Meeting Healthcare Needs With AI and Business Process Management

Back in 2013, the BBC reported that nurses were not able to spend as much time with patients due to the increasing amount of paperwork required of them. It was estimated that one-sixth of the working week was dedicated to non-essential tasks such as filing, photocopying and ordering supplies.

It is not uncommon for a patient to show up for a medical appointment and be met with delays and paperwork issues, or a situation where a new doctor doesn’t have their full medical history. As frustrating as it is, behind the scenes there is a lot more going on than we are aware of.

Each industry has a set of processes. The control of these systems is known as business process management (BPM), and more often than not, each process requires a staggering amount of paperwork. The healthcare system is a clear example of how many processes are becoming digitalized, but there is a long way to go. Figure 1 represents some of the key business processes that are present in the healthcare industry.


Each business process has to be managed. This requires analysis, measurement, optimization and improvement. Today, part of BPM is to automate as much as possible in order for the process to run more smoothly.

A Closer Look at Healthcare BPM

Let’s take a closer look at some of the business processes within the healthcare industry to get a better picture of the breadth of information these organizations must juggle:

• Emergency room operations. As soon as a patient enters the ER, they have to be registered and admitted. Depending on circumstances, it may not be possible to get a complete history of each patient; gaps will be left to be completed later on. Then there is a need to track the ER doctors, specialists, medications used, etc. Each stage must be carefully documented so that the data can be quickly and accurately used in the next stage.

• Drug supply. This is one of the most complex tasks in a hospital, requiring a lot of paperwork to be done on every type of medication a medical center could require. The record-keeping must contain what is in stock, what is used daily and what is needed. Not only this, but the records must be accessible to a number of staff members.

• Infection control. As the recent outbreak of coronavirus has made clear, this process leaves no room for error. Any mistake could lead to an infected person being in contact with non-infected persons, and inevitably the situation becomes worse.

Thanks to modern technology, many of these processes have now been digitalized or automated. But there is still a lot more to be done to get the most out of our data, and AI is the way forward.

Document Management and ECM: Converting Paper to Digital

Whether we like it or not, healthcare is a business, and it needs to be optimized with the end goal of making a profit. This profit is essential for improving the systems and services in place as well as making sure clients, or in this case, patients, are receiving the best possible care.

To increase the chances of healthcare being a successful industry, it is crucial that business process management is in place and using the most up-to-date tools to maximize efficiency. One of the key methods for this is to introduce artificial intelligence (AI).

Gradually, as more information gets stored onto computers we are seeing less paperwork, but regardless of the industry, it is essential to have an effective system or systems to manage the digital information. This is where document management (DM) and electronic content management (ECM) come into place. These two systems will work in conjunction with BPM so that each and every aspect of healthcare can be accurate and systematic.

What is Document Management?

This is a computer system that will store, manage and track documents. As the name implies, it is used for items like Word documents and PDFs. How can a good document management system help with a patient’s medical history?

• Check-in/check-out/locking: Nobody is able to overwrite another person’s version; one doctor can’t just erase the work of another.

• Version control: Allows people to see previous versions; doctors will be able to see other versions of a patient’s past medical history.

• Audit trail: Each edited version can be reconstructed to see who has edited what; one doctor will be able to see if another doctor previously prescribed a certain medication.

• Enhanced security and access control: A patient’s medical history can contain an array of personal information that cannot be accessed by simply anyone.

Using the example of medical histories, you can imagine how the old clipboard and doctor’s notes can be replaced by a tablet that contains absolutely every piece of information related to a patient. There will be no need to send nurses, students or administrators on a paper trail hunt when something is missing, no photocopies have to be made for specialist physicians, and more importantly, human error is greatly reduced.

What is Electronic Content Management? 

ECM is, in a way, very similar to DM. It is a computer system that will store, manage and track information. However, rather than documents, an ECM is aimed at controlling web content, images, audio files, videos, graphics and emails.

