Marketing, media and businesses are being forced more and more to live on a tighter budget and to prove their worthwhileness as part of continuing. This has forced anyone working the books to demonstrate the correlation between things like advertising and sales. But with a growing market in just about every industry and the reliance upon verifiable data, experts have been forced to move from educated guesses to concrete proof, which is much easier said than done. One of the biggest obstacles is that stored data isn’t always located at one site, sometime due to the shear amount of data being gathered. This is a huge dilemma especially within an industry as large as healthcare.

The fact that each of us as some point becomes a patient isn’t a bad thing; many of us seek out our doctor for yearly physicals or try to stay on top of illnesses. As we do this, we are adding to the vast amount of data being created. All this data cannot simply be stored on a general server or a number of siloed locations because it serves very little purpose, doesn’t necessarily fit on traditional databases, and provides no actionable information when spread out. The answer is found in enterprise data warehousing (EDW) where data is stored and available in a single place. This allows for analyzing and making data-driven decisions.

For all those that have had to write reports, conduct research or seek out detailed information in the time before there was Internet understand that many times all the information you were searching out was not housed at one scene like a library. The same is true when moving from individual databases, possibly at each office or location, and combining to create a single-source, single location data source. With everything from medical history to billing and insurance in one area, the ability to find “reliable and repeatable” data is possible.

Especially within an industry that is so vast and complex, being confident with the information you are receiving, along with the abilities of timeliness and accuracy, allow you to make better decisions, make fact-based decisions, avoid prolonged conclusions and even predict necessities within the organization. This exact strategy has been implemented by Crystal Run Healthcare of New York. In order to be more successful, to improve patient care, cut costs, and travel down a more evidence-based route, they have taken the steps to implement things like the EDW, population health management and single-source data system. Crystal Run is just one of many accountable care organizations (ACOs) that is moving as far away from educated guesses and toward value-based care.

In the fast-paced environment we all live in, and with the ability to change old ways of doing business, we have no excuse to not increase how businesses are run. Exchanging the piecemeal way of storing and retrieving data is only one step, but is one that improves that way information is handles and the accuracy in which data is now presented. In an industry that depend so highly upon accuracy and timeliness, healthcare has seen and will continue to see growth that can only be found within a single-source data model.

Data governance is important for all organizations that have data – healthcare or otherwise.

Consider my past job. I worked at a government agency that funded job training and social work programs. We had a vast amount of data. We had data on every person who had ever participated in our programs, in any way, even if they just walked into a Career Center once, from when our program started in the 80s. We had data on youth too, from ages 12 to 18, as long as they qualified for our programs. So, of course, with all this data and record-keeping, we had to have systems to store the data and run reports; we had to have people to do these things (both “data stewards”, if you will, and an overseeing IT team, as well as leadership staff who oversaw everyone).

So, as you can imagine, data governance was an important thing at my last company. And, just like many healthcare organizations now, while I was there we were at a point of trying to streamline and organize our data governance. This was not an easy task. While most of the company was going about their business as usual, entering data and pulling reports when, how and as needed, I was selected to be a part of a committee that was going to head up streamlining our data governance and data systems.

This team included data stewards and leadership from each program department, representatives from IT, representatives from Finance, and even the Vice President of Operations. It was important to have a representative of each type of department who had their hands on the data be present. That way, nothing would go overlooked, and each department would have a say in what went on.

Our first step was to look at what different departments were doing differently. Many things were the same – we used the same program, we had the same positions of people doing similar tasks. But some things were different. Some things were just coded entirely differently from department to department. It was definitely a lot to go through. Once the Finance system was brought in, it was certainly a whole other task. As with many companies, the finance data system was different than the client tracking data system.

In the end, we tested out, chose and purchased a system that worked for both the program side, and the finance side of our organization. It took over a year, and it took lots of work from our committee and especially from the IT and Finance teams. The IT team had to switch past client data over to the new system, and the Finance team had to change their system as well. Everyone had to learn this new system.

But now, just a few years later, my old company runs much more smoothly than it did before. Clients are better tracked and served, with better outcomes, and the Finance side is run automatically and in a much more efficient way than it previously was.

It was a painstaking process to go through, but the results were well worth it.

This type of data governance is the same thing that needs to happen with healthcare organizations. Data governance is an important step in moving forward with healthcare data. And there are guidelines on how best to do it. It is first important to gather the right team of people to start this process. And, in the end, it will have been worth it to get desired outcomes, more efficiency and hopefully cost-saving as well.

It is no secret that every business and industry, especially healthcare, is doing all they can to cut costs and still offer the best product or service. To achieve this benchmark is much easier said than done. In fact, some owners and managers don’t know what needs to be changed or where improvements can be made to facilitate this goal. However, a key instrument has made a resounding entrance to produce fact-based representation and point out the lack-luster areas that need real change. This instrument is known as big data, and healthcare system administrator have taken notice.

