The healthcare industry is in the middle of a significant moment of change, due in large part to the rapid advancement of technology. Providers, patients and consumers alike are experiencing the effects of this transformation in a number of tangible ways, but consider just a few examples.
According to a recent Gartner report, shipments for smart wristbands and other fitness monitors are predicted to reach of 91 million units by 2016. That’s an estimated increase of nearly 20 million units as compared to numbers from 2014. This is just the tip of the iceberg when it comes to connected devices for wellness; Google is developing a contact lens that can monitor the blood sugar levels of someone with diabetes. At this year’s CES we saw the unveiling of a “smart bed” to track a user’s sleeping patterns.
On the software side of things, iOS 8, Apple’s latest mobile operating system released in September 2014, features a new Health app that gives users a centralized dashboard from which they can input and view a variety of health and fitness data. And Apple’s not the only player in the game—Google and Samsung also offer similar apps.
Healthcare providers and insurers are also experiencing the effects of this revolution. Not only can all of these new sources of health data be shared with doctors, therapists, surgeons and specialists with the swipe of a finger, but providers are increasingly maintaining and sharing patient information in the form of Electronic Health Records(EHR).
In fact, according to a study from The Office of the National Coordinator for Health Information Technology (ONC), eight in ten physicians were using an electronic health record or are planning to adopt one. Another study from the ONC conducted in May 2014 found that hospital adoption of EHR systems has increased more than five-fold since 2008.
The end result is an exorbitant amount of data being generated and exchanged between patients, providers, insurers and institutions, in a variety of combinations. But what are we doing with all of this data?
While it’s clear that technology is having a profound impact on how healthcare information is gathered, monitored and acted upon, if data sources remain siloed and/or in different formats, much of the information being gathered will effectively be rendered useless. Data is most meaningful and yields the most actionable insight when it can easily be examined in the context of other data.
Semantic technology provides a natural solution for data standardization and, as a result, compatibility. However, it’s not that simple.
The healthcare industry faces some very specific challenges when it comes to determining a common language, as there are a number of vocabularies, formats, and systems used by all of the players in the space. There are competing standards for encoding diagnoses, and different data types are stored in different formats—for example, one format for lab data, another format for imaging data and potentially another format for procedure codes.
However, the case for solving the issues associated with semantic interoperability is strong, as the benefits for doing so are too impactful to ignore.
From an operations standpoint, better care coordination not only among a patient’s team of doctors, but also including billing departments and insurance companies at various medical institutions result in streamlined processes across the broad.
Imagine if providers had easy access to all lab test results, regardless of where the testing occurred. Not only are the number of unnecessary procedures eliminated, saving time and money for all involved, but claims can be filed and paid more quickly, avoiding confusion and delays around multiple submissions. The same goes for referrals, prescriptions–the list goes on. If this information can be entered in real time as structured data into EHR systems, efficiencies will significantly increase for all involved.
The transformative power of semantic technology becomes most clear when we look at the implications for patient care. Patient records can be analyzed and indexed in large quantities according to diagnoses, treatments, medications and event dates as well as in context of existing knowledge bases. This yields new insight into trends and patterns that may have previously gone undetected, leading to faster, more accurate diagnoses.
Looked at from the other side of the same coin, the rich depository of patient data, once anonymized, provides a wealth of knowledge through which providers can look at trends around diagnoses, success rates of different treatment options or medications in conjunction with other patient variables. As a result, patients receive more accurate and timely information, and ultimately, better care.
We are moving towards an era of unprecedented personalization in healthcare. If leveraged appropriately, semantic technology can uncover valuable new insights from the deluge of personal health data that is being constantly generated, in conjunction with existing knowledge bases. The end result will be streamlined communication and collaboration between different healthcare organizations, and customized patient care to create better quality of life.
Electronic health records are the primary source of information for providing insights into the diagnoses and outcome of clinical treatments. Retrieving useful analytical information from these records is challenging though. The complex nature of clinical text can result in much of the information extracted being of limited value. Natural Language Processing (NLP) techniques, however, can process large volumes of clinical text while automatically encoding clinical information in a structured form.