Value (Business Strategy and Financial Management)
EP-148 - Telemedicine Data Liberation
Sunday, April 29
4:05 PM - 4:20 PM
Location: Education Zone, Booth 2416, Screen 5
Our academic health system was one of the first in the country to adopt an electronic patient record (EMR), even winning an award for its efforts in the mid-1990s. Since then, our health system has developed a robust IT infrastructure and governing data trust. Centralization of telemedicine programs, however, has occurred only recently with the inauguration of an office of telemedicine in 2016.
One of the leading priorities of this office was to create a dedicated, centralized dashboard to communicate the value and impact of its projects within and beyond the institution. The framework below describes the process of building this dashboard.
Substantively, our health system has the following environmental characteristics with regards to data infrastructure and development of its telemedicine programs:
1. Decentralized operations with centralized IT
2. Heavy consolidation of IT under its EMR system
3. Highly prioritized data security within its data bureaucracy
4. Decentralized, clinically driven development of telemedicine programs
5. Limited consumer assessment surveys available for telemedicine
6. Degrees of socioeconomic determinants of health in target populations
7. Scalable relationships with third-party vendors for application development
8. Multi-hospital system in several states, a significant international division, and two major EMR vendors
Within this environment, the office attempted to develop its dashboard with the following milestones:
1. Data needs assessment
2. Resource assessment
4. Determination of KPIs
5. Test environment with use cases
Across the following value dimensions:
4. Financial Impact/Cost
5. Carbon Emission Reduction
6. The joy of medicine
The presentation will describe the lessons learned and achieve its learning objectives by examining the interactions between these three categories of environment, milestones, and dimensions and how they affect the liberation of data.
The findings discussed in the presentation will be useful for entities seeking practical information on large-scale, centralized telemedicine data collection in decentralized environments. It will also compare consequences of engagement with third-party data collection versus "home-grown" apparatuses and generally, the difficulties in collecting telemedicine data in modern, large health systems.
It will also provide mini-cases and examples demonstrating these interactions with specific emphasis on data liberation for large academic institutions.
- Identify available institutional resources and partnerships for telemedicine data
- Decide when to engage a third-party data apparatus
- Prospectively frame telemedicine data-collection initiatives