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Why Healthcare Data Can be Difficult to Manage

This post was last Updated on June 3, 2023 by Himanshu Tyagi to reflect the accuracy and up-to-date information on the page.

Healthcare has always been a forefront concern in civilization. The mysteries of the body and how to attend to its healing have mystified and inspired some of the most significant discoveries and advancements in science throughout the millennia.

Still, our global economy’s (relatively) recent shift into the technological age has meant implementing new practices. Not least of which is the adoption of hybridized technologies utilizing computers.

With computers becoming mainstream and, at the rate our technologies are evolving ever more rapidly, business and medical practitioners have had to try to keep up and anticipate introducing new methods.

For the many variables in these complex systems, maintained by both human and artificial intelligence aids, one of the most consistent struggles in the healthcare industry today is the proper management of personalized medical data.

This article seeks to offer an introductory view into some of the many challenges that arise in the task of medical data management.

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What is Healthcare Data Anyway?

why healthcare data can be difficult to manage

Before understanding why healthcare data can be challenging to manage, we need to understand what that information is and contains.

Healthcare data encompass large swaths of information but can be broken down into parts for greater clarification or distribution.

Healthcare data is any general and specific information associated with individuals’ or communities’ physical, emotional, and mental medical history.

As it relates to an individual, this information can include statistics like diagnosis, medical history, family disease history, and personal insurance information.

Cumulatively, this data can encompass entire populations’ socio-economic situations, such as efficacies of treatments or pharmaceuticals, flu-shot uses for common colds on a state-by-state basis, and, as we are all familiar with, infection rates for worldwide pandemics.

Whatever can be known about an individual or populace interacting with medical histories may be included in the broad definition of “medical data.”

In that respect, the gathering of that information is a monumental task in itself. Still, managing and protecting that data are the backbones of the global economy’s healthcare systems. The following are examples of why healthcare data can be challenging to manage.

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Paper or Code?

One of the most evident challenges today in medical data management is analog (paper and pen) or digital entries.

Most of us can remember walking into the doctor’s office and being greeted by a (hopefully) smiling receptionist who then handed you a clipboard and a stack of paperwork to fill out — for each new office and every new doctor.

After doing so, those office workers must file all that paperwork in folders, usually marked with color-coded tabs. Why does this sound familiar?

Likely it’s because at some point in your lifetime, as you were leaving or entering a doctor’s office, you passed by a wall of manila folders containing medical data, bringing us to data’s first dilemma: the need for physical and digital paperwork.

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There are reasons for the need for both, some of which we will go into later, but the most obvious might be that nurses and doctors require something to keep notes and observations with. Nurses are making their rounds charting; doctors are passing illegible notes, dosages, measurements, etc.

In the last three years, I have only seen a doctor or nurse type any of my information directly into a computer during a checkup. (Budgets might have something to do with not equipping every nurse with an iPad… yet.)

Regardless, we don’t think the directive to arrive twenty minutes early to an appointment to fill out more paperwork will go away soon.

So until then, medical offices must balance digital and analog information management.

The input and translation of that analog information into a digital format take more than just time, it takes precision, skill, and carefully crafted computer systems to file and store all that information for quick recall and sharing.

This brings us to our next point…

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Storage: Where Are We Going to Put All This Data?

As a child, when leaving a doctor’s office with a sticker from the toy chest and, if it was a reputable establishment office, a lollipop! — we have to admit. Some of us wondered what they did with that wall of manilla folders.

As we got older, we noticed that some filing systems seemed to be half falling out of the shelving.

Thankfully, computers had already been invented, and the balance between digital and analog information started, but that doesn’t mean digital information isn’t taking up space.

As the over-abundance of digital information continues to grow in every form online, the need to detail presumably even the most insignificant bit of our medical histories — like that scratched knee in 3rd grade — takes up space.

All joking aside, data storage is and will be an ongoing issue. The costs alone of constructing and managing data centers are staggering, but there is more to consider.

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Where many offices tend to store their data in-house for reasons like accessibility and security, the option of off-site and cloud-based storage servers has become available.

This hybrid approach brings the time-consuming task of ensuring that multiple, separate systems are even correctly communicating. Managing such a task daily and effectively in one office is one thing. It’s entirely another when a whole hospital is given that responsibility.

To make matters even more complex, medical offices — which tend to need to transfer data more often than most industries — have to share all that data.

It’s comforting to know that at least two things most of us learned from kindergarten stuck: patience and sharing.

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Our world has long been considered a global economy, but the medical profession has an odd tendency to require people to get care in far more separate offices than necessary.

Many of us have been there: First, you must go to your general practitioner, who then offers a diagnosis. Next, you’re given a “reference” to see another doctor, commonly across town, who then orders multiple tests, each in its own office or part of the hospital, before you even figure out what’s going on with your body.

