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Data Interoperability and Digital Health Trends Having a Significant Impact on Healthcare Today
Siva Namasivayam
Tuesday, October 20, 2015
The healthcare industry is witnessing a digital revolution that is being driven, in part, by the need for consumer-oriented health solutions that aim to provide the 21st century patient and healthcare consumer with the ability to have more control over their personal health data. Comprising this digital revolution is the convergence of technology trends in healthcare , including analytics, wearables, mobile phones and remote monitoring devices to name a few that have been developed to engage the consumer, ensure adherence, and allow information to be shared with physicians and other clinicians.

At the same time, this new digital health paradigm has become a driver for multitudes of data, also known as 'big data' that can be used to give payers, providers and consumers the information and insights they need to make decisions that impact health, wellness, care efficiency and quality. The challenge is this: with all this data originating from all the different digital sources available on the market today, how do we make this data interoperable, actionable and transparent in order to optimize care, improve the health of the population and decrease costs?

Healthcare Big Data Trends and Challenges
First, the good news: a recent Goldman Sachs report on digital health predicts that connected devices and other Internet solutions have the potential to save over $300 billion in costs for the U.S. healthcare sector. The report specifically focuses on telehealth and remote patient monitoring, two of the biggest areas today in digital health solutions. But there are also wearables produced by companies such as Apple, Fitbit and Jawbone; Electronic Medical Records (EMRs); and numerous other technologies, used either in a healthcare setting or as mobile devices (i.e. blood pressure and blood glucose monitoring devices) that generate scads of data. So here's the challenge: Where does all this data go? How is it used? How do you differentiate between good data and bad data?

Healthcare data is not generated simply from the EMR anymore. In addition to digital devices, there are additional systems that produce valuable information such as insurance claims, pharmacy data, care management and health outreach data, to name a few. With the voluminous amounts of information systems and devices, it is necessary for technology to enable applications that are easy to use, enable systems to communicate with each other, determine how information is processed and managed, and integrate information that is then used for the higher purpose of better health, better care and affordable care. To arrive at these goals, it is critical that the data gleaned from all the different sources available today is transparent, actionable and interoperable.

The lack of interoperability between disparate data sources has arisen as a key challenge to value-based or collaborative care. So the question now is, how do we take huge amounts of data from a variety of sources and make this data interoperable, meaningful and available for a variety of different uses? The answer lies in combining technology with plain, common business sense.

There is no point in 'boiling the ocean.' Instead, you must start with simple business solutions that enable you to prioritize, synthesize, analyze, and apply predictive models against the data to develop meaningful insights and address the most critical areas. And, the companies that realize this will be more successful than those that are simply analyzing trends data or EMR data. The companies that succeed are those who seek out the value in data.

Technology solutions that utilize a flexible architecture will allow for the processing of a significant amount of information in a short period of time, and the ability to clean the data and enable its use for a variety of different applications. And if we examine the types of technology solutions on the market today, it's not difficult to see that data interoperability can turn any one of them into a tool to support the evolving mobile health environment.

Mobility in Healthcare
One of the biggest technology trends in healthcare today is what's known as 'mobile health,' part of the digital health revolution. For example, among the various remote monitoring devices available today is a device that monitors sleep apnea. In the past, one would need to be admitted to a center or hospital as part of a sleep study to be checked for this condition. Now, a CPAP machine can be used as a treatment for sleep apnea and monitored remotely to routinely test a patient's breathing levels. But how does it improve health outcomes and reduce healthcare costs? The data that is generated by such a device needs to be interoperable and transparent in order for it to have value. For example, if this patient was also being treated by four other physicians for four additional conditions, this information becomes valuable when each physician sees how this condition may impact the others. Perhaps this person needs three medications instead of two; or perhaps they need a different medication for sleep apnea because it will interact with another, unrelated condition they are being monitored for. From a cost perspective, think about results such as reducing medication costs; reducing hospital admissions or readmissions, all because this person can be monitored at home, and each of their monitoring devices can communicate with the other. Also, if each physician had visibility into the data, this patient could receive the best care possible.

While the trend in mobile technology is significant in healthcare, it is important to note the difference between data interoperability - the extent to which systems and devices can exchange and interpret shared data; and the ability to make useful insights and meaningful use of the knowledge and information gleaned from many different devices and data sources.

In order for data to be meaningful and valuable, it must engage payers, providers, patients and members to use information to identify areas that have the biggest impact in addressing gaps in care and hopefully, improve the overall quality of a population.

Take the area of consumer analytics, for example. How does an insurer motivate or drive certain outcomes, and know when it needs to intervene and make decisions on behalf of its members? What's going to be the best route for engaging an individual in addressing a gap in care? What incentives for compliance have been developed? These questions all tie back to data interoperability and leveraging it to drive healthcare outcomes in a meaningful way.

As we look ahead to the next five years, it is important to consider where today's trends will be, tomorrow. Certainly, there will be an increased focus on value-based care. And, although technology will eventually be more nimble, this will not come overnight. There will be a greater need for the prioritization of data. Digital technology and mobility in healthcare will continue. Most importantly though, will be the ability for all healthcare devices and data to be interoperable, and for clinicians to utilize the data they collect to assist consumers, employers, insurers and care managers in identifying the greatest opportunities for health improvement and cost avoidance.
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