Bird’s Eye View of How Population Health Management Helps an ACO

In the healthcare industry, demands for better services at lower costs are at the forefront of many conversations both within and without the walls. Many of the mandates that government sets forth also stipulate this. How are organizations supposed to make changes to a business that is dealing with accidents and ailments that have their own unique circumstances? There is a particular tool that these groups now have at their disposal, which provides a better understanding of the community where they are located and the needs of the people found within; this is Population Health Management software. Healthcare providers can make data-driven decisions, plan for the future and improve care all while containing costs.

image courtesy of flickr.com/AnswergenSengen
image courtesy of flickr.com/AnswergenSengen

Population Health Management is defined as the outcomes and distribution of healthcare within a specified group. These groups may be as large as a nation, or a particular community; they may be more exact by selecting persons with disabilities or financial difficulties. However, when a healthcare organization is providing services in a defined area, they want to know the types of services that are most needed, where are the best locations for hospitals and clinics to serve the most number of patients, and where specialty treatments physicians would most conveniently located.

The task of tracking down all this kind of information, creating a report that details the population that is being helped, and doing it in a timely manner is almost impossible. Educated guesses are still just based on making a decision without all the information in hand. This is where and why Population Health Management (PHM) software is crucial in changing decisions from guesses to fact-based and data-driven.

We all participate in adding information to healthcare data systems every time we visit the doctor or end up in the hospital; statistics and notes go into our electronic health record (EHR), which enables the treating expert to know our health history and to add to it. This health information is not only collected for our own personal benefit, but is pulled out and used to understand everyone around us. In other words, when you get the flu and end up in the doctor’s office, information is saved and analytics applied to bring to light health patterns in your area. With a picture of patterns that have occurred over years, and your input, it is easy for decision makers within a healthcare organization to predict when cold and flu season will probably start next year. This is a small example, but the ability to prepare, yet not over prepare, aids in the effort to provide better care and not have waste or overages on the financial side.

The predictive and preparative knowledge gained by understanding and applying population health management strategies also has an effect on managing patients’ risks and reducing negative consequences. As seen in this Becker’s Hospital Review article, PHM turns previously time consuming tasks into much more time sensitive reports and data, which translate directly into effective and efficient care.

PHM isn’t simply loaded onto a bunch of computers and it is ready to use. There is a lot of time, changes and other investments that are required to implement the system. With as much data that is being created and saved, the need for an Enterprise Data Warehouse (EDW) is a must. Along with knowing that implementation isn’t a series of single projects that once completed provide a new, self-contained system. Part of this is due to the fact that every organization has different requirements and unique obligations that must be met. These must be understood so as to integrate them into the system as a whole, and ultimately reach a point where efficiencies are more the norm.

image courtesy of flickr.com/NicoTrinkhaus
image courtesy of flickr.com/NicoTrinkhaus

Truly, it is quite amazing that each one of us is contributing to a huge picture that improves health services down the road. We all live as part of a community and many of the regularities found within communities are repeated. These repeats of patterns and the understanding of how to prevent, prepare and predict health issues is exactly what Population Health Management is all about.

The Importance of Clinical Analytics

Posted onCategoriesMedical

Clinical Analytics is when a healthcare organization utilizes stored and managed data in order to provide data-driven decisions. This may be decisions within a specific clinical setting or to produce information as to the organization’s bottom line or inner workings. The common factor is putting the data that has been collected to work instead of just generating reports with facts and figures.

image courtesy of freedigitalphotos.net/bluebay
image courtesy of freedigitalphotos.net/bluebay

With the introduction of electronic medical records (EMR), and other data warehousing options, the healthcare industry has gained, organized and recorded a huge amount of essential statistics. Storing this data is one thing, but finding actionable information is other story altogether.

Part of what clinical analytics can provide is a picture how past events can have many similarities with current patients, thus yielding information to better treat ailments. Also, tell-tell signs of future issues can be identified sooner and make it possible to avoid negative outcomes due to preventative measures.

Clinical analytics are important for healthcare organizations to have right now. Some aspects of analytics may already be implemented within certain systems, however, having fully integrated software that works with all types of information being received and has the ability to produce meaningful and useful reports is much more effective. Unfortunately, not all clinical analytic software on the market offers the ability to prioritize and increase the value from within.

As in any industry, technology and advancements are coming fast and furious. Healthcare had been one of the last businesses to seek out and utilize many of the data collection, storage, management and analysis systems to improve care and function. However, they have all but made up for the lateness to the party by taking very seriously the produced outputs to change the way we receive care and moderate costs.

image courtesy of flickr.com/DougWaldron
image courtesy of flickr.com/DougWaldron

Think of how far EMR and data analytics has come in just 5 years. How much further will it go in the next 5 years? 10 years? 20 years? Clinical analytics are not on a downward trend, but the use and usability are just beginning to be understood. As more data is collected, and we know this will happen because we all see our doctors or visit hospitals, more information will be gleaned and better analytics will reveal more insights.

The healthcare industry and its professionals have a great tool in their arsenal to help provide better treatment at a lower cost for everyone involved. This is the pathway that is being focused upon to help patient and expert alike. Clinical analytics are not a flash in the pan, but a true answer to many questions that we haven’t even begun to ask.

