Healthcare is a naturally information-intensive sector(opens in a new tab). Data plays a crucial role in decision-making in both organizational and operational settings. 

Current practices for information management revolve around electronic health records(opens in a new tab) (EHR) systems. However, providers are still working through the EHR themselves, let alone the workflows, processes, and capabilities that fit into their clinics. 

As society continues to expand the amount of data it collects and needs to filter through, healthcare needs to embrace data analysis as a way to improve care. 

The Problem with Data in Healthcare

Healthcare is a complex system that regularly collects, manages, and uses thousands if not millions of data points monthly. This data is about patient information, patient care, and organizational information. While this data is rich and useful, many providers aren’t prepared to take advantage of it right away (if at all). 

It’s funny to think about data in healthcare because even though we know that the future of healthcare is technologically-friendly, we all know of that one healthcare provider who is still collecting information about patients using paper and pencil. When we consider these providers (who aren’t really outliers), it can be difficult to suggest that healthcare establishments would be organizationally mature enough to analyze data collected once switched to technologically driven healthcare. 

The reality is that the data that healthcare collects can provide significant value(opens in a new tab) and life-saving technology. Something can be said about data, whether that is identifying ways that patient health is failing, common demographics, or new insights into clinical practices. Without the means or preparation to analyze this data, providers are falling short. 

Providers with no vision, strategy, or planning for this data, including methods of data acquisition, data integration, and data storage, will struggle in healthcare’s data-friendly future.

Why Does Data-Driven Healthcare Matter?

Anyone with an eye to the future in healthcare and societal organization will understand the vital importance of data in healthcare. Healthcare organizations already have substantial costs associated with the administration of patients. Most providers already pay out of pocket for many things because of poor patient admission, poor infection control, lack of planning (for emergencies and outbreaks), and changes in patient needs. COVID highlighted the severity of this situation. In fact, many organizations are realizing how important technology has become in the fast-paced rule changes of the COVID-19 pandemic. Being prepared for change has quickly become a priority and only technology can help with this agility. 

The same occurs with American healthcare systems. Medicare, Medicaid, and other healthcare plans add to healthcare costs as organizations shift their focus to patient experience. More healthcare organizations are also able to provide more services, (and are being required to under government mandates), so organizations are being forced to expand options for relevancy. 

Prevention, personalized care, predictive care(opens in a new tab) (based on population), data-based operational support, remote patient monitoring, and other health initiative management are soon becoming a requirement for most providers.  It only makes sense that strong data management and analysis programs are in place for fast and effective decision-making. 

Moreover, there is actual value in the data being collected, which could put many providers at a strategic advantage over others. 

While there is some cost associated with implementing data collection and actualization, this burden is typically at the beginning. Down the line, the use of data in healthcare will ease personnel burden and actually reduce the cost of many administrative needs.

Embracing the Healthcare Revolution

Old medical records relied on writing down patient needs. Free-formed texts contained unstructured notes, limited patient categorization, poorly written information about medications or medical orders, and other pertinent information. In addition to these notes, patient files are often burdened with imaging from oncology, pathology, cardiology, and radiology as a necessary means for providers to initiate patient care. 

Traditional healthcare information systems are simply outdated. And whether providers make the switch for ease of operations or to stay current with the amount of data information processing out there, the switch is inevitable. 

So how do match this healthcare revolution? 

Clinics can start with basic research around the best information system management out there. Look for systems that provide data mining, data collation, and integrations for data manipulation in the future. Even if you don’t think you need it, you may be surprised at how the data can be used in the future. Programs that silo data generation and storage will be especially useful; particularly if healthcare providers begin collecting substantial patient data. 

Providers will have to consider the core basics of data collection, including storage and data type. Data in a structured setting will be better for interpretation and usability, but it may not be wholly accurate, or it may only provide a limited view of the issue at hand. Data can be collected in structured, semi-structured, and unstructured forms as long as these factors are taken into consideration by the software and team. 

Businesses also need to be prepared and mature enough to contribute personnel and resources to data analytics. Unfortunately, this is a bigger switch that providers aren’t prepared for. 

Research shows(opens in a new tab) that most healthcare organizations lack the skills for analytic resources, technical integrations(opens in a new tab), systems of truth for data, and data governance. These are all, unfortunately, critical to data platforms. Therefore, providers may need to bring on additional support to manage this new side of things.

Why Data-Driven Health is the Way to Go

When it comes to the nitty-gritty of providing patient care, most providers don’t have the time and resources to stop, think, and improve upon already existing patient processes. Well, that is, until the COVID pandemic came, rearing its ugly head. 

The COVID pandemic highlighted that data- and tech-driven health was needed in many organizations and this shift was necessary for survival. Therefore, hopefully, many organizations fully recognize that this shift is now necessary. 

Data in health will support the future of healthcare, which is geared largely towards new and innovative technologies that will produce a lot of rich data points for providers to use. Personalized medicine is slated to be one of the most profound uses of data and AI technology in healthcare as its ability to solve many patient problems is astounding. 

On top of that, genetics will start to play a larger role in clinical practices. Genetics data will need the support of AI technology and data mining processes for interpretation. The use of genetics in personalized medicine will be something that your healthcare organization will need!

While the shift to data-driven healthcare is a massive one, it will become easier as smaller healthcare providers start to recognize its importance and make the switch. 

Ready to see the ways your healthcare office can improve? Reach out to me today!