Without a doubt, data is the lifeblood of any business or industry. It isn’t simply a matter of knowing what orders to fill, how much something costs or keeping client information safe but also learning from that data, implementing insights gleaned from that data and becoming a better business. Within the realm of healthcare, the data is also vitally important but it also is much more difficult to manage due to its diversity. Managing different types of healthcare data may be at the pinnacle of what a database or data warehouse can handle well.
At the crux of the issue are the complexity and the amount of data that a business has to deal with. In most businesses, even one as vast as Amazon.com, there are few rules that change, such as, the product is in, the product is listed, the purchaser pays, payment verified, and the product is shipped. The products will vary over time, and the shipping costs may change depending upon certain criteria, but the rules are easy to set up when programming the database where all the information is stored. This isn’t the case with healthcare because the rules are always changing depending upon mandates from the government, establishment of goals within the organization or better definition of care and services.
Most businesses deal with easy to enter and verify boxes where customers enter letters, numbers and possibly a few special characters. Add in checkboxes, maybe adjustable bars and all the information is easy to quantify, file and analyze. This isn’t always the case with healthcare data: admissions information is pretty typical with a person’s name, address, insurance details, and any prior health issues check marked. From there, things become more complex because the documentation that is added to a person’s digital healthcare record can include things like:
- Imaging, such as x-rays, MRI or CAT scans
- Hand-written notes that are scanned in
- Voice memos specific to the patient
- Lab results
- Prescriptions with directions
One thing to understand when working with stored data is that it isn’t like a filing cabinet where you can simply put in or pull out a file, and if you feeling like changing that files location, it doesn’t take a committee or IT, specialist, to make that happen. This is not the case with software and data management; some of the guidelines in how data is treated must be known beforehand so that the information is treated is a specified way. The technicalities are not easy to explain, and even harder to grasp, but it could be compared to constructing a new building, wherein defined information must be known upfronts, such as size, scope, and materials. Different materials, which could be compared to different department necessities, must be ordered up and handled separately, and many other nuances that you can only begin to imagine.
Managing different types of healthcare data isn’t all about storage and being able to reference that data later, but to learn from the data, find where waste is happening, create necessary reports, schedule necessary personnel, help patients with real-time data, and so much more. The data doesn’t just sit in a folder to collect dust, but truly is the lifeblood of what is going on inside the organization. If you don’t know what is happening below the surface, it can all be crumbling beneath your feet and you may not even know it. Data must work for you, revealing patterns, problems, and even solutions, but it can’t just be collected and do nothing from there. The problem occurs when the data being processed isn’t as straightforward as name, address, and gender; imaging scans and other types of data aren’t as easy to compare, to quantitate and to extract analytical information from.
Having software that is specifically dedicated to and manages the distinct variances that come along with healthcare data, and the high demands that are placed on that information are necessary, especially as government mandates change, technology is improved, and goals are adjusted within an organization. Managing the different types of data is essential throughout the business of healthcare, whether it is the professional or the patient. Though it isn’t as simple as many other industries that rely upon analytics to run their company, the benefits are far-reaching and helping to improve the care provided and the efficacy in which it is done.
How to Measure Healthcare Data Quality
Monitoring the costs and efficacy of healthcare requires the ability to carefully analyze all of the related information. Unfortunately, it is much harder to do this analysis in the healthcare industry than it is in industries like manufacturing. That’s because the recording of healthcare data is mostly unstandardized. Even where standards exist, they are unique to certain aspects of the process and hard to transfer to other parts. This makes it hard to figure out how to measure healthcare data quality, let alone actually use that data.
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