Supported by :

The Med Student’s Guide to Analytics in Healthcare

Last Updated on June 27, 2022 by Laura Turner

As a future physician, you’re constantly learning. You spend years studying, memorizing, reciting, hypothesizing, shadowing, and practicing — laying the foundation for the rest of your career. And if you strive to be a patient advocate, your acquisition of skills and knowledge will only continue. That’s why it’s crucial to start learning the ins and outs of healthcare analytics right now.

With each passing year, technology and data play a larger role in healthcare. So it won’t be long before analytics is a major component of every physician’s daily routine. Getting a head start on the facts means you’ll not only be one step ahead of your future colleagues, but you’ll also arm yourself with the knowledge that could positively impact the health and lifespan of your future patients.

About the Ads

The Importance of Analytics in Medicine

The introduction of technology and data has brought about some amazing changes in healthcare. With electronic health records, doctors have access to more patient information than ever before. And because data provides a well-rounded picture of a patient’s health, it eliminates a lot of the guesswork in diagnostics, cuts down on costs by eliminating unnecessary tests and treatments, and even forecasts when the patient will face health issues.

As more and more facilities take advantage of analytics, physicians’ roles will likely change. With predictive information at their fingertips, they’ll be able to adopt more of a consultative role. And in doing so, they’ll spend more time with individual patients, form longer-lasting patient relationships, and decrease negative patient outcomes.

But like any new initiative, there’s a learning curve, and traditionally, physicians aren’t analytics-focused professionals. What’s more, even if a physician is ready to adopt analytics, many organizations are still in a transitional phase of making this a commonplace process.

However, healthcare is moving in that direction, and as data-driven, predictive medicine becomes pervasive, all physicians will have to be trained on the programs before they can benefit from the massive amounts of information at their fingertips. Luckily, you can avoid the awkward transition period by getting a jump start on learning about healthcare analytics now.

Become Fluent in Data

Data is a vast topic, and fully understanding it can be an overwhelming task. That being said, you need to start with the basics by developing an appreciation of data and how it relates to medicine. You can begin by learning these six terms:

  • Smart data is information that makes sense to users, such as graphs or charts that make meaningless numbers digestible. Algorithms can turn mounds of patient data into actionable insights, which will help doctors make more accurate diagnoses.
  • For example, imagine that a patient visits the ER complaining of chest pain. It can be tough to gauge whether the patient should be hospitalized, but by entering his information into a system with an accurate predictive algorithm, a doctor can supplement his judgment with that of the algorithm. This way, he can make the best decision possible.
  • Big data is a huge buzzword these days, but at its core, it’s actually quite simple: Big data is any data that is too big or too fast to fit within the structures of a conventional database. Having access to this large amount of data will help doctors successfully anticipate, diagnose, and treat illnesses.
  • Analytics leverage data in a particular functional process or application to enable actionable, context-specific insight. Analytics are used in an array of industries to process real-time data so leaders can make quick business decisions. In healthcare, analytics can be used to collect patient feedback on the quality of care, which physicians can use to improve their practices.
  • The Internet of Things (IoT) is the concept of connecting any device with a switch to the Internet or another device. It’s a giant network of connected “things,” including people-to-people, people-to-things, and things-to-things relationships. By the year 2020, it’s estimated that there will be more than 26 billion connected devices.
  • Wearable devices are becoming huge in healthcare for patients who need to track their health information. Some facilities have even started using “smart beds,” which can detect when beds are taken and when patients are getting up. These beds can also apply pressure based on patients’ needs without a nurse’s manual help.
  • Business intelligence (BI) is an umbrella term for a variety of software applications — such as data mining, online analytics processing, querying, and reporting — used to analyze an organization’s raw data. In a healthcare setting, it can be used to cut hospital costs, perform innovative research, and improve the decision-making process. Doctors make critical decisions every day, so BI is an important tool for them.
  • Data dashboards are graphical reports of static or real-time data on a desktop or mobile device. Dashboards provide a quick summary of significant or changing information, including important patient data. With a data dashboard, patient data will be readily visible, which will cut down on the time doctors have to spend sifting through raw data.

Once you’ve gotten a grasp on the terminology and methodology, you can begin investigating where data is stored and how it’s currently being analyzed in the medical world. Look into where organizations are integrating technology and data analysis to improve healthcare. Then, you’ll be ready to tackle the future of data.

There’s a major evolution in healthcare on the horizon that will transform the way medicine is practiced. Refining your foundational skills now will help to position you as a caring, forward-thinking physician in the future.

About the Ads