Closing data gaps in materials management in hospitals faster

Too little or too much?
Procurement management in hospitals and clinics is often subject to the random principles.

the Problem

Hospitals often lack an ongoing inventory. Moreover, since seasonal increases in workload, e.g., due to flu outbreaks or increased risk of accidents in winter, are seldom taken into account, orders and deliveries are made that simply miss the actual need. While we have a highly efficient and recognized healthcare system, there is an epidemic data emergency almost everywhere with regard to the use of efficient data processing. With the PAIRS platform now under development, it will be possible to implement "healthy" planning and ordering management in the future.

the Solution

With a system for automated inventory control and with the establishment of an early warning system for anomalies, epidemics or recurring waves of illness, supply and demand planning can be brought into being in line with requirements. The PAIRS platform enables early detection and crisis preparedness from internal hospital data. With the use of hybrid AI, patterns can be identified from such data and early crisis prevention can be initiated. Since this is highly sensitive data, it requires the use of a system that allows access without violating the GDPR. The architecture of the PAIRS platform, based on IDSA and GAIAX, ensures this. This is complemented by state-of-the-art technologies such as Federated Learning or the patent-pending Trusted Data Hub, which allow confidential data to be used without disclosing the respective raw data. This solution outlined here is capable of detecting patterns in conspicuous anomalies, regardless of timing and hospital boundaries, to provide early detection and crisis prevention.

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The joint project PAIRS is funded as an AI lighthouse project within the framework of the “Innovation Competition Artificial Intelligence” by the Federal Ministry of Economics and Climate Protection (BMWK).