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The modern hospital system is defined by a number of technological features that healthcare workers in the early 20th century could never have imagined in their wildest dreams.

What distinguishes the modern hospital system?

Technologies such as 3D printing, the Internet of Things (IoT), and cognitive computing are making a change in the way hospitals care for patients, communicate, and do business.

3D printing, also known as stereolithography, has been used for the past several years in healthcare applications for printing prosthetics parts and creating customized dental implants.

A newer technology that may be just around the corner is the use of 3D printing to customize medications.

At least one drug company, Aprecia Pharmaceuticals, has already begun testing the technology and has printed oral tablets. Soon, healthcare providers may be able to customize not only the composition of oral medications, but also the precise dosage and even the release schedule.

Devices that connect to the internet as well as interconnecting with one another, collectively referred to as the IoT, are becoming an increasingly common sight in everyday life. Hospitals will be no exception, too.

The IoT will allow healthcare providers to access patient data from wherever they’re working, tune and configure devices remotely, keep track of hospital property, and make sure data are secured in a HIPAA-compliant way.

Imaging data has long been a crucial element of patients’ health information. Yet, imaging services are costly, reimbursements for such expenses are continually diminishing, and healthcare administrators have had to get creative to be able to manage them. 

This is where enterprise imaging (EI) comes in. EI gives healthcare systems a way to standardize and centralize imaging data across medical disciplines and data formats. The result is a bank of image data that can be accessed and viewed by any qualified person from any point in the data management chain.

One example of a centralized, standardized image data system is the radiology PACS (Picture Archiving and Communication System). Files from most any PACS can be housed in a vendor-neutral archive (VNA), allowing them to be read across an entire healthcare system regardless of PACS used by each provider in the network.

The sheer volume of healthcare data is overwhelming, its scale almost impossible to imagine.

Helping hospitals manage the wave after wave of data coming their way will soon be a task entrusted to increasingly smart computers like IBM’s Watson.

These machines are able to simulate human thought processes in increasingly sophisticated ways.

Various components of artificial intelligence (dialogue generation, human-machine interaction, machine learning, narrative generation, natural language processing, reasoning, etc.) go into cognitive computing.

These programs, capable of processing vast amounts of data in a short time, help doctors make faster decisions based on more available data.

IBM has already partnered with the Memorial Sloan-Kettering Cancer Center to create IBM Watson for Oncology, which can analyze the content of more than 12 million pages of data from medical journals, medical textbooks, and other relevant sources.

Medical software platforms, which make use of augmented reality to create 3D images that medical students (and other students in healthcare education programs) can then interact with, has changed the way the healthcare providers of the future will be educated.

Students can now use virtual reality to begin exploring human anatomy, before they ever have to dissect a cadaver.

The same technology is changing the way physicians view imaging data as well.

Radiologists have too often had to rely on 2D data to make sense of what’s happening inside of a 3D human body. Now, CT and PET scan data can be digitized and converted into 3D images, giving M.D.s more diagnostic clues to work with.

3D printing, the IoT, EI, cognitive computing, and augmented reality are only a few of those new technologies that will assist hospitals in delivering the most cost-effective and efficient treatment to the greatest number of people.

Medical technologies such as immunological treatments for cancers – so-called “organs-on-chips” that replicate body tissues for use in clinical trials – and gene editing technologies like CRISPR will undoubtedly also play a large part.


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