The healthcare sector and its data are unique compared to other industries. Compared to other industries, data in healthcare is more difficult to deal with (see Figure 1.4) because it is:
Multifaceted and resides in many systems (silos)
Often unstructured
Under strict regulations
The next sections will go into more depth on each of these issues.
Figure 1.4 Uniqueness of Healthcare Data
Source: Author.
MULTIFACETED AND SILOED DATA
Healthcare data comes from many sources and various systems. It is multifaceted and not linear. One data point does not necessarily follow or precede another since our health or diagnosis does not follow any regimen. As data points can come from handwritten notes, electronic systems, or piles of folders, data quality may be an issue in many organizations. Healthcare data involve many variables that make it challenging to centralize and analyze. Like our human body that consists of many parts to make it work together, healthcare data is very similar. Healthcare data is a combination of individual systems or silos that are very complex and unable to work together. Collecting and managing the healthcare data from each of those systems is often done with disparate applications, which makes it impossible to share and leverage that data across an ecosystem of fragmented applications.
Healthcare data comes from various departments across the organization. Data source systems such as electronic medical records (EMR) and electronic health records (EHR) software store certain data while different departments like radiology or intensive care units also have their own silos of data. In many instances, these types of data are in different formats – text, numeric, digital, paper, pictures, videos, etc. For example, radiology uses images while old medical records exist in note or paper formats while EMR systems can store hundreds of rows of textual and numerical data. Centralizing and aggregating all of this data into a single, unified system such as an enterprise data warehouse is a logical choice to make all of this data accessible and apply analytics for actionable decisions.
UNSTRUCTURED DATA
Healthcare data will not get simpler in the future and will only become more complex due to its variety and volume from unstructured data. Examples of unstructured data include email, social media data, XML data, videos, audio files, photos, images, sensor data, spreadsheets, web log data, mobile device data, RFID tags, and pdf documents. In the report referenced above from IDC, about 80% of the world's healthcare data is unstructured and needs to be treated differently than structured data that are normally in row-and-column format.
Approximately 1.2 billion unstructured clinical and medical documents are created every year. Critical medical information is often kept in these documents since it is so difficult to extract and analyze to obtain insights from them. One important way to improve healthcare, enhance patient care, and accelerate clinical research is by gathering, understanding, and analyzing the insights and relationships that are confined and contained in unstructured data. Such free-form medical text, hospital admission notes, and a patient's medical history are pertinent and relevant data points to help uncover opportunities.
As we embark on the digital transformation, healthcare organizations collect and leverage even more unstructured data from patient-generated tracking devices such as blood pressure sensors, heartbeat monitoring, and location identification. These mobile devices are constantly collecting your data that can be every minute or hour. Over days, months, and years, these data points can become massive in volume and they can be useful for clinicians to have more insight to prescribe to their patient a regimen toward preventive care.
STRICT REGULATIONS
Each time you and I visit a clinician, there are many forms to sign prior to seeing the clinician. One of them is the HIPAA (Health Insurance Portability and Accountability Act) form. This act was developed in 1996 to protect the patient's privacy as much as possible. Under HIPAA, the Department of Health and Human Services (HHS) establishes boundaries on the use and releases of our personal health records. HIPAA also outlines precautions to protect our information and establishes civil and criminal penalties for any violations. The law applies not just to hospitals and medical practices but also to chiropractors, dentists, nursing homes, pharmacies, and psychologists, as well as to business associates such as third-party administrators, pharmacy, benefit managers for health plans, billing and transcription companies, and professionals performing legal, accounting, or administrative work. Misuse of sensitive information about the patient can lead to serious liabilities.
For each clinician, we must sign this form to allow healthcare providers, hospitals, and small practices to collect, store, access, and manage patient data to be HIPAA-compliant. Once the form is signed, your medical records and history are made available for healthcare professionals to access, analyze, and diagnose. HIPAA addresses the use and disclosure of our Protected Health Information (PHI). PHI refers to any information that can be used to identify a patient, including telephone or fax numbers, websites or photos, names of relatives, any number or code that may lead to identifying a patient's identity, and much more. As we transition to the digital world, HIPAA compliance will be enforced to access our personal health records and share what is needed to get quality healthcare.
Healthcare organizations across the country are faced with several data challenges. Managing a tremendous amount of data that includes medical and patient along with an increased demand for on-time access to medical records is an opportunity for improvement. In addition, healthcare organizations want to streamline their application portfolios to protect our health data in a secured environment that is accessible for compliance, reporting, and sharing. Now that we have discussed the data in detail, let's examine the value of analytics and the analytic applications that healthcare organizations use.
VALUE OF ANALYTICS
There are many definitions for analytics and the emphasis and focus on analytics has been in the forefront of many organizations. Analytic applications have surged in the marketplace because many companies globally have recognized the value of analytics, in particular, healthcare analytics which analyze the past, understand the present, and predict the future from all the healthcare data that organizations collect. Analytics can be very broad and has become the generic term for a variety of different business initiatives. According to Gartner, analytics is used to describe statistical and mathematical data analysis that clusters, segments, scores, and predicts what scenarios have happened, are happening, or are most likely to happen. Analytics have become the link between IT and business to exploit the tsunami of data. Based on our interactions with customers, we define analytics as a process of analyzing all of the data to gain knowledge about your business and deliver insight-driven decisions within an organization. Let's examine some common use cases and the value analytics provide in healthcare.
Risk Score on Chronic Disease – With the right data, analytics can help to derive a risk score and predict the likelihood of a person getting the disease