DATA DEMOCRATIZATION IN IMAGING TO DRIVE PATIENT-CENTRIC, VALUE-BASED HEALTHCARE

THU 10:30 - 11:00

This is a 2017 presentation

The global health ecosystem is in the midst of a seismic evolution, and radiology is no exception. Philips is partnering differently, to help health systems successfully address today’s challenges by delivering integrated hardware, software, solutions and services focused on diagnosis and treatment.

Imaging plays a vital role in diagnosis and treatment, and can connect to the insights and data that enable physicians to best determine the right path to the right treatment, from the start, that will lead to the best outcome.

The challenge in driving data-driven healthcare lies in the disparate data streams and stakeholder, leading to distributed, disconnected and often disjointed care.

Data-driven healthcare is centered around patient experience using technology as an augmentation rather than the center. For example, AI with virtual assistants like Siri, Alexa, etc., could perform automated dictation during physician and patient conversation. This allows the physician to spend more time with patients instead of physicians spending more time at a screen – this also helps speed up turnaround times and allows patients to be tended to quickly, from exam to diagnosis, and the hospital to be more efficient overall.  The goal is to shift from “Screen Time” to “Patient Time.” At the institutional level, it’s about finding the efficient workflow pathways to reduce repeat imaging scans and enable much faster diagnoses. This reduces the cost burden of the organization and, at the same time, improves patient experience.
In a quest to achieve data-driven healthcare, we need to overcome historical barriers and enable the underlying technology fabric to support a standardized data format, federate and not duplicate data, provide seamless access and ensure governance for security and privacy of patient data. Additionally, there has to be recognition of the fact that data generated outside the healthcare system (sensor data, activity data, etc.) needs to be connected. Such data types provide a holistic view of the factors that influence healthcare delivery and patient care.
Naturally, this leads to the “democratization of data” to allow data to be shared responsibly with healthcare participants and technologies associated with governed principles. This democratization overcomes historical barriers for data sharing and intended data usage and can lead to an improved patient experience. For data democracy to be achievable and effective, the technology and governance framework must meet or support the following attributes:
•    Identification of the best possible standards that can be used to standardize and streamline diverse and complex data, enabling a shared understanding of the data

•    Promoting and enforcing the use of such standards through appropriate incentive structures and technology frameworks for all the health players, with streamlined security architecture for secure and responsible data access

•    Creating shared governance and oversight frameworks that can ensure the interests of health players are valued and respected

In order to achieve “Data Democracy,” new generation technology and business frameworks must be developed that allow business innovation with data and manage risk among the participants. Solutions in this space are still aspirational. At Philips, we’re striving to provide a holistic approach to connect health systems and patients to data and actionable insights that may improve clinical outcomes.
 

This lecture is made possible by MapR.

  • Theme
    Data Science

    Organisaties beschikken al over extreem veel data. De grote uitdaging zit erin om met de beschikbare data waarde toe te voegen aan een proces of klanttraject. Data science is daarvoor uitstekend geschikt. Finance en het voorspellen van consumentenbehoeften zijn twee gebieden waarop data science effectief is toe te passen. De investering loont sowieso, want beschikt een organisatie over meer inzicht, dan zijn ook slimmere keuzes te maken. Het thema data science neemt precies hierom een steeds prominentere rol in tijdens de Big Data Expo.