Obstacles in Collecting Healthcare Data

Posted onCategoriesMedical

Collecting healthcare data is difficult for a variety of reasons. Where the industry is right now, healthcare data is “owned” by a variety of people, and in a variety of ways. The necessity to make changes to the industry as a whole requires changes that aren’t simple and won’t be met with open arms by all those involved with inputting of data.

image courtesy of freedigitalphotos.net/photostock
image courtesy of freedigitalphotos.net/photostock

In electronic medical records and other forms of healthcare databases, data is recorded both numerically and textually. However, much of the data has a long history of being written out. Converting this data, which is inaccessible to most healthcare professionals due to being located a physical site, requires the time, effort and dedication to transfer into digital form.

To understand better these two different forms of data, numerical data is defined as anything containing a simple number, such as date of birth, age, height, weight, temperature, blood pressure and amount of medicine being administered. Textual data is data in all other forms, including all written information, MRI images, x-rays, etc. This sort of data is much more difficult to delineate into specific areas or categories because it isn’t always an absolute, like numbers are.

This is where we introduce systems like the International Classification of Diseases (ICD), which assigns numbers and codes to different textual data in the healthcare industry. For example, the current ICD-10 code for the Ebola virus is A98.4.

This coding system will certainly help to define healthcare data more precisely, and allow it to all be readable by any system. This is the type of uniformity that is crucial to produce a readable and analytical system. However, making sure that all healthcare professionals are on the same page can be a different story altogether, and adds to the obstacles that make collection of data difficult.

In addition to the two major forms of data (which are hopefully more easily defined by the ICD), data can also come in the form of doctor’s or nurse’s opinion, which cannot always be categorized into the coding system. There certainly are standards in healthcare practices, but there is also variation in the ways doctors might diagnose something or note specifications of a patient. One hopes for consistency across the board, but that can’t happen when from practice to practice, from doctor to doctor, or even from patient to patient there are personalities and uniquenesses that make this impossible.

On top of the obstacle of data collection and varietals, there is also the legality in collecting healthcare data. Different providers “own” their own data. The patient has gone to that doctor and agreed that that doctor/practice/hospital can have their data, but not anyone else. Confidentiality agreements are signed, and the data cannot be shared unless the patient agrees to it.

image courtesy of freedigitalphotos.net/hywards
image courtesy of freedigitalphotos.net/hywards

Undergoing this data transformation is a huge undertaking for everyone in the healthcare field. It means learning new systems to track this data, learning new codes for doing so, and learning how to use and measure this data. While it is certainly a part of the solution, it means doctors, nurses and other healthcare experts will need to learn what is virtually an entire new language to record their data. This will be a challenge, but one that has the potential to benefit both patient and professional.

Though the current system of data collection for healthcare information is not ready for the diversity in how facts and opinions are recorded, technology specifically focused on this classification of data is moving forward and may one day allow for the variety of textual data and still produce a plethora of usable analytics. Until then, finding standardization within the system is necessary and will turn out very useful information that can be beneficial to everyone involved.

What Can Healthcare Analytics Do For You?

Posted onCategoriesUncategorized

Healthcare Analytics and Big Data are huge topics right now in the healthcare industry. Sure – they have some benefits, but getting on board is time-consuming, costly, and not without obstacles.

image courtesy of freedigitalphoto.net/hywards
image courtesy of freedigitalphoto.net/hywards

Doctors and nurses at every level have to take time out of their busy schedules to learn new systems, new languages and convert old data over to such systems and languages. Non-medical personnel have to learn the same things, and often more are hired to take on the burden. So, what’s the point of all this?

There are many benefits of getting on board with electronic medical records and other digital forms of storing healthcare data. To start with, it’s 2015 and everything else is online, so why isn’t the healthcare industry? Virtually every other industry records their data digitally, and healthcare is late to this game.

But, other than just “keeping up with the Joneses,” digital healthcare can actually bring each and every healthcare employee, hospital, practice, and patient many benefits.

Patients often see many doctors to try to get a diagnosis or treatment for an ailment. Maybe a primary care physician was the first visit, but then the patient has to go to a few specialists after that. Wouldn’t it be great if every symptom, conversation, and treatment for these visits were recorded in the same place?

Same for doctors. Why waste time and resources re-examining something that another doctor has already tested and looked at?

Once all the data is stored in one place, we can get even more out of analyzing such healthcare data. Healthcare analytics can improve population health as a whole – making virtually every aspect of our healthcare system run more efficiently and with more cost savings.

With healthcare analyses we get from recorded data, we can map out where diseases and viruses are more prevalent, and where they might not be being treated effectively.

For example, healthcare organizations can map out where there are high populations of women over 40, and over that, map out how many breast cancer screenings are happening in those areas. Maybe there’s an area well populated by such women, but that is lacking in breast cancer screenings. That’s a perfect place to set up a new mobile breast cancer screening site!

image courtesy of freedigitalphotos.net/RenjithKrishnan
image courtesy of freedigitalphotos.net/RenjithKrishnan

Another location-based situation where healthcare analytics is useful is with coordinating emergency medical response teams. They can map out when and from where most calls come in, and have teams closer and ready to go in those areas at those specific times, shortening the amount of time people have to wait for help to arrive.

Healthcare analytics can help avoid keeping people in hospital beds for too long, or, alternately, sending them home too early. They can look at historical data and compare current cases with past cases with a simple search. This type of evidence-based medicine can vastly improve patient outcomes.

The digitization of healthcare data and use of healthcare analytics helps the healthcare industry in many ways. It’s not something to move into without much thought either though. Healthcare organizations need to consider these cornerstones for success. Then, research and adopt a model that works for them. Eventually, the whole industry will see the benefits to having implemented and used healthcare analytics systems.