Now let’s stop for a moment and consider how many offices need access to your medical history. What may be overkill in other industries is a clunky unavoidable necessity in healthcare. As such, data interoperability will always be a concern, even with the invention of new systems and strategies.

Developing cooperative digital infrastructures to manage and share this information efficiently will be a never-ending chore, as will be the challenge of protecting that data. This brings us to perhaps the most concerning aspect of data management: Security.

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While we may be more familiar with stories like grandma being conned into donating your birthday money to a fake non-profit organization, data breaches at massive levels have been occurring with alarming frequency across many different industries.

The medical community is not immune to this. Thankfully, many people have been at work for decades trying to keep, and keep protected, some of your most private information.

Data security is, and will be, the top priority for healthcare organizations. Responses at corporate and governmental levels have sought to standardize those procedures. Regulation and compliance are one side of the task.

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Each medical company is subject to HIPAA standards and regulations, which state that each practice needs to consider technical, physical, and administrative safeguards to ensure that sensitive data is being exposed.

Things like firewalls, multi-factor authentications, and encryption are now commonplace practices, but more often, the forgetful nature of humans tends to make a mess of things.

Entire elaborate systems can be intruded upon simply because a staff member uses the same password often at work. Clumsiness and forgetfulness are forgivable, but insufficient data cleanliness is hard to ignore.

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Clean Data

Various disorders can plague your data: duplicate files, improperly formatted files, incomplete sets, or even misspellings. Put, dirty data is any information that is inaccurate because of corruption or missing information.

It happens every day: An email account is overfilled, an address is spelled wrong, a birthdate is off by a decade, all of these are simple and coming but sometimes troublesome mistakes. They can also be very costly.

Estimates demonstrated that dirty data cost the US economy nearly 3 trillion dollars a year in 2016, according to IBM. Considering all the time it takes to fix little things, it makes sense, but how does one clean information inside a computer?

Computer systems do some of it, but the rest needs to be done by humans, hand, and keyboard. No, rubber gloves are not required in this department, just astoundingly patient data analysts with an uncommonly high tolerance for detail — or that unlucky new intern who can’t turn down a task.

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“Who’s in Charge here?”: The Need for Analysts in Data Management

While data management may not be witnessed on the public side of the medical field, it would be hard to imagine any hospital or medical office running smoothly without the insight and actions of the men and women tasked with managing any of the responsibilities above. There are a variety of base disciplines within the data management role.

Data integration concerns collecting information from separate sources used for analytical and operational use. Data governance oversees the policies and procedures laid out by governmental and corporate entities to ensure that the data being used, collected, and stored maintains consistency operationally and according to legal requirements.

The actual management of quality maintains the goal of checking and fixing inconsistencies (previously mentioned as cleaning), and master data management is in charge of creating and maintaining reference points on and for employees and customers.

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Since data is the concern of every organization, the need for data analysts is growing. It will likely continue to grow in the healthcare industry and many others in the coming decades. The medical field as a whole, though, has faced and will continue to face mounting challenges in the years to come.

COVID brought a massive blow to the industry in terms of staffing shortages in nursing departments, but it might not be a stretch to say that the stress of those years trickled into every department in healthcare offices.

With the need for more staff and the general lack of diversity in hospitals’ employment structures, administrators are increasingly paying attention to racial diversification.

Since those organizational goals are not limited to the medical industry, any position within the data management field will be in unique demand. Still, the importance of timely, effective management is paramount.

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Medicine has always held an important place in human society. Still, the technological shifts in the last century have incited a pace of adaptation for technology in healthcare like never before.

With the influx of these new methods in practice and management, medical institutions have been met with continuously evolving challenges to properly utilize the data gathered from millions of people every day.

Managing that data presents a wide variety of issues to consider and overcome hourly. From storage space issues to data corruption, shareability, and, most importantly, security, not a day goes by that difficulties don’t arise for those responsible for overseeing its use in medical offices.

Despite the messes consistent in the healthcare industry, administrators are aware and informed of how to face these challenges head-on while anticipating the industry’s future.

With all that in mind, the need for intelligent, detail-oriented individuals will be a consistent concern, generating an opportunity for fresh faces in employment.

The more people with these skill sets that can be trained and placed in the workforce will impart stability to the field that is indispensable to our modern world.

Himanshu Tyagi
Himanshu Tyagi
Hello Friends! I am Himanshu, a hobbyist programmer, tech enthusiast, and digital content creator. Founder Cool SaaS Hunter. With CodeItBro, my mission is to promote coding and help people from non-tech backgrounds to learn this modern-age skill!