How an evolving data ecosystem is transforming the healthcare industry


31 May 2017

Image: Andrey_Popov/Shutterstock

IBM executive architect Elizabeth Koumpan outlines how connected devices and increasing data collection are changing how we facilitate and analyse healthcare.

Life Sciences Week 2017

We live in interesting times, where everything is changing. While data has become a commodity, information analytics now deliver us new, interesting insights. Thus, consumers expect more and better services.

We see how wearables have changed our life. We use running shoes that have sensors to track where we’re going, the distance we’ve travelled and calories burned. We even don’t need to carry a smartphone when out for a run. The shoes collect data from up to five workouts, so we can leave mobile devices at home and sync up to the app later. Healthcare professionals can now remotely monitor patient health and keep in touch with them by wirelessly capturing data from their medical devices. Smart contact lenses for diabetic patients could monitor their blood sugar levels by analysing glucose data contained in tears. More intelligent, instrumented, interconnected devices are around us than ever before.

‘In our future vision, I see industries transformed into a new way of delivering services focused on the consumer needs, with personalised touch, at the same time keeping data protected, secured and not abused’

This new generation of mobile devices – fitness trackers, home monitoring devices etc – enables people to collect data about themselves, connecting them with health advisers anywhere, anytime. The need for data sharing via new connected ecosystems – where participants can collaborate, exchange the information, collect data and provide new services – is increasing.

The product-centric model where the main objective of the OEM (original equipment manufacturer) was to develop the product or device is moving to a software and services model, with the focus on information, integration, analytics, cloud and IoT. When designing new devices, companies need to take into consideration that new, developed products will be used by consumers with different needs across different geographies. And, to better serve consumers, OEMs need to analyse historical data, perform sentimental analysis, develop new models and find new approaches to reach to the customers. To be a differentiator, product innovation needs to be done in new ways, expanding it into services and solutions.

The transformed data ecosystem

The healthcare industry has been going through tremendous transformation, forcing other players in the ecosystem around it to transform themselves. This transformation is happening at three levels:

  1. Device-makers, the creators of the medical devices for rehabilitation, treatment, prevention, diagnosis and physical activity tracking.
  2. Users that use such equipment to provide healthcare, such as physicians, laboratories and hospitals.
  3. Payers and insurance providers who contribute to the payment of the device use and service.

Consumers who use such devices for wellbeing, procedures or for healthcare expect better services and an even more personalised approach. So, how can we achieve this?

We have a lot of data generated by participants in this ecosystem, but we have been looking at information in isolation for a long time. We need solutions to provide real-time analytics using integrated data from devices, health systems, payers, patients, providers, and other systems and participants to deliver services that will be targeting particular consumer groups with particular needs. New cognitive capabilities will help us to deliver personalised services.

The data generated by devices can be differentiated into two different sets of data:

  • Data about the devices, equipment functionality and performance data that is aggregated with data from millions of other devices. This data help us to assess equipment quality, usage and services, generating insights that are integrated into the equipment provider’s operations, including product development, manufacturing, supply chain management and services.
  • Data about the consumers or patients who use these devices, aggregated with advanced clinical analytics solutions to compare their data to millions of research articles, clinical practices, similar patient cohorts and other data sources to enable providers to more easily diagnose the patient and adapt the optimal care path, providing remote monitoring.

But what if we combine this data together, in addition aggregating information generated from medical devices with other data related to our consumers and their profiles, extending our data collection from new data sources? We can generate more insights.

Mastering data in healthcare

Hospitals around the world are under increasing pressure to do more with less. A typical hospital has thousands of diverse applications, devices and technologies. To create safer hospitals and to improve patient safety, we need a solution to do analytics on aggregated data, including relevant information from the electronic health record. We need to have remotely accessible infrastructure to support operating rooms, intensive care units, hospital rooms and home healthcare. New solutions should provide the ability to collect and master clinical data such as patient visit information, diagnoses, medications, allergies and procedures, within a single, trusted view to create a longitudinal patient record. The key is gathering and retaining of all patient data in all forms and making this data available as required to healthcare practitioners.

‘The same rule applies and stays forever: personal information needs to be protected and never used without proper consent’

Healthcare organisations are looking to provide a more coordinated and personalised healthcare system. To deliver this, information from disparate systems and sources need to be transformed into intelligent, high-value information assets with secure, continuous and reliable access. Advanced analytics capabilities will help speed up medical research, diagnosis and treatment; and create intelligent environments around specific healthcare problems, to improve patient care and help reduce healthcare costs.

But, with advanced capabilities, new technology, and new ways of data collection and exchange, more issues need to be resolved. The more data we collect, the more challenges we face. We must ensure HIPAA compliance, and we need to secure personal information that is now coming in from new data sources and in new formats – such as voice, speech, video – and going into cloud. We also need to ensure that we have all the mechanisms to protect it.

New technology and new capabilities are creating new challenges that must be sorted out. The same rule applies and stays forever: personal information needs to be protected and never used without proper consent. Consumers may not understand the data compliance challenges, but all those who provide services need to be vigilant and need to protect the interests of the customers, while delivering new insights at the same time.

Closing thoughts

As the times change, bringing in new requirements and new trends, the healthcare ecosystem changes as well. In our future vision, I see industries transformed into a new way of delivering services focused on the consumer needs, with personalised touch, at the same time keeping data protected, secured and not abused.

We will see new and better value delivered in healthcare, where patient data, such as vital signs and pain scores, will be displayed on personal devices with timely alerts of any potential problems sent to a healthcare professional, so they can see what is going on with the patient and address the issues as needed. This will create new models to mitigate the risks and predict events before they happen, and personalise our services to specific consumer needs.

This future is not far away.

By Elizabeth Koumpan

Elizabeth Koumpan is an executive architect at IBM who has been addressing information integration and governance in complex enterprise ecosystems for the last few decades.

A version of this article originally appeared on the IBM blog