Health Data Management Sources

Health Data Management Sources in Healthcare

The healthcare industry has an amazing amount of data that they are dealing with on a daily basis.  It has been some years since hospitals and doctor’s offices have relied on hard copies of patient files, but there is still some transitioning away from handwritten and physical copies to an all-digital system.  This is why health data management sources are an ongoing challenge within the industry.

When a patient seeks any sort of medical attention, whether it is a routine physical, a renewal of a prescription or a full-blown emergency visit, data is gathered, documentation is added to a patients electronic health record (EHR), and information about care and procedures is chronicled for internal and external reporting.  But, there are many sources that help to generate all the data being gathered.  Some of it is easy to determine and compare, while other bits are much more subjective and individualistic. 

Simple Ones and Zeros

As most of us know, there is almost always a packet of paperwork that is required the first time that we see a doctor or specialist.  This information is easy to quantitate and relate to other patients.  This such as name, address, age whether you have insurance, yes or no medical history questions, and dates.  When this data is entered into a computer, it is easy for the system to confirm if the data field contains correct information.  These data fields also make it incredibly straightforward for a comparative outlook, such as: how many current patients have a family history of hypertension?  Or, how many patients live within a certain zip code. 

Many other businesses and industries that work with big data don’t have to worry about much more than the simplest of data, which makes it easy to understanding the underlying aspects and going’s-on of the business.  If healthcare data stopped at the initial workup information, it wouldn’t be that difficult to manage, however, we all know that medical records more often than not contain much more than this type of documentation, which is necessary and helpful for exactness in healthcare treatments, but makes it difficult to create simple reports or appraise where problematic areas within departments exists.

A Picture is Worth a Thousand Bytes

Some of the biggest contributors to the healthcare data are what is considered as non-structured or non-traditional data. They include items such as:

  • Audio files/recordings
  • Video
  • Scanned notes or memos
  • Texts and emails
  • Imaging results (x-rays, CAT scans, MRIs, etc.)
  • Photos 

Each one of these files or recordings takes up a significant amount of space on database or data warehouse but is extremely important to a patient’s care, accuracy in treatment, and history from which to draw upon. 

For the most part, may physicians and healthcare professionals prefer entering this type of data because it is more accurate, allows for more detail and makes it easier when referring back to this information to remember the particulars of that patient.  However, aggregating and analyzing this type of data is nearly impossible, but is allowed in order to provide better care.

The software is coming up to snuff with this and is also making it simpler for a doctor to enter data in a more structured and analytical fashion so as to offer more information to everyone else working to better the running of an organization.  Thus, health data management sources are making a compromise, yet also developing the technology to find ways to integrate and compare the data will also help in this dilemma. 

Because there are different types or sources of data, and so much to manage when it comes to healthcare data, this problem isn’t going to be resolved anytime soon, but as advances are made, as more healthcare professionals adopt a more data-centric way of conducting business, and as more is defined for goals and needs within an organization, more will be discovered and uncovered within that data.

To understand the reporting, it is necessary to understand what is being reported upon. The Centers for Medicare and Medicaid Services (CMS) wants to track the quality of services being provided by physicians, hospitals and other care facilities as a means of setting goals, and ultimately delivering high-quality care for everyone. Some of the areas that were tracked, according to the CMS website include:

  • Health Outcomes
  • Clinical Processes
  • Patient Safety
  • Efficient use of Healthcare Resources
  • Coordination of Care
  • Patient Engagement
  • Population Health
  • Public Health

Once a healthcare organization has decided to improve health data management via data warehousing, it is essential to choose an approach that meets the unique needs of that organization. Common warehouse models include the following:

  • Enterprise Model –
    The enterprise model is a complex, but comprehensive approach to warehousing that involves the advance construction of a large centralized data warehouse. This approach was very common in the early days of warehousing, but while healthcare organizations initially exhibited enthusiasm, many struggled to follow through on overly ambitious plans. One of the biggest challenges attributed to the enterprise model is the need to make major decisions in advance without the ability to adjust for sudden, unforeseen changes. In an increasingly unstable healthcare system, this lack of adaptability can be catastrophic.
  • Independent Data Marts –
    A common alternative to the enterprise model of data warehousing, independent data marts allow healthcare organizations to start small, building targeted data marts for each department and later combining them to create larger analytic infrastructure repositories. According to data mart expert Ralph Kimball, it may be helpful for healthcare organizations to view data warehouses as unions of data marts. Although easier to implement than the standard enterprise model, the independent data mart approach is often not as comprehensive or organized as its alternative. However, it may be an excellent solution for smaller healthcare organizations looking to avoid the expense and time-consuming nature of large enterprise systems.
  • Hub and Spoke Systems –
    The hub and spoke model of data warehousing is increasingly becoming the go-to approach for mid to large healthcare organizations. This warehousing setup combines the comprehensive nature of the enterprise model with the accessibility of data marts. The hub and spoke approach involves an extract transform  and load (ETL) process that draws data from disparate source systems — including data marts — and integrates the information in an easy-to-access warehouse, known as the hub. If needed, this hub-based information can be transitioned to the spokes for greater precision or enhanced control among specific departments.

No one approach to data warehousing is ideal for all healthcare organizations, but in general, the concept of data warehousing serves as a welcome step up from the limited scope of data repositories. A data warehouse can vastly improve analytic organization and flexibility, and, ultimately, improve health data management.