Diagnosing Healthcare Data: The Problem With Inaccessibility and Immaturity

People   |   Brooke Munnings   |   Jul 26, 2023

It was early 2023, and the life insurance company was about to deny me coverage. Over two weeks had passed, and one of my doctors still hadn’t sent my medical records to the life insurance company. What was taking so long? The doctor’s office was either too backlogged or their systems were too outdated to comply. Either way, this was about to affect my coverage and could have severe consequences for my family. Thankfully, I was able to get the medical records I needed through some sleuthing inside my patient portal, but this experience was symptomatic of a much larger problem that plagues U.S. healthcare systems.  

Throughout my many years of studying and working in health informatics and healthcare analytics, I’ve noticed one chronic symptom that ails hospitals and clinics alike: immature data practices. Here’s why it’s a problem. 

Symptoms of immature data practices 

Data inaccessibility and immaturity affect countless organizations, especially healthcare organizations, which, by my estimation, tend to lag about 10 years or more behind other sectors. While every sector can relate to the difficulty of digital transformation and the need for more mature data practices, in healthcare, it can be a matter of life and death. 

Imagine ending up incapacitated in a hospital, and you can’t tell the doctor which medications you’re on, what allergies you have, or about any existing comorbidities. If you need surgery, the anesthesiologist has to take a stab in the dark about which comorbidities you may have and how they might affect the anesthesia administered — which could have mortal repercussions. 

While this sounds dramatic, it’s not far from what many hospitals deal with on a daily basis. On a smaller scale, many people are likewise familiar with the headache of having to call around and get their medical records sent from hospital A to hospital B. If they can’t get them sent, hospital B is going to make the patient redo all of those X-rays and procedures — adding costs and time.  

But why do healthcare organizations have such a hard time with data? Well, for starters, a lot of these health information management departments and hospitals are simply backlogged. They don’t have the right IT staff or infrastructure to handle all the incoming and outgoing requests. 

Transparency and cleanliness are equal problems. EMRs (electronic medical records) can vary from provider to provider. And two different facilities might capture data differently, even though they’re using the same EMR. As a data professional, it can be time-consuming, tedious, and painful to aggregate that data from various healthcare sources. Don’t get me started on the healthcare organizations that are still using paper and fax machines. Yes, they still exist. 

How silos are born 

I’m going to use Indiana as an example since I’m from there, and Indiana University Health (IU) encompasses every facet of healthcare: They have hospitals, primary care providers, imaging facilities, surgical facilities, facilities that specialize in cancer treatment, cardiovascular centers, and so on.   

But IU didn’t start out having all of these facilities. These facilities were previously standalone small companies or private practices that had been acquired. As with any acquisition, in healthcare or otherwise, systems aren’t integrated overnight. There’s so much involved in integrating electronic systems, or, heaven forbid, digitizing paper records (stop using paper!).  

So even though IU is all one network, there are individual companies within IU, and they might be using different EMRs. Whenever a data professional is trying to find new insights — for example, comparing the vitals and health outcomes of patients who actively use their patient portals versus those who don’t —  it’s beyond difficult to gather the appropriate data. As you can see, there are many elements that data inaccessibility and immaturity affect, from the patient side to the analyst and clinician. So, what’s the fix? 

Moving toward greater data access  

Some states have started creating health information exchange networks that healthcare organizations can participate in. It’s essentially where a hospital or clinic adds medical records to an exchange. Access is limited to clinicians and regulated at the state or federal level.  

This type of exchange allows doctors to get medical records much, much quicker. So if you’re vacationing in a different state, and you break a leg and have to go to a hospital you’ve never been to, they have all of your health information on hand. 

This can have life-saving implications. While, it’s understandable that many people wouldn’t want governments handling sensitive personal information, and there is a risk of cyber attacks, I believe the benefits outweigh the risks.  

First, having a health exchange is better for clinics because they no longer have to fax and request medical records to and from other hospitals. It also minimizes the labor costs of maintaining a lengthy health records department. It’s better for doctors because they can make treatment decisions faster and easier. And above all else, it’s better for patients, who can receive better, faster, and more cost-effective care. 

Keep fighting for better data practices 

I don’t know if widespread adoption of healthcare information exchanges will ever happen, but I’m here for the fight for as long as it takes — along with many other passionate healthcare data professionals. Yes, it will be an expensive and long fight, but greater data maturity and data practices will help everyone achieve new insights and better health outcomes. And what could be a better cause than that? 

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