Many people of great importance throw around this buzzword, yet may not fully understand the fundamentals of big data. One of the most down-to-earth definitions of big data is: “…voluminous amount of structured, semi-structured and unstructured data that has the potential to be mined for information.” Specifically, voluminous is classified in petabytes and exabytes. That much data generation is found in industries like financial firms, social media giants, retail organizations, telecommunication services and medical providers.

Many of the strongest run businesses within the named industries rely heavily on big data to run their day to day actions and to be more profitable over competitors, especially those that do not employ big data tools. The healthcare industry is in a very different predicament because many of their directives to cut spending and improve overall care are mandated to them. Thus, the necessity to implement any system of rules to realize the established regulations is essential, and big data performs this dutifully.

At some point or another, all of us will be a patient. Most of us seek out a local physician to conduct wellness checkups, and to help with any ailments that afflict us. Some of us end up in the hospital or emergency room due to quick onset symptoms, accidents or prolonged discomfort. Every bit of information that is captured while in any medical setting is stored. This information may be as simple as our name, date of birth, height and weight, but there is so much more that is obtained like blood pressure, current prescriptions, allergies, family history, prior surgeries, along with any notes and further treatment, follow-ups or referrals. Basically, we are walking data generators.

By no means are healthcare professionals treating us as data points on a chart or information packages. Yet, it is through all input that we have received better and more precise care. Image conducting a survey and the more people you are able to petition the more accurate your findings will be. This is no different, excepted in scale to a simple survey. Healthcare experts work toward treating each patient as an individual with particular needs, with the end goal of positive outcomes. Each visit with each patient in every situation, whether routine or absolutely unique, holds the potential of helping someone else. That someone else becomes each of us now.

All the big data collected isn’t purely for the benefit of treating patients effectively and efficiently, but also works towards financial benefits for the organization, which trickles down to patient costs. When a system runs more finely-tuned, with less waste, a reduction in errors, and prevention in fraudulent circumstances. This allows for a greater focus on the part of the professional to his or her specialty and less on outside preoccupations.

Healthcare relies on the information that big data supplies to treat each patient, to run a business, to find inefficiencies, to prevent negative results at any level or department, and to plan for the future. That is a lot to glean and benefit from when entrusting all your information to a developing and growing strategy. However, without this program, the accuracy of care, the potential to remove impracticalities and to better an industry has been completely removed, and healthcare professionals are left to their own devices. Not a comforting thought or a way to pave a path to the future.

Healthcare business intelligence is about how and when we use the data that the healthcare industry collects. The industry as a whole is and has been putting a lot of valuable time into putting all medical records and healthcare data into big data warehouses or other data storage systems. But, if we don’t use this data, it’s a waste of time.

Healthcare business intelligence is about taking this data and using it to improve many facets of healthcare: quality of patient care, cost effectiveness and efficiency, reduce waste, create consistency, conduct future research and satisfy new governmental requirements. Hopefully using the intelligence we’re gaining from all these new systems and processes means we will achieve all of these things in the future.

But how do we use this intelligence? This has to do with adopting an effective data storing system and also a good model for analyzing such data. If your systems aren’t working, neither will the intelligence you get out of them.

Electronic medical records are one way to store data. But they hold static information and do not always keep up with the changing data or the different needs or the reports we need to get out of such data. More flexible data warehouses might be more useful, as they simply hold data, but in its early stages so that it is available to produce whatever report and in whatever format might be needed.

The sole use of data warehouses, not electronic medical records seems to be gaining popularity. Maybe for some organizations electronic medical records are more useful, or for some both are. But the overwhelming majority seem to support electronic data warehouses. But, unlike electronic medical records, it seems organizations need to have a solid action plan on how to incorporate such data warehouses.

Once the data is stored, the next step is using it, and deciding who uses it, who has access to it and what kind of access those people have. Having nurses or doctors take care of healthcare business intelligence is likely not the most efficient way to use them. On the other hand, most healthcare organizations have IT teams who man the data warehouses, reporting and all other aspects of healthcare business intelligence. But for some larger organizations, maybe that is not enough. Larger hospitals and the like are hiring data analysts, or other data specialists to actually be in charge of the data that is going in and out of the hospital. This person “owns” that hospitals healthcare business intelligence.

Healthcare business intelligence is a relatively new term, and new aspect in the healthcare industry. It will likely take on new meanings, new jobs, and new ways to change the healthcare industry. Either way, it is the all-encompassing way in which we use the vast amounts of healthcare data that is out there for the better for everyone.