Dashboards and Data Viz | Healthcare

When it comes to data, the healthcare industry faces some unique challenges. Most of us tend to think of data as being very structured and linear, but healthcare data can be complex and, frankly, messy. The volume of data the industry must contend with is vast. It can be unstructured, inconsistent and disorganized. But, healthcare data is essential, not only for making better and more informed patient care decisions, but for remaining compliant.

If healthcare data is to be useful, it must be complete, accurate, and easy to understand. Interactive data tools like dashboards are key to helping the industry overcome an essential challenge: streamline data collection and reporting, and make the vast amounts of healthcare data more easily accessible to those who need it most.

Unique Data Challenges Specific to the Healthcare Sector

Unique Data Challenges Specific to the Healthcare Sector

For most of us data centric minds, we like information to follow a very clear structure. B follows A, C follows B, and D follows C. But in the healthcare industry, it hardly ever works that way, if it ever does. While there are several unique factors that contribute to this non-linear structure, we’re going to take a look at the following:

  • The data is everywhere.
  • The data is both structured and unstructured.
  • The data is inconsistent.

Multiple Data Sources 

Think about how many departments there are in any given hospital. Radiology, cardiology, neonatal, neurology, occupational therapy, gynecology… the list goes on and on. Now, consider how many healthcare specialties there are. Dermatology, immunology, otolaryngology, pathology, endovascular surgical neuroradiology, and a host of other –ologies, -iatries, medicines, and practices—more than 120, in fact. Data is collected from each of these departments and from specialty areas, but that’s not all; much of the data exists in different systems and different formats. For instance, a radiologist may use images to identify a broken arm, but in order to file an insurance claim, the medial coder must categorize the broken bone as a “813.8”   for the claims data. Each of these factors contributes to duplicate data, making it more difficult than ever for industry experts to discern between what is relevant, what is not, and what is duplicate data.

The Problem with Unstructured Data

The Problem with Unstructured Data

Though regulatory agencies have attempted to get all healthcare providers to capture and report data in one industry-wide way, it’s been a slow-going process. Because these agencies are more concerned about the quality of care versus data reporting, they haven’t stressed a universal approach. This has not hindered the industry’s ability to collect data at all, but it has resulted in mountains of data that is unstructured and therefore, difficult to aggregate.

Electronic medical records have provided a framework for a type of standardized structure, but care providers who have grown used to unstructured data capture might stick to their comfort zones. On a case-by-case basis, it’s not hard to imagine old processes mixing with new in the name of not rocking the boat. This causes serious complications in records keeping, reporting, and data analysis. After all, when data is scattered and follows no coherent structure, it’s nearly impossible to share or analyze.

Read next: Partner Your EHR Technology with Data Visualization: Here’s How

Inconsistency

The healthcare industry has, arguably, more data variables than any other industry. This makes it difficult for data analysts to define a target, much less measure it. These variables can often be inconsistent, as diagnostic criteria often change or are subject to the interpretation of the physician. Ask any OB/GYN about their thoughts on what pregnant women should and should not do. One might tell you that it’s okay for expectant mothers to drink coffee in moderation, and that seafood is bad, and that exercise is paramount to the health of the baby. Down the hall in the same hospital, another OB might warn future mothers against caffeinated products altogether, suggest seafood in moderation for its Omega-3, and recommend against running or any other strenuous activity. Of course, what a doctor recommends will all depend on the individual in question.

This is how it is across all healthcare specialties—each practitioner has their own opinion of what’s “best,” and each patient has their own unique health concerns to consider. These types of variables make it extremely difficult to collect any sort of consistent data. If a group of practitioners can come to a general consensus on a particular issue, there is a very good chance that new information will soon emerge to change what clinicians view as important, the way certain information is measured, how and when it should be measured, and the particular goals to target.

Why Data (and Data Visualization) Matters in Healthcare 

data visualization healthcare

Historically, healthcare administrators and clinicians had to submit report requests to analysts, and then wait for those analysts to compile a report. This process was slow and clunky, and the relevancy of the data in the reports deteriorated the longer it took to compile. Reports were often “data dumps,” enormous spreadsheets that contained all of the data but few insights or analytics. To expect physicians and administrators to be able to make data-based decisions from reports that dense was a long shot. Truth be told, it is easier to trust one’s gut than an unintelligible spreadsheet. This resulted in patient care that was more judgment-based as opposed to evidence based.

Data visualization has changed the healthcare data game. With interactive healthcare dashboards, data from multiple sources can be combined into one visually appealing, easy-to-digest view that staff, physicians, administration, and even patients can understand. Disparate data sources can connect and correlate, revealing insights previously uncovered. Instead of healthcare providers and researchers having to spend hours sifting throughout otherwise impertinent data, they can glance at a single source of truth and gain the real time information they need to make on-the-spot decisions.

Streamline Metrics with Healthcare Dashboards 

It is more important than ever for healthcare professionals to make data-informed decisions regarding patient care. With mountains of unstructured data, hundreds of data sources to compile from, and numerous variables to contend with, it can seem daunting to undertake a data visualization healthcare project. However, interactive healthcare dashboards report on metrics automatically and in real time, actually saving resources and time.

Interactive dashboards such as those offered by iDashboards comes with real-time data reporting, which accounts for any changes in research, patient condition, protocol, or any other significant changes that may affect how and when a patient is treated. With this type of immediate information, it becomes easier for healthcare professionals to intervene while a patient’s information is still fresh in their memory, as opposed to waiting weeks for a data report to make its way into their hands.

Want to learn more about data visualization and dashboards? Click here to download our free guide, Everything You Need to Know About Dashboards!

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Beth Bryant Account Executive @iDashboards

Beth Bryant brings over 15 years of experience in working with customers to help them increase their ROI. Specifically, she’s worked with Non-Profit organizations to create awareness, increase donations, and donor retention. When Beth isn’t helping customers she enjoys cooking and documenting her foodie adventures on her personal blog.

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