DiMe toolkits offer digital sensor data integration guidance
The Digital Medicine Society says the kits are designed to support the use of sensor data such as smartwatches on a much broader scale.
Four new best practice guides are now available to help organizations that want to improve their ability to use health data gathered by digital sensors – ranging from smartwatches to ingestible capsules – on a much larger scale.
The “sensor data integration toolkits” from the not-for-profit Digital Medicine Society (DiMe) are designed to support the use of data for a broad range of purposes. These could include, for example, integrating sensor data into electronic health records across many sites at a large delivery system or aggregating and sharing the data to support research on new drugs and treatments, says Jennifer Goldsack, CEO of the society.
“The problem we are trying to get ahead of is that currently, as we build out this field, we’re doing it at a smaller scale,” Goldsack says. “As we establish trust and value, we need to take this to scale to improve the way we care for people. We need to build architectures and systems that allow streams of sensor data, coupled with other clinical data, to flow through systems in a way so it can be used and reused by decisionmakers.”
In a report on sensor data integrations, DiMe states: “The current surge of data from sensor technologies is outpacing the industry’s ability to collect, store, analyze, protect and use this data effectively for research and patient care.”
DiMe has prepared a primer for the four toolkits. Here’s a rundown of what each kit offers:
- The Sensor Data Standards Toolkit outlines a common language and a shared approach to distributing, storing and interpreting information.
- The Sensor Data Architecture Toolkit translates business needs into data and system requirements and seeks to manage data and its flow through the enterprise. The data architecture describes the structure of an organization’s data assets. The toolkit also includes the models, policies, rules and standards that govern the collection, storage, arrangement, integration and use of data within an ecosystem.
- The SDI Implementation Toolkit outlines six criteria that are essential to a successful sensor data integration efforts: data collection, transmission, processing, security, privacy and quality. It also provides best practices that can help balance these criteria.
- The Organizational Readiness Toolkit contains materials to benchmark an organization’s capabilities and create a process map for sensor data integrations.
The new DiMe guidance, Goldsack stresses, “makes the strong case that privacy and security should be your top priority. Without privacy and security, none of this matters because we will lose trust.”
Shifting to larger scale use cases
Sensors, such as smartwatches, already can be used on a small scale to improve care, such as by monitoring an individual’s blood pressure to determine if hypertension medication is working, Goldsack says.
“The problem is that every time someone selects a sensor and a use case for the flow of data, they’re essentially building spoke integrations for that flow of data. And that doesn’t scale,” she explains. If a healthcare delivery system wants to equip all of its clinics to readily access sensor data via EHRs, it needs to leverage a standards-based data flow process that takes advantage of a “sensor data ecosystem suitable for scale,” she adds.
And building such an ecosystem requires participation of HIPAA-covered entities as well as device manufacturers, data processors and others “to make sure we are building systems that are safe, trustworthy, private and secure,” DiME’s CEO notes.
Participants that collaborated with DiMe to create the new open-access resources are Amazon Web Services, Oracle, Takeda Pharmaceutical,
Moffitt Cancer Center, the U.S. Food and Drug Administration, the U.S. Department of Veterans Affairs, Elevance Health (formerly Anthem), Evidation, Human First, the Institute of Electrical and Electronics Engineers, Medable, Open mHealth and Savvy Cooperative.
The four toolkits are designed for use by:
- Data producers, including connected sensor technology manufacturers and digital measurement companies as well as individuals authorized to enter, document, change or transmit sensor data.
- Data processors, including analytics companies, cloud service providers, data aggregators, data platforms, data scientists and data engineers.
- Data consumers, including clinicians, researchers, healthcare administrators, payers, health technology assessment bodies, regulators and public health agencies.
DiMe is encouraging organizations that use the new toolkits to share their experiences via a “Resources in Action” case study hub.