific characteristics of the data that meet (or don’t meet) your needs.
If you depend on data to make good decisions, you should know how to describe the data and articulate the strengths and limitations. AHIMA’s Data Quality Management (DQM) Model is a good place to start. The DQM is a blueprint for institutional data governance that is updated every few years. As such it contains characteristics and goals of a enterprise data model, including one of the better models for describing healthcare data quality.
Data Quality Characteristics (from DQM) [mfn] Davoudi, Sion & Dooling, Julie & Glondys, Barb & Jones, Theresa & Kadlec, Lesley & Overgaard, Shauna & Ruben, Kerry & Wendicke, Annemarie. (2015). Data Quality Management Model (Updated). Journal of AHIMA. 86. 62-65.[/mfn]
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