ECM takes organization to a whole new level. Not only will it save time, but it will also reduce costs and risks while increasing productivity. When a medical facility installs an ECM, time will be given back to practitioners so they can spend it with their patients, and the end result is improved patient care on every level.

Although DM and ECM are both marvelous concepts, they bring fresh new problems, and not just within the healthcare industry. While entire rooms may no longer be needed just to store paperwork and filing cabinets, there is still a massive amount of digital data, and
this has to be organized and managed.

If we take a step back from the healthcare industry and consider all business industries, imagine just how much data is gathered and stored on our computers. The data must be saved in a way that is easily accessible to multiple teams or even departments. Most importantly, the data must be sorted into unstructured or structured formats. Essentially, the user needs to be able to extract insights from the data in order to make informed business decisions. This is where AI plays
its part.

AI’s Pace in Today’s Healthcare Industry

It is a common misconception that AI is bleeding edge technology. As with all technology, the advances we are seeing are incredible, but the first mention of AI dates back to the 1950s. It is really over the last decade, however, that AI has made its way into the healthcare industry, particularly in diagnostic imaging. Some common uses of AI in healthcare include:

Radiology: AI is able to detect tiny changes that the naked eye would miss.

Disease diagnosis: Diabetes and cardiovascular disease are just two conditions that are more accurately diagnosed thanks to AI.

Telehealth: Wearable devices report the patient’s activity and symptoms directly to the physician.

Creation of new drugs: One noteworthy example is DSP-1181, a drug used for OCD that was invented by AI.

Digital consultant apps: Apps used to compare a patient’s medical history and symptoms against a database of illnesses.

How can AI be Used Alongside DM and ECM?

We’ve established that DM and ECM are digital systems that collect data and also sort and manage existing data. In terms of healthcare, this will encompass all of the information related to business process management, from the number of free beds to the supply of painkillers.

But there is still an enormous job of extracting useful information from the data. Many organizations find it hard to turn unstructured data into structured, meaning that they are able to collect it but then basically don’t know what to do with it.

AI is incredibly sophisticated software that is capable of reading documents, analyzing the content and classifying it accordingly. AI can be used alongside DM and ECM, so it can extract meaningful information from documents, emails, images and other electronic content and decide what is relevant and what is not.

Metadata is known as “information about information.” It is how AI takes all the information from a system and, by reading the content, can search for relationships between documents based on people, objects, logos and speech to text. In the past, information searches had to be based on a limited number of fields, perhaps the client’s name or a reference number. With metadata, additional fields can be added more easily, more data can be stored and relevant information can be found by searching the content you are specifically looking for. For example,  you could run a search based on the side effects of medicine within an age group or the bed occupancy per department. The list of possibilities is endless.

What’s more important, the use of an AI framework further improves the organization of data. Studies show that a great deal of the data we gather is redundant or trivial. AI frameworks function in layers, so it is possible to identify the “useless” information and either eliminate it or apply low-touch policies to make processes even more efficient.

In Conclusion

Imagine having the ability to scan an image of a prescription drug and immediately receive the correct dosage information, the side effects, who the medication is suitable for, the statistics based on its performance, how much of this medication is available in stock — all on your smartphone in an instant, without having to search through internet sites to get all this specific information.

The advantages of AI are clear across all industries, not only healthcare:

• Reduced costs

• Improved data quality

• Faster business processes

• Fewer compliance risks

There isn’t an organization in the world that wouldn’t want to make the most of one or even all of the above mentioned. For the healthcare industry, it is even more fundamental since AI can help save lives.

Zorana Bogicevic-Loncar is Head of the Global Pre-Sales Engineering team at Therefore Corporation GmbH. She has an extensive background with more than 15 years of experience in software engineering and more than 10 years in workflow automation and document management solutions. Her main area of interest nowadays is artificial intelligence and how it is about to change the world that we live in.