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81%u00a0of individuals went to a healthcare provider at least once in the last year. While that is not surprising, pairing it with another stat tells a very different story.<br><br>If you are looking for Healthcare Data. Visit Us:- https://www.ezdi.com/<br>
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81% of individuals went to a healthcare provider at least once in the last year. While that is not surprising, pairing it with another stat tells a very different story. 80% of healthcare data is unstructured today. Unstructured data serves a critical purpose, but it cannot be pigeonholed. And when billions of patients are concerned, the very nature of unstructured data gives way to inefficient care on a grand scale.
According to a survey by HIMSS Media, 56% of healthcare professionals cited unstructured data as a key barrier to optimizing clinical workflows. Structured data in spreadsheets and relational databases are presented in a way that facilitates easier search and analysis. It is functional. But unstructured data in handwritten prescriptions and pathology reports defy rigid rules and systems to convey a deeper awareness of a patient’s condition. It can be insightful.
The Dichotomy of Structured and Unstructured Data The importance of both kinds of data depends on how they are managed. Structured data lends itself to the organization and mechanical analysis, a task befitting most current systems. Imagine a spreadsheet sprawling with names, dates, heights, weights, currencies, blood types, diagnostic codes, and many more values. Such data is mandatory for insurance companies in the event of reimbursement claims. Its management is more straightforward and requires little human intervention.
However, structured data has clinical value as it is backed by unstructured data. The problem lies in the inability of typical analytic solutions to analyze this data since it exists in the form of free text and narrative. Here’s a hypothetical situation at a clinic: “Hello, doc, I’m here for my monthly checkup.” “Yes, of course, please have a seat. Let’s take a look at your vitals. Your blood pressure is 130/80, a little on the higher side.”
“Is that manageable, doc?” “Of course! But you shouldn’t take too much stress. How does your schedule look like this week?” “I’ll be at work for most days of the week. I was planning to take a leave on Thursday, it’s my daughter’s birthday. But there’s some urgent business at work so I wasn’t sure about taking it.”
“I would urge you to take that leave. With your busy schedule, you could do 10 to 15 minutes of meditation every day. Perhaps this stress at work is making you spend less time with your family. Get out of the office early whenever possible. I’m prescribing a diuretic for you as well as a chest X-ray. Take the medicine for a week and pay me a visit once you get the report.” “Thanks, doc. I’ll try to follow what you said.” “Please do. Take care.”
A 130/80 level of blood pressure and the prescribed diuretic can fit neatly in a spreadsheet. But the recommendations of meditation and spending more time at home cannot. The forthcoming X-ray report won’t find a place either. Yet it is those bits of information that reveal a lot more about the patient’s current and future state of health than a single blood pressure level or a medication. Both these facts might be specific to the patient but are also generic in the information they convey. A study in the Journal of the American Medical Informatics Association (JAMIA) states that real-world data in electronic health records (EHRs) provide more accuracy, but only when it is mined by trained algorithms. The study found that with structured EHR data, the average precision and recall were 98.3% and 51.7% respectively. With unstructured data, the corresponding rates were 95.3% and 95.5%.
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